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38591
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1434
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5
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2026-05-13T17:50:09.260264+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694609260_m2.jpg...
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PhpStorm
|
faVsco.js – Activity.php
|
1
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NULL
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monitor_2
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NULL
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NULL
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NULL
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NULL
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PhostormINavigarecodeProiect v= custom.log& co PhostormINavigarecodeProiect v= custom.log& console [PROD]© LayoutRepository.phpC Leackepository.onpC EmailTextRelay.pnp© ValidateSendingMessage.phpA console (EU]iid stages [EU]fiò teams (EU]© Activity.php X A console [STAGING]class Activity extends Model implementsc Promllekepository.onpС кecora lyperielavaluesc stacekeposilorv.ono© SyncBatchRepositorv.pl> C GeographyC) ActiveStreamsRepositorv.cC Textkelay.pnpDashboardController.onoC) UpdateActivityElasticSearchDocumentCommand.php© ConferenceCrmMatcherJob.phdmand.oho© ImportParticipants.php© ProspectCache.phg© OpportunityRepository.php xC) UpdateSinqleEntity.php(C) ActivityStatusin.phpclass OpportunityRepository implements RetentionRepositoryInterfaceC) ActivitvcommentRepositorC) ActivitvLoaRepositorv.phoC) ActivitvMessageRepositonC) ActivitvMomentReoositorvC) ActivitvProviderReoositorvC ActivitvRenositor.ohoC) ActivitvSearchsilterRevosit@ ActivitvShareRenositorv.oh© ActivityUploadSettingRepoc) A PromntRenositorv nhn.© AskAnythingRepository.phpC) AutomatedRenortsRenoçit.© CallImportRepository.php© CoachingFeedbackRepositC) CrmTemnlateSilterRenocita© CrmTemplateRepository.ph© CrmTemplateRunRepositor© DeviceRepository.phpclasticacuivilykeposilory.olccmallmessacerepostorv.oc) GenericAlPromptRepositonc Grouprepository.phpInboxRepository.php© InvitationRepository.phpc) oorenositorv.onoC) LanquageRepositor.ohoC) MomentRepositorv.oho@ NotificationRepositorv.phpC) ParticioantReoositor.ohoC) ParticinantStatsRenositorvC) PlavbookcatedorvRenositoC) PlavbookRenositorv nhn@ PlavlistActivityRepository.p© PlaylistRepository.php@ PlavlistShareRenositorv.nh© QuestionRepository.phpe PoloChanaoSventDonocital© RoleRepository.php© SearchRepository.php© SnapshotRepository.phpм 014143 ^ v 20962091public function findOneByAccountAndOpportunity0wner(Configuration Sconfiguration,Account saccount,ant suserio?int ScontactId = null): ?Opportunity {return Sthis->buildAccountOpportunityQuery(Sconfiquration, Saccount, ScontactId)>where colu'user 1d', suser10)->t1rStorivate function bu1ldAccount0poortunitvouervConfiquration Sconfiquration.Pint ScontactId = null• HasManv <1Scriteria = Sthis->resolve@nnortunitv0rderSconfiauration):return Sconfiauration>onnontunitieso->whene & colunlaccount idi Caccount->ao+Tdon->when($criterial'only_open'], fn (Squery) => $query->where( column: 'is_closed'.onerator: falce)i-swhendvalue: Scontac+td 1== nul1)fn ($query) => $query->orderByRaw(sql:'EXISTS (SELECT 1 FROM opportunity_contacts'.'WHERE opportunity_contacts.opportunity_id= opportunities.id'.'AND opportunity_contacts.contact id = ?) DESC'.[ScontactIdl2121212121232126->orderBy(Scriterial'order_by']. Scriterial'direction'])* Sind all non-internal onportunities bu account ID and confiauratio213110094 434 Auppor conzeginuel,concaccinuetscage null,string|null*r srecoruspublic function updateActivityCrmData(array Srecords): voidexcract che records.[Slead. Saccount. Sopportunity. Scontact. Sstagel = Srecords:Sstrateay = SresolvesolveForActavitySlead. Scontact. Saccount):1+ Sstrateov == Uodatecrmbata.vStrateov::Lead)<// Also update the parent activity if required, checking we don't create a mixed lead/account record.i+ (Sthis->account id zz= null &x Sthis->contact id zz= null && Sthis->lead id zzz nulb«Sthis->lead id = Slead->id:if (Sthis->stage 1d za= null &s Sstage) <Sthic-sctade 1d = Sctanp->id-Sthis-scaved•} elseif ($strategy == UpdateCrmDataByStrategy::Contact) {// Also update the parent activity if required, checking we don't create a mixed lead/account record.Sthis->lead_id = null;if (Sthis->stage && $this->stage->getType() === Stage::TYPE_LEAD) {sch1s->scage 1d = null# Don't trust previous matched account id as it might have been changed in the CRMif (Saccount && Saccount->id !== Sthis->account id) {Sth1s->account 1d = Saccount->1d*if (Sthis->stage id === null && Sstage) {Sthis-›stage id = Sstage->id:if (Soppontunity &s Sthis->opportunitv id 1== Sopportunitv->id) fif (Sonnontunitv ss Sthis-svalue Ier Sonnontunitv-svalue) fSthis->value = Connontunitv->value•100% L2Wed 13 May 20:50:08AskJiminnyReportActivityServiceTest vcascadeTrial Owner Role SeleRetactoring User EmaActivity Stage ID Upda+0 ..@Open Preview cT. Share Conversation© Activity Stage ID Update InvestigatiorDownload Trajectory© Activity Status vs Recording Status Investigation© Debugging Es Activity Update~ Cascade UsageQ, Download DiaanosticsDashboard Activity DebuggingCalls part icinantCrmLookun) for each3. participantCrmLookup() (Line 283-332)• Logs: "Prospect attendee found. Attempting to match to a CRM record"Calls findProspectDataBvEmailo (Line 296)4. findProspectDataByEmail() (Line 399-433)• Uses GachedCrmServiceDecorator to search•Loas show: "Searching Hk for opportunity by owner" (cache search)• Loas show: "Opportunity DB search results" (found in cache)Poturne cached CPM recorde5. Cache Hit Loas show•"Prospect match: Cache / local search hit"• Returns existina onportunity data: & onnortunitv: 7842553. stage: 18775 }6. updateActivityCrmData() (Line 105-136)Gets oridinal activity data: stage: 18775• Calls Activitv->updateActivitvCrmData (Line 121)• Gets current activity data: { stage: 18775 }• Loas: "Updated activity crm data" showina original data == current dataKev FindinaThe stade id was NOT chanaed hv this iohliison"oriqina data": "stage": 18775"current datall. "ctaag". 18775 %tthle mosnceel Contiqure Rulesª Contiaure Skills% Configure Workflows< Edit Memories•stage id: 18775 was already set on the activity before ConferenceCrmMatcherJob ranThe iob confirmed the existina data via cache hitNo actual chande occurredlWhen Was stage id Initially Set?Since this iob at 08:21:40 didn't chance the stage id (fit was already 18775). and vour activitv was created at 08:00:00)the stage id was likely set by:1Initiol extivity crastion vie calandar imnortlwahbask (bafora 00:01:10\Ask anvthina (84L)SWE-16W Windsurf Toams 77-18UTF.8io 4 spaces...
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NULL
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-7410059144130534415
|
NULL
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visual_change
|
ocr
|
NULL
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PhostormINavigarecodeProiect v= custom.log& co PhostormINavigarecodeProiect v= custom.log& console [PROD]© LayoutRepository.phpC Leackepository.onpC EmailTextRelay.pnp© ValidateSendingMessage.phpA console (EU]iid stages [EU]fiò teams (EU]© Activity.php X A console [STAGING]class Activity extends Model implementsc Promllekepository.onpС кecora lyperielavaluesc stacekeposilorv.ono© SyncBatchRepositorv.pl> C GeographyC) ActiveStreamsRepositorv.cC Textkelay.pnpDashboardController.onoC) UpdateActivityElasticSearchDocumentCommand.php© ConferenceCrmMatcherJob.phdmand.oho© ImportParticipants.php© ProspectCache.phg© OpportunityRepository.php xC) UpdateSinqleEntity.php(C) ActivityStatusin.phpclass OpportunityRepository implements RetentionRepositoryInterfaceC) ActivitvcommentRepositorC) ActivitvLoaRepositorv.phoC) ActivitvMessageRepositonC) ActivitvMomentReoositorvC) ActivitvProviderReoositorvC ActivitvRenositor.ohoC) ActivitvSearchsilterRevosit@ ActivitvShareRenositorv.oh© ActivityUploadSettingRepoc) A PromntRenositorv nhn.© AskAnythingRepository.phpC) AutomatedRenortsRenoçit.© CallImportRepository.php© CoachingFeedbackRepositC) CrmTemnlateSilterRenocita© CrmTemplateRepository.ph© CrmTemplateRunRepositor© DeviceRepository.phpclasticacuivilykeposilory.olccmallmessacerepostorv.oc) GenericAlPromptRepositonc Grouprepository.phpInboxRepository.php© InvitationRepository.phpc) oorenositorv.onoC) LanquageRepositor.ohoC) MomentRepositorv.oho@ NotificationRepositorv.phpC) ParticioantReoositor.ohoC) ParticinantStatsRenositorvC) PlavbookcatedorvRenositoC) PlavbookRenositorv nhn@ PlavlistActivityRepository.p© PlaylistRepository.php@ PlavlistShareRenositorv.nh© QuestionRepository.phpe PoloChanaoSventDonocital© RoleRepository.php© SearchRepository.php© SnapshotRepository.phpм 014143 ^ v 20962091public function findOneByAccountAndOpportunity0wner(Configuration Sconfiguration,Account saccount,ant suserio?int ScontactId = null): ?Opportunity {return Sthis->buildAccountOpportunityQuery(Sconfiquration, Saccount, ScontactId)>where colu'user 1d', suser10)->t1rStorivate function bu1ldAccount0poortunitvouervConfiquration Sconfiquration.Pint ScontactId = null• HasManv <1Scriteria = Sthis->resolve@nnortunitv0rderSconfiauration):return Sconfiauration>onnontunitieso->whene & colunlaccount idi Caccount->ao+Tdon->when($criterial'only_open'], fn (Squery) => $query->where( column: 'is_closed'.onerator: falce)i-swhendvalue: Scontac+td 1== nul1)fn ($query) => $query->orderByRaw(sql:'EXISTS (SELECT 1 FROM opportunity_contacts'.'WHERE opportunity_contacts.opportunity_id= opportunities.id'.'AND opportunity_contacts.contact id = ?) DESC'.[ScontactIdl2121212121232126->orderBy(Scriterial'order_by']. Scriterial'direction'])* Sind all non-internal onportunities bu account ID and confiauratio213110094 434 Auppor conzeginuel,concaccinuetscage null,string|null*r srecoruspublic function updateActivityCrmData(array Srecords): voidexcract che records.[Slead. Saccount. Sopportunity. Scontact. Sstagel = Srecords:Sstrateay = SresolvesolveForActavitySlead. Scontact. Saccount):1+ Sstrateov == Uodatecrmbata.vStrateov::Lead)<// Also update the parent activity if required, checking we don't create a mixed lead/account record.i+ (Sthis->account id zz= null &x Sthis->contact id zz= null && Sthis->lead id zzz nulb«Sthis->lead id = Slead->id:if (Sthis->stage 1d za= null &s Sstage) <Sthic-sctade 1d = Sctanp->id-Sthis-scaved•} elseif ($strategy == UpdateCrmDataByStrategy::Contact) {// Also update the parent activity if required, checking we don't create a mixed lead/account record.Sthis->lead_id = null;if (Sthis->stage && $this->stage->getType() === Stage::TYPE_LEAD) {sch1s->scage 1d = null# Don't trust previous matched account id as it might have been changed in the CRMif (Saccount && Saccount->id !== Sthis->account id) {Sth1s->account 1d = Saccount->1d*if (Sthis->stage id === null && Sstage) {Sthis-›stage id = Sstage->id:if (Soppontunity &s Sthis->opportunitv id 1== Sopportunitv->id) fif (Sonnontunitv ss Sthis-svalue Ier Sonnontunitv-svalue) fSthis->value = Connontunitv->value•100% L2Wed 13 May 20:50:08AskJiminnyReportActivityServiceTest vcascadeTrial Owner Role SeleRetactoring User EmaActivity Stage ID Upda+0 ..@Open Preview cT. Share Conversation© Activity Stage ID Update InvestigatiorDownload Trajectory© Activity Status vs Recording Status Investigation© Debugging Es Activity Update~ Cascade UsageQ, Download DiaanosticsDashboard Activity DebuggingCalls part icinantCrmLookun) for each3. participantCrmLookup() (Line 283-332)• Logs: "Prospect attendee found. Attempting to match to a CRM record"Calls findProspectDataBvEmailo (Line 296)4. findProspectDataByEmail() (Line 399-433)• Uses GachedCrmServiceDecorator to search•Loas show: "Searching Hk for opportunity by owner" (cache search)• Loas show: "Opportunity DB search results" (found in cache)Poturne cached CPM recorde5. Cache Hit Loas show•"Prospect match: Cache / local search hit"• Returns existina onportunity data: & onnortunitv: 7842553. stage: 18775 }6. updateActivityCrmData() (Line 105-136)Gets oridinal activity data: stage: 18775• Calls Activitv->updateActivitvCrmData (Line 121)• Gets current activity data: { stage: 18775 }• Loas: "Updated activity crm data" showina original data == current dataKev FindinaThe stade id was NOT chanaed hv this iohliison"oriqina data": "stage": 18775"current datall. "ctaag". 18775 %tthle mosnceel Contiqure Rulesª Contiaure Skills% Configure Workflows< Edit Memories•stage id: 18775 was already set on the activity before ConferenceCrmMatcherJob ranThe iob confirmed the existina data via cache hitNo actual chande occurredlWhen Was stage id Initially Set?Since this iob at 08:21:40 didn't chance the stage id (fit was already 18775). and vour activitv was created at 08:00:00)the stage id was likely set by:1Initiol extivity crastion vie calandar imnortlwahbask (bafora 00:01:10\Ask anvthina (84L)SWE-16W Windsurf Toams 77-18UTF.8io 4 spaces...
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NULL
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NULL
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NULL
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NULL
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38593
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1434
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6
|
2026-05-13T17:50:20.906520+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694620906_m2.jpg...
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PhpStorm
|
faVsco.js – OpportunityRepository.php
|
1
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NULL
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monitor_2
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NULL
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NULL
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NULL
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NULL
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PhostormINavigarecodeFV faVsco.js?9 masterProledey PhostormINavigarecodeFV faVsco.js?9 masterProledeyN Webhook© EmailTextRelay.php© ValidateSendingMessage.php© Account.ono© Acuvity.onp© Adaress.onp© SmsRelayFailed.phpC AIPrompt.ont© DashboardController.phcC)JiminnyDebuacommand.onoc) Aulomaleckeport.ono© AutomatedReportResult.phC) UpdateActivityElasticSearchDocumentCommand.php© ConferenceCrmMatcherJob.php©)ImportParticipants.phoc) calendar.php©OpportunityRepository.php x© UpdateSingleEntity.php© ActivityStatusin.phpc) callimport.phpclass OpportunityRepository implements RetentionRepositoryInterface) coachinaFeedback.ohp© CoachingFeedbackVisibilit.c) coachinaSection.phpC) coachinoSectioncriterionfC) CoachinaSectionFeedbackC CommentAbstract.php1 Commentinterface.oho© Contact.phpC) Device nhn© EmailMessage.php© GenericAiPrompt.php© Group.php© Inbox.php© InboxEmail.php© InboxEmailBatch.phpc) Invitation.ono© JobLog.php©.JobTitle.php© Lanquage.php© LanquageDialect.phpc) Lead.phpc Mobilesetting.phpc, Model.phpc) Moment.phpc) Nudge.onoC) NudaeRun.ohoC @pportunitv.ohoC) Particioant. ohoC) Partner.ohoC) Permission.ohoC) PhoneNumber.oheC) Plavbackitheme.ohnC) Plavbook nhnC) PlavbookCategorv nhnC) Plavlist nhnlC) Patel imit nhn© Region.php(C Polo nhnl© RoleChangeEvent.php© ScopeGroup.php© Session.phppublic function findOneByAccountAndOpportunity0wner(Configuration Sconfiguration,account saccount,ant suserio?int ScontactId = null): ?Opportunity {return Sthis->buildAccountOpportunityQuery(Sconfiquration, Saccount, ScontactId)>where colu'user 1d', suser10)->t1rStprivate funct.ion buildAccount0pportunitvouervConfiquration Sconfiquration.Dint Scontactid = nulu): HasMany 1!Scriteria = Sthis->resolve@nnortunitv0rderSconfiauration):return Sconfiauration>onnontunitieso->whene & colunlaccount idi Caccount->ao+Tdon->when(Scriterial'only_open'], fn (Squery) => $query->where( column: 'is_closed',-swhendvalue: Scontac+td 1== nul1)fn ($query) => $query->orderByRaw(sql:'EXISTS (SELECT 1 FROM opportunity_contacts '.'WHERE opportunity_contacts.opportunity_id=opportunities.id''AND opportunity_contacts.contact id = ?) DESC'.[ScontactIdl->orderBy(Scriterial'order_by']. Scriterial'direction'])* Sind all non-internal onportunities bu account ID and confiauration= custom.logscratch. &.isonA SF jiminny@localhost]& HS_local [jiminny@localhost]& console [PROD]A console (EU]tid stages [EU]fiò teams (EU]o Acuivily.onpxA console [STAGING]class Activity extends Model implements2085-2086208/C) ProspectCache.php02 A2 43 л v 20912108onerator: falce)i— 2124213394 434 AOpportunity|null,Contact|null,scage nullstring|null*} Srecordspuoiac functon updateActzvatycrmbata (array Srecords): voidExtract the records.[Slead, Saccount. Sopportunity. Scontact. $staqel = Srecords:Sresolver = sthis->getUpdatecrmbataResolver:Sstrateay = Sresolve->resolveForActivitySlead. Scontact. Saccount)•if (Sstrategy == UpdateCrmDataByStrategy::Lead) 1// Also update the parent activity if required, checking we don't create a mixed lead/account record.if (Sthis->account_id === null && Sthis->contact_id === null && $this->lead_id === null) iSthis-Slead 1d = Slead->id+if (Sthis->stage_id === null && $stage) {$this->stage_id = $stage->id;Sthis->saveO:ll}elseif ($strategy == UpdateCrmDataByStrategy::Contact) {I/ Also update the parent activity if required, checking we don't create a mixed lead/account record.sunis->lead 10 = nuLl.if (Sthis->stage && Sthis->stage->qetType( === Staqe::TYPE LEAD) {sth1s->stage 1d = nulbII Don't trust previous matched account id as it might have been changed in the CRMif (Saccount &s Saccount->id |== Sthis->account id) {Sthis->account id = Saccount->id:if (Sthis->stage id === null && Sstage) {Sthis->stage id = Sstage->id.i* (Sonnontunitv && Sthis->onnontunitv id I== Connontunitv->id)&i€ (Sonnontunitv &c Sthis->value I== Sonnontunitv->value) ₫Sthic-svaluo - Connontunitv-svalno»100% L2Wed 13 May 20:50:20U AskJiminnyReportActivityServiceTest vcascadeTrial Owner Role SeleRetactoring User EmaActivity Stage ID Upda@ Open PreviewT. Share Conversation© Activity Stage ID Update InvestigatiorDownload Trajectory© Debugging Es Activity Update~ Cascade UsageQ, Download DiaanosticsDashboard Activity DebuggingCalls part icinantCrmLookun() for each3. participantCrmLookup() (Line 283-332)• Logs: "Prospect attendee found. Attempting to match to a CRM record"Calls findProsoectDataBvEmailo (Line 296)4. findProspectDataByEmail() (Line 399-433)• Uses GachedCrmServiceDecorator to search•Loas show: "Searching Hk for opportunity by owner" (cache search)• Loas show: "Opportunity DB search results" (found in cache))Peturns cached CPM recordo5. Cache Hit Loas show•"Prospect match: Cache / local search hit"Returns existina opportunity data: & onnortunitv: 7842553 stage: 18775 }6. updateActivityCrmData() (Line 105-136)Gets oridinal activity data: stage: 18775• Calls Activitv->updateActivitvCrmData Line 121)• Gets current activity data: { stage: 18775 }• Loas: "Updated activity crm data" showina original data == current dataKev FindinaThe stade id was NOT chanaed hv this iohliison"original data": { "stage": 18775 }"current datall. "ctaag". 18775 %tthle mosnceel Contiqure Rulesª Contiaure Skills% Configure Workflows< Edit Memories•stage id: 18775 was already set on the activity before ConferenceCrmMatcherJob ranThe iob confirmed the existing data via cache hitNo actual chande occurredlWhen Was stage id Initially Set?Since this iob at 08:21:40 didn't chance the stage id (fit was already 18775). and vour activitv was created at 08:00:00)the stage id was likely set by:1Initiol extivity crastion vie colandar imnortlwahhask (hafara 09:21:10}Ask anvthina (84L)SWE-16WN Windsurf Toams 2109-21UTF.8io 4 spaces...
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NULL
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-1143769613979395490
|
NULL
|
click
|
ocr
|
NULL
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PhostormINavigarecodeFV faVsco.js?9 masterProledey PhostormINavigarecodeFV faVsco.js?9 masterProledeyN Webhook© EmailTextRelay.php© ValidateSendingMessage.php© Account.ono© Acuvity.onp© Adaress.onp© SmsRelayFailed.phpC AIPrompt.ont© DashboardController.phcC)JiminnyDebuacommand.onoc) Aulomaleckeport.ono© AutomatedReportResult.phC) UpdateActivityElasticSearchDocumentCommand.php© ConferenceCrmMatcherJob.php©)ImportParticipants.phoc) calendar.php©OpportunityRepository.php x© UpdateSingleEntity.php© ActivityStatusin.phpc) callimport.phpclass OpportunityRepository implements RetentionRepositoryInterface) coachinaFeedback.ohp© CoachingFeedbackVisibilit.c) coachinaSection.phpC) coachinoSectioncriterionfC) CoachinaSectionFeedbackC CommentAbstract.php1 Commentinterface.oho© Contact.phpC) Device nhn© EmailMessage.php© GenericAiPrompt.php© Group.php© Inbox.php© InboxEmail.php© InboxEmailBatch.phpc) Invitation.ono© JobLog.php©.JobTitle.php© Lanquage.php© LanquageDialect.phpc) Lead.phpc Mobilesetting.phpc, Model.phpc) Moment.phpc) Nudge.onoC) NudaeRun.ohoC @pportunitv.ohoC) Particioant. ohoC) Partner.ohoC) Permission.ohoC) PhoneNumber.oheC) Plavbackitheme.ohnC) Plavbook nhnC) PlavbookCategorv nhnC) Plavlist nhnlC) Patel imit nhn© Region.php(C Polo nhnl© RoleChangeEvent.php© ScopeGroup.php© Session.phppublic function findOneByAccountAndOpportunity0wner(Configuration Sconfiguration,account saccount,ant suserio?int ScontactId = null): ?Opportunity {return Sthis->buildAccountOpportunityQuery(Sconfiquration, Saccount, ScontactId)>where colu'user 1d', suser10)->t1rStprivate funct.ion buildAccount0pportunitvouervConfiquration Sconfiquration.Dint Scontactid = nulu): HasMany 1!Scriteria = Sthis->resolve@nnortunitv0rderSconfiauration):return Sconfiauration>onnontunitieso->whene & colunlaccount idi Caccount->ao+Tdon->when(Scriterial'only_open'], fn (Squery) => $query->where( column: 'is_closed',-swhendvalue: Scontac+td 1== nul1)fn ($query) => $query->orderByRaw(sql:'EXISTS (SELECT 1 FROM opportunity_contacts '.'WHERE opportunity_contacts.opportunity_id=opportunities.id''AND opportunity_contacts.contact id = ?) DESC'.[ScontactIdl->orderBy(Scriterial'order_by']. Scriterial'direction'])* Sind all non-internal onportunities bu account ID and confiauration= custom.logscratch. &.isonA SF jiminny@localhost]& HS_local [jiminny@localhost]& console [PROD]A console (EU]tid stages [EU]fiò teams (EU]o Acuivily.onpxA console [STAGING]class Activity extends Model implements2085-2086208/C) ProspectCache.php02 A2 43 л v 20912108onerator: falce)i— 2124213394 434 AOpportunity|null,Contact|null,scage nullstring|null*} Srecordspuoiac functon updateActzvatycrmbata (array Srecords): voidExtract the records.[Slead, Saccount. Sopportunity. Scontact. $staqel = Srecords:Sresolver = sthis->getUpdatecrmbataResolver:Sstrateay = Sresolve->resolveForActivitySlead. Scontact. Saccount)•if (Sstrategy == UpdateCrmDataByStrategy::Lead) 1// Also update the parent activity if required, checking we don't create a mixed lead/account record.if (Sthis->account_id === null && Sthis->contact_id === null && $this->lead_id === null) iSthis-Slead 1d = Slead->id+if (Sthis->stage_id === null && $stage) {$this->stage_id = $stage->id;Sthis->saveO:ll}elseif ($strategy == UpdateCrmDataByStrategy::Contact) {I/ Also update the parent activity if required, checking we don't create a mixed lead/account record.sunis->lead 10 = nuLl.if (Sthis->stage && Sthis->stage->qetType( === Staqe::TYPE LEAD) {sth1s->stage 1d = nulbII Don't trust previous matched account id as it might have been changed in the CRMif (Saccount &s Saccount->id |== Sthis->account id) {Sthis->account id = Saccount->id:if (Sthis->stage id === null && Sstage) {Sthis->stage id = Sstage->id.i* (Sonnontunitv && Sthis->onnontunitv id I== Connontunitv->id)&i€ (Sonnontunitv &c Sthis->value I== Sonnontunitv->value) ₫Sthic-svaluo - Connontunitv-svalno»100% L2Wed 13 May 20:50:20U AskJiminnyReportActivityServiceTest vcascadeTrial Owner Role SeleRetactoring User EmaActivity Stage ID Upda@ Open PreviewT. Share Conversation© Activity Stage ID Update InvestigatiorDownload Trajectory© Debugging Es Activity Update~ Cascade UsageQ, Download DiaanosticsDashboard Activity DebuggingCalls part icinantCrmLookun() for each3. participantCrmLookup() (Line 283-332)• Logs: "Prospect attendee found. Attempting to match to a CRM record"Calls findProsoectDataBvEmailo (Line 296)4. findProspectDataByEmail() (Line 399-433)• Uses GachedCrmServiceDecorator to search•Loas show: "Searching Hk for opportunity by owner" (cache search)• Loas show: "Opportunity DB search results" (found in cache))Peturns cached CPM recordo5. Cache Hit Loas show•"Prospect match: Cache / local search hit"Returns existina opportunity data: & onnortunitv: 7842553 stage: 18775 }6. updateActivityCrmData() (Line 105-136)Gets oridinal activity data: stage: 18775• Calls Activitv->updateActivitvCrmData Line 121)• Gets current activity data: { stage: 18775 }• Loas: "Updated activity crm data" showina original data == current dataKev FindinaThe stade id was NOT chanaed hv this iohliison"original data": { "stage": 18775 }"current datall. "ctaag". 18775 %tthle mosnceel Contiqure Rulesª Contiaure Skills% Configure Workflows< Edit Memories•stage id: 18775 was already set on the activity before ConferenceCrmMatcherJob ranThe iob confirmed the existing data via cache hitNo actual chande occurredlWhen Was stage id Initially Set?Since this iob at 08:21:40 didn't chance the stage id (fit was already 18775). and vour activitv was created at 08:00:00)the stage id was likely set by:1Initiol extivity crastion vie colandar imnortlwahhask (hafara 09:21:10}Ask anvthina (84L)SWE-16WN Windsurf Toams 2109-21UTF.8io 4 spaces...
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38591
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NULL
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NULL
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NULL
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38592
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1433
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7
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2026-05-13T17:50:20.907019+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694620907_m1.jpg...
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PhpStorm
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faVsco.js – OpportunityRepository.php
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1
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monitor_1
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iTerm2ShellEditViewSessionlScriptsProfilesWindowHe iTerm2ShellEditViewSessionlScriptsProfilesWindowHelplabolA100% <7ec2-user@ip-10-30-129-190:~-zsh8•Wed 13 May 20:50:20181ec2-user@ip-10-20-31-14.₴7DOCKERO 81DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)|83ffmpeg€[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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-7477082713136142363
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click
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ocr
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iTerm2ShellEditViewSessionlScriptsProfilesWindowHe iTerm2ShellEditViewSessionlScriptsProfilesWindowHelplabolA100% <7ec2-user@ip-10-30-129-190:~-zsh8•Wed 13 May 20:50:20181ec2-user@ip-10-20-31-14.₴7DOCKERO 81DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)|83ffmpeg€[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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38595
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1434
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7
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2026-05-13T17:50:27.851040+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694627851_m2.jpg...
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PhpStorm
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faVsco.js – OpportunityRepository.php
|
1
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monitor_2
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PhostormFV faVsco.jsProledey© UserSettings.phpC) V PhostormFV faVsco.jsProledey© UserSettings.phpC) Vocabulary-pnp© VocabularyPronunciation.p© VoiceAccess.php© VoiceConsentPrefix.php› D Notifications> @ Observers> O Policiesv @ Providers© ActivityServiceProvider.ph© ApiServiceProvider.php€ AppServiceProvider.phpAuthServiceProvider.phpc) BroadcastserviceProvider.ll© CalendarServiceProvider.pC) CreateParticipantsService:©) crmServiceProvider.ohoC) EncrvotionServiceProviderC)EventServiceProvider.onoC) -uosootlourna ServicePro@ HubspotWebhookServicePC).liminnvServiceProvider.ohil© PlanhatServiceProvider.ph|C) PronhetHandlerServicePro© PusherServiceProvider.phpc) Queuel onServiceProvider il© QueueStatsdServiceProvid© ResponseMacroServiceProC) RouteServiceProvider.ong© SsoServiceProvider.php© UtilServiceProvider.php© ViewerGuardServiceProvid› D Queuev C Repositories> CAi> C AutoScorind> 0 Calendarv 0 Crmc) AccountRepositorv.phpc) contactRepositorv.phpc) contactRoleRevositorv.© CrmConfigurationReposC) CrmEntitvRenositorv.onC) FieldDataReoositor.ohiC) FieldRenositorv.oh(C) LavoutEntitvRepositorv.C) LavoutRenositorv.oho9 OpportunityRepository.p(C) RecordTvneFioldValuescode= custom.logscratch. &.isonA SF jiminny@localhost]& console [PROD]© ValidateSendingMessage.phpA console (EU]iid stages [EU]fiò teams (EU]© Activity.php X A console [STAGING]class Activity extends Model implements© DashboardController.phcC)JiminnyDebuacommand.ono2085-2086208/C) UpdateActivityElasticSearchDocumentCommand.php© ConferenceCrmMatcherJob.php© ImportParticipants.phpC) ProspectCache.php© OpportunityRepository.php x© UpdateSingleEntity.php© ActivityStatusin.phpclass OpportunityRepository implements RetentionRepositoryInterface41A3 л v 2091public function findOneByAccountAndOpportunity0wner(Configuration Sconfiguration,Account saccount,ant suserio?int ScontactId = null): ?Opportunity {return Sthis->buildAccountOpportunityQuery(Sconfiquration, Saccount, ScontactId)>where colu'user 1d', suser10)->t1rStprivate funct.ion buildAccount0pportunitvouervConfiquration Sconfiquration.2108Dint Scontactid = nulu•): HasMany 4|Scriteria = Sthis->resolve@nnortunitv0rderSconfiauration):return Sconfiauration>onnontunitieso->whene & colunlaccount idi Caccount->ao+Tdon->when(Scriterial'only_open'], fn (Squery) => $query->where( column: 'is_closed',onerator: falce)i-swhen(value: ScontactId !== null,fn ($query) => $query->orderByRaw(sql:'EXISTS (SELECT 1 FROM opportunity_contacts '.'WHERE opportunity_contacts.opportunity_id = opportunities.id'.'AND opportunity_contacts.contact id = ?) DESC'.[ScontactIdl2123—2124->orderBy(Scriterial'order_by']. Scriterial'direction'])* Sind all non-internal onportunities bu account ID and confiauration213394 434 AOpportunity|null,Contact|null,scage nullstring|null*} Srecordspuoiac functon updateActzvatycrmbata (array Srecords): voidExtract the records.[Slead. Saccount. Sopportunity. Scontact. Sstagel = Srecords:Sresolver = sthis->getUpdatecrmbataResolver:Sstrateay = Sresolve->resolveForActivitySlead. Scontact. Saccount)•if (Sstrategy == UpdateCrmDataByStrategy::Lead) 1// Also update the parent activity if required, checking we don't create a mixed lead/account record.if (Sthis->account_id === null && Sthis->contact_id === null && $this->lead_id === null) iSthis-Slead 1d = Slead->id+if (Sthis->stage_id === null && $stage) {$this->stage_id = $stage->id;Sthis->saveO:}elseif ($strategy == UpdateCrmDataByStrategy::Contact) {I/ Also update the parent activity if required, checking we don't create a mixed lead/account record.Sthis->lead id = null:if (Sthis->stage && Sthis->stage->qetType( === Staqe::TYPE LEAD) {sth1s->stage 1d = nulbII Don't trust previous matched account id as it might have been changed in the CRMif (Saccount &s Saccount->id |== Sthis->account id) {Sthis->account id = Saccount->id:if (Sthis->stage id === null && Sstage) {Sthis->stage id = Sstage->id.i* (Sonnontunitv && Sthis->onnontunitv id I== Connontunitv->id)&i€ (Sonnontunitv &c Sthis->value I== Sonnontunitv->value) ₫Sthic-svaluo - Connontunitv-svalno»100% L2Wed 13 May 20:50:27AskJiminnyReportActivityServiceTest vcascadeTrial Owner Role SeleRetactoring User EmaActivity Stage ID Upda# Open PreviewT. Share Conversation© Activity Stage ID Update InvestigatiorDownload Trajectory© Debugging Es Activity Update~ Cascade UsageQ, Download DiaanosticsDashboard Activity DebuggingCalls part icinantCrmLookun() for each3. participantCrmLookup() (Line 283-332)• Logs: "Prospect attendee found. Attempting to match to a CRM record"Calls findProsoectDataBvEmailo (Line 296)4. findProspectDataByEmail() (Line 399-433)• Uses GachedCrmServiceDecorator to search•Loas show: "Searching Hk for opportunity by owner" (cache search)• Loas show: "Opportunity DB search results" (found in cache))Peturns cached CPM recorde5. Cache Hit Loas show•"Prospect match: Cache / local search hit"Returns existina opportunity data: & onnortunitv: 7842553 stage: 18775 }6. updateActivityCrmData() (Line 105-136)Gets oridinal activity data: stage: 18775• Calls Activitv->updateActivitvCrmData Line 121)• Gets current activity data: { stage: 18775 }• Loas: "Updated activity crm data" showina original data == current dataKev FindinaThe stade id was NOT chanaed hv this iohliison"oriqinal data": " "stage": 18775"current datall. "ctaag". 18775 %tthle mosneeel Contiqure Rulesª Contiaure Skills% Configure Workflows< Edit Memories•stage id: 18775 was already set on the activity before ConferenceCrmMatcherJob ranThe iob confirmed the existing data via cache hitNo actual chande occurredlWhen Was stage id Initially Set?Since this iob at 08:21:40 didn't chance the stage id (fit was already 18775). and vour activitv was created at 08:00:00)the stage id was likely set by:1Initiol extivity crastion vie colandar imnortlwahhask (hafara 09:21:10}Ask anvthina (84L)SWE-16W Windsurf Toams 77-17 UTF.8io 4 spaces...
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NULL
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8185389216734164707
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NULL
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click
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ocr
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PhostormFV faVsco.jsProledey© UserSettings.phpC) V PhostormFV faVsco.jsProledey© UserSettings.phpC) Vocabulary-pnp© VocabularyPronunciation.p© VoiceAccess.php© VoiceConsentPrefix.php› D Notifications> @ Observers> O Policiesv @ Providers© ActivityServiceProvider.ph© ApiServiceProvider.php€ AppServiceProvider.phpAuthServiceProvider.phpc) BroadcastserviceProvider.ll© CalendarServiceProvider.pC) CreateParticipantsService:©) crmServiceProvider.ohoC) EncrvotionServiceProviderC)EventServiceProvider.onoC) -uosootlourna ServicePro@ HubspotWebhookServicePC).liminnvServiceProvider.ohil© PlanhatServiceProvider.ph|C) PronhetHandlerServicePro© PusherServiceProvider.phpc) Queuel onServiceProvider il© QueueStatsdServiceProvid© ResponseMacroServiceProC) RouteServiceProvider.ong© SsoServiceProvider.php© UtilServiceProvider.php© ViewerGuardServiceProvid› D Queuev C Repositories> CAi> C AutoScorind> 0 Calendarv 0 Crmc) AccountRepositorv.phpc) contactRepositorv.phpc) contactRoleRevositorv.© CrmConfigurationReposC) CrmEntitvRenositorv.onC) FieldDataReoositor.ohiC) FieldRenositorv.oh(C) LavoutEntitvRepositorv.C) LavoutRenositorv.oho9 OpportunityRepository.p(C) RecordTvneFioldValuescode= custom.logscratch. &.isonA SF jiminny@localhost]& console [PROD]© ValidateSendingMessage.phpA console (EU]iid stages [EU]fiò teams (EU]© Activity.php X A console [STAGING]class Activity extends Model implements© DashboardController.phcC)JiminnyDebuacommand.ono2085-2086208/C) UpdateActivityElasticSearchDocumentCommand.php© ConferenceCrmMatcherJob.php© ImportParticipants.phpC) ProspectCache.php© OpportunityRepository.php x© UpdateSingleEntity.php© ActivityStatusin.phpclass OpportunityRepository implements RetentionRepositoryInterface41A3 л v 2091public function findOneByAccountAndOpportunity0wner(Configuration Sconfiguration,Account saccount,ant suserio?int ScontactId = null): ?Opportunity {return Sthis->buildAccountOpportunityQuery(Sconfiquration, Saccount, ScontactId)>where colu'user 1d', suser10)->t1rStprivate funct.ion buildAccount0pportunitvouervConfiquration Sconfiquration.2108Dint Scontactid = nulu•): HasMany 4|Scriteria = Sthis->resolve@nnortunitv0rderSconfiauration):return Sconfiauration>onnontunitieso->whene & colunlaccount idi Caccount->ao+Tdon->when(Scriterial'only_open'], fn (Squery) => $query->where( column: 'is_closed',onerator: falce)i-swhen(value: ScontactId !== null,fn ($query) => $query->orderByRaw(sql:'EXISTS (SELECT 1 FROM opportunity_contacts '.'WHERE opportunity_contacts.opportunity_id = opportunities.id'.'AND opportunity_contacts.contact id = ?) DESC'.[ScontactIdl2123—2124->orderBy(Scriterial'order_by']. Scriterial'direction'])* Sind all non-internal onportunities bu account ID and confiauration213394 434 AOpportunity|null,Contact|null,scage nullstring|null*} Srecordspuoiac functon updateActzvatycrmbata (array Srecords): voidExtract the records.[Slead. Saccount. Sopportunity. Scontact. Sstagel = Srecords:Sresolver = sthis->getUpdatecrmbataResolver:Sstrateay = Sresolve->resolveForActivitySlead. Scontact. Saccount)•if (Sstrategy == UpdateCrmDataByStrategy::Lead) 1// Also update the parent activity if required, checking we don't create a mixed lead/account record.if (Sthis->account_id === null && Sthis->contact_id === null && $this->lead_id === null) iSthis-Slead 1d = Slead->id+if (Sthis->stage_id === null && $stage) {$this->stage_id = $stage->id;Sthis->saveO:}elseif ($strategy == UpdateCrmDataByStrategy::Contact) {I/ Also update the parent activity if required, checking we don't create a mixed lead/account record.Sthis->lead id = null:if (Sthis->stage && Sthis->stage->qetType( === Staqe::TYPE LEAD) {sth1s->stage 1d = nulbII Don't trust previous matched account id as it might have been changed in the CRMif (Saccount &s Saccount->id |== Sthis->account id) {Sthis->account id = Saccount->id:if (Sthis->stage id === null && Sstage) {Sthis->stage id = Sstage->id.i* (Sonnontunitv && Sthis->onnontunitv id I== Connontunitv->id)&i€ (Sonnontunitv &c Sthis->value I== Sonnontunitv->value) ₫Sthic-svaluo - Connontunitv-svalno»100% L2Wed 13 May 20:50:27AskJiminnyReportActivityServiceTest vcascadeTrial Owner Role SeleRetactoring User EmaActivity Stage ID Upda# Open PreviewT. Share Conversation© Activity Stage ID Update InvestigatiorDownload Trajectory© Debugging Es Activity Update~ Cascade UsageQ, Download DiaanosticsDashboard Activity DebuggingCalls part icinantCrmLookun() for each3. participantCrmLookup() (Line 283-332)• Logs: "Prospect attendee found. Attempting to match to a CRM record"Calls findProsoectDataBvEmailo (Line 296)4. findProspectDataByEmail() (Line 399-433)• Uses GachedCrmServiceDecorator to search•Loas show: "Searching Hk for opportunity by owner" (cache search)• Loas show: "Opportunity DB search results" (found in cache))Peturns cached CPM recorde5. Cache Hit Loas show•"Prospect match: Cache / local search hit"Returns existina opportunity data: & onnortunitv: 7842553 stage: 18775 }6. updateActivityCrmData() (Line 105-136)Gets oridinal activity data: stage: 18775• Calls Activitv->updateActivitvCrmData Line 121)• Gets current activity data: { stage: 18775 }• Loas: "Updated activity crm data" showina original data == current dataKev FindinaThe stade id was NOT chanaed hv this iohliison"oriqinal data": " "stage": 18775"current datall. "ctaag". 18775 %tthle mosneeel Contiqure Rulesª Contiaure Skills% Configure Workflows< Edit Memories•stage id: 18775 was already set on the activity before ConferenceCrmMatcherJob ranThe iob confirmed the existing data via cache hitNo actual chande occurredlWhen Was stage id Initially Set?Since this iob at 08:21:40 didn't chance the stage id (fit was already 18775). and vour activitv was created at 08:00:00)the stage id was likely set by:1Initiol extivity crastion vie colandar imnortlwahhask (hafara 09:21:10}Ask anvthina (84L)SWE-16W Windsurf Toams 77-17 UTF.8io 4 spaces...
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38594
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1433
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8
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2026-05-13T17:50:27.873334+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694627873_m1.jpg...
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PhpStorm
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faVsco.js – OpportunityRepository.php
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1
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NULL
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monitor_1
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NULL
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NULL
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NULL
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NULL
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelplabolAec2-user@ip-10-30-129-190:~-zsh100% <78•Wed 13 May 20:50:27181ec2-user@ip-10-20-31-14…..₴7DOCKER₴81DEV (docker)Last login: Wed May 13 09:16:21on ttys010$82APP (-zsh)|83screenpipe"€[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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NULL
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-1602560510040588441
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NULL
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click
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ocr
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NULL
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelplabolAec2-user@ip-10-30-129-190:~-zsh100% <78•Wed 13 May 20:50:27181ec2-user@ip-10-20-31-14…..₴7DOCKER₴81DEV (docker)Last login: Wed May 13 09:16:21on ttys010$82APP (-zsh)|83screenpipe"€[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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38592
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NULL
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38596
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1433
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9
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2026-05-13T17:50:30.556863+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694630556_m1.jpg...
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PhpStorm
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faVsco.js – OpportunityRepository.php
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1
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NULL
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monitor_1
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NULL
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NULL
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NULL
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NULL
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iTerm2ShellEditViewSessionlScriptsProfilesWindowHe iTerm2ShellEditViewSessionlScriptsProfilesWindowHelplabolA100% <7ec2-user@ip-10-30-129-190:~-zsh*48•Wed 13 May 20:50:30181ec2-user@ip-10-20-31-14.₴7DOCKERO 81DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version 2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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NULL
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-1802263130619597378
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NULL
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click
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ocr
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NULL
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iTerm2ShellEditViewSessionlScriptsProfilesWindowHe iTerm2ShellEditViewSessionlScriptsProfilesWindowHelplabolA100% <7ec2-user@ip-10-30-129-190:~-zsh*48•Wed 13 May 20:50:30181ec2-user@ip-10-20-31-14.₴7DOCKERO 81DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version 2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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NULL
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38597
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1434
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8
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2026-05-13T17:50:33.264952+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694633264_m2.jpg...
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PhpStorm
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faVsco.js – OpportunityRepository.php
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1
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NULL
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monitor_2
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NULL
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NULL
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NULL
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Project: faVsco.js, menu
master, menu
|
[{"role":"AXButton","text" [{"role":"AXButton","text":"Project: faVsco.js, menu","depth":5,"bounds":{"left":0.025930852,"top":0.019952115,"width":0.03856383,"height":0.025538707},"on_screen":true,"help_text":"~/jiminny/app","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"master, menu","depth":5,"bounds":{"left":0.064494684,"top":0.019952115,"width":0.040226065,"height":0.025538707},"on_screen":true,"help_text":"Git Branch: master<br/>Some incoming commits are not fetched<br/>","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false}]...
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-7673782238848625796
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-8646559087753982588
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click
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hybrid
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NULL
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Project: faVsco.js, menu
master, menu
PhostormFV f Project: faVsco.js, menu
master, menu
PhostormFV faVsco.jsroledey© UserSettings.phpC) Vocabulary-pnp© VocabularyPronunciation.p© VoiceAccess.php© VoiceConsentPrefix.php› D Notifications> @ Observers> O Policiesv @ Providers© ActivityServiceProvider.ph© ApiServiceProvider.php€ AppServiceProvider.phpAuthServiceProvider.phpc) BroadcastserviceProvider.ll© CalendarServiceProvider.pC) CreateParticipantsService:©) crmServiceProvider.ohoC) EncrvotionServiceProviderC)EventServiceProvider.onoC) -uosootlourna ServicePro@ HubspotWebhookServicePC).liminnvServiceProvider.ohil© PlanhatServiceProvider.ph|C) PronhetHandlerServicePro© PusherServiceProvider.phpc) Queuel onServiceProvider il© QueueStatsdServiceProvid© ResponseMacroServiceProC) RouteServiceProvider.ong© SsoServiceProvider.php© UtilServiceProvider.php© ViewerGuardServiceProvid› D Queuev [ Repositories> CAi> C AutoScorind> 0 Calendarv 0 Crmc) AccountRepositorv.phpc) contactRepositorv.phpc) contactRoleRevositorv.© CrmConfigurationReposC) CrmEntitvRenositorv.onC) FieldDataReoositor.ohiC) FieldRenositorv.oh(C) LavoutEntitvRepositorv.C) LavoutRenositorv.oho9 OpportunityRepository.p(C) RecordTvneSioldValuescode= custom.logscratch. &.isonA SF jiminny@localhost]& console [PROD]© ValidateSendingMessage.phpA console (EU]iid stages [EU]fiò teams (EU]© Activity.php X A console [STAGING]class Activity extends Model implements© DashboardController.phcC)JiminnyDebuacommand.ono2085-2086208/C) UpdateActivityElasticSearchDocumentCommand.php© ConferenceCrmMatcherJob.php© ImportParticipants.phpC) ProspectCache.php© OpportunityRepository.php x© UpdateSingleEntity.php() ActivityStatusin.phpclass OpportunityRepository implements RetentionRepositoryInterface41A3 л v 2091public function findOneByAccountAndOpportunity0wner(Configuration Sconfiguration,Account saccount,ant suserio?int ScontactId = null): ?Opportunity {return Sthis->buildAccountOpportunityQuery(Sconfiquration, Saccount, ScontactId)>where colu'user 1d', suser10)->t1rStprivate funct.ion buildAccount0pportunitvouervConfiquration Sconfiquration.2108Dint Scontactid = nulu•): HasMany 4|Scriteria = Sthis->resolve@onortunitv0rderSconfiauration):return Sconfiauration>onnontunitieso->whene & colunlaccount idi Caccount->ao+Tdon->when(Scriterial'only_open'], fn (Squery) => $query->where( column: 'is_closed',onerator falco)))-swhen(value: ScontactId !== null,fn ($query) => $query->orderByRaw(sql:'EXISTS (SELECT 1 FROM opportunity_contacts '.'WHERE opportunity_contacts.opportunity_id = opportunities.id'.'AND opportunity_contacts.contact id = ?) DESC'.[ScontactIdl2123—2124->orderBy(Scriterial'order_by']. Scriterial'direction'])* Sind all non-internal onportunities bu account ID and confiauration213394 434 AOpportunity|null,Contact|null,scage nullstring|null*} Srecordspuoiac functaon updateActzvatycrmbata (array Srecords): voidExtract the records.[Slead. Saccount. Sopportunity. Scontact. Sstagel = Srecords:Sresolver = sthis->getUpdatecrmbataResolver:Sstrateay = Sresolve->resolveForActivitySlead. Scontact. Saccount)•if (Sstrategy == UpdateCrmDataByStrategy::Lead) 1// Also update the parent activity if required, checking we don't create a mixed lead/account record.if (Sthis->account_id === null && Sthis->contact_id === null && $this->lead_id === null) iSthis-Slead 1d = Slead->id»if (Sthis->stage_id === null && $stage) {$this->stage_id = $stage->id;Sthis->saveO:}elseif ($strategy == UpdateCrmDataByStrategy::Contact) {I/ Also update the parent activity if required, checking we don't create a mixed lead/account record.Sthis->lead id = null:if (Sthis->stage && $this->stage->qetType( === Staqe::TYPE LEAD) {sth1s->stage 1d = nulbII Don't trust previous matched account id as it might have been changed in the CRMif (Saccount &s Saccount->id |== Sthis->account id) {Sthis->account id = Saccount->id:if (Sthis->stage id === null && Sstage) {Sthis->stage id = Sstage->id.i* (Sonnontunitv && Sthis->onnontunitv id I== Connontunitv->id)&i€ (Sonnontunitv &c Sthis->value I== Sonnontunitv->value) ₫Sthic-svaluo - Connontunitv-svalno»100% 2Wed 13 May 20:50:32AskJiminnyReportActivityServiceTest vcascadeTrial Owner Role SeleRetactoring User EmaActivity Stage ID Upda# Open PreviewT. Share Conversation© Activity Stage ID Update InvestigatiorDownload Trajectory© Debugging Es Activity Update~ Cascade UsageQ, Download DiaanosticsDashboard Activity DebuggingCalls narticinantCrmLookun() for each3. participantCrmLookup() (Line 283-332)• Logs: "Prospect attendee found. Attempting to match to a CRM record"Calls findProsoectDataBvEmailo (Line 296)4. findProspectDataByEmail() (Line 399-433)• Uses GachedCrmServiceDecorator to search•Loas show: "Searching Hk for opportunity by owner" (cache search)• Loas show: "Opportunity DB search results" (found in cache))Peturns cached CPM recorde5. Cache Hit Loas show•"Prospect match: Cache / local search hit"Returns existina opportunity data: & onnortunitv: 7842553 stage: 18775 }6. updateActivityCrmData() (Line 105-136)Gets oridinal activity data: stage: 18775• Calls Activitv->updateActivitvCrmData Line 121)• Gets current activity data: { stage: 18775 }• Loas: "Updated activity crm data" showina original data == current dataKev FindinaThe stade id was NOT chanaed hv this iohliison"oriqinal data": " "stage": 18775"current datall. "ctaag". 18775 %tthle mosneeel Contiqure Rulesª Contiaure Skills% Configure Workflows< Edit Memories•stage id: 18775 was already set on the activity before ConferenceCrmMatcherJob ranThe iob confirmed the existing data via cache hitNo actual chande occurredlWhen Was stage id Initially Set?Since this iob at 08:21:40 didn't chance the stage id (fit was already 18775). and vour activitv was created at 08:00:00)the stage id was likely set by:1Initiol extivity crastion vie colandar imnortlwahhask (hafara 09:21:10}Ask anvthina (84L)SWE-16W Windsurf Toams 77-17 UTF.8io 4 spaces...
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faVsco.js – OpportunityRepository.php
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Project: faVsco.js, menu
master, menu
Start Listen Project: faVsco.js, menu
master, menu
Start Listening for PHP Debug Connections
AskJiminnyReportActivityServiceTest
Run 'AskJiminnyReportActivityServiceTest'...
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Project: faVsco.js, menu
master, menu
Start Listen Project: faVsco.js, menu
master, menu
Start Listening for PHP Debug Connections
AskJiminnyReportActivityServiceTest
Run 'AskJiminnyReportActivityServiceTest'
iTerm2ShellEditViewSessionlScriptsProfilesWindowHelplabolA100% <7ec2-user@ip-10-30-129-190:~-zsh*48•Wed 13 May 20:50:33181ec2-user@ip-10-20-31-14.₴7DOCKERO 81DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)|[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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NN1 (SRD-6848] Sidekick SMS issue -Platform Sprin NN1 (SRD-6848] Sidekick SMS issue -Platform Sprin 4 Q2 - Platform Te:( Dependabot aleris-jiminmyier. x® Elastic Container Service B 53 ® Coder3o?) Aurora and RDSiố AmazCloudWatch > worker-default/worker-default/bc099028c55140e3b94c9273f776c526 > worker-default> Log management@ CloudFrontaia MediaLiveCloudWatchLog eventsYou can use the filter bar below to search for and match terms, phrases, or values in your log events. Learn more about filter patterns L?HomeDMSJiminny …..yEh External connections# StarredÔ jiminny-x-integrati…..& platform-inner-team@ Channels# ai-chapter# alerts# backend# bugs# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launchesi random# releases# sofia-office# support# thank-vous# the_people_of jimi...•? Direct messages88. Mario Georgiev€. Vasil VasilevC. Nikolay Ivanov2o James Graham2. Stoyan Tanev #P. Galya DimitrovaR. Steliyan Georgiev "( Petko KashinskiA. Aneliya Angelovaf. Stefka Stoyanova. Lukas Kovalik y...# AppsJira Cloud• ToastQ Describe what you are looking forUnreads E Al conversations ~ Sorted by recommended order ~• 0 loastReview Toast APP 2:23 PMPR review requested by @stefka-jiminny on @nikolaybiaivanov's PRPR review requested by stefka-jiminny on nikolaybiaivanov's PR#12058 JY-18091 | Update composer to support php 8.5 by| 10 commits • 260 files changedJIRA: JY-18091Deployment notes:• Noneninny/apoAdded by Toast for GitHub• • Jira CloudJira Cloud APP 6:00 PM# @Stefka Stoyanova created a Technical Story you are assigned toJY-20897 [Laravel 13] Testing of Platform DomainStatus: BacklogType: Technical StoryLK Assignee: Lukas Kovalik1 Priority: Medium4 @Stefka Stoyanova updated the description of a Technical Story You are assigned toJY-16113 |Laravel 12esting of Plattorm DomainTvoe: Technical StoryLK) Assignee: Lukas KovalikT Priority: Medium_ @Stefka Stoyanova assigned a Technical Story from you — UnassignedJY-20897 (Laravel 13] Testing of Platform DomainStatus: BacklogType: Technical StoryAcciones- Unaccioned1 Prioritur MediumTransitionMore actions...Mark All Messages Read• wea 13 May 20:00..Mark as Read3 messages Press Esc toMark as Read...
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NN1 (SRD-6848] Sidekick SMS issue -Platform Sprin NN1 (SRD-6848] Sidekick SMS issue -Platform Sprin 4 Q2 - Platform Te:( Dependabot aleris-jiminmyier. x® Elastic Container Service B 53 ® Coder3o?) Aurora and RDSiố AmazCloudWatch > worker-default/worker-default/bc099028c55140e3b94c9273f776c526 > worker-default> Log management@ CloudFrontaia MediaLiveCloudWatchLog eventsYou can use the filter bar below to search for and match terms, phrases, or values in your log events. Learn more about filter patterns L?HomeDMSJiminny …..yEh External connections# StarredÔ jiminny-x-integrati…..& platform-inner-team@ Channels# ai-chapter# alerts# backend# bugs# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launchesi random# releases# sofia-office# support# thank-vous# the_people_of jimi...•? Direct messages88. Mario Georgiev€. Vasil VasilevC. Nikolay Ivanov2o James Graham2. Stoyan Tanev #P. Galya DimitrovaR. Steliyan Georgiev "( Petko KashinskiA. Aneliya Angelovaf. Stefka Stoyanova. Lukas Kovalik y...# AppsJira Cloud• ToastQ Describe what you are looking forUnreads E Al conversations ~ Sorted by recommended order ~• 0 loastReview Toast APP 2:23 PMPR review requested by @stefka-jiminny on @nikolaybiaivanov's PRPR review requested by stefka-jiminny on nikolaybiaivanov's PR#12058 JY-18091 | Update composer to support php 8.5 by| 10 commits • 260 files changedJIRA: JY-18091Deployment notes:• Noneninny/apoAdded by Toast for GitHub• • Jira CloudJira Cloud APP 6:00 PM# @Stefka Stoyanova created a Technical Story you are assigned toJY-20897 [Laravel 13] Testing of Platform DomainStatus: BacklogType: Technical StoryLK Assignee: Lukas Kovalik1 Priority: Medium4 @Stefka Stoyanova updated the description of a Technical Story You are assigned toJY-16113 |Laravel 12esting of Plattorm DomainTvoe: Technical StoryLK) Assignee: Lukas KovalikT Priority: Medium_ @Stefka Stoyanova assigned a Technical Story from you — UnassignedJY-20897 (Laravel 13] Testing of Platform DomainStatus: BacklogType: Technical StoryAcciones- Unaccioned1 Prioritur MediumTransitionMore actions...Mark All Messages Read• wea 13 May 20:00..Mark as Read3 messages Press Esc toMark as Read...
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Last login: Wed May 13 09:16:21 on ttys010
Poetry Last login: Wed May 13 09:16:21 on ttys010
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
ec2-user@ip-10-30-129-190:~ (nc)
Close Tab
ec2-user@ip-10-20-31-146:~ (nc)
Close Tab
⌥⌘1
ec2-user@ip-10-30-129-190:~...
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login: Wed May 13 09:16:21 on ttys010\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80\nEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalik@jiminny.com: \nWarning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.\n\nA newer release of \"Amazon Linux\" is available.\n Version 2023.10.20260330:\n Version 2023.11.20260406:\n Version 2023.11.20260413:\n Version 2023.11.20260427:\n Version 2023.11.20260505:\n Version 2023.11.20260509:\nRun \"/usr/bin/dnf check-release-update\" for full release and version update info\n , #_\n ~\\_ ####_\n ~~ \\_#####\\\n ~~ \\###|\n ~~ \\#/ ___ Amazon Linux 2023 (ECS Optimized)\n ~~ V~' '->\n ~~~ /\n ~~._. _/\n _/ _/\n _/m/'\n\nFor documentation, visit 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Last login: Wed May 13 09:16:21 on ttys010
Poetry Last login: Wed May 13 09:16:21 on ttys010
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$
DOCKER
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DEV (docker)
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screenpipe"
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ec2-user@ip-10-30-129-190:~ (nc)
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ec2-user@ip-10-20-31-146:~ (nc)
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⌥⌘1
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eu-west-1.console.aws.amazon.com/cloudwatch/home?r eu-west-1.console.aws.amazon.com/cloudwatch/home?region=eu-west-1#logsV2:log-groups/log-group/worker-default/log-events/worker-default$252Fworker-default$252Fbc099028c55140e3b94c9273f776c526$3Fstart$3D2026-05-08T08$253A21$253A40.263Z...
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Usage | Windsurf
Usage | Windsurf
JY-20891 add sup Usage | Windsurf
Usage | Windsurf
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
Close tab
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Useful commands - Engineering - Confluence
Useful commands - Engineering - Confluence
Dev Tools - Elastic
Dev Tools - Elastic
Jiminny
Jiminny
[SRD-6853] Moxso - Potential deal stages bug - Jira
[SRD-6853] Moxso - Potential deal stages bug - Jira
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Usage | Windsurf
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JY-20891 add sup Usage | Windsurf
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
Jiminny
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Configure SSH access to multiple environment - Engineering - Confluence
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Useful commands - Engineering - Confluence
Useful commands - Engineering - Confluence
Dev Tools - Elastic
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[SRD-6853] Moxso - Potential deal stages bug - Jira
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
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[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
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Configure SSH access to multiple environment - Engineering - Confluence
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Useful commands - Engineering - Confluence
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
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Configure SSH access to multiple environment - Engineering - Confluence
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[SRD-6853] Moxso - Potential deal stages bug - Jira
[SRD-6853] Moxso - Potential deal stages bug - Jira
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JY-208 Usage | Windsurf
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Useful commands - Engineering - Confluence
Useful commands - Engineering - Confluence
Dev Tools - Elastic...
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Useful commands - Engineering - Confluence
Useful commands - Engineering - Confluence
Dev Tools - Elastic...
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NULL
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NULL
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NULL
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NULL
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38603
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1433
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13
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2026-05-13T17:51:08.170662+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694668170_m1.jpg...
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windsurf.com/subscription/usage
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Usage | Windsurf
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Useful commands - Engineering - Confluence
Useful commands - Engineering - Confluence
Dev Tools - Elastic
Dev Tools - Elastic
Jiminny
Jiminny
[SRD-6853] Moxso - Potential deal stages bug - Jira...
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
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Useful commands - Engineering - Confluence
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Jiminny
Jiminny
[SRD-6853] Moxso - Potential deal stages bug - Jira...
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Useful commands - Engineering - Confluence
Useful commands - Engineering - Confluence
Dev Tools - Elastic
Dev Tools - Elastic
Jiminny
Jiminny
[SRD-6853] Moxso - Potential deal stages bug - Jira
[SRD-6853] Moxso - Potential deal stages bug - Jira
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
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Configure SSH access to multiple environment - Engineering - Confluence
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Useful commands - Engineering - Confluence
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Dev Tools - Elastic
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Jiminny
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[SRD-6853] Moxso - Potential deal stages bug - Jira
[SRD-6853] Moxso - Potential deal stages bug - Jira
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Screenpipe — Archive
Screenpipe — Archive
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Manage extra usage for paid Claude plans | Claude Help Center
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NULL
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NULL
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NULL
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NULL
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38606
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1433
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2026-05-13T17:51:13.716384+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694673716_m1.jpg...
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Firefox
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Claude — Personal
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1
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claude.ai/settings/usage
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monitor_1
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NULL
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NULL
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NULL
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NULL
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Screenpipe — Archive
Screenpipe — Archive
All docs Screenpipe — Archive
Screenpipe — Archive
All docs · AFFiNE
All docs · AFFiNE
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Manage extra usage for paid Claude plans | Claude Help Center
Manage extra usage for paid Claude plans | Claude Help Center
2 TB in 25 MB/s - Google Search
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3920472681682315476
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click
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accessibility
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NULL
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Screenpipe — Archive
Screenpipe — Archive
All docs Screenpipe — Archive
Screenpipe — Archive
All docs · AFFiNE
All docs · AFFiNE
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
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Screenpipe — Archive
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SQLite Web: archive.db
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SQLite Web: db.sqlite
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Claude
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Manage extra usage for paid Claude plans | Claude Help Center
Manage extra usage for paid Claude plans | Claude Help Center
2 TB in 25 MB/s - Google Search
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New Tab
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38603
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NULL
|
NULL
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NULL
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38608
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1433
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15
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2026-05-13T17:51:14.665013+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694674665_m1.jpg...
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Firefox
|
Manage extra usage for paid Claude plans | Claude Manage extra usage for paid Claude plans | Claude Help Center — Personal...
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1
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support.claude.com/en/articles/12429409-manage-ext support.claude.com/en/articles/12429409-manage-extra-usage-for-paid-claude-plans...
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monitor_1
|
NULL
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NULL
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NULL
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NULL
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Screenpipe — Archive
Screenpipe — Archive
All docs Screenpipe — Archive
Screenpipe — Archive
All docs · AFFiNE
All docs · AFFiNE
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
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Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
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Claude
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Manage extra usage for paid Claude plans | Claude Help Center
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Open menu for conversation actions....
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Screenpipe — Archive
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Screenpipe — Archive
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You said...
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Screenpipe — Archive
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You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
You said
Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
Listen
Show thinking
Gemini said
Gemini said
Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.
ScreenPipe is fundamentally designed to be a
100% local, privacy-first
application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.
View source details. Opens side panel.
1. Where It Starts: The Capture Layer
1. Where It Starts: The Capture Layer
The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:
System Audio:
Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).
Microphone Input:
Everything you say into your mic.
View source details. Opens side panel.
Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.
2. How It Gets Transferred and Transcribed
2. How It Gets Transferred and Transcribed
Because ScreenPipe prioritizes local processing, the "transfer" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.
Here is the transcription pipeline:
The Engine:
The raw audio chunks are fed into a local speech-to-text model.
By default, ScreenPipe uses
OpenAI Whisper
running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).
View source details. Opens side panel.
Diarization:
As it transcribes the text, the engine also performs "diarization"—a technical term for speaker identification.
It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.
View source details. Opens side panel.
Storage:
The final transcribed text is then indexed into a local
SQLite database
. This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.
3. The "Work in Progress" (WIP) Stage
3. The "Work in Progress" (WIP) Stage
There is a slight bottleneck between
hearing
the audio and
saving
the text, which acts as the WIP stage:
Buffering:
Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.
Processing Queue:
Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.
Finalization:
Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.
4. Understanding the Folder Structure
4. Understanding the Folder Structure
All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like
~/.screenpipe
on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:
The SQLite Database (
):
This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is "done."
The
or
folders:
This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.
Temp Files:
If you see rapidly changing files, temporary
chunks, or locked database journals (like
), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.
Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?
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Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":24,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ScreenPipe is fundamentally designed to be a","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"100% local, privacy-first","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":27,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"1. Where It Starts: The Capture Layer","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Where It Starts: The Capture Layer","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"System Audio:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Microphone Input:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Everything you say into your mic.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How It Gets Transferred and Transcribed","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How It Gets Transferred and Transcribed","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Because ScreenPipe prioritizes local processing, the \"transfer\" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is the transcription pipeline:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Engine:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The raw audio chunks are fed into a local speech-to-text model.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, ScreenPipe uses","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"OpenAI Whisper","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Diarization:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"As it transcribes the text, the engine also performs \"diarization\"—a technical term for speaker identification.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. 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The \"Work in Progress\" (WIP) Stage","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. The \"Work in Progress\" (WIP) Stage","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"There is a slight bottleneck between","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"hearing","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the audio and","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"saving","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the text, which acts as the WIP stage:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Buffering:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Processing Queue:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Finalization:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"4. Understanding the Folder Structure","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"4. Understanding the Folder Structure","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The SQLite Database (","depth":29,"bounds":{"left":0.09142287,"top":0.0,"width":0.05817819,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"):","depth":29,"bounds":{"left":0.17885639,"top":0.0,"width":0.0034906915,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is \"done.\"","depth":29,"bounds":{"left":0.09142287,"top":0.0,"width":0.21010639,"height":0.037110932},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The","depth":29,"bounds":{"left":0.09142287,"top":0.0,"width":0.011303191,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":29,"bounds":{"left":0.120678194,"top":0.0,"width":0.008144947,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"folders:","depth":29,"bounds":{"left":0.14960106,"top":0.0,"width":0.020944148,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is where the compressed, raw audio files and JPEG screenshots are stored permanently. 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You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
You said
Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
Listen
Show thinking
Gemini said
Gemini said
Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.
ScreenPipe is fundamentally designed to be a
100% local, privacy-first
application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.
View source details. Opens side panel.
1. Where It Starts: The Capture Layer
1. Where It Starts: The Capture Layer
The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:
System Audio:
Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).
Microphone Input:
Everything you say into your mic.
View source details. Opens side panel.
Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.
2. How It Gets Transferred and Transcribed
2. How It Gets Transferred and Transcribed
Because ScreenPipe prioritizes local processing, the "transfer" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.
Here is the transcription pipeline:
The Engine:
The raw audio chunks are fed into a local speech-to-text model.
By default, ScreenPipe uses
OpenAI Whisper
running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).
View source details. Opens side panel.
Diarization:
As it transcribes the text, the engine also performs "diarization"—a technical term for speaker identification.
It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.
View source details. Opens side panel.
Storage:
The final transcribed text is then indexed into a local
SQLite database
. This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.
3. The "Work in Progress" (WIP) Stage
3. The "Work in Progress" (WIP) Stage
There is a slight bottleneck between
hearing
the audio and
saving
the text, which acts as the WIP stage:
Buffering:
Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.
Processing Queue:
Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.
Finalization:
Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.
4. Understanding the Folder Structure
4. Understanding the Folder Structure
All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like
~/.screenpipe
on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:
The SQLite Database (
):
This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is "done."
The
or
folders:
This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.
Temp Files:
If you see rapidly changing files, temporary
chunks, or locked database journals (like
), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.
Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694675646_m1.jpg...
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Copy prompt
You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
You said
Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
Listen
Show thinking
Gemini said
Gemini said
Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.
ScreenPipe is fundamentally designed to be a
100% local, privacy-first
application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.
View source details. Opens side panel.
1. Where It Starts: The Capture Layer
1. Where It Starts: The Capture Layer
The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:
System Audio:
Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).
Microphone Input:
Everything you say into your mic.
View source details. Opens side panel.
Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.
2. How It Gets Transferred and Transcribed
2. How It Gets Transferred and Transcribed
Because ScreenPipe prioritizes local processing, the "transfer" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.
Here is the transcription pipeline:
The Engine:
The raw audio chunks are fed into a local speech-to-text model.
By default, ScreenPipe uses
OpenAI Whisper
running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).
View source details. Opens side panel.
Diarization:
As it transcribes the text, the engine also performs "diarization"—a technical term for speaker identification.
It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.
View source details. Opens side panel.
Storage:
The final transcribed text is then indexed into a local
SQLite database
. This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.
3. The "Work in Progress" (WIP) Stage
3. The "Work in Progress" (WIP) Stage
There is a slight bottleneck between
hearing
the audio and
saving
the text, which acts as the WIP stage:
Buffering:
Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.
Processing Queue:
Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.
Finalization:
Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.
4. Understanding the Folder Structure
4. Understanding the Folder Structure
All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like
~/.screenpipe
on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:
The SQLite Database (
):
This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is "done."
The
or
folders:
This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.
Temp Files:
If you see rapidly changing files, temporary
chunks, or locked database journals (like
), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.
Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?
Sources
Sources
Good response
Bad response
Share and export
Copy
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Copy prompt
You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
You said
I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
Expand
Listen
Show thinking
Gemini said
Gemini said
Yes, those
.mp4
files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.
Here is exactly what those files are doing sitting in your
~/.screenpipe/data/
directory and how they interact with the rest of the system.
1. The "Time Machine" Playback
1. The "Time Machine" Playback
The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the
db.sqlite
database along with
precise timestamps and file path references
.
When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific
.mp4
file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.
2. Re-processing and Model Upgrades
2. Re-processing and Model Upgrades
Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw
.mp4
files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.
3. The Source of Truth for Hallucinations
3. The Source of Truth for Hallucinations
Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that
.mp4
file is your fallback source of truth to verify what was actually said.
How the Database Views Them
How the Database Views Them
If you were to open up your
db.sqlite
and query the tables (e.g.,
audio_transcriptions
), you would see that the database treats the
~/.screenpipe/data/
folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like
soundcore AeroClip (input)_2026-05-12_07-40-48.mp4
.
What happens if you delete them?
If you manually...
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Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":24,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ScreenPipe is fundamentally designed to be a","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"100% local, privacy-first","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":27,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"1. Where It Starts: The Capture Layer","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Where It Starts: The Capture Layer","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"System Audio:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Microphone Input:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Everything you say into your mic.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How It Gets Transferred and Transcribed","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How It Gets Transferred and Transcribed","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Because ScreenPipe prioritizes local processing, the \"transfer\" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is the transcription pipeline:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Engine:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The raw audio chunks are fed into a local speech-to-text model.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, ScreenPipe uses","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"OpenAI Whisper","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Diarization:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"As it transcribes the text, the engine also performs \"diarization\"—a technical term for speaker identification.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Storage:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The final transcribed text is then indexed into a local","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SQLite database","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. The \"Work in Progress\" (WIP) Stage","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. The \"Work in Progress\" (WIP) Stage","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"There is a slight bottleneck between","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"hearing","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the audio and","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"saving","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the text, which acts as the WIP stage:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Buffering:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Processing Queue:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Finalization:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"4. Understanding the Folder Structure","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"4. Understanding the Folder Structure","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The SQLite Database (","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"):","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is \"done.\"","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"folders:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Temp Files:","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you see rapidly changing files, temporary","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"chunks, or locked database journals (like","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Sources","depth":26,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Sources","depth":28,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Good response","depth":24,"on_screen":true,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Bad response","depth":24,"on_screen":true,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Share and export","depth":23,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":24,"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":23,"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy prompt","depth":21,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":24,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yes, those","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is exactly what those files are doing sitting in your","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe/data/","depth":28,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"directory and how they interact with the rest of the system.","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. The \"Time Machine\" Playback","depth":26,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. The \"Time Machine\" Playback","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"db.sqlite","depth":28,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"database along with","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"precise timestamps and file path references","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. Re-processing and Model Upgrades","depth":26,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. Re-processing and Model Upgrades","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. The Source of Truth for Hallucinations","depth":26,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. The Source of Truth for Hallucinations","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"file is your fallback source of truth to verify what was actually said.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"How the Database Views Them","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How the Database Views Them","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you were to open up your","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"db.sqlite","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and query the tables (e.g.,","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"audio_transcriptions","depth":28,"bounds":{"left":0.0,"top":0.21333334,"width":0.11666667,"height":0.020555556},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"), you would see that the database treats the","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe/data/","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"soundcore AeroClip (input)_2026-05-12_07-40-48.mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":27,"bounds":{"left":0.0,"top":0.29833335,"width":0.003125,"height":0.022777777},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What happens if you delete them?","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you manually","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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2 TB in 25 MB/s - Google Search
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You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
You said
Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
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Gemini said
Gemini said
Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.
ScreenPipe is fundamentally designed to be a
100% local, privacy-first
application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.
View source details. Opens side panel.
1. Where It Starts: The Capture Layer
1. Where It Starts: The Capture Layer
The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:
System Audio:
Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).
Microphone Input:
Everything you say into your mic.
View source details. Opens side panel.
Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.
2. How It Gets Transferred and Transcribed
2. How It Gets Transferred and Transcribed
Because ScreenPipe prioritizes local processing, the "transfer" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.
Here is the transcription pipeline:
The Engine:
The raw audio chunks are fed into a local speech-to-text model.
By default, ScreenPipe uses
OpenAI Whisper
running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).
View source details. Opens side panel.
Diarization:
As it transcribes the text, the engine also performs "diarization"—a technical term for speaker identification.
It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.
View source details. Opens side panel.
Storage:
The final transcribed text is then indexed into a local
SQLite database
. This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.
3. The "Work in Progress" (WIP) Stage
3. The "Work in Progress" (WIP) Stage
There is a slight bottleneck between
hearing
the audio and
saving
the text, which acts as the WIP stage:
Buffering:
Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.
Processing Queue:
Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.
Finalization:
Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.
4. Understanding the Folder Structure
4. Understanding the Folder Structure
All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like
~/.screenpipe
on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:
The SQLite Database (
):
This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is "done."
The
or
folders:
This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.
Temp Files:
If you see rapidly changing files, temporary
chunks, or locked database journals (like
), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.
Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?
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You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
You said
I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
Expand
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Gemini said
Gemini said
Yes, those
.mp4
files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.
Here is exactly what those files are doing sitting in your
~/.screenpipe/data/
directory and how they interact with the rest of the system.
1. The "Time Machine" Playback
1. The "Time Machine" Playback
The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the
db.sqlite
database along with
precise timestamps and file path references
.
When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific
.mp4
file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.
2. Re-processing and Model Upgrades
2. Re-processing and Model Upgrades
Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw
.mp4
files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.
3. The Source of Truth for Hallucinations
3. The Source of Truth for Hallucinations
Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that
.mp4
file is your fallback source of truth to verify what was actually said.
How the Database Views Them
How the Database Views Them
If you were to open up your
db.sqlite
and query the tables (e.g.,
audio_transcriptions
), you would see that the database treats the
~/.screenpipe/data/
folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like
soundcore AeroClip (input)_2026-05-12_07-40-48.mp4
.
What happens if you delete them?
If you manually...
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Screenpipe — Archive
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Copy prompt
You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
You said
Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
Listen
Show thinking
Gemini said
Gemini said
Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.
ScreenPipe is fundamentally designed to be a
100% local, privacy-first
application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.
View source details. Opens side panel.
1. Where It Starts: The Capture Layer
1. Where It Starts: The Capture Layer
The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:
System Audio:
Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).
Microphone Input:
Everything you say into your mic.
View source details. Opens side panel.
Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.
2. How It Gets Transferred and Transcribed
2. How It Gets Transferred and Transcribed
Because ScreenPipe prioritizes local processing, the "transfer" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.
Here is the transcription pipeline:
The Engine:
The raw audio chunks are fed into a local speech-to-text model.
By default, ScreenPipe uses
OpenAI Whisper
running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).
View source details. Opens side panel.
Diarization:
As it transcribes the text, the engine also performs "diarization"—a technical term for speaker identification.
It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.
View source details. Opens side panel.
Storage:
The final transcribed text is then indexed into a local
SQLite database
. This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.
3. The "Work in Progress" (WIP) Stage
3. The "Work in Progress" (WIP) Stage
There is a slight bottleneck between
hearing
the audio and
saving
the text, which acts as the WIP stage:
Buffering:
Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.
Processing Queue:
Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.
Finalization:
Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.
4. Understanding the Folder Structure
4. Understanding the Folder Structure
All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like
~/.screenpipe
on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:
The SQLite Database (
):
This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is "done."
The
or
folders:
This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.
Temp Files:
If you see rapidly changing files, temporary
chunks, or locked database journals (like
), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.
Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?
Sources
Sources
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Copy prompt
You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
You said
I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
Expand
Listen
Show thinking
Gemini said
Gemini said
Yes, those
.mp4
files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.
Here is exactly what those files are doing sitting in your
~/.screenpipe/data/
directory and how they interact with the rest of the system.
1. The "Time Machine" Playback
1. The "Time Machine" Playback
The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the
db.sqlite
database along with
precise timestamps and file path references
.
When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific
.mp4
file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.
2. Re-processing and Model Upgrades
2. Re-processing and Model Upgrades
Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw
.mp4
files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.
3. The Source of Truth for Hallucinations
3. The Source of Truth for Hallucinations
Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that
.mp4
file is your fallback source of truth to verify what was actually said.
How the Database Views Them
How the Database Views Them
If you were to open up your
db.sqlite
and query the tables (e.g.,
audio_transcriptions
), you would see that the database treats the
~/.screenpipe/data/
folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like
soundcore AeroClip (input)_2026-05-12_07-40-48.mp4
.
What happens if you delete them?
If you manually
rm
those files to free up space on your Mac's SSD, ScreenPipe won't crash. The SQLite database will still hold all your searchable text. However, any attempt to play back the audio for those older transcripts will silently fail or throw a "file not found" error in the background logs.
Managing the Storage Footprint
Managing the Storage Footprint
Because ScreenPipe records continuously, this folder will inevitably grow over time.
Built-in Garbage Collection:
ScreenPipe usually handles this automatically based on retention settings (e.g., deleting media older than 30 days or when the folder hits a specific GB limit).
Archiving:
If you prefer to keep a permanent, searchable "life log" without eating up your local SSD space, you don't necessarily have to let ScreenPipe delete them. You could script a simple cron job to regularly
older
files to your massive 4-drive RAID 5 array, replacing the local files with symlinks. This would keep the database references intact while offloading the heavy media storage to your NAS.
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You said yes I will do that. Is there a way to setup languages to transcription?
You said
yes I will do that. Is there a way to setup languages to transcription?
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Gemini said
Gemini said
That is a solid plan. Offloading those older media files to your 4-drive RAID 5 setup (or even the secondary SSD-only Beelink NAS if you end up building it) will keep your local SSD lean while keeping your database searchable.
As for setting up languages for transcription,
yes, you can configure it
, but it helps to understand how ScreenPipe handles language natively first.
How the Transcription Engine Handles Language
How the Transcription Engine Handles Language
By default, ScreenPipe uses a
multilingual Whisper model
and sets the language configuration to
Auto-Detect
.
When a new audio chunk comes in, the model listens to the first few seconds of audio, guesses the language, and transcribes the rest of that chunk using that assumption.
The Advantage:
If you are watching a tutorial in English, and then an hour later you are in a Zoom call speaking Bulgarian, ScreenPipe will automatically switch gears without you having to touch the settings.
The Drawback:
Auto-detect can sometimes guess wrong, especially if there is heavy background noise, if someone starts a sentence with a foreign loanword, or if you are rapidly code-switching between Slovak and English in the same conversation. When it guesses wrong, it might try to force Slovak words into English spelling, resulting in gibberish.
How to Force a Specific Language
How to Force a Specific Language
If you want to ensure maximum accuracy and you know you will primarily be recording in one language for a specific period, you can explicitly set the language. This also slightly speeds up the processing because the model skips the detection phase.
If you are using the Desktop App UI:
Open the ScreenPipe settings.
Navigate to the
Audio
or
AI/Transcription
section.
Look for the
Whisper Language
or
Transcription Language
dropdown.
Change it from "Auto" to your specific language (e.g., English, Bulgarian, or Slovak).
If you are running ScreenPipe via CLI/Config:
You can modify your underlying configuration (usually found in
~/.screenpipe/pipe.json
or by passing a flag when starting the daemon) to force a specific language code. You would use the standard ISO language codes:
(Slovak)
(Bulgarian)
(English)
If you find yourself frequently jumping between those three languages, your best bet is to leave it on Auto-Detect and perhaps run a slightly larger, more accurate Whisper model (like Whisper 'Small' or 'Base' instead of 'Tiny') if your hardware has the headroom for it.
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Gemini","depth":15,"bounds":{"left":0.068484046,"top":0.14764565,"width":0.0003324468,"height":0.0007980846},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Conversation with Gemini","depth":16,"bounds":{"left":0.068484046,"top":0.15003991,"width":0.1200133,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy prompt","depth":21,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":24,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ScreenPipe is fundamentally designed to be a","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"100% local, privacy-first","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":27,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"1. Where It Starts: The Capture Layer","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Where It Starts: The Capture Layer","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"System Audio:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Microphone Input:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Everything you say into your mic.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How It Gets Transferred and Transcribed","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How It Gets Transferred and Transcribed","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Because ScreenPipe prioritizes local processing, the \"transfer\" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is the transcription pipeline:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Engine:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The raw audio chunks are fed into a local speech-to-text model.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, ScreenPipe uses","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"OpenAI Whisper","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Diarization:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"As it transcribes the text, the engine also performs \"diarization\"—a technical term for speaker identification.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Storage:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The final transcribed text is then indexed into a local","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SQLite database","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. The \"Work in Progress\" (WIP) Stage","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. The \"Work in Progress\" (WIP) Stage","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"There is a slight bottleneck between","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"hearing","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the audio and","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"saving","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the text, which acts as the WIP stage:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Buffering:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Processing Queue:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Finalization:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"4. Understanding the Folder Structure","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"4. Understanding the Folder Structure","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The SQLite Database (","depth":29,"bounds":{"left":0.09142287,"top":0.0,"width":0.05817819,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"):","depth":29,"bounds":{"left":0.17885639,"top":0.0,"width":0.0034906915,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is \"done.\"","depth":29,"bounds":{"left":0.09142287,"top":0.0,"width":0.21010639,"height":0.037110932},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The","depth":29,"bounds":{"left":0.09142287,"top":0.0,"width":0.011303191,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":29,"bounds":{"left":0.120678194,"top":0.0,"width":0.008144947,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"folders:","depth":29,"bounds":{"left":0.14960106,"top":0.0,"width":0.020944148,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.","depth":29,"bounds":{"left":0.09142287,"top":0.0,"width":0.21542554,"height":0.037110932},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Temp Files:","depth":29,"bounds":{"left":0.09142287,"top":0.029928172,"width":0.028922873,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you see rapidly changing files, temporary","depth":29,"bounds":{"left":0.12034574,"top":0.029928172,"width":0.106715426,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"chunks, or locked database journals (like","depth":29,"bounds":{"left":0.09142287,"top":0.029928172,"width":0.21991356,"height":0.037110932},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.","depth":29,"bounds":{"left":0.09142287,"top":0.050678372,"width":0.22174202,"height":0.057861134},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?","depth":27,"bounds":{"left":0.0787899,"top":0.13288109,"width":0.22456782,"height":0.037110932},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Sources","depth":26,"bounds":{"left":0.0787899,"top":0.18715084,"width":0.036402926,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Sources","depth":28,"bounds":{"left":0.091755316,"top":0.19592977,"width":0.017785905,"height":0.014764565},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Good response","depth":24,"bounds":{"left":0.075465426,"top":0.23184358,"width":0.010638298,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Bad response","depth":24,"bounds":{"left":0.08610372,"top":0.23184358,"width":0.010638298,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Share and export","depth":23,"bounds":{"left":0.09674202,"top":0.23184358,"width":0.010638298,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":24,"bounds":{"left":0.107380316,"top":0.23184358,"width":0.010638298,"height":0.025538707},"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":23,"bounds":{"left":0.11801862,"top":0.23184358,"width":0.010638298,"height":0.025538707},"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy prompt","depth":21,"bounds":{"left":0.14029256,"top":0.292498,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?","depth":21,"bounds":{"left":0.16023937,"top":0.30207503,"width":0.13696809,"height":0.09577015},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"bounds":{"left":0.068484046,"top":0.3028731,"width":0.019946808,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?","depth":23,"bounds":{"left":0.16023937,"top":0.30367118,"width":0.13663563,"height":0.13128492},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"bounds":{"left":0.29720744,"top":0.30207503,"width":0.013297873,"height":0.031923383},"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":24,"bounds":{"left":0.3025266,"top":0.42976856,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"bounds":{"left":0.09208777,"top":0.43216282,"width":0.030917553,"height":0.014764565},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"bounds":{"left":0.08976064,"top":0.4736632,"width":0.0003324468,"height":0.0007980846},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"bounds":{"left":0.08976064,"top":0.47565842,"width":0.04105718,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yes, those","depth":27,"bounds":{"left":0.0787899,"top":0.47685555,"width":0.025930852,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"bounds":{"left":0.106715426,"top":0.47805268,"width":0.011136968,"height":0.014764565},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.","depth":27,"bounds":{"left":0.0787899,"top":0.47685555,"width":0.23005319,"height":0.037110932},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is exactly what those files are doing sitting in your","depth":27,"bounds":{"left":0.0787899,"top":0.5271349,"width":0.1341423,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe/data/","depth":28,"bounds":{"left":0.21492687,"top":0.528332,"width":0.053025264,"height":0.014764565},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"directory and how they interact with the rest of the system.","depth":27,"bounds":{"left":0.0787899,"top":0.5271349,"width":0.22623006,"height":0.037110932},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. The \"Time Machine\" Playback","depth":26,"bounds":{"left":0.0787899,"top":0.5885874,"width":0.234375,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. The \"Time Machine\" Playback","depth":27,"bounds":{"left":0.0787899,"top":0.59018356,"width":0.08194814,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The primary reason ScreenPipe keeps these files is for audio playback. 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Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw","depth":27,"bounds":{"left":0.0787899,"top":0.83918595,"width":0.23254654,"height":0.07861133},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"bounds":{"left":0.117519945,"top":0.90263367,"width":0.011136968,"height":0.014764565},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files allows you to re-process historical audio. 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The SQLite database will still hold all your searchable text. However, any attempt to play back the audio for those older transcripts will silently fail or throw a \"file not found\" error in the background logs.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Managing the Storage Footprint","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Managing the Storage Footprint","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Because ScreenPipe records continuously, this folder will inevitably grow over time.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Built-in Garbage Collection:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ScreenPipe usually handles this automatically based on retention settings (e.g., deleting media older than 30 days or when the folder hits a specific GB limit).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Archiving:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you prefer to keep a permanent, searchable \"life log\" without eating up your local SSD space, you don't necessarily have to let ScreenPipe delete them. You could script a simple cron job to regularly","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"older","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files to your massive 4-drive RAID 5 array, replacing the local files with symlinks. This would keep the database references intact while offloading the heavy media storage to your NAS.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Good response","depth":24,"on_screen":false,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Bad response","depth":24,"on_screen":false,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Share and export","depth":23,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":24,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":23,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy prompt","depth":21,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Edit","depth":21,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said yes I will do that. Is there a way to setup languages to transcription?","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"yes I will do that. Is there a way to setup languages to transcription?","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":24,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"That is a solid plan. Offloading those older media files to your 4-drive RAID 5 setup (or even the secondary SSD-only Beelink NAS if you end up building it) will keep your local SSD lean while keeping your database searchable.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"As for setting up languages for transcription,","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"yes, you can configure it","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", but it helps to understand how ScreenPipe handles language natively first.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"How the Transcription Engine Handles Language","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How the Transcription Engine Handles Language","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, ScreenPipe uses a","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"multilingual Whisper model","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and sets the language configuration to","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Auto-Detect","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When a new audio chunk comes in, the model listens to the first few seconds of audio, guesses the language, and transcribes the rest of that chunk using that assumption.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Advantage:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you are watching a tutorial in English, and then an hour later you are in a Zoom call speaking Bulgarian, ScreenPipe will automatically switch gears without you having to touch the settings.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Drawback:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Auto-detect can sometimes guess wrong, especially if there is heavy background noise, if someone starts a sentence with a foreign loanword, or if you are rapidly code-switching between Slovak and English in the same conversation. When it guesses wrong, it might try to force Slovak words into English spelling, resulting in gibberish.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"How to Force a Specific Language","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How to Force a Specific Language","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you want to ensure maximum accuracy and you know you will primarily be recording in one language for a specific period, you can explicitly set the language. 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You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
You said
Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
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Gemini said
Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.
ScreenPipe is fundamentally designed to be a
100% local, privacy-first
application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.
View source details. Opens side panel.
1. Where It Starts: The Capture Layer
1. Where It Starts: The Capture Layer
The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:
System Audio:
Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).
Microphone Input:
Everything you say into your mic.
View source details. Opens side panel.
Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.
2. How It Gets Transferred and Transcribed
2. How It Gets Transferred and Transcribed
Because ScreenPipe prioritizes local processing, the "transfer" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.
Here is the transcription pipeline:
The Engine:
The raw audio chunks are fed into a local speech-to-text model.
By default, ScreenPipe uses
OpenAI Whisper
running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).
View source details. Opens side panel.
Diarization:
As it transcribes the text, the engine also performs "diarization"—a technical term for speaker identification.
It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.
View source details. Opens side panel.
Storage:
The final transcribed text is then indexed into a local
SQLite database
. This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.
3. The "Work in Progress" (WIP) Stage
3. The "Work in Progress" (WIP) Stage
There is a slight bottleneck between
hearing
the audio and
saving
the text, which acts as the WIP stage:
Buffering:
Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.
Processing Queue:
Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.
Finalization:
Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.
4. Understanding the Folder Structure
4. Understanding the Folder Structure
All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like
~/.screenpipe
on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:
The SQLite Database (
):
This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is "done."
The
or
folders:
This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.
Temp Files:
If you see rapidly changing files, temporary
chunks, or locked database journals (like
), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.
Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?
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You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
You said
I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
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Gemini said
Gemini said
Yes, those
.mp4
files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.
Here is exactly what those files are doing sitting in your
~/.screenpipe/data/
directory and how they interact with the rest of the system.
1. The "Time Machine" Playback
1. The "Time Machine" Playback
The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the
db.sqlite
database along with
precise timestamps and file path references
.
When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific
.mp4
file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.
2. Re-processing and Model Upgrades
2. Re-processing and Model Upgrades
Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw
.mp4
files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.
3. The Source of Truth for Hallucinations
3. The Source of Truth for Hallucinations
Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that
.mp4
file is your fallback source of truth to verify what was actually said.
How the Database Views Them
How the Database Views Them
If you were to open up your
db.sqlite
and query the tables (e.g.,
audio_transcriptions
), you would see that the database treats the
~/.screenpipe/data/
folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like
soundcore AeroClip (input)_2026-05-12_07-40-48.mp4
.
What happens if you delete them?
If you manually
rm
those files to free up space on your Mac's SSD, ScreenPipe won't crash. The SQLite database will still hold all your searchable text. However, any attempt to play back the audio for those older transcripts will silently fail or throw a "file not found" error in the background logs.
Managing the Storage Footprint
Managing the Storage Footprint
Because ScreenPipe records continuously, this folder will inevitably grow over time.
Built-in Garbage Collection:
ScreenPipe usually handles this automatically based on retention settings (e.g., deleting media older than 30 days or when the folder hits a specific GB limit).
Archiving:
If you prefer to keep a permanent, searchable "life log" without eating up your local SSD space, you don't necessarily have to let ScreenPipe delete them. You could script a simple cron job to regularly
older
files to your massive 4-drive RAID 5 array, replacing the local files with symlinks. This would keep the database references intact while offloading the heavy media storage to your NAS.
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You said yes I will do that. Is there a way to setup languages to transcription?
You said
yes I will do that. Is there a way to setup languages to transcription?
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Gemini said
Gemini said
That is a solid plan. Offloading those older media files to your 4-drive RAID 5 setup (or even the secondary SSD-only Beelink NAS if you end up building it) will keep your local SSD lean while keeping your database searchable.
As for setting up languages for transcription,
yes, you can configure it
, but it helps to understand how ScreenPipe handles language natively first.
How the Transcription Engine Handles Language
How the Transcription Engine Handles Language
By default, ScreenPipe uses a
multilingual Whisper model
and sets the language configuration to
Auto-Detect
.
When a new audio chunk comes in, the model listens to the first few seconds of audio, guesses the language, and transcribes the rest of that chunk using that assumption.
The Advantage:
If you are watching a tutorial in English, and then an hour later you are in a Zoom call speaking Bulgarian, ScreenPipe will automatically switch gears without you having to touch the settings.
The Drawback:
Auto-detect can sometimes guess wrong, especially if there is heavy background noise, if someone starts a sentence with a foreign loanword, or if you are rapidly code-switching between Slovak and English in the same conversation. When it guesses wrong, it might try to force Slovak words into English spelling, resulting in gibberish.
How to Force a Specific Language
How to Force a Specific Language
If you want to ensure maximum accuracy and you know you will primarily be recording in one language for a specific period, you can explicitly set the language. This also slightly speeds up the processing because the model skips the detection phase.
If you are using the Desktop App UI:
Open the ScreenPipe settings.
Navigate to the
Audio
or
AI/Transcription
section.
Look for the
Whisper Language
or
Transcription Language
dropdown.
Change it from "Auto" to your specific language (e.g., English, Bulgarian, or Slovak).
If you are running ScreenPipe via CLI/Config:
You can modify your underlying configuration (usually found in
~/.screenpipe/pipe.json
or by passing a flag when starting the daemon) to force a specific language code. You would use the standard ISO language codes:
(Slovak)
(Bulgarian)
(English)
If you find yourself frequently jumping between those three languages, your best bet is to leave it on Auto-Detect and perhaps run a slightly larger, more accurate Whisper model (like Whisper 'Small' or 'Base' instead of 'Tiny') if your hardware has the headroom for it.
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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[JY-20773] User Pilot not receiving events on report generated - Jira
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JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
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Userpilot | Ask Jiminny Report Generated
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Dependabot alerts · jiminny/app
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[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
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Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
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Useful commands - Engineering - Confluence
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Jiminny
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[SRD-6853] Moxso - Potential deal stages bug - Jira
[SRD-6853] Moxso - Potential deal stages bug - Jira
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JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Useful commands - Engineering - Confluence
Useful commands - Engineering - Confluence
Dev Tools - Elastic
Dev Tools - Elastic
Jiminny
Jiminny
[SRD-6853] Moxso - Potential deal stages bug - Jira
[SRD-6853] Moxso - Potential deal stages bug - Jira
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Usage | Windsurf
Usage | Windsurf
Close tab
JY-208 Usage | Windsurf
Usage | Windsurf
Close tab
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
JY-20891 add support for secondary email by LakyLak · Pull Request #12073 · jiminny/app
[SRD-6848] Sidekick SMS issue - Jira
[SRD-6848] Sidekick SMS issue - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Dependabot alerts · jiminny/prophet
Dependabot alerts · jiminny/prophet
[JY-19958] Upgrade BE libraries - May - Jira
[JY-19958] Upgrade BE libraries - May - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
[JY-20773] User Pilot not receiving events on report generated - Jira
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
JY-19957 | Remove abanded sympfony debug, compose upgrade by nikolaybiaivanov · Pull Request #12022 · jiminny/app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
TypeError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line 218 — jiminny — app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
[JY-19957] Upgrade BE libraries - Apr - Jira
[JY-19957] Upgrade BE libraries - Apr - Jira
Dependabot alerts · jiminny/app
Dependabot alerts · jiminny/app
[JY-20891] Sidekick SMS issue - Jira
[JY-20891] Sidekick SMS issue - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
[SRD-6849] Recorded call does not appear on the dashboard - Jira
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Jiminny
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Useful commands - Engineering - Confluence
Useful commands - Engineering - Confluence
Dev Tools - Elastic
Dev Tools - Elastic
Jiminny
Jiminny
[SRD-6853] Moxso - Potential deal stages bug - Jira
[SRD-6853] Moxso - Potential deal stages bug - Jira
CloudWatch | eu-west-1
CloudWatch | eu-west-1
CloudWatch | eu-west-1
CloudWatch | eu-west-1
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Windsurf Usage Summary
Next billing cycle is in
2
days
on
May 15, 2026
.
Your daily quota
98.00
% remaining
Daily quota resets every day and usage resumes once quota refreshes.
Resets
14 May, 11:00 EEST
Your weekly quota
31.00
% remaining
Weekly quota resets every week and can still limit usage after the daily reset.
Resets
17 May, 11:00 EEST
Extra usage balance available
$
-0.11
Once the quota is reached, Windsurf can continue to be used with free models.
To continue using premium models,
purchase extra usage
.
Purchase usage...
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Alfred Search Field
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ClaudeVIewWindowmeltUpdating packages in Laravel v ClaudeVIewWindowmeltUpdating packages in Laravel vQ, Chat= Cowork" Coae+ New chatã Projectso0 Arutacts₴ CustomizeBulgarian citizenship application proces:Dawarich location tracking projectUpdating packages in LaravelScreenpipe data sunc and retention manScreenpipe sync script failing after recelHubspot BadRequest headers debuggin)Monthly expense trackingexporting transaction data from Notion• How much have I spent for groc…April 2026 spending by categoryCode diff reviewHubSpot rate limit implementation stratescreenpipe retention policy code locaticViewing retention policy in screenpipeClean shot x video recording terminaticHubSoot rate limit handlling with executeScreen pipe. Is there ability…SMR mount access inconsistency betw.What is the best switch I can.Screennine svnc database attachmenteIn laravel project how can l update packages?Relaunch to updateik tukas. ProIdentified technical Laravel question and formulated direct answer ›In Laravel projects, you've got both Composer (PHP) and npm/yarn (JS) to deal with.Composer (PHP packages)cheek whar'e outaated.Reolvcomposer outdatedUpdate everything within version constraints in composer.json :composer updaceUpdate a specine package:composer update vendor/packageUpdate with dependenciescomposer update vendor/package --with-dependenciesTo bumo to a new maior version, edit composer. ison (eg. "laravel/framework": "A11,0" )then run composer update. The --dry-run flag is useful to preview changes withoutabd ving them.as nackagesSince vou've migrated to Yarn v4:varn outdated# not in v4 bv defaultuse varn uograde-interactive insteadYou're out of usage credits. Buy more to keep going now, or wait until Thursday at 6:00 PM whenvour plan usage resetsBuv moreWrite a message…Opus 4.7 AdaptivevCiaudo ic Alandican make mictakas Plesce double-chock racnoncocOOO IMay 2026 Week19Sun 10X Chloe Cross (Parental Leave - 256 days)Mon 17Andred Llatanova (Parental Leave - Toy days)Michelle Weston (PTO - o days)Mira Lenkova (PTO - 3 days)Tue 1208:00)09:0011:00|12:0015:00paration for 1 [Support Daily, 1 Support Daily 15:0018:0020:51Wed 13bionr| Mid Sprint ChSuonort Daily 15:00100% L2Wed 13 May 20:51:33Week vTodaySat16Thu14James Graham (PTO - 2 davs)Liz Mulraney (PTO - 1 day)Fri15Daily - Platform 09:45Daily - Platform 09:451 Support Daily 15:00Sunnort Dailv 15...
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ClaudeVIewWindowmeltUpdating packages in Laravel v ClaudeVIewWindowmeltUpdating packages in Laravel vQ, Chat= Cowork" Coae+ New chatã Projectso0 Arutacts₴ CustomizeBulgarian citizenship application proces:Dawarich location tracking projectUpdating packages in LaravelScreenpipe data sunc and retention manScreenpipe sync script failing after recelHubspot BadRequest headers debuggin)Monthly expense trackingexporting transaction data from Notion• How much have I spent for groc…April 2026 spending by categoryCode diff reviewHubSpot rate limit implementation stratescreenpipe retention policy code locaticViewing retention policy in screenpipeClean shot x video recording terminaticHubSoot rate limit handlling with executeScreen pipe. Is there ability…SMR mount access inconsistency betw.What is the best switch I can.Screennine svnc database attachmenteIn laravel project how can l update packages?Relaunch to updateik tukas. ProIdentified technical Laravel question and formulated direct answer ›In Laravel projects, you've got both Composer (PHP) and npm/yarn (JS) to deal with.Composer (PHP packages)cheek whar'e outaated.Reolvcomposer outdatedUpdate everything within version constraints in composer.json :composer updaceUpdate a specine package:composer update vendor/packageUpdate with dependenciescomposer update vendor/package --with-dependenciesTo bumo to a new maior version, edit composer. ison (eg. "laravel/framework": "A11,0" )then run composer update. The --dry-run flag is useful to preview changes withoutabd ving them.as nackagesSince vou've migrated to Yarn v4:varn outdated# not in v4 bv defaultuse varn uograde-interactive insteadYou're out of usage credits. Buy more to keep going now, or wait until Thursday at 6:00 PM whenvour plan usage resetsBuv moreWrite a message…Opus 4.7 AdaptivevCiaudo ic Alandican make mictakas Plesce double-chock racnoncocOOO IMay 2026 Week19Sun 10X Chloe Cross (Parental Leave - 256 days)Mon 17Andred Llatanova (Parental Leave - Toy days)Michelle Weston (PTO - o days)Mira Lenkova (PTO - 3 days)Tue 1208:00)09:0011:00|12:0015:00paration for 1 [Support Daily, 1 Support Daily 15:0018:0020:51Wed 13bionr| Mid Sprint ChSuonort Daily 15:00100% L2Wed 13 May 20:51:33Week vTodaySat16Thu14James Graham (PTO - 2 davs)Liz Mulraney (PTO - 1 day)Fri15Daily - Platform 09:45Daily - Platform 09:451 Support Daily 15:00Sunnort Dailv 15...
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Notion CalendarEditViewWindowHelp>0 lblA100% &l Notion CalendarEditViewWindowHelp>0 lblA100% <78• Wed 13 May 20:51:34T81ec2-user@ip-10-30-129-190:~-zshDOCKERО ₴1DEV (docker)Last login: Wed May 1309:16:21on ttys010882APP (-zsh)883screenpipe"О [EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.tomlfile in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny$ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version 2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:ec2-user@ip-10-20-31-14... *7$131NNotion CalendarFordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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Notion CalendarEditViewWindowHelp>0 lblA100% &l Notion CalendarEditViewWindowHelp>0 lblA100% <78• Wed 13 May 20:51:34T81ec2-user@ip-10-30-129-190:~-zshDOCKERО ₴1DEV (docker)Last login: Wed May 1309:16:21on ttys010882APP (-zsh)883screenpipe"О [EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.tomlfile in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny$ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version 2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:ec2-user@ip-10-20-31-14... *7$131NNotion CalendarFordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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Notion CalendarEditViewWindowHelplabolAec2-user@ip Notion CalendarEditViewWindowHelplabolAec2-user@ip-10-30-129-190:~-zsh100% С8•Wed 13 May 20:51:37181ec2-user@ip-10-20-31-14...₴7DOCKER• ₴1DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)|883screenpipe"• ж5ec2[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version 2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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Notion CalendarEditViewWindowHelplabolAec2-user@ip Notion CalendarEditViewWindowHelplabolAec2-user@ip-10-30-129-190:~-zsh100% С8•Wed 13 May 20:51:37181ec2-user@ip-10-20-31-14...₴7DOCKER• ₴1DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)|883screenpipe"• ж5ec2[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version 2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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Notion CalendarVIewWindowmeltUpdating packages in Notion CalendarVIewWindowmeltUpdating packages in Laravel vQ, Chat= Cowork+ New chatã Projectso0 Arutacts₴ CustomizeBu garian cit zenshio apolication proces:Dawarich location tracking projectUpdating packages in LaravelScreenpipe data sunc and retention manScreenpipe sync script failing after recelHubspot BadRequest headers debuggin)Monthly expense trackingexporting transaction data from Notion• How much have I spent for groc…April 2026 spending by categoryCode diff reviewHubSpot rate limit implementation stratescreenpipe retention policy code locaticViewing retention policy in screenpipeClean shot x video recording terminaticHubSoot rate limit handlling with executeUntitledScreen pipe. Is there ability…SMR mount access inconsistency betw.What is the best switch I can.Screennine svnc database attachmenteRelaunch to updateik tukas. ProIn laravel project how can l update packages?Identified technical Laravel question and formulated direct answer ›In Laravel projects, you've got both Composer (PHP) and npm/yarn (JS) to deal with.Composer (PHP packages)cheek whar'e outaated.Reolvcomposer outdatedUpdate everything within version constraints in composer.json :composer updaceUpdate a specine package:composer update vendor/packageUpdate with dependenciescomposer update vendor/package --with-dependenciesTo bumo to a new maior version, edit composer. ison (eg. "laravel/framework": "A11,0" )then run composer update. The --dry-run flag is useful to preview changes withoutabd ving them.as nackagesSince vou've migrated to Yarn v4:varn outdated# not in v4 bv defaultuse varn uograde-interactive insteadYou're out of usage credits. Buy more to keep going now, or wait until Thursday at 6:00 PM whervour plan usage resetsBuv moreWrite a message…Opus 4.7 AdaptiveCiaudo ic Alandican make mictakas Plesce double-chock racnoncodMay 2026 Week 19Mo Tul12 13 1425 26 27i Schedulina& Meet [EMAIL]•lukas.kovalik@jimi... Default• My cal.• Holidays in Bulgaria^ Who's OutDomáce nrácoSamilv• TravelWork related•relax• usual• vybavovacky• sportXwhdlinm^ Holidavs in BulaarialSviatky na Slovensku• Sviatky v [EMAIL]- Add calendar accountLuka¿ Koválik's NotionP Jira ticketEP TodoMon ti256 days)ave - Toy days)Michelle Weston (PTO - 5 days)Mira Lenkova (PTO - 3 davs)Tue 12aration for ( [Support Daily; 1 Support Daily 15:00Wed 13bionr| Mid Sprint CtSuonort Daily 15:00Thu14James Graham (PTO - 2 davs)Liz Mulraney (PTO - 1 day)Daily - Platform 09:451 Support Daily 15:00Fri15100% S2Wed 13 May 20:51:37Week vTodaySat16Daily - Platform 09:45Sunnort Dailv 15...
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Notion CalendarVIewWindowmeltUpdating packages in Notion CalendarVIewWindowmeltUpdating packages in Laravel vQ, Chat= Cowork+ New chatã Projectso0 Arutacts₴ CustomizeBu garian cit zenshio apolication proces:Dawarich location tracking projectUpdating packages in LaravelScreenpipe data sunc and retention manScreenpipe sync script failing after recelHubspot BadRequest headers debuggin)Monthly expense trackingexporting transaction data from Notion• How much have I spent for groc…April 2026 spending by categoryCode diff reviewHubSpot rate limit implementation stratescreenpipe retention policy code locaticViewing retention policy in screenpipeClean shot x video recording terminaticHubSoot rate limit handlling with executeUntitledScreen pipe. Is there ability…SMR mount access inconsistency betw.What is the best switch I can.Screennine svnc database attachmenteRelaunch to updateik tukas. ProIn laravel project how can l update packages?Identified technical Laravel question and formulated direct answer ›In Laravel projects, you've got both Composer (PHP) and npm/yarn (JS) to deal with.Composer (PHP packages)cheek whar'e outaated.Reolvcomposer outdatedUpdate everything within version constraints in composer.json :composer updaceUpdate a specine package:composer update vendor/packageUpdate with dependenciescomposer update vendor/package --with-dependenciesTo bumo to a new maior version, edit composer. ison (eg. "laravel/framework": "A11,0" )then run composer update. The --dry-run flag is useful to preview changes withoutabd ving them.as nackagesSince vou've migrated to Yarn v4:varn outdated# not in v4 bv defaultuse varn uograde-interactive insteadYou're out of usage credits. Buy more to keep going now, or wait until Thursday at 6:00 PM whervour plan usage resetsBuv moreWrite a message…Opus 4.7 AdaptiveCiaudo ic Alandican make mictakas Plesce double-chock racnoncodMay 2026 Week 19Mo Tul12 13 1425 26 27i Schedulina& Meet [EMAIL]•lukas.kovalik@jimi... Default• My cal.• Holidays in Bulgaria^ Who's OutDomáce nrácoSamilv• TravelWork related•relax• usual• vybavovacky• sportXwhdlinm^ Holidavs in BulaarialSviatky na Slovensku• Sviatky v [EMAIL]- Add calendar accountLuka¿ Koválik's NotionP Jira ticketEP TodoMon ti256 days)ave - Toy days)Michelle Weston (PTO - 5 days)Mira Lenkova (PTO - 3 davs)Tue 12aration for ( [Support Daily; 1 Support Daily 15:00Wed 13bionr| Mid Sprint CtSuonort Daily 15:00Thu14James Graham (PTO - 2 davs)Liz Mulraney (PTO - 1 day)Daily - Platform 09:451 Support Daily 15:00Fri15100% S2Wed 13 May 20:51:37Week vTodaySat16Daily - Platform 09:45Sunnort Dailv 15...
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Notion calendalw QQ, Chat= Cowork" Coae+ New Notion calendalw QQ, Chat= Cowork" Coae+ New chatã Projectso0 Arutacts₴ CustomizeBulgarian citizenship application proces:Dawarich location tracking projectUpdating packages in LaravelScreenpipe data sunc and retention manScreenpipe sync script failing after recelHubspot BadRequest headers debuggin)Monthly expense trackingexporting transaction data from Notion• How much have I spent for groc…April 2026 spending by categoryCode diff reviewHubSpot rate limit implementation stratescreenpipe retention policy code locaticViewing retention policy in screenpipeClean shot x video recording terminaticHubSoot rate limit handlling with executeScreen pipe. Is there ability…SMR mount access inconsistency betw.What is the best switch I can.Screennine svnc database attachmenteWindowUpdating packages in Laravel vRelaunch to updateik tukas. ProIn laravel project how can l update packages?Identified technical Laravel question and formulated direct answer ›In Laravel projects, you've got both Composer (PHP) and npm/yarn (JS) to deal with.Composer (PHP packages)cheek whar'e outaated.Reolvcomposer outdatedUpdate everything within version constraints in composer.json :composer updaceUpdate a specine package:composer update vendor/packageUpdate with dependenciescomposer update vendor/package --with-dependenciesTo bumo to a new maior version, edit composer. ison (eg. "laravel/framework": "A11,0" )then run composer update. The --dry-run flag is useful to preview changes withoutabd ving them.as nackagesSince vou've migrated to Yarn v4:varn outdated# not in v4 bv defaultuse varn uograde-interactive insteadYou're out of usage credits. Buy more to keep going now, or wait until Thursday at 6:00 PM whervour plan usage resetsBuv moreWrite a message…Opus 4.7 AdaptiveCiaudo ic Alandican make mictakas Plesce double-chock racnoncodMay 2026 Week19Mo Tu12 13 1425 26 27# Schedulind& Meet [EMAIL]• My call• Holidays in Bulgarial^ Who's OuiFamilyWork relatedvwbavovackyOXuielium^1 Holidavs in Bulaarial• Sviatky v Bulharsku6 [EMAIL]- Add calendar accountLuka¿ Koválik's NotionJira ticketER TodgMon ti256 days)ave - Toy days)Michelle Weston (PTO - o days)Mira Lenkova (PTO - 3 davs)Tue 12ration for { Support Daily; 1 Support Daily 15:00Wed 13bionr| Mid Sprint ChSuonort Daily 15:00Thu14James Graham (PTO - 2 davs)Liz Mulraney (PTO - 1 day)Daily - Platform 09:45Sunnort Daily 15:00Fri15100% 52• wea 13 May 20:01•30Week vTodaySat16Daily - Platform 09:45Sunnort Dailv 15...
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Notion calendalw QQ, Chat= Cowork" Coae+ New Notion calendalw QQ, Chat= Cowork" Coae+ New chatã Projectso0 Arutacts₴ CustomizeBulgarian citizenship application proces:Dawarich location tracking projectUpdating packages in LaravelScreenpipe data sunc and retention manScreenpipe sync script failing after recelHubspot BadRequest headers debuggin)Monthly expense trackingexporting transaction data from Notion• How much have I spent for groc…April 2026 spending by categoryCode diff reviewHubSpot rate limit implementation stratescreenpipe retention policy code locaticViewing retention policy in screenpipeClean shot x video recording terminaticHubSoot rate limit handlling with executeScreen pipe. Is there ability…SMR mount access inconsistency betw.What is the best switch I can.Screennine svnc database attachmenteWindowUpdating packages in Laravel vRelaunch to updateik tukas. ProIn laravel project how can l update packages?Identified technical Laravel question and formulated direct answer ›In Laravel projects, you've got both Composer (PHP) and npm/yarn (JS) to deal with.Composer (PHP packages)cheek whar'e outaated.Reolvcomposer outdatedUpdate everything within version constraints in composer.json :composer updaceUpdate a specine package:composer update vendor/packageUpdate with dependenciescomposer update vendor/package --with-dependenciesTo bumo to a new maior version, edit composer. ison (eg. "laravel/framework": "A11,0" )then run composer update. The --dry-run flag is useful to preview changes withoutabd ving them.as nackagesSince vou've migrated to Yarn v4:varn outdated# not in v4 bv defaultuse varn uograde-interactive insteadYou're out of usage credits. Buy more to keep going now, or wait until Thursday at 6:00 PM whervour plan usage resetsBuv moreWrite a message…Opus 4.7 AdaptiveCiaudo ic Alandican make mictakas Plesce double-chock racnoncodMay 2026 Week19Mo Tu12 13 1425 26 27# Schedulind& Meet [EMAIL]• My call• Holidays in Bulgarial^ Who's OuiFamilyWork relatedvwbavovackyOXuielium^1 Holidavs in Bulaarial• Sviatky v Bulharsku6 [EMAIL]- Add calendar accountLuka¿ Koválik's NotionJira ticketER TodgMon ti256 days)ave - Toy days)Michelle Weston (PTO - o days)Mira Lenkova (PTO - 3 davs)Tue 12ration for { Support Daily; 1 Support Daily 15:00Wed 13bionr| Mid Sprint ChSuonort Daily 15:00Thu14James Graham (PTO - 2 davs)Liz Mulraney (PTO - 1 day)Daily - Platform 09:45Sunnort Daily 15:00Fri15100% 52• wea 13 May 20:01•30Week vTodaySat16Daily - Platform 09:45Sunnort Dailv 15...
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•Hidden Bar*lalolAec2-user@ip-10-30-129-190:~-zsh1 •Hidden Bar*lalolAec2-user@ip-10-30-129-190:~-zsh100% C8•Wed 13 May 20:51:38181ec2-user@ip-10-20-31-14...₴7DOCKERO 881DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)|83screenpipe"О ₴[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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•Hidden Bar*lalolAec2-user@ip-10-30-129-190:~-zsh1 •Hidden Bar*lalolAec2-user@ip-10-30-129-190:~-zsh100% C8•Wed 13 May 20:51:38181ec2-user@ip-10-20-31-14...₴7DOCKERO 881DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)|83screenpipe"О ₴[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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Hidden BarDOCKERO 881DEV (docker)Last login: Wed M Hidden BarDOCKERO 881DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsPoetry could not find a pyproject.toml file in /Users/lukas orPoetry could not find a pyproject.toml file in /Users/lukas orlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-eEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalikeWarning: Permanently added 'jiminny-prod-ecs1' (ED25519) to theA newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and ve#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Docker Desktop is running• Go to the Dashboard• Sign in / Sign upSettings...TroubleshootGive feedbackAbout Docker DesktopDocker HubDocumentationExtensionsKubernetes Context® Download update• RestartI1 PauseQuit Docker Desktop26,Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |+9-190:-*screenpipe"lalolО ₴5A100% C8•Wed 13 May 20:51:39ec2-user@ip-10-30-129-...ec2-user@ip-10-20-31-14...₴7xe5qk7zis7pa517qLmp3zwm.us-east-2.es.amazonaws.com:80...
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Hidden BarDOCKERO 881DEV (docker)Last login: Wed M Hidden BarDOCKERO 881DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsPoetry could not find a pyproject.toml file in /Users/lukas orPoetry could not find a pyproject.toml file in /Users/lukas orlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-eEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalikeWarning: Permanently added 'jiminny-prod-ecs1' (ED25519) to theA newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and ve#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Docker Desktop is running• Go to the Dashboard• Sign in / Sign upSettings...TroubleshootGive feedbackAbout Docker DesktopDocker HubDocumentationExtensionsKubernetes Context® Download update• RestartI1 PauseQuit Docker Desktop26,Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |+9-190:-*screenpipe"lalolО ₴5A100% C8•Wed 13 May 20:51:39ec2-user@ip-10-30-129-...ec2-user@ip-10-20-31-14...₴7xe5qk7zis7pa517qLmp3zwm.us-east-2.es.amazonaws.com:80...
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Notion calendalw QQ, Chat= Cowork" Coae+ New Notion calendalw QQ, Chat= Cowork" Coae+ New chatã Projectso0 Arutacts₴ CustomizeBulgarian citizenship application proces:Dawarich location tracking projectUpdating packages in LaravelScreenpipe data sunc and retention manScreenpipe sync script failing after recelHubspot BadRequest headers debuggin)Monthly expense trackingexporting transaction data from Notion• How much have I spent for groc…April 2026 spending by categoryCode diff reviewHubSpot rate limit implementation stratescreenpipe retention policy code locaticViewing retention policy in screenpipeClean shot x video recording terminaticHubSoot rate limit handlling with executeScreen pipe. Is there ability…SMR mount access inconsistency betw.What is the best switch I can.Screennine svnc database attachmenteWindowUpdating packages in Laravel vRelaunch to updateik tukas. ProIn laravel project how can l update packages?Identified technical Laravel question and formulated direct answer ›In Laravel projects, you've got both Composer (PHP) and npm/yarn (JS) to deal with.Composer (PHP packages)cheek whar'e outaated.Reolvcomposer outdatedUpdate everything within version constraints in composer.json :composer updaceUpdate a specine package:composer update vendor/packageUpdate with dependenciescomposer update vendor/package --with-dependenciesTo bumo to a new maior version, edit composer. ison (eg. "laravel/framework": "A11,0" )then run composer update. The --dry-run flag is useful to preview changes withoutabd ving them.as nackagesSince vou've migrated to Yarn v4:varn outdated# not in v4 bv defaultuse varn uograde-interactive insteadYou're out of usage credits. Buy more to keep going now, or wait until Thursday at 6:00 PM whervour plan usage resetsBuv moreWrite a message…Opus 4.7 AdaptiveCiaudo ic Alandican make mictakas Plesce double-chock racnoncodMay 2026 Week19Mo Tu12 13 1425 26 27# Schedulind& Meet [EMAIL]• My call• Holidays in Bulgarial^ Who's OuiFamilyWork relatedvwbavovackyOXuielium^1 Holidavs in Bulaarial• Sviatky v Bulharsku6 [EMAIL]- Add calendar accountLuka¿ Koválik's NotionJira ticketER TodgMon ti256 days)ave - Toy days)Michelle Weston (PTO - o days)Mira Lenkova (PTO - 3 davs)Tue 12ration for { Support Daily; 1 Support Daily 15:00Wed 13bionr| Mid Sprint ChSuonort Daily 15:00Thu14James Graham (PTO - 2 davs)Liz Mulraney (PTO - 1 day)Daily - Platform 09:45Sunnort Daily 15:00Fri15100% 52• wea 13 May 20:01•34Week vTodaySat16Daily - Platform 09:45Sunnort Dailv 15...
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Notion calendalw QQ, Chat= Cowork" Coae+ New Notion calendalw QQ, Chat= Cowork" Coae+ New chatã Projectso0 Arutacts₴ CustomizeBulgarian citizenship application proces:Dawarich location tracking projectUpdating packages in LaravelScreenpipe data sunc and retention manScreenpipe sync script failing after recelHubspot BadRequest headers debuggin)Monthly expense trackingexporting transaction data from Notion• How much have I spent for groc…April 2026 spending by categoryCode diff reviewHubSpot rate limit implementation stratescreenpipe retention policy code locaticViewing retention policy in screenpipeClean shot x video recording terminaticHubSoot rate limit handlling with executeScreen pipe. Is there ability…SMR mount access inconsistency betw.What is the best switch I can.Screennine svnc database attachmenteWindowUpdating packages in Laravel vRelaunch to updateik tukas. ProIn laravel project how can l update packages?Identified technical Laravel question and formulated direct answer ›In Laravel projects, you've got both Composer (PHP) and npm/yarn (JS) to deal with.Composer (PHP packages)cheek whar'e outaated.Reolvcomposer outdatedUpdate everything within version constraints in composer.json :composer updaceUpdate a specine package:composer update vendor/packageUpdate with dependenciescomposer update vendor/package --with-dependenciesTo bumo to a new maior version, edit composer. ison (eg. "laravel/framework": "A11,0" )then run composer update. The --dry-run flag is useful to preview changes withoutabd ving them.as nackagesSince vou've migrated to Yarn v4:varn outdated# not in v4 bv defaultuse varn uograde-interactive insteadYou're out of usage credits. Buy more to keep going now, or wait until Thursday at 6:00 PM whervour plan usage resetsBuv moreWrite a message…Opus 4.7 AdaptiveCiaudo ic Alandican make mictakas Plesce double-chock racnoncodMay 2026 Week19Mo Tu12 13 1425 26 27# Schedulind& Meet [EMAIL]• My call• Holidays in Bulgarial^ Who's OuiFamilyWork relatedvwbavovackyOXuielium^1 Holidavs in Bulaarial• Sviatky v Bulharsku6 [EMAIL]- Add calendar accountLuka¿ Koválik's NotionJira ticketER TodgMon ti256 days)ave - Toy days)Michelle Weston (PTO - o days)Mira Lenkova (PTO - 3 davs)Tue 12ration for { Support Daily; 1 Support Daily 15:00Wed 13bionr| Mid Sprint ChSuonort Daily 15:00Thu14James Graham (PTO - 2 davs)Liz Mulraney (PTO - 1 day)Daily - Platform 09:45Sunnort Daily 15:00Fri15100% 52• wea 13 May 20:01•34Week vTodaySat16Daily - Platform 09:45Sunnort Dailv 15...
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38624
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1433
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23
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2026-05-13T17:51:40.854401+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694700854_m1.jpg...
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iTerm2
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monitor_1
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Hidden Bar*lalolA100% C8•ec2-user@ip-10-30-129-190 Hidden Bar*lalolA100% C8•ec2-user@ip-10-30-129-190:~-zshWed 13 May 20:51:40181ec2-user@ip-10-20-31-14...₴7DOCKERO 881DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)|83screenpipe"О ₴[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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399237668447208303
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visual_change
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ocr
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Hidden Bar*lalolA100% C8•ec2-user@ip-10-30-129-190 Hidden Bar*lalolA100% C8•ec2-user@ip-10-30-129-190:~-zshWed 13 May 20:51:40181ec2-user@ip-10-20-31-14...₴7DOCKERO 881DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)|83screenpipe"О ₴[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$ |...
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38625
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1433
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24
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2026-05-13T17:51:42.523072+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694702523_m1.jpg...
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iTerm2
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monitor_1
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Hidden Bar*lalolA100% (C478•Wed 13 May 20:51:42181 Hidden Bar*lalolA100% (C478•Wed 13 May 20:51:42181ec2-user@ip-10-30-129-190:~-zshDOCKERO 881DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)83screenpipe"О ₴[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1-L 7970:vpc-activities7g-t6nxe5qk7zis/pa517qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)ec2-user@ip-10-20-31-14….Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$...
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-1093027722412582096
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click
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ocr
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Hidden Bar*lalolA100% (C478•Wed 13 May 20:51:42181 Hidden Bar*lalolA100% (C478•Wed 13 May 20:51:42181ec2-user@ip-10-30-129-190:~-zshDOCKERO 881DEV (docker)Last login: Wed May 13 09:16:21on ttys010882APP (-zsh)83screenpipe"О ₴[EMAIL] could not find a pyproject.toml file in /Users/lukas or its parentsPoetry could not find a pyproject.toml file in /Users/lukas or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1-L 7970:vpc-activities7g-t6nxe5qk7zis/pa517qlmp3zwm.us-east-2.es.amazonaws.com:80Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.A newer release of "Amazon Linux" is available.Version 2023.10.20260330:Version 2023.11.20260406:Version2023.11.20260413:Version 2023.11.20260427:Version 2023.11.20260505:Version 2023.11.20260509:Run "/usr/bin/dnf check-release-update" for full release and version update info#_####_\_#####\\###|\#/v~'Amazon Linux 2023 (ECS Optimized)ec2-user@ip-10-20-31-14….Im/*Fordocumentation,visit [URL_WITH_CREDENTIALS] ~]$...
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38624
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38626
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1434
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22
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2026-05-13T17:51:42.539760+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694702539_m2.jpg...
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iTerm2
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NULL
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1
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Notion calendalw QQ, Chat= Cowork" Coae+ New Notion calendalw QQ, Chat= Cowork" Coae+ New chatã Projectso0 Arutacts₴ CustomizeBulgarian citizenship application proces:Dawarich location tracking projectUpdating packages in LaravelScreenpipe data sunc and retention manScreenpipe sync script failing after recelHubspot BadRequest headers debuggin)Monthly expense trackingexporting transaction data from Notion• How much have I spent for groc…April 2026 spending by categoryCode diff reviewHubSpot rate limit implementation stratescreenpipe retention policy code locaticViewing retention policy in screenpipeClean shot x video recording terminaticHubSoot rate limit handlling with executeScreen pipe. Is there ability…SMR mount access inconsistency betw.What is the best switch I can.Screennine svnc database attachmenteWindowUpdating packages in Laravel vRelaunch to updateik tukas. ProIn laravel project how can l update packages?Identified technical Laravel question and formulated direct answer ›In Laravel projects, you've got both Composer (PHP) and npm/yarn (JS) to deal with.Composer (PHP packages)cheek whar'e outaated.Reolvcomposer outdatedUpdate everything within version constraints in composer.json :composer updaceUpdate a specine package:composer update vendor/packageUpdate with dependenciescomposer update vendor/package --with-dependenciesTo bumo to a new maior version, edit composer. ison (eg. "laravel/framework": "A11,0" )then run composer update. The --dry-run flag is useful to preview changes withoutabd ving them.as nackagesSince vou've migrated to Yarn v4:varn outdated# not in v4 bv defaultuse varn uograde-interactive insteadYou're out of usage credits. Buy more to keep going now, or wait until Thursday at 6:00 PM whervour plan usage resetsBuv moreWrite a message…Opus 4.7 AdaptiveCiaudo ic Alandican make mictakas Plesce double-chock racnoncodMay 2026 Week19Mo Tu12 13 1425 26 27# Schedulind& Meet [EMAIL]• My call• Holidays in Bulgarial^ Who's OuiFamilyWork relatedvwbavovackyOXuielium^1 Holidavs in Bulaarial• Sviatky v Bulharsku6 [EMAIL]- Add calendar accountLuka¿ Koválik's NotionJira ticketER TodgMon ti256 days)ave - Toy days)Michelle Weston (PTo - o days)Mira Lenkova (PTO - 3 davs)Tue 12ration for { Support Daily; 1 Support Daily 15:00Wed 13bionr| Mid Sprint ChSuonort Daily 15:00Thu14James Graham (PTO - 2 days)Liz Mulraney (PTO - 1 day)Daily - Platform 09:45Sunnort Daily 15:00Fri15100% 52• wea 13 May 20:01:44Week vTodaySat16Daily - Platform 09:45Sunnort Dailv 15...
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NULL
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-5805367262637552006
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NULL
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click
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ocr
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NULL
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Notion calendalw QQ, Chat= Cowork" Coae+ New Notion calendalw QQ, Chat= Cowork" Coae+ New chatã Projectso0 Arutacts₴ CustomizeBulgarian citizenship application proces:Dawarich location tracking projectUpdating packages in LaravelScreenpipe data sunc and retention manScreenpipe sync script failing after recelHubspot BadRequest headers debuggin)Monthly expense trackingexporting transaction data from Notion• How much have I spent for groc…April 2026 spending by categoryCode diff reviewHubSpot rate limit implementation stratescreenpipe retention policy code locaticViewing retention policy in screenpipeClean shot x video recording terminaticHubSoot rate limit handlling with executeScreen pipe. Is there ability…SMR mount access inconsistency betw.What is the best switch I can.Screennine svnc database attachmenteWindowUpdating packages in Laravel vRelaunch to updateik tukas. ProIn laravel project how can l update packages?Identified technical Laravel question and formulated direct answer ›In Laravel projects, you've got both Composer (PHP) and npm/yarn (JS) to deal with.Composer (PHP packages)cheek whar'e outaated.Reolvcomposer outdatedUpdate everything within version constraints in composer.json :composer updaceUpdate a specine package:composer update vendor/packageUpdate with dependenciescomposer update vendor/package --with-dependenciesTo bumo to a new maior version, edit composer. ison (eg. "laravel/framework": "A11,0" )then run composer update. The --dry-run flag is useful to preview changes withoutabd ving them.as nackagesSince vou've migrated to Yarn v4:varn outdated# not in v4 bv defaultuse varn uograde-interactive insteadYou're out of usage credits. Buy more to keep going now, or wait until Thursday at 6:00 PM whervour plan usage resetsBuv moreWrite a message…Opus 4.7 AdaptiveCiaudo ic Alandican make mictakas Plesce double-chock racnoncodMay 2026 Week19Mo Tu12 13 1425 26 27# Schedulind& Meet [EMAIL]• My call• Holidays in Bulgarial^ Who's OuiFamilyWork relatedvwbavovackyOXuielium^1 Holidavs in Bulaarial• Sviatky v Bulharsku6 [EMAIL]- Add calendar accountLuka¿ Koválik's NotionJira ticketER TodgMon ti256 days)ave - Toy days)Michelle Weston (PTo - o days)Mira Lenkova (PTO - 3 davs)Tue 12ration for { Support Daily; 1 Support Daily 15:00Wed 13bionr| Mid Sprint ChSuonort Daily 15:00Thu14James Graham (PTO - 2 days)Liz Mulraney (PTO - 1 day)Daily - Platform 09:45Sunnort Daily 15:00Fri15100% 52• wea 13 May 20:01:44Week vTodaySat16Daily - Platform 09:45Sunnort Dailv 15...
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38627
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1433
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25
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2026-05-13T17:51:43.884392+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694703884_m1.jpg...
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iTerm2
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screenpipe"
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whisper_backend_init_gpu: device 0: Metal (type: 1 whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:19:33.292044Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:20:41.739676Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=visual_change)
2026-05-13T20:20:43.764153Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)
2026-05-13T20:20:44.336319Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=6760567930269346508, trigger=click)
2026-05-13T20:20:44.353283Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)
2026-05-13T20:20:45.171964Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=6760567930269346508, trigger=click)
2026-05-13T20:20:45.227770Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:21:36.710876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
https://screenpi.pe
2026-05-13T20:22:34.765083Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=59 elapsed=5.033707583s
2026-05-13T20:22:34.767680Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 59 eligible frames
2026-05-13T20:22:37.078655Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 25 frames, 7.1MB → 0.8MB (9.2x), 25 JPEGs deleted
2026-05-13T20:22:40.300501Z WARN sqlx::query: summary="SELECT DISTINCT app_name, window_name, …" db.statement="\n\nSELECT\n DISTINCT app_name,\n window_name,\n browser_url\nFROM\n frames\nWHERE\n timestamp > datetime('now', '-30 seconds')\n AND app_name IS NOT NULL\n AND window_name IS NOT NULL\n" rows_affected=0 rows_returned=428 elapsed=1.425157125s
2026-05-13T20:22:41.718930Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.1MB → 1.4MB (3.7x), 32 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:23:41.034922Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:27:53.479247Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=70 elapsed=11.674598333s
2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames
2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted
2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:33:17.883716Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=99 elapsed=8.890067292s
2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames
2026-05-13T20:33:17.891727Z WARN sqlx::query: summary="SELECT DISTINCT app_name, window_name, …" db.statement="\n\nSELECT\n DISTINCT app_name,\n window_name,\n browser_url\nFROM\n frames\nWHERE\n timestamp > datetime('now', '-30 seconds')\n AND app_name IS NOT NULL\n AND window_name IS NOT NULL\n" rows_affected=1 rows_returned=430 elapsed=3.709471458s
2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted
2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:38:37.344312Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=44 elapsed=5.107326084s
2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames
2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted
2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
https://screenpi.pe
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:43:42.753501Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=22 elapsed=1.527175333s
2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted
2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:48:47.503128Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=11 elapsed=2.495709958s
2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames
2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted
2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted
2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)
2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)
2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1
2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart
2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)
2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)
2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-13T20:49:46.278662Z WARN sqlx::query: summary="INSERT INTO frames ( …" db.statement="\n\nINSERT INTO\n frames (\n video_chunk_id,\n offset_index,\n timestamp,\n name,\n browser_url,\n app_name,\n window_name,\n focused,\n device_name,\n snapshot_path,\n capture_trigger,\n accessibility_text,\n text_source,\n accessibility_tree_json,\n content_hash,\n simhash,\n full_text,\n elements_ref_frame_id,\n document_path\n )\nVALUES\n (\n NULL,\n 0,\n ?1,\n ?2,\n ?3,\n ?4,\n ?5,\n ?6,\n ?7,\n ?8,\n ?9,\n ?10,\n ?11,\n ?12,\n ?13,\n ?14,\n ?15,\n ?16,\n ?17\n )\n" rows_affected=1 rows_returned=0 elapsed=1.244703625s
2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)
2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) ...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:19:33.292044Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:20:41.739676Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=visual_change)\n2026-05-13T20:20:43.764153Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)\n2026-05-13T20:20:44.336319Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=6760567930269346508, trigger=click)\n2026-05-13T20:20:44.353283Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)\n2026-05-13T20:20:45.171964Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=6760567930269346508, trigger=click)\n2026-05-13T20:20:45.227770Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:21:36.710876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-13T20:22:34.765083Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=59 elapsed=5.033707583s\n2026-05-13T20:22:34.767680Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 59 eligible frames\n2026-05-13T20:22:37.078655Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 25 frames, 7.1MB → 0.8MB (9.2x), 25 JPEGs deleted\n2026-05-13T20:22:40.300501Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=0 rows_returned=428 elapsed=1.425157125s\n2026-05-13T20:22:41.718930Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.1MB → 1.4MB (3.7x), 32 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:23:41.034922Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:27:53.479247Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=70 elapsed=11.674598333s\n2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames\n2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted\n2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:33:17.883716Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=99 elapsed=8.890067292s\n2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames\n2026-05-13T20:33:17.891727Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=3.709471458s\n2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted\n2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:38:37.344312Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=44 elapsed=5.107326084s\n2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames\n2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted\n2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:43:42.753501Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=22 elapsed=1.527175333s\n2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted\n2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:48:47.503128Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=11 elapsed=2.495709958s\n2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames\n2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted\n2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted\n2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-13T20:49:46.278662Z WARN sqlx::query: summary=\"INSERT INTO frames ( …\" db.statement=\"\\n\\nINSERT INTO\\n frames (\\n video_chunk_id,\\n offset_index,\\n timestamp,\\n name,\\n browser_url,\\n app_name,\\n window_name,\\n focused,\\n device_name,\\n snapshot_path,\\n capture_trigger,\\n accessibility_text,\\n text_source,\\n accessibility_tree_json,\\n content_hash,\\n simhash,\\n full_text,\\n elements_ref_frame_id,\\n document_path\\n )\\nVALUES\\n (\\n NULL,\\n 0,\\n ?1,\\n ?2,\\n ?3,\\n ?4,\\n ?5,\\n ?6,\\n ?7,\\n ?8,\\n ?9,\\n ?10,\\n ?11,\\n ?12,\\n ?13,\\n ?14,\\n ?15,\\n ?16,\\n ?17\\n )\\n\" rows_affected=1 rows_returned=0 elapsed=1.244703625s\n2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)\n2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) → inserting 109.9ms silence (10554 samples)\n2026-05-13T20:49:50.138185Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 123.4ms elapsed (expected 5.3ms) → inserting 118.1ms silence (11335 samples)\n2026-05-13T20:49:50.422739Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.2ms elapsed (expected 5.3ms) → inserting 76.9ms silence (7383 samples)\n2026-05-13T20:49:50.671835Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 249.1ms elapsed (expected 5.3ms) → inserting 243.8ms silence (23401 samples)\n2026-05-13T20:49:57.489211Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=14.406079875s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-13T20:50:25.337392Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.06712725s\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:50:34.187500Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:50:40.135101Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.170097666s\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json","depth":4,"on_screen":true,"value":"whisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:19:33.292044Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:20:41.739676Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=visual_change)\n2026-05-13T20:20:43.764153Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)\n2026-05-13T20:20:44.336319Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=6760567930269346508, trigger=click)\n2026-05-13T20:20:44.353283Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)\n2026-05-13T20:20:45.171964Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=6760567930269346508, trigger=click)\n2026-05-13T20:20:45.227770Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:21:36.710876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-13T20:22:34.765083Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=59 elapsed=5.033707583s\n2026-05-13T20:22:34.767680Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 59 eligible frames\n2026-05-13T20:22:37.078655Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 25 frames, 7.1MB → 0.8MB (9.2x), 25 JPEGs deleted\n2026-05-13T20:22:40.300501Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=0 rows_returned=428 elapsed=1.425157125s\n2026-05-13T20:22:41.718930Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.1MB → 1.4MB (3.7x), 32 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:23:41.034922Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:27:53.479247Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=70 elapsed=11.674598333s\n2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames\n2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted\n2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:33:17.883716Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=99 elapsed=8.890067292s\n2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames\n2026-05-13T20:33:17.891727Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=3.709471458s\n2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted\n2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:38:37.344312Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=44 elapsed=5.107326084s\n2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames\n2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted\n2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:43:42.753501Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=22 elapsed=1.527175333s\n2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted\n2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:48:47.503128Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=11 elapsed=2.495709958s\n2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames\n2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted\n2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted\n2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-13T20:49:46.278662Z WARN sqlx::query: summary=\"INSERT INTO frames ( …\" db.statement=\"\\n\\nINSERT INTO\\n frames (\\n video_chunk_id,\\n offset_index,\\n timestamp,\\n name,\\n browser_url,\\n app_name,\\n window_name,\\n focused,\\n device_name,\\n snapshot_path,\\n capture_trigger,\\n accessibility_text,\\n text_source,\\n accessibility_tree_json,\\n content_hash,\\n simhash,\\n full_text,\\n elements_ref_frame_id,\\n document_path\\n )\\nVALUES\\n (\\n NULL,\\n 0,\\n ?1,\\n ?2,\\n ?3,\\n ?4,\\n ?5,\\n ?6,\\n ?7,\\n ?8,\\n ?9,\\n ?10,\\n ?11,\\n ?12,\\n ?13,\\n ?14,\\n ?15,\\n ?16,\\n ?17\\n )\\n\" rows_affected=1 rows_returned=0 elapsed=1.244703625s\n2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)\n2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) → inserting 109.9ms silence (10554 samples)\n2026-05-13T20:49:50.138185Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 123.4ms elapsed (expected 5.3ms) → inserting 118.1ms silence (11335 samples)\n2026-05-13T20:49:50.422739Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.2ms elapsed (expected 5.3ms) → inserting 76.9ms silence (7383 samples)\n2026-05-13T20:49:50.671835Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 249.1ms elapsed (expected 5.3ms) → inserting 243.8ms silence (23401 samples)\n2026-05-13T20:49:57.489211Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=14.406079875s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-13T20:50:25.337392Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.06712725s\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:50:34.187500Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:50:40.135101Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.170097666s\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.14097223,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (docker)","depth":2,"bounds":{"left":0.14097223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14513889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28159723,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.2857639,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.42222223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4263889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.5628472,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56701386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (nc)","depth":2,"bounds":{"left":0.7034722,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70763886,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-20-31-146:~ (nc)","depth":2,"bounds":{"left":0.8440972,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.84826386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.95625,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.47152779,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
|
-856878531618862470
|
-852231706446596640
|
visual_change
|
accessibility
|
NULL
|
whisper_backend_init_gpu: device 0: Metal (type: 1 whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:19:33.292044Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:20:41.739676Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=visual_change)
2026-05-13T20:20:43.764153Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)
2026-05-13T20:20:44.336319Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=6760567930269346508, trigger=click)
2026-05-13T20:20:44.353283Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)
2026-05-13T20:20:45.171964Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=6760567930269346508, trigger=click)
2026-05-13T20:20:45.227770Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6760567930269346508, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:21:36.710876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
https://screenpi.pe
2026-05-13T20:22:34.765083Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=59 elapsed=5.033707583s
2026-05-13T20:22:34.767680Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 59 eligible frames
2026-05-13T20:22:37.078655Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 25 frames, 7.1MB → 0.8MB (9.2x), 25 JPEGs deleted
2026-05-13T20:22:40.300501Z WARN sqlx::query: summary="SELECT DISTINCT app_name, window_name, …" db.statement="\n\nSELECT\n DISTINCT app_name,\n window_name,\n browser_url\nFROM\n frames\nWHERE\n timestamp > datetime('now', '-30 seconds')\n AND app_name IS NOT NULL\n AND window_name IS NOT NULL\n" rows_affected=0 rows_returned=428 elapsed=1.425157125s
2026-05-13T20:22:41.718930Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.1MB → 1.4MB (3.7x), 32 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:23:41.034922Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:27:53.479247Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=70 elapsed=11.674598333s
2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames
2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted
2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:33:17.883716Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=99 elapsed=8.890067292s
2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames
2026-05-13T20:33:17.891727Z WARN sqlx::query: summary="SELECT DISTINCT app_name, window_name, …" db.statement="\n\nSELECT\n DISTINCT app_name,\n window_name,\n browser_url\nFROM\n frames\nWHERE\n timestamp > datetime('now', '-30 seconds')\n AND app_name IS NOT NULL\n AND window_name IS NOT NULL\n" rows_affected=1 rows_returned=430 elapsed=3.709471458s
2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted
2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:38:37.344312Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=44 elapsed=5.107326084s
2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames
2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted
2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
https://screenpi.pe
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:43:42.753501Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=22 elapsed=1.527175333s
2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted
2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:48:47.503128Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=11 elapsed=2.495709958s
2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames
2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted
2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted
2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)
2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)
2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1
2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart
2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)
2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)
2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-13T20:49:46.278662Z WARN sqlx::query: summary="INSERT INTO frames ( …" db.statement="\n\nINSERT INTO\n frames (\n video_chunk_id,\n offset_index,\n timestamp,\n name,\n browser_url,\n app_name,\n window_name,\n focused,\n device_name,\n snapshot_path,\n capture_trigger,\n accessibility_text,\n text_source,\n accessibility_tree_json,\n content_hash,\n simhash,\n full_text,\n elements_ref_frame_id,\n document_path\n )\nVALUES\n (\n NULL,\n 0,\n ?1,\n ?2,\n ?3,\n ?4,\n ?5,\n ?6,\n ?7,\n ?8,\n ?9,\n ?10,\n ?11,\n ?12,\n ?13,\n ?14,\n ?15,\n ?16,\n ?17\n )\n" rows_affected=1 rows_returned=0 elapsed=1.244703625s
2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)
2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) ...
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2026-05-13T17:51:44.870780+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694704870_m2.jpg...
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iTerm2
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ec2-user@ip-10-30-129-190:~
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monitor_2
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Last login: Wed May 13 09:16:21 on ttys010
Poetry Last login: Wed May 13 09:16:21 on ttys010
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
ec2-user@ip-10-30-129-190:~ (nc)
Close Tab
ec2-user@ip-10-20-31-146:~ (nc)
Close Tab
⌥⌘1
ec2-user@ip-10-30-129-190:~...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Wed May 13 09:16:21 on ttys010\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80\nEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalik@jiminny.com: \nWarning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.\n\nA newer release of \"Amazon Linux\" is available.\n Version 2023.10.20260330:\n Version 2023.11.20260406:\n Version 2023.11.20260413:\n Version 2023.11.20260427:\n Version 2023.11.20260505:\n Version 2023.11.20260509:\nRun \"/usr/bin/dnf check-release-update\" for full release and version update info\n , #_\n ~\\_ ####_\n ~~ \\_#####\\\n ~~ \\###|\n ~~ \\#/ ___ Amazon Linux 2023 (ECS Optimized)\n ~~ V~' '->\n ~~~ /\n ~~._. _/\n _/ _/\n _/m/'\n\nFor documentation, visit http://aws.amazon.com/documentation/ecs\nLast login: Wed May 13 11:43:03 2026 from 10.30.45.167\n[ec2-user@ip-10-30-129-190 ~]$","depth":4,"bounds":{"left":0.27027926,"top":1.0,"width":0.4793883,"height":-0.06304872},"on_screen":true,"value":"Last login: Wed May 13 09:16:21 on ttys010\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80\nEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalik@jiminny.com: \nWarning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.\n\nA newer release of \"Amazon Linux\" is available.\n Version 2023.10.20260330:\n Version 2023.11.20260406:\n Version 2023.11.20260413:\n Version 2023.11.20260427:\n Version 2023.11.20260505:\n Version 2023.11.20260509:\nRun \"/usr/bin/dnf check-release-update\" for full release and version update info\n , #_\n ~\\_ ####_\n ~~ \\_#####\\\n ~~ \\###|\n ~~ \\#/ ___ Amazon Linux 2023 (ECS Optimized)\n ~~ V~' '->\n ~~~ /\n ~~._. _/\n _/ _/\n _/m/'\n\nFor documentation, visit http://aws.amazon.com/documentation/ecs\nLast login: Wed May 13 11:43:03 2026 from 10.30.45.167\n[ec2-user@ip-10-30-129-190 ~]$","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.0674867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (docker)","depth":2,"bounds":{"left":0.33776596,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.33976063,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.40508643,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.40708113,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.47240692,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4744016,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.5397274,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.54172206,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (nc)","depth":2,"bounds":{"left":0.60704786,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.6090425,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-20-31-146:~ (nc)","depth":2,"bounds":{"left":0.6743683,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.67636305,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7280585,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"ec2-user@ip-10-30-129-190:~","depth":1,"bounds":{"left":0.47573137,"top":1.0,"width":0.068484046,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
|
-3100254718425624841
|
-1404540281898360358
|
click
|
accessibility
|
NULL
|
Last login: Wed May 13 09:16:21 on ttys010
Poetry Last login: Wed May 13 09:16:21 on ttys010
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
ec2-user@ip-10-30-129-190:~ (nc)
Close Tab
ec2-user@ip-10-20-31-146:~ (nc)
Close Tab
⌥⌘1
ec2-user@ip-10-30-129-190:~...
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38628
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1433
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26
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2026-05-13T17:51:44.900620+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694704900_m1.jpg...
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iTerm2
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ec2-user@ip-10-30-129-190:~
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Last login: Wed May 13 09:16:21 on ttys010
Poetry Last login: Wed May 13 09:16:21 on ttys010
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
ec2-user@ip-10-30-129-190:~ (nc)
Close Tab
ec2-user@ip-10-20-31-146:~ (nc)
Close Tab
⌥⌘1
ec2-user@ip-10-30-129-190:~...
|
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_/\n _/ _/\n _/m/'\n\nFor documentation, visit http://aws.amazon.com/documentation/ecs\nLast login: Wed May 13 11:43:03 2026 from 10.30.45.167\n[ec2-user@ip-10-30-129-190 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login: Wed May 13 09:16:21 on ttys010\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80\nEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalik@jiminny.com: \nWarning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.\n\nA newer release of \"Amazon Linux\" is available.\n Version 2023.10.20260330:\n Version 2023.11.20260406:\n Version 2023.11.20260413:\n Version 2023.11.20260427:\n Version 2023.11.20260505:\n Version 2023.11.20260509:\nRun \"/usr/bin/dnf check-release-update\" for full release and version update info\n , #_\n ~\\_ ####_\n ~~ \\_#####\\\n ~~ \\###|\n ~~ \\#/ ___ Amazon Linux 2023 (ECS Optimized)\n ~~ V~' '->\n ~~~ /\n ~~._. _/\n _/ _/\n _/m/'\n\nFor documentation, visit http://aws.amazon.com/documentation/ecs\nLast login: Wed May 13 11:43:03 2026 from 10.30.45.167\n[ec2-user@ip-10-30-129-190 ~]$","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.14097223,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (docker)","depth":2,"bounds":{"left":0.14097223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close 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(nc)","depth":2,"bounds":{"left":0.7034722,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70763886,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-20-31-146:~ (nc)","depth":2,"bounds":{"left":0.8440972,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close 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click
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Last login: Wed May 13 09:16:21 on ttys010
Poetry Last login: Wed May 13 09:16:21 on ttys010
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ ssh jiminny-prod-ecs1 -L 7970:vpc-activities7g-t6nxe5qk7zis7pa5i7qlmp3zwm.us-east-2.es.amazonaws.com:80
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
Warning: Permanently added 'jiminny-prod-ecs1' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
ec2-user@ip-10-30-129-190:~ (nc)
Close Tab
ec2-user@ip-10-20-31-146:~ (nc)
Close Tab
⌥⌘1
ec2-user@ip-10-30-129-190:~...
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38627
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NULL
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38631
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0
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2026-05-13T17:51:48.294095+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694708294_m2.jpg...
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iTerm2
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ec2-user@ip-10-20-31-146:~
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monitor_2
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Last login: Wed May 13 15:24:32 on ttys011
Poetry Last login: Wed May 13 15:24:32 on ttys011
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging
Starting environment staging
Started environment(s) staging
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
nc: read failed (0/10): Broken pipe
Connection closed by UNKNOWN port 65535
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2
Warning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$ docker exec -it $(docker ps --format "{{.ID}}" --filter "name=ecs-worker" | head -1) /bin/bash -c "cd /home/jiminny && bash"
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110
[2026-05-13 15:28:23] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-1184-72ca-8c79-d9e09814baa4\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
Flow refresh required.
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R
[2026-05-13 15:28:31] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-319c-7501-8b0e-d3118c6534f8\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
Flow refresh required.
root@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$
DOCKER
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APP (-zsh)
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screenpipe"
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ec2-user@ip-10-30-129-190:~ (nc)
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ec2-user@ip-10-20-31-146:~ (nc)
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ec2-user@ip-10-20-31-146:~...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Wed May 13 15:24:32 on ttys011\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging\nStarting environment staging\nStarted environment(s) staging\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu \nEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalik@jiminny.com: \nnc: read failed (0/10): Broken pipe\nConnection closed by UNKNOWN port 65535\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2\nWarning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.\n\nA newer release of \"Amazon Linux\" is available.\n Version 2023.10.20260330:\n Version 2023.11.20260406:\n Version 2023.11.20260413:\n Version 2023.11.20260427:\n Version 2023.11.20260505:\n Version 2023.11.20260509:\nRun \"/usr/bin/dnf check-release-update\" for full release and version update info\n , #_\n ~\\_ ####_\n ~~ \\_#####\\\n ~~ \\###|\n ~~ \\#/ ___ Amazon Linux 2023 (ECS Optimized)\n ~~ V~' '->\n ~~~ /\n ~~._. _/\n _/ _/\n _/m/'\n\nFor documentation, visit http://aws.amazon.com/documentation/ecs\nLast login: Tue May 12 13:56:11 2026 from 10.20.163.228\n[ec2-user@ip-10-20-31-146 ~]$ docker exec -it $(docker ps --format \"{{.ID}}\" --filter \"name=ecs-worker\" | head -1) /bin/bash -c \"cd /home/jiminny && bash\"\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 \n[2026-05-13 15:28:23] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-1184-72ca-8c79-d9e09814baa4\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R\n[2026-05-13 15:28:31] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-319c-7501-8b0e-d3118c6534f8\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$","depth":4,"on_screen":true,"value":"Last login: Wed May 13 15:24:32 on ttys011\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging\nStarting environment staging\nStarted environment(s) staging\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu \nEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalik@jiminny.com: \nnc: read failed (0/10): Broken pipe\nConnection closed by UNKNOWN port 65535\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2\nWarning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.\n\nA newer release of \"Amazon Linux\" is available.\n Version 2023.10.20260330:\n Version 2023.11.20260406:\n Version 2023.11.20260413:\n Version 2023.11.20260427:\n Version 2023.11.20260505:\n Version 2023.11.20260509:\nRun \"/usr/bin/dnf check-release-update\" for full release and version update info\n , #_\n ~\\_ ####_\n ~~ \\_#####\\\n ~~ \\###|\n ~~ \\#/ ___ Amazon Linux 2023 (ECS Optimized)\n ~~ V~' '->\n ~~~ /\n ~~._. _/\n _/ _/\n _/m/'\n\nFor documentation, visit http://aws.amazon.com/documentation/ecs\nLast login: Tue May 12 13:56:11 2026 from 10.20.163.228\n[ec2-user@ip-10-20-31-146 ~]$ docker exec -it $(docker ps --format \"{{.ID}}\" --filter \"name=ecs-worker\" | head -1) /bin/bash -c \"cd /home/jiminny && bash\"\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 \n[2026-05-13 15:28:23] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-1184-72ca-8c79-d9e09814baa4\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R\n[2026-05-13 15:28:31] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-319c-7501-8b0e-d3118c6534f8\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.0674867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (docker)","depth":2,"bounds":{"left":0.33776596,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.33976063,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.40508643,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.40708113,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.47240692,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4744016,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.5397274,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.54172206,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (nc)","depth":2,"bounds":{"left":0.60704786,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.6090425,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-20-31-146:~ (nc)","depth":2,"bounds":{"left":0.6743683,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.67636305,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7280585,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"ec2-user@ip-10-20-31-146:~","depth":1,"bounds":{"left":0.47706118,"top":1.0,"width":0.06549202,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
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-7542693588077229645
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-80532371099046699
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click
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accessibility
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NULL
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Last login: Wed May 13 15:24:32 on ttys011
Poetry Last login: Wed May 13 15:24:32 on ttys011
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging
Starting environment staging
Started environment(s) staging
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
nc: read failed (0/10): Broken pipe
Connection closed by UNKNOWN port 65535
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2
Warning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$ docker exec -it $(docker ps --format "{{.ID}}" --filter "name=ecs-worker" | head -1) /bin/bash -c "cd /home/jiminny && bash"
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110
[2026-05-13 15:28:23] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-1184-72ca-8c79-d9e09814baa4\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
Flow refresh required.
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R
[2026-05-13 15:28:31] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-319c-7501-8b0e-d3118c6534f8\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
Flow refresh required.
root@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
ec2-user@ip-10-30-129-190:~ (nc)
Close Tab
ec2-user@ip-10-20-31-146:~ (nc)
Close Tab
⌥⌘1
ec2-user@ip-10-20-31-146:~...
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38629
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NULL
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NULL
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NULL
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38630
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1433
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27
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2026-05-13T17:51:48.294099+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694708294_m1.jpg...
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iTerm2
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ec2-user@ip-10-20-31-146:~
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1
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NULL
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monitor_1
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NULL
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NULL
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NULL
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NULL
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Last login: Wed May 13 15:24:32 on ttys011
Poetry Last login: Wed May 13 15:24:32 on ttys011
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging
Starting environment staging
Started environment(s) staging
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
nc: read failed (0/10): Broken pipe
Connection closed by UNKNOWN port 65535
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2
Warning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$ docker exec -it $(docker ps --format "{{.ID}}" --filter "name=ecs-worker" | head -1) /bin/bash -c "cd /home/jiminny && bash"
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110
[2026-05-13 15:28:23] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-1184-72ca-8c79-d9e09814baa4\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
Flow refresh required.
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R
[2026-05-13 15:28:31] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-319c-7501-8b0e-d3118c6534f8\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
Flow refresh required.
root@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
ec2-user@ip-10-30-129-190:~ (nc)
Close Tab
ec2-user@ip-10-20-31-146:~ (nc)
Close Tab
⌥⌘1
ec2-user@ip-10-20-31-146:~...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Wed May 13 15:24:32 on ttys011\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging\nStarting environment staging\nStarted environment(s) staging\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu \nEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalik@jiminny.com: \nnc: read failed (0/10): Broken pipe\nConnection closed by UNKNOWN port 65535\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2\nWarning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.\n\nA newer release of \"Amazon Linux\" is available.\n Version 2023.10.20260330:\n Version 2023.11.20260406:\n Version 2023.11.20260413:\n Version 2023.11.20260427:\n Version 2023.11.20260505:\n Version 2023.11.20260509:\nRun \"/usr/bin/dnf check-release-update\" for full release and version update info\n , #_\n ~\\_ ####_\n ~~ \\_#####\\\n ~~ \\###|\n ~~ \\#/ ___ Amazon Linux 2023 (ECS Optimized)\n ~~ V~' '->\n ~~~ /\n ~~._. _/\n _/ _/\n _/m/'\n\nFor documentation, visit http://aws.amazon.com/documentation/ecs\nLast login: Tue May 12 13:56:11 2026 from 10.20.163.228\n[ec2-user@ip-10-20-31-146 ~]$ docker exec -it $(docker ps --format \"{{.ID}}\" --filter \"name=ecs-worker\" | head -1) /bin/bash -c \"cd /home/jiminny && bash\"\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 \n[2026-05-13 15:28:23] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-1184-72ca-8c79-d9e09814baa4\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R\n[2026-05-13 15:28:31] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-319c-7501-8b0e-d3118c6534f8\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$","depth":4,"on_screen":true,"value":"Last login: Wed May 13 15:24:32 on ttys011\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging\nStarting environment staging\nStarted environment(s) staging\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu \nEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalik@jiminny.com: \nnc: read failed (0/10): Broken pipe\nConnection closed by UNKNOWN port 65535\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2\nWarning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.\n\nA newer release of \"Amazon Linux\" is available.\n Version 2023.10.20260330:\n Version 2023.11.20260406:\n Version 2023.11.20260413:\n Version 2023.11.20260427:\n Version 2023.11.20260505:\n Version 2023.11.20260509:\nRun \"/usr/bin/dnf check-release-update\" for full release and version update info\n , #_\n ~\\_ ####_\n ~~ \\_#####\\\n ~~ \\###|\n ~~ \\#/ ___ Amazon Linux 2023 (ECS Optimized)\n ~~ V~' '->\n ~~~ /\n ~~._. _/\n _/ _/\n _/m/'\n\nFor documentation, visit http://aws.amazon.com/documentation/ecs\nLast login: Tue May 12 13:56:11 2026 from 10.20.163.228\n[ec2-user@ip-10-20-31-146 ~]$ docker exec -it $(docker ps --format \"{{.ID}}\" --filter \"name=ecs-worker\" | head -1) /bin/bash -c \"cd /home/jiminny && bash\"\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 \n[2026-05-13 15:28:23] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-1184-72ca-8c79-d9e09814baa4\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R\n[2026-05-13 15:28:31] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-319c-7501-8b0e-d3118c6534f8\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.14097223,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (docker)","depth":2,"bounds":{"left":0.14097223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14513889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28159723,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.2857639,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.42222223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4263889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.5628472,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56701386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (nc)","depth":2,"bounds":{"left":0.7034722,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70763886,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-20-31-146:~ (nc)","depth":2,"bounds":{"left":0.8440972,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.84826386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.95625,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"ec2-user@ip-10-20-31-146:~","depth":1,"bounds":{"left":0.43194443,"top":0.033333335,"width":0.13680555,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
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-7542693588077229645
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-80532371099046699
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click
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accessibility
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NULL
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Last login: Wed May 13 15:24:32 on ttys011
Poetry Last login: Wed May 13 15:24:32 on ttys011
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging
Starting environment staging
Started environment(s) staging
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
nc: read failed (0/10): Broken pipe
Connection closed by UNKNOWN port 65535
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2
Warning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$ docker exec -it $(docker ps --format "{{.ID}}" --filter "name=ecs-worker" | head -1) /bin/bash -c "cd /home/jiminny && bash"
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110
[2026-05-13 15:28:23] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-1184-72ca-8c79-d9e09814baa4\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
Flow refresh required.
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R
[2026-05-13 15:28:31] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-319c-7501-8b0e-d3118c6534f8\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
Flow refresh required.
root@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$
DOCKER
Close Tab
DEV (docker)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
ec2-user@ip-10-30-129-190:~ (nc)
Close Tab
ec2-user@ip-10-20-31-146:~ (nc)
Close Tab
⌥⌘1
ec2-user@ip-10-20-31-146:~...
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2026-05-13T17:51:55.988169+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778694715988_m1.jpg...
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iTerm2
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ec2-user@ip-10-20-31-146:~
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1
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monitor_1
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Last login: Wed May 13 15:24:32 on ttys011
Poetry Last login: Wed May 13 15:24:32 on ttys011
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging
Starting environment staging
Started environment(s) staging
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
nc: read failed (0/10): Broken pipe
Connection closed by UNKNOWN port 65535
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2
Warning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$ docker exec -it $(docker ps --format "{{.ID}}" --filter "name=ecs-worker" | head -1) /bin/bash -c "cd /home/jiminny && bash"
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110
[2026-05-13 15:28:23] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-1184-72ca-8c79-d9e09814baa4\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
Flow refresh required.
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R
[2026-05-13 15:28:31] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-319c-7501-8b0e-d3118c6534f8\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
Flow refresh required.
root@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$ exirt
-bash: exirt: command not found
[ec2-user@ip-10-20-31-146 ~]$ exit
logout
Connection to jiminny-eu-ecs2 closed.
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ sp-st
DOCKER
Close Tab
DEV (-zsh)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
ec2-user@ip-10-30-129-190:~ (nc)
Close Tab
ec2-user@ip-10-20-31-146:~ (-zsh)
Close Tab
⌥⌘1
ec2-user@ip-10-20-31-146:~...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Wed May 13 15:24:32 on ttys011\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging\nStarting environment staging\nStarted environment(s) staging\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu \nEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalik@jiminny.com: \nnc: read failed (0/10): Broken pipe\nConnection closed by UNKNOWN port 65535\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2\nWarning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.\n\nA newer release of \"Amazon Linux\" is available.\n Version 2023.10.20260330:\n Version 2023.11.20260406:\n Version 2023.11.20260413:\n Version 2023.11.20260427:\n Version 2023.11.20260505:\n Version 2023.11.20260509:\nRun \"/usr/bin/dnf check-release-update\" for full release and version update info\n , #_\n ~\\_ ####_\n ~~ \\_#####\\\n ~~ \\###|\n ~~ \\#/ ___ Amazon Linux 2023 (ECS Optimized)\n ~~ V~' '->\n ~~~ /\n ~~._. _/\n _/ _/\n _/m/'\n\nFor documentation, visit http://aws.amazon.com/documentation/ecs\nLast login: Tue May 12 13:56:11 2026 from 10.20.163.228\n[ec2-user@ip-10-20-31-146 ~]$ docker exec -it $(docker ps --format \"{{.ID}}\" --filter \"name=ecs-worker\" | head -1) /bin/bash -c \"cd /home/jiminny && bash\"\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 \n[2026-05-13 15:28:23] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-1184-72ca-8c79-d9e09814baa4\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R\n[2026-05-13 15:28:31] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-319c-7501-8b0e-d3118c6534f8\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$ exirt\n-bash: exirt: command not found\n[ec2-user@ip-10-20-31-146 ~]$ exit\nlogout\nConnection to jiminny-eu-ecs2 closed.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ sp-st","depth":4,"on_screen":true,"value":"Last login: Wed May 13 15:24:32 on ttys011\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging\nStarting environment staging\nStarted environment(s) staging\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu \nEnter MFA code for arn:aws:iam::438740370364:mfa/lukas.kovalik@jiminny.com: \nnc: read failed (0/10): Broken pipe\nConnection closed by UNKNOWN port 65535\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2\nWarning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.\n\nA newer release of \"Amazon Linux\" is available.\n Version 2023.10.20260330:\n Version 2023.11.20260406:\n Version 2023.11.20260413:\n Version 2023.11.20260427:\n Version 2023.11.20260505:\n Version 2023.11.20260509:\nRun \"/usr/bin/dnf check-release-update\" for full release and version update info\n , #_\n ~\\_ ####_\n ~~ \\_#####\\\n ~~ \\###|\n ~~ \\#/ ___ Amazon Linux 2023 (ECS Optimized)\n ~~ V~' '->\n ~~~ /\n ~~._. _/\n _/ _/\n _/m/'\n\nFor documentation, visit http://aws.amazon.com/documentation/ecs\nLast login: Tue May 12 13:56:11 2026 from 10.20.163.228\n[ec2-user@ip-10-20-31-146 ~]$ docker exec -it $(docker ps --format \"{{.ID}}\" --filter \"name=ecs-worker\" | head -1) /bin/bash -c \"cd /home/jiminny && bash\"\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 \n[2026-05-13 15:28:23] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-1184-72ca-8c79-d9e09814baa4\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\n[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec\",\"trace_id\":\"1a72fef6-427a-4e63-a9ba-b340103c976b\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R\n[2026-05-13 15:28:31] production.INFO: Jiminny\\Console\\Commands\\Command::run Memory usage before starting command {\"command\":\"jiminny:token-info\",\"memoryBeforeCommandInMb\":116.0,\"memoryPeakBeforeCommandInMb\":116.0} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {\"socialAccountId\":30110,\"provider\":\"hubspot\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {\"mode\":\"legacy\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"refreshToken\":\"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c\",\"state\":\"full-refresh\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {\"socialAccountId\":30110,\"provider\":\"hubspot\",\"responseBody\":\"{\\\"status\\\":\\\"BAD_HUB\\\",\\\"message\\\":\\\"missing or unknown hub id\\\",\\\"correlationId\\\":\\\"019e21f4-319c-7501-8b0e-d3118c6534f8\\\",\\\"error\\\":\\\"access_denied\\\",\\\"error_description\\\":\\\"missing or unknown hub id\\\"}\"} {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\n[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {\"correlation_id\":\"b1e2505a-8c60-4607-a96a-a33209efd4c4\",\"trace_id\":\"001e9c48-df0f-4111-9988-d3bb8bf7bfa8\"}\n\nFlow refresh required.\nroot@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$ exirt\n-bash: exirt: command not found\n[ec2-user@ip-10-20-31-146 ~]$ exit\nlogout\nConnection to jiminny-eu-ecs2 closed.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ sp-st","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.14097223,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.14097223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14513889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28159723,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.2857639,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.42222223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4263889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.5628472,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56701386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (nc)","depth":2,"bounds":{"left":0.7034722,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70763886,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-20-31-146:~ (-zsh)","depth":2,"bounds":{"left":0.8440972,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.84826386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.95625,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"ec2-user@ip-10-20-31-146:~","depth":1,"bounds":{"left":0.43194443,"top":0.033333335,"width":0.13680555,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
|
-5019667841766001512
|
9088796471031540949
|
visual_change
|
accessibility
|
NULL
|
Last login: Wed May 13 15:24:32 on ttys011
Poetry Last login: Wed May 13 15:24:32 on ttys011
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
Poetry could not find a pyproject.toml file in /Users/lukas or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ app
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias tenv
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ scripts/toggle_environment start staging
Starting environment staging
Started environment(s) staging
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20891-improve-sms-text-relays) $ veu
Enter MFA code for arn:aws:iam::438740370364:mfa/[EMAIL]:
nc: read failed (0/10): Broken pipe
Connection closed by UNKNOWN port 65535
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ veu2
Warning: Permanently added 'jiminny-eu-ecs2' (ED25519) to the list of known hosts.
A newer release of "Amazon Linux" is available.
Version 2023.10.20260330:
Version 2023.11.20260406:
Version 2023.11.20260413:
Version 2023.11.20260427:
Version 2023.11.20260505:
Version 2023.11.20260509:
Run "/usr/bin/dnf check-release-update" for full release and version update info
, #_
~\_ ####_
~~ \_#####\
~~ \###|
~~ \#/ ___ Amazon Linux 2023 (ECS Optimized)
~~ V~' '->
~~~ /
~~._. _/
_/ _/
_/m/'
For documentation, visit [URL_WITH_CREDENTIALS] ~]$ docker exec -it $(docker ps --format "{{.ID}}" --filter "name=ecs-worker" | head -1) /bin/bash -c "cd /home/jiminny && bash"
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110
[2026-05-13 15:28:23] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-1184-72ca-8c79-d9e09814baa4\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
[2026-05-13 15:28:23] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"ed1a364d-0b07-4c47-95a7-d22fd8ef6bec","trace_id":"1a72fef6-427a-4e63-a9ba-b340103c976b"}
Flow refresh required.
root@453da0675541:/home/jiminny# php artisan jiminny:token-info -A 30110 -R
[2026-05-13 15:28:31] production.INFO: Jiminny\Console\Commands\Command::run Memory usage before starting command {"command":"jiminny:token-info","memoryBeforeCommandInMb":116.0,"memoryPeakBeforeCommandInMb":116.0} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Fetching token {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Token needs refreshing {"socialAccountId":30110,"provider":"hubspot"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [EncryptedTokenManager] Generating access token. {"mode":"legacy"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:31] production.INFO: [SocialAccountService] Refreshing token from provider {"socialAccountId":30110,"provider":"hubspot","refreshToken":"9417a6a067cd68efa0bd023e970cc27482ef7db27b876a4383f5a246c4e8d81c","state":"full-refresh"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.ERROR: [SocialAccountService] Failed to refresh token {"socialAccountId":30110,"provider":"hubspot","responseBody":"{\"status\":\"BAD_HUB\",\"message\":\"missing or unknown hub id\",\"correlationId\":\"019e21f4-319c-7501-8b0e-d3118c6534f8\",\"error\":\"access_denied\",\"error_description\":\"missing or unknown hub id\"}"} {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
[2026-05-13 15:28:32] production.INFO: [SocialAccountObserver] Saving model {"correlation_id":"b1e2505a-8c60-4607-a96a-a33209efd4c4","trace_id":"001e9c48-df0f-4111-9988-d3bb8bf7bfa8"}
Flow refresh required.
root@453da0675541:/home/jiminny# [ec2-user@ip-10-20-31-146 ~]$ exirt
-bash: exirt: command not found
[ec2-user@ip-10-20-31-146 ~]$ exit
logout
Connection to jiminny-eu-ecs2 closed.
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ sp-st
DOCKER
Close Tab
DEV (-zsh)
Close Tab
APP (-zsh)
Close Tab
-zsh
Close Tab
screenpipe"
Close Tab
ec2-user@ip-10-30-129-190:~ (nc)
Close Tab
ec2-user@ip-10-20-31-146:~ (-zsh)
Close Tab
⌥⌘1
ec2-user@ip-10-20-31-146:~...
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38630
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NULL
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NULL
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NULL
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38633
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1435
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0
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2026-05-14T06:24:59.201328+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-14/1778 /Users/lukas/.screenpipe/data/data/2026-05-14/1778739899201_m1.jpg...
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iTerm2
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screenpipe"
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1
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NULL
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monitor_1
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NULL
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NULL
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NULL
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NULL
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whisper_init_state: kv pad size = 2.36 MB
whi whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:27:53.479247Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=70 elapsed=11.674598333s
2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames
2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted
2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-14T09:24:58.131971Z INFO screenpipe_engine...
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:27:53.479247Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=70 elapsed=11.674598333s\n2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames\n2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted\n2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:33:17.883716Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=99 elapsed=8.890067292s\n2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames\n2026-05-13T20:33:17.891727Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=3.709471458s\n2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted\n2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:38:37.344312Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=44 elapsed=5.107326084s\n2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames\n2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted\n2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:43:42.753501Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=22 elapsed=1.527175333s\n2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted\n2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:48:47.503128Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=11 elapsed=2.495709958s\n2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames\n2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted\n2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted\n2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-13T20:49:46.278662Z WARN sqlx::query: summary=\"INSERT INTO frames ( …\" db.statement=\"\\n\\nINSERT INTO\\n frames (\\n video_chunk_id,\\n offset_index,\\n timestamp,\\n name,\\n browser_url,\\n app_name,\\n window_name,\\n focused,\\n device_name,\\n snapshot_path,\\n capture_trigger,\\n accessibility_text,\\n text_source,\\n accessibility_tree_json,\\n content_hash,\\n simhash,\\n full_text,\\n elements_ref_frame_id,\\n document_path\\n )\\nVALUES\\n (\\n NULL,\\n 0,\\n ?1,\\n ?2,\\n ?3,\\n ?4,\\n ?5,\\n ?6,\\n ?7,\\n ?8,\\n ?9,\\n ?10,\\n ?11,\\n ?12,\\n ?13,\\n ?14,\\n ?15,\\n ?16,\\n ?17\\n )\\n\" rows_affected=1 rows_returned=0 elapsed=1.244703625s\n2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)\n2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) → inserting 109.9ms silence (10554 samples)\n2026-05-13T20:49:50.138185Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 123.4ms elapsed (expected 5.3ms) → inserting 118.1ms silence (11335 samples)\n2026-05-13T20:49:50.422739Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.2ms elapsed (expected 5.3ms) → inserting 76.9ms silence (7383 samples)\n2026-05-13T20:49:50.671835Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 249.1ms elapsed (expected 5.3ms) → inserting 243.8ms silence (23401 samples)\n2026-05-13T20:49:57.489211Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=14.406079875s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-13T20:50:25.337392Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.06712725s\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:50:34.187500Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:50:40.135101Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.170097666s\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-13T20:51:47.151342Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=432 elapsed=1.377976291s\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-14T09:24:58.542992Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-14T09:24:58.543188Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-14T09:24:58.545885Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-14T09:24:58.546638Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-14T09:24:58.546795Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-14T09:24:58.547356Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-14T09:24:58.547453Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-14T09:24:58.547767Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-14T09:24:58.547888Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\n2026-05-14T09:24:58.550735Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-14T09:24:58.552083Z INFO screenpipe: starting UI event capture\n2026-05-14T09:24:58.555587Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-14T09:24:58.557961Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-14T09:24:58.568371Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-14T09:24:58.584826Z INFO screenpipe: text-PII worker skipped at startup — async_pii_redaction=false. OPF model (~2.8 GB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584861Z INFO screenpipe: image-PII worker skipped at startup — async_image_pii_redaction=false. rfdetr_v9 model (~108 MB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584915Z INFO screenpipe_engine::ui_recorder: UI recording session started: 25f92ee5-c210-4bb0-aa44-4054d2351b03\n2026-05-14T09:24:58.584978Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-14T09:24:58.585134Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-13 06:24:58.585133 UTC to 2026-05-14 06:24:58.585133 UTC)\n2026-05-14T09:24:58.585862Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-14T09:24:58.594987Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-14T09:24:58.599110Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-14T09:24:58.699260Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-14T09:24:58.699315Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.699350Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.746653Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-14T09:24:58.746781Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-14T09:24:58.746794Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-14T09:24:58.746801Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-14T09:24:58.746815Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-14T09:24:59.307089Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)","depth":4,"on_screen":true,"value":"whisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:27:53.479247Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=70 elapsed=11.674598333s\n2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames\n2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted\n2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:33:17.883716Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=99 elapsed=8.890067292s\n2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames\n2026-05-13T20:33:17.891727Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=3.709471458s\n2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted\n2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:38:37.344312Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=44 elapsed=5.107326084s\n2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames\n2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted\n2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:43:42.753501Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=22 elapsed=1.527175333s\n2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted\n2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:48:47.503128Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=11 elapsed=2.495709958s\n2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames\n2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted\n2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted\n2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-13T20:49:46.278662Z WARN sqlx::query: summary=\"INSERT INTO frames ( …\" db.statement=\"\\n\\nINSERT INTO\\n frames (\\n video_chunk_id,\\n offset_index,\\n timestamp,\\n name,\\n browser_url,\\n app_name,\\n window_name,\\n focused,\\n device_name,\\n snapshot_path,\\n capture_trigger,\\n accessibility_text,\\n text_source,\\n accessibility_tree_json,\\n content_hash,\\n simhash,\\n full_text,\\n elements_ref_frame_id,\\n document_path\\n )\\nVALUES\\n (\\n NULL,\\n 0,\\n ?1,\\n ?2,\\n ?3,\\n ?4,\\n ?5,\\n ?6,\\n ?7,\\n ?8,\\n ?9,\\n ?10,\\n ?11,\\n ?12,\\n ?13,\\n ?14,\\n ?15,\\n ?16,\\n ?17\\n )\\n\" rows_affected=1 rows_returned=0 elapsed=1.244703625s\n2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)\n2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) → inserting 109.9ms silence (10554 samples)\n2026-05-13T20:49:50.138185Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 123.4ms elapsed (expected 5.3ms) → inserting 118.1ms silence (11335 samples)\n2026-05-13T20:49:50.422739Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.2ms elapsed (expected 5.3ms) → inserting 76.9ms silence (7383 samples)\n2026-05-13T20:49:50.671835Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 249.1ms elapsed (expected 5.3ms) → inserting 243.8ms silence (23401 samples)\n2026-05-13T20:49:57.489211Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=14.406079875s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-13T20:50:25.337392Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.06712725s\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:50:34.187500Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:50:40.135101Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.170097666s\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-13T20:51:47.151342Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=432 elapsed=1.377976291s\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-14T09:24:58.542992Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-14T09:24:58.543188Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-14T09:24:58.545885Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-14T09:24:58.546638Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-14T09:24:58.546795Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-14T09:24:58.547356Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-14T09:24:58.547453Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-14T09:24:58.547767Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-14T09:24:58.547888Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\n2026-05-14T09:24:58.550735Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-14T09:24:58.552083Z INFO screenpipe: starting UI event capture\n2026-05-14T09:24:58.555587Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-14T09:24:58.557961Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-14T09:24:58.568371Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-14T09:24:58.584826Z INFO screenpipe: text-PII worker skipped at startup — async_pii_redaction=false. OPF model (~2.8 GB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584861Z INFO screenpipe: image-PII worker skipped at startup — async_image_pii_redaction=false. rfdetr_v9 model (~108 MB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584915Z INFO screenpipe_engine::ui_recorder: UI recording session started: 25f92ee5-c210-4bb0-aa44-4054d2351b03\n2026-05-14T09:24:58.584978Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-14T09:24:58.585134Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-13 06:24:58.585133 UTC to 2026-05-14 06:24:58.585133 UTC)\n2026-05-14T09:24:58.585862Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-14T09:24:58.594987Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-14T09:24:58.599110Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-14T09:24:58.699260Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-14T09:24:58.699315Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.699350Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.746653Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-14T09:24:58.746781Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-14T09:24:58.746794Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-14T09:24:58.746801Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-14T09:24:58.746815Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-14T09:24:59.307089Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.14097223,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.14097223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14513889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28159723,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.2857639,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.42222223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4263889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.5628472,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56701386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (-zsh)","depth":2,"bounds":{"left":0.7034722,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70763886,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-20-31-146:~ (-zsh)","depth":2,"bounds":{"left":0.8440972,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.84826386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.95625,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.47152779,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
|
1324975219323174460
|
-5463917742053853728
|
manual
|
accessibility
|
NULL
|
whisper_init_state: kv pad size = 2.36 MB
whi whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:27:53.479247Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=70 elapsed=11.674598333s
2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames
2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted
2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-14T09:24:58.131971Z INFO screenpipe_engine...
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1436
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0
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2026-05-14T06:24:59.247586+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-14/1778 /Users/lukas/.screenpipe/data/data/2026-05-14/1778739899247_m2.jpg...
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iTerm2
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screenpipe"
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1
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monitor_2
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whisper_init_state: compute buffer (conv) = 14 whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:27:53.479247Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=70 elapsed=11.674598333s
2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames
2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted
2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor starte...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:27:53.479247Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=70 elapsed=11.674598333s\n2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames\n2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted\n2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:33:17.883716Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=99 elapsed=8.890067292s\n2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames\n2026-05-13T20:33:17.891727Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=3.709471458s\n2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted\n2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:38:37.344312Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=44 elapsed=5.107326084s\n2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames\n2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted\n2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:43:42.753501Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=22 elapsed=1.527175333s\n2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted\n2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:48:47.503128Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=11 elapsed=2.495709958s\n2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames\n2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted\n2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted\n2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-13T20:49:46.278662Z WARN sqlx::query: summary=\"INSERT INTO frames ( …\" db.statement=\"\\n\\nINSERT INTO\\n frames (\\n video_chunk_id,\\n offset_index,\\n timestamp,\\n name,\\n browser_url,\\n app_name,\\n window_name,\\n focused,\\n device_name,\\n snapshot_path,\\n capture_trigger,\\n accessibility_text,\\n text_source,\\n accessibility_tree_json,\\n content_hash,\\n simhash,\\n full_text,\\n elements_ref_frame_id,\\n document_path\\n )\\nVALUES\\n (\\n NULL,\\n 0,\\n ?1,\\n ?2,\\n ?3,\\n ?4,\\n ?5,\\n ?6,\\n ?7,\\n ?8,\\n ?9,\\n ?10,\\n ?11,\\n ?12,\\n ?13,\\n ?14,\\n ?15,\\n ?16,\\n ?17\\n )\\n\" rows_affected=1 rows_returned=0 elapsed=1.244703625s\n2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)\n2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) → inserting 109.9ms silence (10554 samples)\n2026-05-13T20:49:50.138185Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 123.4ms elapsed (expected 5.3ms) → inserting 118.1ms silence (11335 samples)\n2026-05-13T20:49:50.422739Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.2ms elapsed (expected 5.3ms) → inserting 76.9ms silence (7383 samples)\n2026-05-13T20:49:50.671835Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 249.1ms elapsed (expected 5.3ms) → inserting 243.8ms silence (23401 samples)\n2026-05-13T20:49:57.489211Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=14.406079875s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-13T20:50:25.337392Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.06712725s\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:50:34.187500Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:50:40.135101Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.170097666s\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-13T20:51:47.151342Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=432 elapsed=1.377976291s\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-14T09:24:58.542992Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-14T09:24:58.543188Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-14T09:24:58.545885Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-14T09:24:58.546638Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-14T09:24:58.546795Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-14T09:24:58.547356Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-14T09:24:58.547453Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-14T09:24:58.547767Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-14T09:24:58.547888Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\n2026-05-14T09:24:58.550735Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-14T09:24:58.552083Z INFO screenpipe: starting UI event capture\n2026-05-14T09:24:58.555587Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-14T09:24:58.557961Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-14T09:24:58.568371Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-14T09:24:58.584826Z INFO screenpipe: text-PII worker skipped at startup — async_pii_redaction=false. OPF model (~2.8 GB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584861Z INFO screenpipe: image-PII worker skipped at startup — async_image_pii_redaction=false. rfdetr_v9 model (~108 MB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584915Z INFO screenpipe_engine::ui_recorder: UI recording session started: 25f92ee5-c210-4bb0-aa44-4054d2351b03\n2026-05-14T09:24:58.584978Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-14T09:24:58.585134Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-13 06:24:58.585133 UTC to 2026-05-14 06:24:58.585133 UTC)\n2026-05-14T09:24:58.585862Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-14T09:24:58.594987Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-14T09:24:58.599110Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-14T09:24:58.699260Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-14T09:24:58.699315Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.699350Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.746653Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-14T09:24:58.746781Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-14T09:24:58.746794Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-14T09:24:58.746801Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-14T09:24:58.746815Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-14T09:24:59.307089Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-14T09:24:59.416921Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)","depth":4,"on_screen":true,"value":"whisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:27:53.479247Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=70 elapsed=11.674598333s\n2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames\n2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted\n2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:33:17.883716Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=99 elapsed=8.890067292s\n2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames\n2026-05-13T20:33:17.891727Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=3.709471458s\n2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted\n2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:38:37.344312Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=44 elapsed=5.107326084s\n2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames\n2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted\n2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:43:42.753501Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=22 elapsed=1.527175333s\n2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted\n2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:48:47.503128Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=11 elapsed=2.495709958s\n2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames\n2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted\n2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted\n2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-13T20:49:46.278662Z WARN sqlx::query: summary=\"INSERT INTO frames ( …\" db.statement=\"\\n\\nINSERT INTO\\n frames (\\n video_chunk_id,\\n offset_index,\\n timestamp,\\n name,\\n browser_url,\\n app_name,\\n window_name,\\n focused,\\n device_name,\\n snapshot_path,\\n capture_trigger,\\n accessibility_text,\\n text_source,\\n accessibility_tree_json,\\n content_hash,\\n simhash,\\n full_text,\\n elements_ref_frame_id,\\n document_path\\n )\\nVALUES\\n (\\n NULL,\\n 0,\\n ?1,\\n ?2,\\n ?3,\\n ?4,\\n ?5,\\n ?6,\\n ?7,\\n ?8,\\n ?9,\\n ?10,\\n ?11,\\n ?12,\\n ?13,\\n ?14,\\n ?15,\\n ?16,\\n ?17\\n )\\n\" rows_affected=1 rows_returned=0 elapsed=1.244703625s\n2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)\n2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) → inserting 109.9ms silence (10554 samples)\n2026-05-13T20:49:50.138185Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 123.4ms elapsed (expected 5.3ms) → inserting 118.1ms silence (11335 samples)\n2026-05-13T20:49:50.422739Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.2ms elapsed (expected 5.3ms) → inserting 76.9ms silence (7383 samples)\n2026-05-13T20:49:50.671835Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 249.1ms elapsed (expected 5.3ms) → inserting 243.8ms silence (23401 samples)\n2026-05-13T20:49:57.489211Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=14.406079875s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-13T20:50:25.337392Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.06712725s\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:50:34.187500Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:50:40.135101Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.170097666s\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-13T20:51:47.151342Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=432 elapsed=1.377976291s\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-14T09:24:58.542992Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-14T09:24:58.543188Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-14T09:24:58.545885Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-14T09:24:58.546638Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-14T09:24:58.546795Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-14T09:24:58.547356Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-14T09:24:58.547453Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-14T09:24:58.547767Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-14T09:24:58.547888Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\n2026-05-14T09:24:58.550735Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-14T09:24:58.552083Z INFO screenpipe: starting UI event capture\n2026-05-14T09:24:58.555587Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-14T09:24:58.557961Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-14T09:24:58.568371Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-14T09:24:58.584826Z INFO screenpipe: text-PII worker skipped at startup — async_pii_redaction=false. OPF model (~2.8 GB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584861Z INFO screenpipe: image-PII worker skipped at startup — async_image_pii_redaction=false. rfdetr_v9 model (~108 MB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584915Z INFO screenpipe_engine::ui_recorder: UI recording session started: 25f92ee5-c210-4bb0-aa44-4054d2351b03\n2026-05-14T09:24:58.584978Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-14T09:24:58.585134Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-13 06:24:58.585133 UTC to 2026-05-14 06:24:58.585133 UTC)\n2026-05-14T09:24:58.585862Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-14T09:24:58.594987Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-14T09:24:58.599110Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-14T09:24:58.699260Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-14T09:24:58.699315Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.699350Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.746653Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-14T09:24:58.746781Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-14T09:24:58.746794Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-14T09:24:58.746801Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-14T09:24:58.746815Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-14T09:24:59.307089Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-14T09:24:59.416921Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.0674867,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.33776596,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.33976063,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.40508643,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.40708113,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.47240692,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4744016,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.5397274,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.54172206,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (-zsh)","depth":2,"bounds":{"left":0.60704786,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.6090425,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-20-31-146:~ (-zsh)","depth":2,"bounds":{"left":0.6743683,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.67636305,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7280585,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.49601063,"top":1.0,"width":0.027925532,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
|
-5989896626091703807
|
-5463917750643788320
|
manual
|
accessibility
|
NULL
|
whisper_init_state: compute buffer (conv) = 14 whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:27:53.479247Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=70 elapsed=11.674598333s
2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames
2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted
2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor starte...
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2026-05-14T06:25:04.791009+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-14/1778 /Users/lukas/.screenpipe/data/data/2026-05-14/1778739904791_m1.jpg...
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screenpipe"
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ggml_metal_init: use fusion = true
ggml_me ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:27:53.479247Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=70 elapsed=11.674598333s
2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames
2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted
2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-14T09:24:58.542992Z INFO screenpipe_engine::...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"ggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:27:53.479247Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=70 elapsed=11.674598333s\n2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames\n2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted\n2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:33:17.883716Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=99 elapsed=8.890067292s\n2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames\n2026-05-13T20:33:17.891727Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=3.709471458s\n2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted\n2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:38:37.344312Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=44 elapsed=5.107326084s\n2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames\n2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted\n2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:43:42.753501Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=22 elapsed=1.527175333s\n2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted\n2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:48:47.503128Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=11 elapsed=2.495709958s\n2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames\n2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted\n2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted\n2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-13T20:49:46.278662Z WARN sqlx::query: summary=\"INSERT INTO frames ( …\" db.statement=\"\\n\\nINSERT INTO\\n frames (\\n video_chunk_id,\\n offset_index,\\n timestamp,\\n name,\\n browser_url,\\n app_name,\\n window_name,\\n focused,\\n device_name,\\n snapshot_path,\\n capture_trigger,\\n accessibility_text,\\n text_source,\\n accessibility_tree_json,\\n content_hash,\\n simhash,\\n full_text,\\n elements_ref_frame_id,\\n document_path\\n )\\nVALUES\\n (\\n NULL,\\n 0,\\n ?1,\\n ?2,\\n ?3,\\n ?4,\\n ?5,\\n ?6,\\n ?7,\\n ?8,\\n ?9,\\n ?10,\\n ?11,\\n ?12,\\n ?13,\\n ?14,\\n ?15,\\n ?16,\\n ?17\\n )\\n\" rows_affected=1 rows_returned=0 elapsed=1.244703625s\n2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)\n2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) → inserting 109.9ms silence (10554 samples)\n2026-05-13T20:49:50.138185Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 123.4ms elapsed (expected 5.3ms) → inserting 118.1ms silence (11335 samples)\n2026-05-13T20:49:50.422739Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.2ms elapsed (expected 5.3ms) → inserting 76.9ms silence (7383 samples)\n2026-05-13T20:49:50.671835Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 249.1ms elapsed (expected 5.3ms) → inserting 243.8ms silence (23401 samples)\n2026-05-13T20:49:57.489211Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=14.406079875s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-13T20:50:25.337392Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.06712725s\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:50:34.187500Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:50:40.135101Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.170097666s\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-13T20:51:47.151342Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=432 elapsed=1.377976291s\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-14T09:24:58.542992Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-14T09:24:58.543188Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-14T09:24:58.545885Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-14T09:24:58.546638Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-14T09:24:58.546795Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-14T09:24:58.547356Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-14T09:24:58.547453Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-14T09:24:58.547767Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-14T09:24:58.547888Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\n2026-05-14T09:24:58.550735Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-14T09:24:58.552083Z INFO screenpipe: starting UI event capture\n2026-05-14T09:24:58.555587Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-14T09:24:58.557961Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-14T09:24:58.568371Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-14T09:24:58.584826Z INFO screenpipe: text-PII worker skipped at startup — async_pii_redaction=false. OPF model (~2.8 GB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584861Z INFO screenpipe: image-PII worker skipped at startup — async_image_pii_redaction=false. rfdetr_v9 model (~108 MB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584915Z INFO screenpipe_engine::ui_recorder: UI recording session started: 25f92ee5-c210-4bb0-aa44-4054d2351b03\n2026-05-14T09:24:58.584978Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-14T09:24:58.585134Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-13 06:24:58.585133 UTC to 2026-05-14 06:24:58.585133 UTC)\n2026-05-14T09:24:58.585862Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-14T09:24:58.594987Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-14T09:24:58.599110Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-14T09:24:58.699260Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-14T09:24:58.699315Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.699350Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.746653Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-14T09:24:58.746781Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-14T09:24:58.746794Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-14T09:24:58.746801Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-14T09:24:58.746815Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-14T09:24:59.307089Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-14T09:24:59.416921Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-14T09:24:59.478046Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=38633, dur=113ms\n2026-05-14T09:24:59.615567Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=38634, dur=139ms\n2026-05-14T09:25:04.109913Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=9423 elapsed=5.524093667s\n2026-05-14T09:25:04.143960Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 9423 frame entries, coverage from 2026-05-13 06:24:58.585133 UTC","depth":4,"on_screen":true,"value":"ggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:27:53.479247Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=70 elapsed=11.674598333s\n2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames\n2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted\n2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:33:17.883716Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=99 elapsed=8.890067292s\n2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames\n2026-05-13T20:33:17.891727Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=3.709471458s\n2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted\n2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:38:37.344312Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=44 elapsed=5.107326084s\n2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames\n2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted\n2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:43:42.753501Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=22 elapsed=1.527175333s\n2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted\n2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:48:47.503128Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=11 elapsed=2.495709958s\n2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames\n2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted\n2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted\n2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-13T20:49:46.278662Z WARN sqlx::query: summary=\"INSERT INTO frames ( …\" db.statement=\"\\n\\nINSERT INTO\\n frames (\\n video_chunk_id,\\n offset_index,\\n timestamp,\\n name,\\n browser_url,\\n app_name,\\n window_name,\\n focused,\\n device_name,\\n snapshot_path,\\n capture_trigger,\\n accessibility_text,\\n text_source,\\n accessibility_tree_json,\\n content_hash,\\n simhash,\\n full_text,\\n elements_ref_frame_id,\\n document_path\\n )\\nVALUES\\n (\\n NULL,\\n 0,\\n ?1,\\n ?2,\\n ?3,\\n ?4,\\n ?5,\\n ?6,\\n ?7,\\n ?8,\\n ?9,\\n ?10,\\n ?11,\\n ?12,\\n ?13,\\n ?14,\\n ?15,\\n ?16,\\n ?17\\n )\\n\" rows_affected=1 rows_returned=0 elapsed=1.244703625s\n2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)\n2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) → inserting 109.9ms silence (10554 samples)\n2026-05-13T20:49:50.138185Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 123.4ms elapsed (expected 5.3ms) → inserting 118.1ms silence (11335 samples)\n2026-05-13T20:49:50.422739Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.2ms elapsed (expected 5.3ms) → inserting 76.9ms silence (7383 samples)\n2026-05-13T20:49:50.671835Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 249.1ms elapsed (expected 5.3ms) → inserting 243.8ms silence (23401 samples)\n2026-05-13T20:49:57.489211Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=14.406079875s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-13T20:50:25.337392Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.06712725s\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:50:34.187500Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:50:40.135101Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.170097666s\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-13T20:51:47.151342Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=432 elapsed=1.377976291s\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-14T09:24:58.542992Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-14T09:24:58.543188Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-14T09:24:58.545885Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-14T09:24:58.546638Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-14T09:24:58.546795Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-14T09:24:58.547356Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-14T09:24:58.547453Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-14T09:24:58.547767Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-14T09:24:58.547888Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\n2026-05-14T09:24:58.550735Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-14T09:24:58.552083Z INFO screenpipe: starting UI event capture\n2026-05-14T09:24:58.555587Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-14T09:24:58.557961Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-14T09:24:58.568371Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-14T09:24:58.584826Z INFO screenpipe: text-PII worker skipped at startup — async_pii_redaction=false. OPF model (~2.8 GB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584861Z INFO screenpipe: image-PII worker skipped at startup — async_image_pii_redaction=false. rfdetr_v9 model (~108 MB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584915Z INFO screenpipe_engine::ui_recorder: UI recording session started: 25f92ee5-c210-4bb0-aa44-4054d2351b03\n2026-05-14T09:24:58.584978Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-14T09:24:58.585134Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-13 06:24:58.585133 UTC to 2026-05-14 06:24:58.585133 UTC)\n2026-05-14T09:24:58.585862Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-14T09:24:58.594987Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-14T09:24:58.599110Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-14T09:24:58.699260Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-14T09:24:58.699315Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.699350Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.746653Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-14T09:24:58.746781Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-14T09:24:58.746794Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-14T09:24:58.746801Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-14T09:24:58.746815Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-14T09:24:59.307089Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-14T09:24:59.416921Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-14T09:24:59.478046Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=38633, dur=113ms\n2026-05-14T09:24:59.615567Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=38634, dur=139ms\n2026-05-14T09:25:04.109913Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=9423 elapsed=5.524093667s\n2026-05-14T09:25:04.143960Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 9423 frame entries, coverage from 2026-05-13 06:24:58.585133 UTC","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.14097223,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.14097223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14513889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28159723,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.2857639,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.42222223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4263889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.5628472,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56701386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (-zsh)","depth":2,"bounds":{"left":0.7034722,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70763886,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-20-31-146:~ (-zsh)","depth":2,"bounds":{"left":0.8440972,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.84826386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.95625,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.47152779,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
|
-4557196159420754940
|
-5463917750643788320
|
visual_change
|
accessibility
|
NULL
|
ggml_metal_init: use fusion = true
ggml_me ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:25:47.446143Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:27:53.479247Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=70 elapsed=11.674598333s
2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames
2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted
2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-14T09:24:58.542992Z INFO screenpipe_engine::...
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38633
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NULL
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NULL
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38636
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1435
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2
|
2026-05-14T06:25:10.853277+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-14/1778 /Users/lukas/.screenpipe/data/data/2026-05-14/1778739910853_m1.jpg...
|
iTerm2
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screenpipe"
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1
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NULL
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monitor_1
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NULL
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NULL
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NULL
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NULL
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2026-05-13T20:27:52.347858Z INFO screenpipe_audio 2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:27:53.479247Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=70 elapsed=11.674598333s
2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames
2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted
2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-14T09:24:58.542992Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-14T09:24:58.543188Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-14T09:24:58.545885Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-14T09:24:58.546638Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-14T09:24:58.546795Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-14T09:24:58.547356Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-14T09:24:58.547453Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-14T09:24:58.547767Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-14T09:24:58.547888Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
2026-05-14T09:24:58.550735Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ false │
│ vision disabled │ false │
│ pause on DRM content │ false │
│ audio engine │ Parakeet │
│ vad engine │ Silero │
│ data directory │ /Users/lukas/.screenpipe │
│ debug mode │ false │
│ telemetry │ true │
│ use pii removal │ true │
│ use all monitors │ true │
│ ignored windows │ [] │
│ included windows │ [] │
│ cloud sync │ disabled │
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
│ encrypt secrets │ disabled │
│ retention days │ 14 │
│ retention mode │ media-only (keep transcripts) │
├────────────────────────┼────────────────────────────────────┤
│ languages │ ...
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:27:53.479247Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=70 elapsed=11.674598333s\n2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames\n2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted\n2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:33:17.883716Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=99 elapsed=8.890067292s\n2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames\n2026-05-13T20:33:17.891727Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=3.709471458s\n2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted\n2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:38:37.344312Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=44 elapsed=5.107326084s\n2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames\n2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted\n2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:43:42.753501Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=22 elapsed=1.527175333s\n2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted\n2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:48:47.503128Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=11 elapsed=2.495709958s\n2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames\n2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted\n2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted\n2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-13T20:49:46.278662Z WARN sqlx::query: summary=\"INSERT INTO frames ( …\" db.statement=\"\\n\\nINSERT INTO\\n frames (\\n video_chunk_id,\\n offset_index,\\n timestamp,\\n name,\\n browser_url,\\n app_name,\\n window_name,\\n focused,\\n device_name,\\n snapshot_path,\\n capture_trigger,\\n accessibility_text,\\n text_source,\\n accessibility_tree_json,\\n content_hash,\\n simhash,\\n full_text,\\n elements_ref_frame_id,\\n document_path\\n )\\nVALUES\\n (\\n NULL,\\n 0,\\n ?1,\\n ?2,\\n ?3,\\n ?4,\\n ?5,\\n ?6,\\n ?7,\\n ?8,\\n ?9,\\n ?10,\\n ?11,\\n ?12,\\n ?13,\\n ?14,\\n ?15,\\n ?16,\\n ?17\\n )\\n\" rows_affected=1 rows_returned=0 elapsed=1.244703625s\n2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)\n2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) → inserting 109.9ms silence (10554 samples)\n2026-05-13T20:49:50.138185Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 123.4ms elapsed (expected 5.3ms) → inserting 118.1ms silence (11335 samples)\n2026-05-13T20:49:50.422739Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.2ms elapsed (expected 5.3ms) → inserting 76.9ms silence (7383 samples)\n2026-05-13T20:49:50.671835Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 249.1ms elapsed (expected 5.3ms) → inserting 243.8ms silence (23401 samples)\n2026-05-13T20:49:57.489211Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=14.406079875s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-13T20:50:25.337392Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.06712725s\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:50:34.187500Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:50:40.135101Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.170097666s\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-13T20:51:47.151342Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=432 elapsed=1.377976291s\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-14T09:24:58.542992Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-14T09:24:58.543188Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-14T09:24:58.545885Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-14T09:24:58.546638Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-14T09:24:58.546795Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-14T09:24:58.547356Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-14T09:24:58.547453Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-14T09:24:58.547767Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-14T09:24:58.547888Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\n2026-05-14T09:24:58.550735Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-14T09:24:58.552083Z INFO screenpipe: starting UI event capture\n2026-05-14T09:24:58.555587Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-14T09:24:58.557961Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-14T09:24:58.568371Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-14T09:24:58.584826Z INFO screenpipe: text-PII worker skipped at startup — async_pii_redaction=false. OPF model (~2.8 GB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584861Z INFO screenpipe: image-PII worker skipped at startup — async_image_pii_redaction=false. rfdetr_v9 model (~108 MB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584915Z INFO screenpipe_engine::ui_recorder: UI recording session started: 25f92ee5-c210-4bb0-aa44-4054d2351b03\n2026-05-14T09:24:58.584978Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-14T09:24:58.585134Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-13 06:24:58.585133 UTC to 2026-05-14 06:24:58.585133 UTC)\n2026-05-14T09:24:58.585862Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-14T09:24:58.594987Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-14T09:24:58.599110Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-14T09:24:58.699260Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-14T09:24:58.699315Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.699350Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.746653Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-14T09:24:58.746781Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-14T09:24:58.746794Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-14T09:24:58.746801Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-14T09:24:58.746815Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-14T09:24:59.307089Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-14T09:24:59.416921Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-14T09:24:59.478046Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=38633, dur=113ms\n2026-05-14T09:24:59.615567Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=38634, dur=139ms\n2026-05-14T09:25:04.109913Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=9423 elapsed=5.524093667s\n2026-05-14T09:25:04.143960Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 9423 frame entries, coverage from 2026-05-13 06:24:58.585133 UTC\n2026-05-14T09:25:08.557254Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-14T09:25:08.557399Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-14T09:25:08.557427Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\nggml_metal_library_init: loaded in 0.045 sec\nggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)\nggml_metal_device_init: GPU name: Apple M1\nggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)\nggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)\nggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)\nggml_metal_device_init: simdgroup reduction = true\nggml_metal_device_init: simdgroup matrix mul. = true\nggml_metal_device_init: has unified memory = true\nggml_metal_device_init: has bfloat = true\nggml_metal_device_init: has tensor = false\nggml_metal_device_init: use residency sets = true\nggml_metal_device_init: use shared buffers = true\nggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB\nwhisper_init_with_params_no_state: devices = 3\nwhisper_init_with_params_no_state: backends = 3\nwhisper_model_load: loading model\nwhisper_model_load: n_vocab = 51865\nwhisper_model_load: n_audio_ctx = 1500\nwhisper_model_load: n_audio_state = 384\nwhisper_model_load: n_audio_head = 6\nwhisper_model_load: n_audio_layer = 4\nwhisper_model_load: n_text_ctx = 448\nwhisper_model_load: n_text_state = 384\nwhisper_model_load: n_text_head = 6\nwhisper_model_load: n_text_layer = 4\nwhisper_model_load: n_mels = 80\nwhisper_model_load: ftype = 1\nwhisper_model_load: qntvr = 0\nwhisper_model_load: type = 1 (tiny)\nwhisper_model_load: adding 1608 extra tokens\nwhisper_model_load: n_langs = 99\nwhisper_model_load: Metal total size = 77.11 MB\nwhisper_model_load: model size = 77.11 MB\n2026-05-14T09:25:08.714171Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-14T09:25:08.721297Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)\n2026-05-14T09:25:08.727575Z INFO screenpipe_audio::audio_manager::manager: seeded 21 speakers (named + unnamed) from DB into embedding manager\n2026-05-14T09:25:08.727664Z INFO screenpipe_audio::audio_manager::manager: audio manager started\n2026-05-14T09:25:08.727731Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events\n2026-05-14T09:25:09.238925Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)\n2026-05-14T09:25:09.325492Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-14T09:25:09.326604Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-14T09:25:09.326657Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)","depth":4,"on_screen":true,"value":"2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:27:53.479247Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=70 elapsed=11.674598333s\n2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames\n2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted\n2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:31:59.059676Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:33:17.883716Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=99 elapsed=8.890067292s\n2026-05-13T20:33:17.883941Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 99 eligible frames\n2026-05-13T20:33:17.891727Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=3.709471458s\n2026-05-13T20:33:20.639856Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 34 frames, 9.7MB → 0.5MB (18.5x), 34 JPEGs deleted\n2026-05-13T20:33:32.188498Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 63 frames, 12.9MB → 5.8MB (2.2x), 63 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:34:02.333860Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:35:59.996074Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:36:06.828724Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:36:08.344162Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:38:09.099371Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:38:37.344312Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=44 elapsed=5.107326084s\n2026-05-13T20:38:37.346139Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 44 eligible frames\n2026-05-13T20:38:38.686723Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 18 frames, 5.1MB → 0.5MB (10.0x), 18 JPEGs deleted\n2026-05-13T20:38:41.220417Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 24 frames, 5.4MB → 3.3MB (1.6x), 24 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:40:11.364685Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:42:13.293671Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:43:42.753501Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=22 elapsed=1.527175333s\n2026-05-13T20:43:42.753626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-13T20:43:43.862384Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.8MB → 0.5MB (5.8x), 10 JPEGs deleted\n2026-05-13T20:43:44.995456Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.0MB → 0.3MB (5.9x), 10 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:44:15.490296Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:46:17.561354Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:48:19.446216Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:48:47.503128Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=11 elapsed=2.495709958s\n2026-05-13T20:48:47.503288Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 11 eligible frames\n2026-05-13T20:48:48.316165Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 5 frames, 1.4MB → 0.5MB (2.9x), 5 JPEGs deleted\n2026-05-13T20:48:48.942276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 4 frames, 0.8MB → 0.3MB (2.4x), 4 JPEGs deleted\n2026-05-13T20:49:42.528723Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-13T20:49:43.434142Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-13T20:49:43.440276Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-13T20:49:44.371959Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-13T20:49:44.767833Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-13T20:49:44.767967Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-13T20:49:44.785602Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-13T20:49:45.364548Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364628Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-13T20:49:45.364676Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-13T20:49:46.278662Z WARN sqlx::query: summary=\"INSERT INTO frames ( …\" db.statement=\"\\n\\nINSERT INTO\\n frames (\\n video_chunk_id,\\n offset_index,\\n timestamp,\\n name,\\n browser_url,\\n app_name,\\n window_name,\\n focused,\\n device_name,\\n snapshot_path,\\n capture_trigger,\\n accessibility_text,\\n text_source,\\n accessibility_tree_json,\\n content_hash,\\n simhash,\\n full_text,\\n elements_ref_frame_id,\\n document_path\\n )\\nVALUES\\n (\\n NULL,\\n 0,\\n ?1,\\n ?2,\\n ?3,\\n ?4,\\n ?5,\\n ?6,\\n ?7,\\n ?8,\\n ?9,\\n ?10,\\n ?11,\\n ?12,\\n ?13,\\n ?14,\\n ?15,\\n ?16,\\n ?17\\n )\\n\" rows_affected=1 rows_returned=0 elapsed=1.244703625s\n2026-05-13T20:49:46.796019Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-13T20:49:47.183906Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-13T20:49:48.460135Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 96.4ms elapsed (expected 5.3ms) → inserting 91.1ms silence (8742 samples)\n2026-05-13T20:49:49.414321Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 115.3ms elapsed (expected 5.3ms) → inserting 109.9ms silence (10554 samples)\n2026-05-13T20:49:50.138185Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 123.4ms elapsed (expected 5.3ms) → inserting 118.1ms silence (11335 samples)\n2026-05-13T20:49:50.422739Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.2ms elapsed (expected 5.3ms) → inserting 76.9ms silence (7383 samples)\n2026-05-13T20:49:50.671835Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 249.1ms elapsed (expected 5.3ms) → inserting 243.8ms silence (23401 samples)\n2026-05-13T20:49:57.489211Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=14.406079875s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-13T20:50:25.337392Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.06712725s\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T20:50:34.187500Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T20:50:40.135101Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=430 elapsed=1.170097666s\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-13T20:51:47.151342Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=432 elapsed=1.377976291s\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start\nzsh: command not found: alias\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias\naddssh='ssh-add ~/.ssh/*'\napp='cd ~/jiminny/app'\ncnt='docker exec -ti $(docker ps | grep worker | awk '\\''{print $1}'\\'') /bin/bash -c \"cd /home/jiminny && bash\"'\nco='git checkout'\ncov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'\ncsfix='make cs-fix'\ndev='docker exec -ti $(docker ps -q --filter \"name=docker_lamp_1\") /bin/bash'\neu='ssh lukas@jiminny-eu-bastion -D 127.0.0.1:7073 -L 7532:db:3306'\neues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'\next='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'\nfe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'\nfe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'\ngbr='git branch --sort=-committerdate'\ngcb='git branch --show-current | pbcopy'\ngs='git status'\nhhh=history\nhhs='history 0 | grep '\ninstall_nano='apt-get update & apt-get install nano'\nkar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'\nll='ls -la --color=tty'\nlock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'\nnas='ssh Adm1n@192.168.0.242 -p22'\npoetryshell='eval \"\"'\nprod='ssh lukas@jiminny-prod-bastion -D 127.0.0.1:7072 -L 7632:db:3306'\nprodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'\nprophet='cd ~/jiminny/app'\nprophetdown='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down\"'\nprophetup='aws-vault exec staging -- bash -c \"env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build\"'\nqa='ssh lukas@jiminny-qa-bastion -D 127.0.0.1:7074 -L 7432:db:3306'\nqaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'\nqai='ssh lukas@jiminny-qai-bastion -D 127.0.0.1:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'\nrmbc='rm -rf bootstrap/cache/*.php'\nrun-help=man\nsp-db='sqlite3 ~/.screenpipe/db.sqlite '\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nsp-status='curl -s http://localhost:3030/health | jq \"{status, frame_status, audio_status, last_frame: .last_frame_timestamp, uptime: .pipeline.uptime_secs, fps: .pipeline.capture_fps_actual, frames: .pipeline.frames_captured}\"'\nsp-stop='pkill -f screenpipe && echo '\\''screenpipe stopped'\\'\nstg='ssh lukas@jiminny-stage-bastion -D 127.0.0.1:7071 -L 7732:db:3306'\nstges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'\nveu='ssh jiminny-eu-ecs1'\nveu10='ssh jiminny-eu-ecs10'\nveu11='ssh jiminny-eu-ecs11'\nveu12='ssh jiminny-eu-ecs12'\nveu2='ssh jiminny-eu-ecs2'\nveu3='ssh jiminny-eu-ecs3'\nveu4='ssh jiminny-eu-ecs4'\nveu5='ssh jiminny-eu-ecs5'\nveu6='ssh jiminny-eu-ecs6'\nveu7='ssh jiminny-eu-ecs7'\nveu8='ssh jiminny-eu-ecs8'\nveu9='ssh jiminny-eu-ecs9'\nvprod='ssh jiminny-prod-ecs1'\nvprod10='ssh jiminny-prod-ecs10'\nvprod11='ssh jiminny-prod-ecs11'\nvprod12='ssh jiminny-prod-ecs12'\nvprod2='ssh jiminny-prod-ecs2'\nvprod3='ssh jiminny-prod-ecs3'\nvprod4='ssh jiminny-prod-ecs4'\nvprod5='ssh jiminny-prod-ecs5'\nvprod6='ssh jiminny-prod-ecs6'\nvprod7='ssh jiminny-prod-ecs7'\nvprod8='ssh jiminny-prod-ecs8'\nvprod9='ssh jiminny-prod-ecs9'\nvqa='ssh jiminny-qa-ecs1'\nvqa2='ssh jiminny-qa-ecs2'\nvqai='ssh jiminny-qai-ecs1'\nvqai2='ssh jiminny-qai-ecs2'\nvstage='ssh ec2-user@jiminny-subenv-worker-app0'\nvstg='ssh jiminny-stage-ecs1'\nvstg2='ssh ubuntu@jiminny-stage-ecs2'\nwhich-command=whence\nwork='cd ~/jiminny/infrastructure/dev/docker && docker compose up'\nworkoff='kill %1'\nworkon='caffeinate -d & echo \"Display sleep disabled (PID $!)\"'\nxd='make docker-xdebug-disable'\nxe='make docker-xdebug-enable'\nzp='nano ~/.zprofile'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-14T09:24:58.542992Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-14T09:24:58.543188Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-14T09:24:58.545885Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-14T09:24:58.546638Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-14T09:24:58.546795Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-14T09:24:58.547356Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-14T09:24:58.547453Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-14T09:24:58.547767Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-14T09:24:58.547888Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\n2026-05-14T09:24:58.550735Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-14T09:24:58.552083Z INFO screenpipe: starting UI event capture\n2026-05-14T09:24:58.555587Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-14T09:24:58.557961Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-14T09:24:58.568371Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-14T09:24:58.584826Z INFO screenpipe: text-PII worker skipped at startup — async_pii_redaction=false. OPF model (~2.8 GB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584861Z INFO screenpipe: image-PII worker skipped at startup — async_image_pii_redaction=false. rfdetr_v9 model (~108 MB) will NOT be downloaded or loaded. Toggle via Settings → Privacy → AI PII removal.\n2026-05-14T09:24:58.584915Z INFO screenpipe_engine::ui_recorder: UI recording session started: 25f92ee5-c210-4bb0-aa44-4054d2351b03\n2026-05-14T09:24:58.584978Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-14T09:24:58.585134Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-13 06:24:58.585133 UTC to 2026-05-14 06:24:58.585133 UTC)\n2026-05-14T09:24:58.585862Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-14T09:24:58.594987Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-14T09:24:58.599110Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-14T09:24:58.699260Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-14T09:24:58.699315Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.699350Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-14T09:24:58.746653Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-14T09:24:58.746781Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-14T09:24:58.746794Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-14T09:24:58.746801Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-14T09:24:58.746815Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-14T09:24:59.307089Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-14T09:24:59.416921Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-14T09:24:59.478046Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=38633, dur=113ms\n2026-05-14T09:24:59.615567Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=38634, dur=139ms\n2026-05-14T09:25:04.109913Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=9423 elapsed=5.524093667s\n2026-05-14T09:25:04.143960Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 9423 frame entries, coverage from 2026-05-13 06:24:58.585133 UTC\n2026-05-14T09:25:08.557254Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-14T09:25:08.557399Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-14T09:25:08.557427Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\nggml_metal_library_init: loaded in 0.045 sec\nggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)\nggml_metal_device_init: GPU name: Apple M1\nggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)\nggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)\nggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)\nggml_metal_device_init: simdgroup reduction = true\nggml_metal_device_init: simdgroup matrix mul. = true\nggml_metal_device_init: has unified memory = true\nggml_metal_device_init: has bfloat = true\nggml_metal_device_init: has tensor = false\nggml_metal_device_init: use residency sets = true\nggml_metal_device_init: use shared buffers = true\nggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB\nwhisper_init_with_params_no_state: devices = 3\nwhisper_init_with_params_no_state: backends = 3\nwhisper_model_load: loading model\nwhisper_model_load: n_vocab = 51865\nwhisper_model_load: n_audio_ctx = 1500\nwhisper_model_load: n_audio_state = 384\nwhisper_model_load: n_audio_head = 6\nwhisper_model_load: n_audio_layer = 4\nwhisper_model_load: n_text_ctx = 448\nwhisper_model_load: n_text_state = 384\nwhisper_model_load: n_text_head = 6\nwhisper_model_load: n_text_layer = 4\nwhisper_model_load: n_mels = 80\nwhisper_model_load: ftype = 1\nwhisper_model_load: qntvr = 0\nwhisper_model_load: type = 1 (tiny)\nwhisper_model_load: adding 1608 extra tokens\nwhisper_model_load: n_langs = 99\nwhisper_model_load: Metal total size = 77.11 MB\nwhisper_model_load: model size = 77.11 MB\n2026-05-14T09:25:08.714171Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-14T09:25:08.721297Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)\n2026-05-14T09:25:08.727575Z INFO screenpipe_audio::audio_manager::manager: seeded 21 speakers (named + unnamed) from DB into embedding manager\n2026-05-14T09:25:08.727664Z INFO screenpipe_audio::audio_manager::manager: audio manager started\n2026-05-14T09:25:08.727731Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events\n2026-05-14T09:25:09.238925Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)\n2026-05-14T09:25:09.325492Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-14T09:25:09.326604Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-14T09:25:09.326657Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.14097223,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.14097223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14513889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28159723,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.2857639,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.42222223,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4263889,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.5628472,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56701386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (-zsh)","depth":2,"bounds":{"left":0.7034722,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70763886,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-20-31-146:~ (-zsh)","depth":2,"bounds":{"left":0.8440972,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.84826386,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.95625,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.47152779,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
|
-3044940751880024210
|
-5463354800690367008
|
visual_change
|
accessibility
|
NULL
|
2026-05-13T20:27:52.347858Z INFO screenpipe_audio 2026-05-13T20:27:52.347858Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T20:27:53.479247Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=70 elapsed=11.674598333s
2026-05-13T20:27:53.484186Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 70 eligible frames
2026-05-13T20:27:56.974006Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 28 frames, 7.9MB → 0.9MB (8.8x), 28 JPEGs deleted
2026-05-13T20:28:08.932176Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 40 frames, 9.0MB → 6.8MB (1.3x), 40 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T20:29:55.273894Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias sp-start
zsh: command not found: alias
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ alias
addssh='ssh-add ~/.ssh/*'
app='cd ~/jiminny/app'
cnt='docker exec -ti $(docker ps | grep worker | awk '\''{print $1}'\'') /bin/bash -c "cd /home/jiminny && bash"'
co='git checkout'
cov='./vendor/bin/phpunit tests/Unit --coverage-html=build/coverage'
csfix='make cs-fix'
dev='docker exec -ti $(docker ps -q --filter "name=docker_lamp_1") /bin/bash'
eu='ssh lukas@jiminny-eu-bastion -D [IP_ADDRESS]:7073 -L 7532:db:3306'
eues='ssh ubuntu@jiminny-eu-ecs1 -L 7960:vpc-activities7-e7pfbl7wojjjnvp7olfpudrgke.eu-west-1.es.amazonaws.com:80'
ext='nvm use 20 && cd ~/jiminny/extension-app && yarn build:dev && yarn preview'
fe='yarn && nvm use 24 && cd ~/jiminny/app/front-end && yarn build:watch'
fe3='cd ~/jiminny/app/front-end-vue3 && yarn build:watch:production'
gbr='git branch --sort=-committerdate'
gcb='git branch --show-current | pbcopy'
gs='git status'
hhh=history
hhs='history 0 | grep '
install_nano='apt-get update & apt-get install nano'
kar='cp -f ~/DEV/settings/goku-karabiner-settings/karabiner.edn ~/.config/karabiner.edn && goku'
ll='ls -la --color=tty'
lock='kill %1 2>/dev/null; sleep 1 && pmset displaysleepnow'
nas='ssh Adm1n@[IP_ADDRESS] -p22'
poetryshell='eval ""'
prod='ssh lukas@jiminny-prod-bastion -D [IP_ADDRESS]:7072 -L 7632:db:3306'
prodes='ssh ubuntu@jiminny-prod-ecs1 -L 7970:vpc-activities7-3o2zlrelmga5qicf2yxxwtx6bi.us-east-2.es.amazonaws.com:80'
prophet='cd ~/jiminny/app'
prophetdown='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml down"'
prophetup='aws-vault exec staging -- bash -c "env | grep AWS_ > aws-creds.env && docker compose -f docker-compose.yml -f docker-compose.dev.yml up --build"'
qa='ssh lukas@jiminny-qa-bastion -D [IP_ADDRESS]:7074 -L 7432:db:3306'
qaes='ssh ubuntu@jiminny-qa-ecs1 -L 7950:vpc-activities7-s5zchrs4xqcnav3rjzmxgxvfvq.us-east-2.es.amazonaws.com:80'
qai='ssh lukas@jiminny-qai-bastion -D [IP_ADDRESS]:7075 -L 7777:jiminny-db-qai.c3uemcm84st0.us-east-2.rds.amazonaws.com:3306'
rmbc='rm -rf bootstrap/cache/*.php'
run-help=man
sp-db='sqlite3 ~/.screenpipe/db.sqlite '
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
sp-status='curl -s [URL_WITH_CREDENTIALS] -D [IP_ADDRESS]:7071 -L 7732:db:3306'
stges='ssh ubuntu@jiminny-stage-ecs1 -L 7980:vpc-activities7-tgeodjeaugnaiigqgdcjjkrrj4.us-east-2.es.amazonaws.com:80'
veu='ssh jiminny-eu-ecs1'
veu10='ssh jiminny-eu-ecs10'
veu11='ssh jiminny-eu-ecs11'
veu12='ssh jiminny-eu-ecs12'
veu2='ssh jiminny-eu-ecs2'
veu3='ssh jiminny-eu-ecs3'
veu4='ssh jiminny-eu-ecs4'
veu5='ssh jiminny-eu-ecs5'
veu6='ssh jiminny-eu-ecs6'
veu7='ssh jiminny-eu-ecs7'
veu8='ssh jiminny-eu-ecs8'
veu9='ssh jiminny-eu-ecs9'
vprod='ssh jiminny-prod-ecs1'
vprod10='ssh jiminny-prod-ecs10'
vprod11='ssh jiminny-prod-ecs11'
vprod12='ssh jiminny-prod-ecs12'
vprod2='ssh jiminny-prod-ecs2'
vprod3='ssh jiminny-prod-ecs3'
vprod4='ssh jiminny-prod-ecs4'
vprod5='ssh jiminny-prod-ecs5'
vprod6='ssh jiminny-prod-ecs6'
vprod7='ssh jiminny-prod-ecs7'
vprod8='ssh jiminny-prod-ecs8'
vprod9='ssh jiminny-prod-ecs9'
vqa='ssh jiminny-qa-ecs1'
vqa2='ssh jiminny-qa-ecs2'
vqai='ssh jiminny-qai-ecs1'
vqai2='ssh jiminny-qai-ecs2'
vstage='ssh ec2-user@jiminny-subenv-worker-app0'
vstg='ssh jiminny-stage-ecs1'
vstg2='ssh ubuntu@jiminny-stage-ecs2'
which-command=whence
work='cd ~/jiminny/infrastructure/dev/docker && docker compose up'
workoff='kill %1'
workon='caffeinate -d & echo "Display sleep disabled (PID $!)"'
xd='make docker-xdebug-disable'
xe='make docker-xdebug-enable'
zp='nano ~/.zprofile'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~ $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-14T09:24:57.412901Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-14T09:24:57.504235Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-14T09:24:58.108327Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-14T09:24:58.110039Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-14T09:24:58.110396Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-14T09:24:58.131971Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-14T09:24:58.132049Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-14T09:24:58.543048Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-14T09:24:58.543106Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-14T09:24:58.542983Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-14T09:24:58.542992Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-14T09:24:58.543188Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-14T09:24:58.545885Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-14T09:24:58.546638Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-14T09:24:58.546795Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-14T09:24:58.547356Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-14T09:24:58.547453Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-14T09:24:58.547767Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-14T09:24:58.547888Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
2026-05-14T09:24:58.550735Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ false │
│ vision disabled │ false │
│ pause on DRM content │ false │
│ audio engine │ Parakeet │
│ vad engine │ Silero │
│ data directory │ /Users/lukas/.screenpipe │
│ debug mode │ false │
│ telemetry │ true │
│ use pii removal │ true │
│ use all monitors │ true │
│ ignored windows │ [] │
│ included windows │ [] │
│ cloud sync │ disabled │
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
│ encrypt secrets │ disabled │
│ retention days │ 14 │
│ retention mode │ media-only (keep transcripts) │
├────────────────────────┼────────────────────────────────────┤
│ languages │ ...
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp0 Ihl • | Daily - Platform • in 20 m100% (4 8• Thu 14 May 9:25:13181DOCKERO ₴1DEV (-zsh)whisper_model_load:loadingmodelwhisper_model_load:n_vocab51865whisper_model_load:n_audio_ctx1500whisper_model_load:n_audio_state = 384whisper_model_load:n_audio_head6whisper_model_load:n_audio_layer4whisper_model_load:n_text_ctx= 448whisper_model_load:n_text_state= 384whisper_model_load:n_text_head=6whisper_model_load:n_text_layer4whisper_model_load:n_mels80whisper_model_load:ftype= 1whisper_model_load:qntvr0whisper_model_load:type= 1(tiny)whisper_model_load:adding1608extratokenswhisner model1o0d: n lanas99w'• ₴2APP (-zsh)83screenpipe"-zshscreenpipe*885ec2-user@ip-10-30-129-...₴6ec2-user@ip-10-20-31-14... 27N9.Firefoxggmь-mемьeьe.MwrewinCrurggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize2.36 MBwhisper_init_state:computebuffer (conv)14.17 MBwhisper_init_state:computebuffer (encode)=65.96 MBwhisper_init_state: compute buffer (cross)8.50 MBwhisper_init_state: computebuffer(decode) =96.83 MB2026-05-14T09:25:08.721297ZINFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)2026-05-14T09:25:08.727575ZINFO screenpipe_audio::audio_manager::manager: seeded 21 speakers (named + unnamed) from DB into embedding manager2026-05-14T09:25:08.727664ZINFOscreenpipe_audio::audio_manager::manager: audio manager started2026-05-14T09:25:08.727731ZINFO screenpipe_audio::audio_manager::manager: calendar-assisted speakerdiarization: listening for meetingevents2026-05-14709:25:09.238925ZINFOscreenpipe_audio::device::device_manager: starting recording for device: System Audio (output)2026-05-14T09:25:09.325492ZINFOscreenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)2026-05-14T09:25:09.326604ZINFOscreenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)5-05-14T09:25:09.326657ZINFOscreenp:core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)...
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp0 Ihl • | Daily - Platform • in 20 m100% (4 8• Thu 14 May 9:25:13181DOCKERO ₴1DEV (-zsh)whisper_model_load:loadingmodelwhisper_model_load:n_vocab51865whisper_model_load:n_audio_ctx1500whisper_model_load:n_audio_state = 384whisper_model_load:n_audio_head6whisper_model_load:n_audio_layer4whisper_model_load:n_text_ctx= 448whisper_model_load:n_text_state= 384whisper_model_load:n_text_head=6whisper_model_load:n_text_layer4whisper_model_load:n_mels80whisper_model_load:ftype= 1whisper_model_load:qntvr0whisper_model_load:type= 1(tiny)whisper_model_load:adding1608extratokenswhisner model1o0d: n lanas99w'• ₴2APP (-zsh)83screenpipe"-zshscreenpipe*885ec2-user@ip-10-30-129-...₴6ec2-user@ip-10-20-31-14... 27N9.Firefoxggmь-mемьeьe.MwrewinCrurggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize2.36 MBwhisper_init_state:computebuffer (conv)14.17 MBwhisper_init_state:computebuffer (encode)=65.96 MBwhisper_init_state: compute buffer (cross)8.50 MBwhisper_init_state: computebuffer(decode) =96.83 MB2026-05-14T09:25:08.721297ZINFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)2026-05-14T09:25:08.727575ZINFO screenpipe_audio::audio_manager::manager: seeded 21 speakers (named + unnamed) from DB into embedding manager2026-05-14T09:25:08.727664ZINFOscreenpipe_audio::audio_manager::manager: audio manager started2026-05-14T09:25:08.727731ZINFO screenpipe_audio::audio_manager::manager: calendar-assisted speakerdiarization: listening for meetingevents2026-05-14709:25:09.238925ZINFOscreenpipe_audio::device::device_manager: starting recording for device: System Audio (output)2026-05-14T09:25:09.325492ZINFOscreenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)2026-05-14T09:25:09.326604ZINFOscreenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)5-05-14T09:25:09.326657ZINFOscreenp:core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)...
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selection• screenpipe [SSH: nas)• _ #recycieV tr a selection• screenpipe [SSH: nas)• _ #recycieV tr appinteractions.py8 do saliteA screennine. dbscreenpipe_sync.shscreenpioe_sync_helpers.shinsumers › activity.py › ...det audio seqments(tor date: date None = None) → List dict str, Any :start. end = date range(d)main.ov Mactivity.pyMXDv"0app› • DockernleWORKDIR /ap;Q copyrequirements.txt |RIN nin install --no-cache-dir -r requirements.txCOPY.14 SypocE 9a0016 cмD ("uvicorn", "main:app"screenpipe_sync_files.shWORKDIR /appcopy requirements.extCOPY .eypose gaddCMD ["uvicorn",w Dally - Platorm • In 20m100% 12PInu 14 May 9-2o:13Refactor Sync Script.tt-toolbar < display:flex; gap:10px; align-itens:center: flex-wrap:wrap; }+0 .*•solid var(--border); border-radius:8px; padding:12px 14px; displayThoughtsSELECTUNNEHHENEudio chunk id = c.idORDER BY t.timestampendfetchallreturn dictr for r in rowsiOutouDebua Consoleabash-apo +v @ M m ... |e x7) .map(s BThoughts}) -map(a => {All requested chanaes comnlete• Addedi.ttcaudio-sen.active CSS class with white inset bordeModified <› ttRenderAudioSeaments/) to hiahliaht audio seaments within 5 seconds of current nosition• Audio timeline now shows visual hiahliaht iust like video timelineAudio auto-olav OfF ov derault•Changed _ttAutoPlayAudio from true to false•Updated button text to "*. Auto-Play Audio: OFF*• Modified ‹/› ttShowAudioTranscription() to only play audio when auto-play is enabledAudin romaine dicabled on page refresh and navigationCollansible time rance filter.•Added collapsible " 7 Time Range Filter" section with From/To time inputs•Added ‹› ttToggleTimeFiltero.‹› ttApplyTimeFiltero,‹› ttCleartimeFilter functions• Updated ‹› ttRenderSeqments and‹› ttRenderAudioSeqments to filter segments by time range•Filter shows only segments within the specified time period (e.g.. 9:45 to 10:30)Ask anvthindScreen Reader Optimized Ln 1, Col 1 Spaces: 4 UTF-8 LF Python 3.11.2 64-bit Teams Windsurf - Settings...
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selection• screenpipe [SSH: nas)• _ #recycieV tr a selection• screenpipe [SSH: nas)• _ #recycieV tr appinteractions.py8 do saliteA screennine. dbscreenpipe_sync.shscreenpioe_sync_helpers.shinsumers › activity.py › ...det audio seqments(tor date: date None = None) → List dict str, Any :start. end = date range(d)main.ov Mactivity.pyMXDv"0app› • DockernleWORKDIR /ap;Q copyrequirements.txt |RIN nin install --no-cache-dir -r requirements.txCOPY.14 SypocE 9a0016 cмD ("uvicorn", "main:app"screenpipe_sync_files.shWORKDIR /appcopy requirements.extCOPY .eypose gaddCMD ["uvicorn",w Dally - Platorm • In 20m100% 12PInu 14 May 9-2o:13Refactor Sync Script.tt-toolbar < display:flex; gap:10px; align-itens:center: flex-wrap:wrap; }+0 .*•solid var(--border); border-radius:8px; padding:12px 14px; displayThoughtsSELECTUNNEHHENEudio chunk id = c.idORDER BY t.timestampendfetchallreturn dictr for r in rowsiOutouDebua Consoleabash-apo +v @ M m ... |e x7) .map(s BThoughts}) -map(a => {All requested chanaes comnlete• Addedi.ttcaudio-sen.active CSS class with white inset bordeModified <› ttRenderAudioSeaments/) to hiahliaht audio seaments within 5 seconds of current nosition• Audio timeline now shows visual hiahliaht iust like video timelineAudio auto-olav OfF ov derault•Changed _ttAutoPlayAudio from true to false•Updated button text to "*. Auto-Play Audio: OFF*• Modified ‹/› ttShowAudioTranscription() to only play audio when auto-play is enabledAudin romaine dicabled on page refresh and navigationCollansible time rance filter.•Added collapsible " 7 Time Range Filter" section with From/To time inputs•Added ‹› ttToggleTimeFiltero.‹› ttApplyTimeFiltero,‹› ttCleartimeFilter functions• Updated ‹› ttRenderSeqments and‹› ttRenderAudioSeqments to filter segments by time range•Filter shows only segments within the specified time period (e.g.. 9:45 to 10:30)Ask anvthindScreen Reader Optimized Ln 1, Col 1 Spaces: 4 UTF-8 LF Python 3.11.2 64-bit Teams Windsurf - Settings...
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Screenpipe — Archive
Screenpipe — Archive
All docs Screenpipe — Archive
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SQLite Web: archive.db
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You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
You said
Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
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Gemini said
Gemini said
Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.
ScreenPipe is fundamentally designed to be a
100% local, privacy-first
application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.
View source details. Opens side panel.
1. Where It Starts: The Capture Layer
1. Where It Starts: The Capture Layer
The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:
System Audio:
Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).
Microphone Input:
Everything you say into your mic.
View source details. Opens side panel.
Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.
2. How It Gets Transferred and Transcribed
2. How It Gets Transferred and Transcribed
Because ScreenPipe prioritizes local processing, the "transfer" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.
Here is the transcription pipeline:
The Engine:
The raw audio chunks are fed into a local speech-to-text model.
By default, ScreenPipe uses
OpenAI Whisper
running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).
View source details. Opens side panel.
Diarization:
As it transcribes the text, the engine also performs "diarization"—a technical term for speaker identification.
It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.
View source details. Opens side panel.
Storage:
The final transcribed text is then indexed into a local
SQLite database
. This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.
3. The "Work in Progress" (WIP) Stage
3. The "Work in Progress" (WIP) Stage
There is a slight bottleneck between
hearing
the audio and
saving
the text, which acts as the WIP stage:
Buffering:
Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.
Processing Queue:
Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.
Finalization:
Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.
4. Understanding the Folder Structure
4. Understanding the Folder Structure
All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like
~/.screenpipe
on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:
The SQLite Database (
):
This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is "done."
The
or
folders:
This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.
Temp Files:
If you see rapidly changing files, temporary
chunks, or locked database journals (like
), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.
Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?
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You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
You said
I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
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Gemini said
Gemini said
Yes, those
.mp4
files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.
Here is exactly what those files are doing sitting in your
~/.screenpipe/data/
directory and how they interact with the rest of the system.
1. The "Time Machine" Playback
1. The "Time Machine" Playback
The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the
db.sqlite
database along with
precise timestamps and file path references
.
When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific
.mp4
file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.
2. Re-processing and Model Upgrades
2. Re-processing and Model Upgrades
Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw
.mp4
files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.
3. The Source of Truth for Hallucinations
3. The Source of Truth for Hallucinations
Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that
.mp4
file is your fallback source of truth to verify what was actually said.
How the Database Views Them
How the Database Views Them
If you were to open up your
db.sqlite
and query the tables (e.g.,
audio_transcriptions
), you would see that the database treats the
~/.screenpipe/data/
folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like
soundcore AeroClip (input)_2026-05-12_07-40-48.mp4
.
What happens if you delete them?
If you manually
rm
those files to free up space on your Mac's SSD, ScreenPipe won't crash. The SQLite database will still hold all your searchable text. However, any attempt to play back the audio for those older transcripts will silently fail or throw a "file not found" error in the background logs.
Managing the Storage Footprint
Managing the Storage Footprint
Because ScreenPipe records continuously, this folder will inevitably grow over time.
Built-in Garbage Collection:
ScreenPipe usually handles this automatically based on retention settings (e.g., deleting media older than 30 days or when the folder hits a specific GB limit).
Archiving:
If you prefer to keep a permanent, searchable "life log" without eating up your local SSD space, you don't necessarily have to let ScreenPipe delete them. You could script a simple cron job to regularly
older
files to your massive 4-drive RAID 5 array, replacing the local files with symlinks. This would keep the database references intact while offloading the heavy media storage to your NAS.
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You said yes I will do that. Is there a way to setup languages to transcription?
You said
yes I will do that. Is there a way to setup languages to transcription?
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Gemini said
Gemini said
That is a solid plan. Offloading those older media files to your 4-drive RAID 5 setup (or even the secondary SSD-only Beelink NAS if you end up building it) will keep your local SSD lean while keeping your database searchable.
As for setting up languages for transcription,
yes, you can configure it
, but it helps to understand how ScreenPipe handles language natively first.
How the Transcription Engine Handles Language
How the Transcription Engine Handles Language
By default, ScreenPipe uses a
multilingual Whisper model
and sets the language configuration to
Auto-Detect
.
When a new audio chunk comes in, the model listens to the first few seconds of audio, guesses the language, and transcribes the rest of that chunk using that assumption.
The Advantage:
If you are watching a tutorial in English, and then an hour later you are in a Zoom call speaking Bulgarian, ScreenPipe will automatically switch gears without you having to touch the settings.
The Drawback:
Auto-detect can sometimes guess wrong, especially if there is heavy background noise, if someone starts a sentence with a foreign loanword, or if you are rapidly code-switching between Slovak and English in the same conversation. When it guesses wrong, it might try to force Slovak words into English spelling, resulting in gibberish.
How to Force a Specific Language
How to Force a Specific Language
If you want to ensure maximum accuracy and you know you will primarily be recording in one language for a specific period, you can explicitly set the language. This also slightly speeds up the processing because the model skips the detection phase.
If you are using the Desktop App UI:
Open the ScreenPipe settings.
Navigate to the
Audio
or
AI/Transcription
section.
Look for the
Whisper Language
or
Transcription Language
dropdown.
Change it from "Auto" to your specific language (e.g., English, Bulgarian, or Slovak).
If you are running ScreenPipe via CLI/Config:
You can modify your underlying configuration (usually found in
~/.screenpipe/pipe.json
or by passing a flag when starting the daemon) to force a specific language code. You would use the standard ISO language codes:
(Slovak)
(Bulgarian)
(English)
If you find yourself frequently jumping between those three languages, your best bet is to leave it on Auto-Detect and perhaps run a slightly larger, more accurate Whisper model (like Whisper 'Small' or 'Base' instead of 'Tiny') if your hardware has the headroom for it.
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How can I see from the folder structure what has been done and what hasn't been done?","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":24,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ScreenPipe is fundamentally designed to be a","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"100% local, privacy-first","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":27,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"1. Where It Starts: The Capture Layer","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Where It Starts: The Capture Layer","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"System Audio:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Microphone Input:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Everything you say into your mic.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How It Gets Transferred and Transcribed","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How It Gets Transferred and Transcribed","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Because ScreenPipe prioritizes local processing, the \"transfer\" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is the transcription pipeline:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Engine:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The raw audio chunks are fed into a local speech-to-text model.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, ScreenPipe uses","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"OpenAI Whisper","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Diarization:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"As it transcribes the text, the engine also performs \"diarization\"—a technical term for speaker identification.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Storage:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The final transcribed text is then indexed into a local","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SQLite database","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. The \"Work in Progress\" (WIP) Stage","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. The \"Work in Progress\" (WIP) Stage","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"There is a slight bottleneck between","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"hearing","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the audio and","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"saving","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the text, which acts as the WIP stage:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Buffering:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Processing Queue:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Finalization:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"4. Understanding the Folder Structure","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"4. Understanding the Folder Structure","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The SQLite Database (","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"):","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is \"done.\"","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"folders:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Temp Files:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you see rapidly changing files, temporary","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"chunks, or locked database journals (like","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Sources","depth":26,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Sources","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Good response","depth":24,"on_screen":false,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Bad response","depth":24,"on_screen":false,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Share and export","depth":23,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":24,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":23,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy prompt","depth":21,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":24,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yes, those","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is exactly what those files are doing sitting in your","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe/data/","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"directory and how they interact with the rest of the system.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. The \"Time Machine\" Playback","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. The \"Time Machine\" Playback","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"db.sqlite","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"database along with","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"precise timestamps and file path references","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. Re-processing and Model Upgrades","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. Re-processing and Model Upgrades","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. The Source of Truth for Hallucinations","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. The Source of Truth for Hallucinations","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"file is your fallback source of truth to verify what was actually said.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"How the Database Views Them","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How the Database Views Them","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you were to open up your","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"db.sqlite","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and query the tables (e.g.,","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"audio_transcriptions","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"), you would see that the database treats the","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe/data/","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"soundcore AeroClip (input)_2026-05-12_07-40-48.mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What happens if you delete them?","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you manually","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"rm","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"those files to free up space on your Mac's SSD, ScreenPipe won't crash. The SQLite database will still hold all your searchable text. However, any attempt to play back the audio for those older transcripts will silently fail or throw a \"file not found\" error in the background logs.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Managing the Storage Footprint","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Managing the Storage Footprint","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Because ScreenPipe records continuously, this folder will inevitably grow over time.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Built-in Garbage Collection:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ScreenPipe usually handles this automatically based on retention settings (e.g., deleting media older than 30 days or when the folder hits a specific GB limit).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Archiving:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you prefer to keep a permanent, searchable \"life log\" without eating up your local SSD space, you don't necessarily have to let ScreenPipe delete them. You could script a simple cron job to regularly","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"older","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files to your massive 4-drive RAID 5 array, replacing the local files with symlinks. This would keep the database references intact while offloading the heavy media storage to your NAS.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Good response","depth":24,"on_screen":true,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Bad response","depth":24,"on_screen":true,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Share and export","depth":23,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":24,"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":23,"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy prompt","depth":21,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Edit","depth":21,"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said yes I will do that. Is there a way to setup languages to transcription?","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"yes I will do that. Is there a way to setup languages to transcription?","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":24,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"That is a solid plan. Offloading those older media files to your 4-drive RAID 5 setup (or even the secondary SSD-only Beelink NAS if you end up building it) will keep your local SSD lean while keeping your database searchable.","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"As for setting up languages for transcription,","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"yes, you can configure it","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", but it helps to understand how ScreenPipe handles language natively first.","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"How the Transcription Engine Handles Language","depth":26,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How the Transcription Engine Handles Language","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, ScreenPipe uses a","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"multilingual Whisper model","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and sets the language configuration to","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Auto-Detect","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When a new audio chunk comes in, the model listens to the first few seconds of audio, guesses the language, and transcribes the rest of that chunk using that assumption.","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Advantage:","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you are watching a tutorial in English, and then an hour later you are in a Zoom call speaking Bulgarian, ScreenPipe will automatically switch gears without you having to touch the settings.","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Drawback:","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Auto-detect can sometimes guess wrong, especially if there is heavy background noise, if someone starts a sentence with a foreign loanword, or if you are rapidly code-switching between Slovak and English in the same conversation. When it guesses wrong, it might try to force Slovak words into English spelling, resulting in gibberish.","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"How to Force a Specific Language","depth":26,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How to Force a Specific Language","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you want to ensure maximum accuracy and you know you will primarily be recording in one language for a specific period, you can explicitly set the language. This also slightly speeds up the processing because the model skips the detection phase.","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you are using the Desktop App UI:","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open the ScreenPipe settings.","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Navigate to the","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audio","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI/Transcription","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"section.","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Look for the","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Whisper Language","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Transcription Language","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"dropdown.","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Change it from \"Auto\" to your specific language (e.g., English, Bulgarian, or Slovak).","depth":29,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you are running ScreenPipe via CLI/Config:","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can modify your underlying configuration (usually found in","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe/pipe.json","depth":28,"bounds":{"left":0.0,"top":0.0,"width":0.134375,"height":0.020555556},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or by passing a flag when starting the daemon) to force a specific language code. You would use the standard ISO language codes:","depth":27,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Slovak)","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Bulgarian)","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(English)","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you find yourself frequently jumping between those three languages, your best bet is to leave it on Auto-Detect and perhaps run a slightly larger, more accurate Whisper model (like Whisper 'Small' or 'Base' instead of 'Tiny') if your hardware has the headroom for it.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Good response","depth":23,"on_screen":false,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Bad response","depth":23,"on_screen":false,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Redo","depth":23,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Share and export","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":23,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":22,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"Ask Gemini","depth":20,"on_screen":true,"value":"Ask Gemini","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Ask Gemini","depth":21,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Open upload file menu","depth":20,"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Tools","depth":18,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Open mode picker","depth":20,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Pro","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Microphone","depth":19,"on_screen":true,"role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Send message","depth":19,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":false,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Gemini is AI and can make mistakes, including about people.","depth":17,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Your privacy and Gemini Opens in a new window","depth":17,"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Your privacy and Gemini","depth":18,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Opens in a new window","depth":19,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Summarize page","depth":7,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Summarize page","depth":9,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Screenpipe [archive.db · 2071.1MB]","depth":7,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Screenpipe","depth":8,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"[archive.db · 2071.1MB]","depth":9,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Activity","depth":7,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Search","depth":7,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Audio","depth":7,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Work Report","depth":7,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Timetable","depth":7,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"AI Summary","depth":7,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Date","depth":8,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"12","depth":9,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/","depth":8,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"05","depth":9,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/","depth":8,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2026","depth":9,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Calendar","depth":8,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Monitor","depth":9,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jump to","depth":9,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"--","depth":10,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":9,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"--","depth":10,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Go","depth":8,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"📅 Time Range Filter ▼","depth":9,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"📅 Time Range Filter","depth":10,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"▼","depth":10,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"From:","depth":11,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"09","depth":12,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":11,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"45","depth":12,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"To:","depth":11,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"10","depth":12,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":11,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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accessibility
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Screenpipe — Archive
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SQLite Web: archive.db
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SQLite Web: db.sqlite
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You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
You said
Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
Listen
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Gemini said
Gemini said
Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.
ScreenPipe is fundamentally designed to be a
100% local, privacy-first
application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.
View source details. Opens side panel.
1. Where It Starts: The Capture Layer
1. Where It Starts: The Capture Layer
The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:
System Audio:
Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).
Microphone Input:
Everything you say into your mic.
View source details. Opens side panel.
Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.
2. How It Gets Transferred and Transcribed
2. How It Gets Transferred and Transcribed
Because ScreenPipe prioritizes local processing, the "transfer" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.
Here is the transcription pipeline:
The Engine:
The raw audio chunks are fed into a local speech-to-text model.
By default, ScreenPipe uses
OpenAI Whisper
running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).
View source details. Opens side panel.
Diarization:
As it transcribes the text, the engine also performs "diarization"—a technical term for speaker identification.
It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.
View source details. Opens side panel.
Storage:
The final transcribed text is then indexed into a local
SQLite database
. This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.
3. The "Work in Progress" (WIP) Stage
3. The "Work in Progress" (WIP) Stage
There is a slight bottleneck between
hearing
the audio and
saving
the text, which acts as the WIP stage:
Buffering:
Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.
Processing Queue:
Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.
Finalization:
Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.
4. Understanding the Folder Structure
4. Understanding the Folder Structure
All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like
~/.screenpipe
on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:
The SQLite Database (
):
This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is "done."
The
or
folders:
This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.
Temp Files:
If you see rapidly changing files, temporary
chunks, or locked database journals (like
), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.
Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?
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You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
You said
I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
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Show thinking
Gemini said
Gemini said
Yes, those
.mp4
files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.
Here is exactly what those files are doing sitting in your
~/.screenpipe/data/
directory and how they interact with the rest of the system.
1. The "Time Machine" Playback
1. The "Time Machine" Playback
The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the
db.sqlite
database along with
precise timestamps and file path references
.
When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific
.mp4
file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.
2. Re-processing and Model Upgrades
2. Re-processing and Model Upgrades
Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw
.mp4
files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.
3. The Source of Truth for Hallucinations
3. The Source of Truth for Hallucinations
Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that
.mp4
file is your fallback source of truth to verify what was actually said.
How the Database Views Them
How the Database Views Them
If you were to open up your
db.sqlite
and query the tables (e.g.,
audio_transcriptions
), you would see that the database treats the
~/.screenpipe/data/
folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like
soundcore AeroClip (input)_2026-05-12_07-40-48.mp4
.
What happens if you delete them?
If you manually
rm
those files to free up space on your Mac's SSD, ScreenPipe won't crash. The SQLite database will still hold all your searchable text. However, any attempt to play back the audio for those older transcripts will silently fail or throw a "file not found" error in the background logs.
Managing the Storage Footprint
Managing the Storage Footprint
Because ScreenPipe records continuously, this folder will inevitably grow over time.
Built-in Garbage Collection:
ScreenPipe usually handles this automatically based on retention settings (e.g., deleting media older than 30 days or when the folder hits a specific GB limit).
Archiving:
If you prefer to keep a permanent, searchable "life log" without eating up your local SSD space, you don't necessarily have to let ScreenPipe delete them. You could script a simple cron job to regularly
older
files to your massive 4-drive RAID 5 array, replacing the local files with symlinks. This would keep the database references intact while offloading the heavy media storage to your NAS.
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You said yes I will do that. Is there a way to setup languages to transcription?
You said
yes I will do that. Is there a way to setup languages to transcription?
Listen
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Gemini said
Gemini said
That is a solid plan. Offloading those older media files to your 4-drive RAID 5 setup (or even the secondary SSD-only Beelink NAS if you end up building it) will keep your local SSD lean while keeping your database searchable.
As for setting up languages for transcription,
yes, you can configure it
, but it helps to understand how ScreenPipe handles language natively first.
How the Transcription Engine Handles Language
How the Transcription Engine Handles Language
By default, ScreenPipe uses a
multilingual Whisper model
and sets the language configuration to
Auto-Detect
.
When a new audio chunk comes in, the model listens to the first few seconds of audio, guesses the language, and transcribes the rest of that chunk using that assumption.
The Advantage:
If you are watching a tutorial in English, and then an hour later you are in a Zoom call speaking Bulgarian, ScreenPipe will automatically switch gears without you having to touch the settings.
The Drawback:
Auto-detect can sometimes guess wrong, especially if there is heavy background noise, if someone starts a sentence with a foreign loanword, or if you are rapidly code-switching between Slovak and English in the same conversation. When it guesses wrong, it might try to force Slovak words into English spelling, resulting in gibberish.
How to Force a Specific Language
How to Force a Specific Language
If you want to ensure maximum accuracy and you know you will primarily be recording in one language for a specific period, you can explicitly set the language. This also slightly speeds up the processing because the model skips the detection phase.
If you are using the Desktop App UI:
Open the ScreenPipe settings.
Navigate to the
Audio
or
AI/Transcription
section.
Look for the
Whisper Language
or
Transcription Language
dropdown.
Change it from "Auto" to your specific language (e.g., English, Bulgarian, or Slovak).
If you are running ScreenPipe via CLI/Config:
You can modify your underlying configuration (usually found in
~/.screenpipe/pipe.json
or by passing a flag when starting the daemon) to force a specific language code. You would use the standard ISO language codes:
(Slovak)
(Bulgarian)
(English)
If you find yourself frequently jumping between those three languages, your best bet is to leave it on Auto-Detect and perhaps run a slightly larger, more accurate Whisper model (like Whisper 'Small' or 'Base' instead of 'Tiny') if your hardware has the headroom for it.
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Copy prompt
You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
You said
Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
Listen
Show thinking
Gemini said
Gemini said
Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.
ScreenPipe is fundamentally designed to be a
100% local, privacy-first
application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.
View source details. Opens side panel.
1. Where It Starts: The Capture Layer
1. Where It Starts: The Capture Layer
The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:
System Audio:
Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).
Microphone Input:
Everything you say into your mic.
View source details. Opens side panel.
Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.
2. How It Gets Transferred and Transcribed
2. How It Gets Transferred and Transcribed
Because ScreenPipe prioritizes local processing, the "transfer" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.
Here is the transcription pipeline:
The Engine:
The raw audio chunks are fed into a local speech-to-text model.
By default, ScreenPipe uses
OpenAI Whisper
running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).
View source details. Opens side panel.
Diarization:
As it transcribes the text, the engine also performs "diarization"—a technical term for speaker identification.
It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.
View source details. Opens side panel.
Storage:
The final transcribed text is then indexed into a local
SQLite database
. This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.
3. The "Work in Progress" (WIP) Stage
3. The "Work in Progress" (WIP) Stage
There is a slight bottleneck between
hearing
the audio and
saving
the text, which acts as the WIP stage:
Buffering:
Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.
Processing Queue:
Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.
Finalization:
Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.
4. Understanding the Folder Structure
4. Understanding the Folder Structure
All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like
~/.screenpipe
on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:
The SQLite Database (
):
This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is "done."
The
or
folders:
This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.
Temp Files:
If you see rapidly changing files, temporary
chunks, or locked database journals (like
), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.
Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?
Sources
Sources
Good response
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Share and export
Copy
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Copy prompt
You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
You said
I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
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Gemini said
Gemini said
Yes, those
.mp4
files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.
Here is exactly what those files are doing sitting in your
~/.screenpipe/data/
directory and how they interact with the rest of the system.
1. The "Time Machine" Playback
1. The "Time Machine" Playback
The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the
db.sqlite
database along with
precise timestamps and file path references
.
When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific
.mp4
file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.
2. Re-processing and Model Upgrades
2. Re-processing and Model Upgrades
Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw
.mp4
files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.
3. The Source of Truth for Hallucinations
3. The Source of Truth for Hallucinations
Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that
.mp4
file is your fallback source of truth to verify what was actually said.
How the Database Views Them
How the Database Views Them
If you were to open up your
db.sqlite
and query the tables (e.g.,
audio_transcriptions
), you would see that the database treats the
~/.screenpipe/data/
folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like
soundcore AeroClip (input)_2026-05-12_07-40-48.mp4
.
What happens if you delete them?
If you manually
rm
those files to free up space on your Mac's SSD, ScreenPipe won't crash. The SQLite database will still hold all your searchable text. However, any attempt to play back the audio for those older transcripts will silently fail or throw a "file not found" error in the background logs.
Managing the Storage Footprint
Managing the Storage Footprint
Because ScreenPipe records continuously, this folder will inevitably grow over time.
Built-in Garbage Collection:
ScreenPipe usually handles this automatically based on retention settings (e.g., deleting media older than 30 days or when the folder hits a specific GB limit).
Archiving:
If you prefer to keep a permanent, searchable "life log" without eating up your local SSD space, you don't necessarily have to let ScreenPipe delete them. You could script a simple cron job to regularly
older
files to your massive 4-drive RAID 5 array, replacing the local files with symlinks. This would keep the database references intact while offloading the heavy media storage to your NAS.
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You said yes I will do that. Is there a way to setup languages to transcription?
You said
yes I will do that. Is there a way to setup languages to transcription?
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Gemini said
Gemini said
That is a solid plan. Offloading those older media files to your 4-drive RAID 5 setup (or even the secondary SSD-only Beelink NAS if you end up building it) will keep your local SSD lean while keeping your database searchable.
As for setting up languages for transcription,
yes, you can configure it
, but it helps to understand how ScreenPipe handles language natively first.
How the Transcription Engine Handles Language
How the Transcription Engine Handles Language
By default, ScreenPipe uses a
multilingual Whisper model
and sets the language configuration to
Auto-Detect
.
When a new audio chunk comes in, the model listens to the first few seconds of audio, guesses the language, and transcribes the rest of that chunk using that assumption.
The Advantage:
If you are watching a tutorial in English, and then an hour later you are in a Zoom call speaking Bulgarian, ScreenPipe will automatically switch gears without you having to touch the settings.
The Drawback:
Auto-detect can sometimes guess wrong, especially if there is heavy background noise, if someone starts a sentence with a foreign loanword, or if you are rapidly code-switching between Slovak and English in the same conversation. When it guesses wrong, it might try to force Slovak words into English spelling, resulting in gibberish.
How to Force a Specific Language
How to Force a Specific Language
If you want to ensure maximum accuracy and you know you will primarily be recording in one language for a specific period, you can explicitly set the language. This also slightly speeds up the processing because the model skips the detection phase.
If you are using the Desktop App UI:
Open the ScreenPipe settings.
Navigate to the
Audio
or
AI/Transcription
section.
Look for the
Whisper Language
or
Transcription Language
dropdown.
Change it from "Auto" to your specific language (e.g., English, Bulgarian, or Slovak).
If you are running ScreenPipe via CLI/Config:
You can modify your underlying configuration (usually found in
~/.screenpipe/pipe.json
or by passing a flag when starting the daemon) to force a specific language code. You would use the standard ISO language codes:
(Slovak)
(Bulgarian)
(English)
If you find yourself frequently jumping between those three languages, your best bet is to leave it on Auto-Detect and perhaps run a slightly larger, more accurate Whisper model (like Whisper 'Small' or 'Base' instead of 'Tiny') if your hardware has the headroom for it.
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Screenpipe [archive.db · 2071.1MB]
Screenpipe
[archive.db · 2071.1MB]
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Gemini","depth":15,"bounds":{"left":0.068484046,"top":0.14764565,"width":0.0003324468,"height":0.0007980846},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Conversation with Gemini","depth":16,"bounds":{"left":0.068484046,"top":0.15003991,"width":0.1200133,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy prompt","depth":21,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":24,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ScreenPipe is fundamentally designed to be a","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"100% local, privacy-first","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":27,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"1. Where It Starts: The Capture Layer","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Where It Starts: The Capture Layer","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"System Audio:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Microphone Input:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Everything you say into your mic.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How It Gets Transferred and Transcribed","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How It Gets Transferred and Transcribed","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Because ScreenPipe prioritizes local processing, the \"transfer\" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is the transcription pipeline:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Engine:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The raw audio chunks are fed into a local speech-to-text model.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, ScreenPipe uses","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"OpenAI Whisper","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Diarization:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"As it transcribes the text, the engine also performs \"diarization\"—a technical term for speaker identification.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details. Opens side panel.","depth":29,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Storage:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The final transcribed text is then indexed into a local","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SQLite database","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. The \"Work in Progress\" (WIP) Stage","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. The \"Work in Progress\" (WIP) Stage","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"There is a slight bottleneck between","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"hearing","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the audio and","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"saving","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the text, which acts as the WIP stage:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Buffering:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Processing Queue:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Finalization:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"4. Understanding the Folder Structure","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"4. Understanding the Folder Structure","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The SQLite Database (","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"):","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is \"done.\"","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"folders:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Temp Files:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you see rapidly changing files, temporary","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"chunks, or locked database journals (like","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Sources","depth":26,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Sources","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Good response","depth":24,"on_screen":false,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Bad response","depth":24,"on_screen":false,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Share and export","depth":23,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":24,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":23,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy prompt","depth":21,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"on_screen":false,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":24,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yes, those","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is exactly what those files are doing sitting in your","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe/data/","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"directory and how they interact with the rest of the system.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. The \"Time Machine\" Playback","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. The \"Time Machine\" Playback","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"db.sqlite","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"database along with","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"precise timestamps and file path references","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. Re-processing and Model Upgrades","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. Re-processing and Model Upgrades","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. The Source of Truth for Hallucinations","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. The Source of Truth for Hallucinations","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"file is your fallback source of truth to verify what was actually said.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"How the Database Views Them","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How the Database Views Them","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you were to open up your","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"db.sqlite","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and query the tables (e.g.,","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"audio_transcriptions","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"), you would see that the database treats the","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"~/.screenpipe/data/","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"soundcore AeroClip (input)_2026-05-12_07-40-48.mp4","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What happens if you delete them?","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you manually","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"rm","depth":28,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"those files to free up space on your Mac's SSD, ScreenPipe won't crash. The SQLite database will still hold all your searchable text. However, any attempt to play back the audio for those older transcripts will silently fail or throw a \"file not found\" error in the background logs.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Managing the Storage Footprint","depth":26,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Managing the Storage Footprint","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Because ScreenPipe records continuously, this folder will inevitably grow over time.","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Built-in Garbage Collection:","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ScreenPipe usually handles this automatically based on retention settings (e.g., deleting media older than 30 days or when the folder hits a specific GB limit).","depth":29,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Archiving:","depth":29,"bounds":{"left":0.09142287,"top":0.0,"width":0.02642952,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you prefer to keep a permanent, searchable \"life log\" without eating up your local SSD space, you don't necessarily have to let ScreenPipe delete them. You could script a simple cron job to regularly","depth":29,"bounds":{"left":0.09142287,"top":0.0,"width":0.22041224,"height":0.057861134},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"older","depth":29,"bounds":{"left":0.18035239,"top":0.0,"width":0.015292553,"height":0.016360734},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"files to your massive 4-drive RAID 5 array, replacing the local files with symlinks. This would keep the database references intact while offloading the heavy media storage to your NAS.","depth":29,"bounds":{"left":0.09142287,"top":0.0,"width":0.22174202,"height":0.057861134},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Good response","depth":24,"bounds":{"left":0.075465426,"top":0.029928172,"width":0.010638298,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Bad response","depth":24,"bounds":{"left":0.08610372,"top":0.029928172,"width":0.010638298,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Share and export","depth":23,"bounds":{"left":0.09674202,"top":0.029928172,"width":0.010638298,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":24,"bounds":{"left":0.107380316,"top":0.029928172,"width":0.010638298,"height":0.025538707},"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":23,"bounds":{"left":0.11801862,"top":0.029928172,"width":0.010638298,"height":0.025538707},"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy prompt","depth":21,"bounds":{"left":0.12566489,"top":0.0905826,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Edit","depth":21,"bounds":{"left":0.14029256,"top":0.0905826,"width":0.013297873,"height":0.031923383},"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said yes I will do that. Is there a way to setup languages to transcription?","depth":21,"bounds":{"left":0.16023937,"top":0.100159615,"width":0.15026596,"height":0.03830806},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"bounds":{"left":0.068484046,"top":0.1009577,"width":0.019946808,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"yes I will do that. Is there a way to setup languages to transcription?","depth":23,"bounds":{"left":0.16023937,"top":0.10175578,"width":0.12849069,"height":0.035514764},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":24,"bounds":{"left":0.3025266,"top":0.17039107,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":28,"bounds":{"left":0.09208777,"top":0.17278531,"width":0.030917553,"height":0.014764565},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"bounds":{"left":0.08976064,"top":0.21428572,"width":0.0003324468,"height":0.0007980846},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"bounds":{"left":0.08976064,"top":0.21628092,"width":0.04105718,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"That is a solid plan. Offloading those older media files to your 4-drive RAID 5 setup (or even the secondary SSD-only Beelink NAS if you end up building it) will keep your local SSD lean while keeping your database searchable.","depth":27,"bounds":{"left":0.0787899,"top":0.21747805,"width":0.23088431,"height":0.057861134},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"As for setting up languages for transcription,","depth":27,"bounds":{"left":0.0787899,"top":0.28850758,"width":0.10920878,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"yes, you can configure it","depth":27,"bounds":{"left":0.18799867,"top":0.28850758,"width":0.06333112,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", but it helps to understand how ScreenPipe handles language natively first.","depth":27,"bounds":{"left":0.0787899,"top":0.28850758,"width":0.20994017,"height":0.037110932},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"How the Transcription Engine Handles Language","depth":26,"bounds":{"left":0.0787899,"top":0.3499601,"width":0.234375,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How the Transcription Engine Handles Language","depth":27,"bounds":{"left":0.0787899,"top":0.35155627,"width":0.12549867,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, ScreenPipe uses a","depth":27,"bounds":{"left":0.0787899,"top":0.37789306,"width":0.072972074,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"multilingual Whisper model","depth":27,"bounds":{"left":0.15176196,"top":0.37789306,"width":0.07047872,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and sets the language configuration to","depth":27,"bounds":{"left":0.0787899,"top":0.37789306,"width":0.23321144,"height":0.037110932},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Auto-Detect","depth":27,"bounds":{"left":0.08510638,"top":0.39864326,"width":0.032247342,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":27,"bounds":{"left":0.11735372,"top":0.39864326,"width":0.0013297872,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When a new audio chunk comes in, the model listens to the first few seconds of audio, guesses the language, and transcribes the rest of that chunk using that assumption.","depth":27,"bounds":{"left":0.0787899,"top":0.42817238,"width":0.23038563,"height":0.037110932},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Advantage:","depth":29,"bounds":{"left":0.09142287,"top":0.47845173,"width":0.040724736,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you are watching a tutorial in English, and then an hour later you are in a Zoom call speaking Bulgarian, ScreenPipe will automatically switch gears without you having to touch the settings.","depth":29,"bounds":{"left":0.09142287,"top":0.47845173,"width":0.22174202,"height":0.057861134},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Drawback:","depth":29,"bounds":{"left":0.09142287,"top":0.5494813,"width":0.038896278,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Auto-detect can sometimes guess wrong, especially if there is heavy background noise, if someone starts a sentence with a foreign loanword, or if you are rapidly code-switching between Slovak and English in the same conversation. 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Screenpipe — Archive
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SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
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You said Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
You said
Exaplin me: how does the ScreenPipe audio recording work? Where did it start? How is it getting transferred and transcribed? Is there some work in progress stage? How can I see from the folder structure what has been done and what hasn't been done?
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Gemini said
Gemini said
Here is a breakdown of how ScreenPipe handles audio recording, from the moment it captures sound to how it organizes the data on your machine.
ScreenPipe is fundamentally designed to be a
100% local, privacy-first
application, meaning the vast majority of its processing happens directly on your hardware without relying on the cloud.
View source details. Opens side panel.
1. Where It Starts: The Capture Layer
1. Where It Starts: The Capture Layer
The process begins locally by tapping directly into your operating system’s audio routing. ScreenPipe simultaneously captures two separate audio streams:
System Audio:
Everything your computer outputs (e.g., the voices of other people in a Zoom or Teams meeting, a YouTube video, or Spotify).
Microphone Input:
Everything you say into your mic.
View source details. Opens side panel.
Because ScreenPipe acts as a 24/7 background process, it continuously listens to these streams and breaks the continuous audio into manageable chunks to prepare them for the next stage.
2. How It Gets Transferred and Transcribed
2. How It Gets Transferred and Transcribed
Because ScreenPipe prioritizes local processing, the "transfer" step is incredibly short. The audio data never leaves your machine unless you explicitly set up a cloud plugin.
Here is the transcription pipeline:
The Engine:
The raw audio chunks are fed into a local speech-to-text model.
By default, ScreenPipe uses
OpenAI Whisper
running locally on your hardware. (Users can also configure it to use cloud providers like Deepgram if they need faster processing, but local Whisper is the standard).
View source details. Opens side panel.
Diarization:
As it transcribes the text, the engine also performs "diarization"—a technical term for speaker identification.
It analyzes the audio to distinguish between your voice and the voices of others, labeling who said what.
View source details. Opens side panel.
Storage:
The final transcribed text is then indexed into a local
SQLite database
. This database uses Full-Text Search (FTS5), which is what allows you to instantly search for a phrase you heard in a meeting three weeks ago.
3. The "Work in Progress" (WIP) Stage
3. The "Work in Progress" (WIP) Stage
There is a slight bottleneck between
hearing
the audio and
saving
the text, which acts as the WIP stage:
Buffering:
Audio is recorded into a temporary buffer in your system's RAM or written as temporary chunk files on your disk.
Processing Queue:
Whisper requires CPU/GPU resources to transcribe. If you are having a rapid, multi-person conversation, the raw audio chunks line up in a processing queue.
Finalization:
Once the AI finishes transcribing a chunk, the text is committed to the SQLite database alongside a timestamp, and the raw audio is compressed and saved so you can play it back later.
4. Understanding the Folder Structure
4. Understanding the Folder Structure
All of ScreenPipe's data lives locally on your machine (usually in a hidden directory like
~/.screenpipe
on Mac/Linux or in your AppData folder on Windows). You can determine what has been processed by looking at a few key areas in this directory:
The SQLite Database (
):
This is the master ledger. If text exists inside this database, it means the audio has been fully transcribed, diarized, and is "done."
The
or
folders:
This is where the compressed, raw audio files and JPEG screenshots are stored permanently. Think of this as the raw archive.
Temp Files:
If you see rapidly changing files, temporary
chunks, or locked database journals (like
), this indicates the system is actively processing a backlog of audio (the WIP stage). Once the engine catches up, these temporary chunk files are usually cleared out or moved to permanent storage, and the database updates.
Are you setting up ScreenPipe for a specific workflow (like summarizing meetings or tracking your daily tasks), or just exploring how the architecture works under the hood?
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You said I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
You said
I see the files in ~/.screenpipe/data/ as LakyLak bose qc35 II (input)_2026-05-12_06-49-17.mp4 or MacBook Pro Microphone (input)_2026-05-12_12-17-23.mp4 or soundcore AeroClip (input)_2026-05-12_07-40-48.mp4 or System Audio (output)_2026-05-11_06-17-14.mp4. Are these used for anything after transcribing and storing in sqlite db?
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Gemini said
Gemini said
Yes, those
.mp4
files are absolutely still used after the transcription process is complete. They are not temporary processing chunks; they act as your permanent media archive.
Here is exactly what those files are doing sitting in your
~/.screenpipe/data/
directory and how they interact with the rest of the system.
1. The "Time Machine" Playback
1. The "Time Machine" Playback
The primary reason ScreenPipe keeps these files is for audio playback. When Whisper transcribes your meetings or ambient audio, it writes the text into the
db.sqlite
database along with
precise timestamps and file path references
.
When you search your ScreenPipe history for a specific conversation, the UI doesn't just show you the text—it uses the file path stored in the database to pull up that specific
.mp4
file and starts playing it at the exact second the keyword was spoken. Without these files, you get the transcript, but you lose the ability to actually listen to the context, tone, or nuance of the original conversation.
2. Re-processing and Model Upgrades
2. Re-processing and Model Upgrades
Local LLMs and transcription models are improving rapidly. Right now, your system might be using a quantized Whisper model to balance CPU load with accuracy. If you later decide to run a heavier, more accurate model—or if a radically better speaker diarization algorithm is released—having the raw
.mp4
files allows you to re-process historical audio. Without the raw input files, your data is permanently locked to the quality of the transcription model you were running on May 12th.
3. The Source of Truth for Hallucinations
3. The Source of Truth for Hallucinations
Speech-to-text engines, even great ones, occasionally hallucinate or misinterpret technical jargon, overlapping voices, or background noise. If a database query returns a completely nonsensical sentence, that
.mp4
file is your fallback source of truth to verify what was actually said.
How the Database Views Them
How the Database Views Them
If you were to open up your
db.sqlite
and query the tables (e.g.,
audio_transcriptions
), you would see that the database treats the
~/.screenpipe/data/
folder essentially as a blob storage backend. The tables contain columns acting as soft foreign keys pointing to filenames like
soundcore AeroClip (input)_2026-05-12_07-40-48.mp4
.
What happens if you delete them?
If you manually
rm
those files to free up space on your Mac's SSD, ScreenPipe won't crash. The SQLite database will still hold all your searchable text. However, any attempt to play back the audio for those older transcripts will silently fail or throw a "file not found" error in the background logs.
Managing the Storage Footprint
Managing the Storage Footprint
Because ScreenPipe records continuously, this folder will inevitably grow over time.
Built-in Garbage Collection:
ScreenPipe usually handles this automatically based on retention settings (e.g., deleting media older than 30 days or when the folder hits a specific GB limit).
Archiving:
If you prefer to keep a permanent, searchable "life log" without eating up your local SSD space, you don't necessarily have to let ScreenPipe delete them. You could script a simple cron job to regularly
older
files to your massive 4-drive RAID 5 array, replacing the local files with symlinks. This would keep the database references intact while offloading the heavy media storage to your NAS.
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You said yes I will do that. Is there a way to setup languages to transcription?
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yes I will do that. Is there a way to setup languages to transcription?
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Gemini said
Gemini said
That is a solid plan. Offloading those older media files to your 4-drive RAID 5 setup (or even the secondary SSD-only Beelink NAS if you end up building it) will keep your local SSD lean while keeping your database searchable.
As for setting up languages for transcription,
yes, you can configure it
, but it helps to understand how ScreenPipe handles language natively first.
How the Transcription Engine Handles Language
How the Transcription Engine Handles Language
By default, ScreenPipe uses a
multilingual Whisper model
and sets the language configuration to
Auto-Detect
.
When a new audio chunk comes in, the model listens to the first few seconds of audio, guesses the language, and transcribes the rest of that chunk using that assumption.
The Advantage:
If you are watching a tutorial in English, and then an hour later you are in a Zoom call speaking Bulgarian, ScreenPipe will automatically switch gears without you having to touch the settings.
The Drawback:
Auto-detect can sometimes guess wrong, especially if there is heavy background noise, if someone starts a sentence with a foreign loanword, or if you are rapidly code-switching between Slovak and English in the same conversation. When it guesses wrong, it might try to force Slovak words into English spelling, resulting in gibberish.
How to Force a Specific Language
How to Force a Specific Language
If you want to ensure maximum accuracy and you know you will primarily be recording in one language for a specific period, you can explicitly set the language. This also slightly speeds up the processing because the model skips the detection phase.
If you are using the Desktop App UI:
Open the ScreenPipe settings.
Navigate to the
Audio
or
AI/Transcription
section.
Look for the
Whisper Language
or
Transcription Language
dropdown.
Change it from "Auto" to your specific language (e.g., English, Bulgarian, or Slovak).
If you are running ScreenPipe via CLI/Config:
You can modify your underlying configuration (usually found in
~/.screenpipe/pipe.json
or by passing a flag when starting the daemon) to force a specific language code. You would use the standard ISO language codes:
(Slovak)
(Bulgarian)
(English)
If you find yourself frequently jumping between those three languages, your best bet is to leave it on Auto-Detect and perhaps run a slightly larger, more accurate Whisper model (like Whisper 'Small' or 'Base' instead of 'Tiny') if your hardware has the headroom for it.
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Screenpipe [archive.db · 2071.1MB]
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