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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
[SRD-6793] Les Mills activity types not pulling in - Jira
[SRD-6793] Les Mills activity types not pulling in - Jira
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Symfony\Component\Debug\Exception\FatalThrowableError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line
Symfony\Component\Debug\Exception\FatalThrowableError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
[SRD-6793] Les Mills activity types not pulling in - Jira
[SRD-6793] Les Mills activity types not pulling in - Jira
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Symfony\Component\Debug\Exception\FatalThrowableError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line
Symfony\Component\Debug\Exception\FatalThrowableError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line
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Refinement 2026-04-20.mp4
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Refinement 2026-04-20.mp4...
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Refinement 2026-04-20.mp4
QuickTime PlayerFileEditViewWindowHelpGalya Dimitrova (Presenting, annotating)SafariFileHistoryookmarksDevelopHelpnny.atlassian.net|)5 HubSpotAWOCUВAnDAPlanhat88For you© Recent |# Starred89 Apps8 Plans0, SpacesStarredJiminny (New)I ( Platform TeamIID Processing TeamUD SE KanbanIID Capture Team|IID Enterprise Stability I...M Discovery# ProductRecentService-Desk= More spaces= FiltersB DashboardsOperations& Customers# Seit Service8 Dust Docs• AwS US |S. GTM Tren.Q Search|Spaces / Jiminny (New)Platform TeamSummary|% TimelineE BacklogII) Active sprintsCalendarQ Search backlog|210800Version vEpic vPiatrorm sprint s uz Zy Apr - 15 May (15 worK items)@ JY-20625 Jiminny MCP Connector|A JY-20412 Change Auto-log delayA JY-20361 AJ Panorama for Call Scoring in ODAUTOMATED.JY-20699 Wrong formatting for summary in th..@ JY-19628 Evaluation of AJ PanoramaASK ANYTHI...• JY-20676 Notify the user if a Panorama prom…AJ REPORTS• JY-20615 Notify the user if a SS is deleted bu...AJ REPORTSA JY-20613 Allow owner's role to be selected w...A JY-20500 Batch initial sync for SalesforceA JY-20501 Batch initial sync for HubspotCRM SYNCH..@ JY-20503 Batch insert/update CRM objects in….meet.google.com is shA JY-20410 Update the templi•))01:45:22, 0• Refinement 2026-04-20.mp4₽j Support Daily - in 4 h 9 m100% C478Tue 21 Apr 10:51:358J Emoll2 Features.2 ReportsMore 9+Type vMore v205 10 0BACKLOGBACKLOSV=BACKLOG2.5= 8BACKLOG=BACKLOG=BACKLOG3=8BACKLOG=BACKLOGv=BACKLOG=BACKLOG8LOP KOCKEV+ Create8 • Mon 20 Apr 16:47+›* Campus X|rurodseту м.© Demo Exe.UpgradeAsk Rovo@ Jira work itemBacklog ~Xx Improve Story• DescriptionUsers might attempt to delete a saved searchwhich is used in AJ Report. When they do that weneed to let them know that the report will stopgenerating.• when a user tries to delete a SS which is usedIn Ask Jiminny report, show them aconfirmation message - F Project Phoenix• If the user tries to enable the report withoutselecting a new prompt - don't allow this andshow them a messageSubtasksAdd subtaskLinked work itemsAneliya AngelovaGalya Dimitrova3 othersNikolay Yankov=01:54:46Lukas Kovalik4:47 PM| [Platform] Refinement...
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Refinement 2026-04-20.mp4
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6340868489213470854
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NULL
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rewind
play/pause
fast forward
mute
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rewind
play/pause
fast forward
mute
More Controls
toggle full screen
show external playback menu
show external playback menu
show media selection menu
toggle picture-in-picture playback
show action menu
share
show chapter menu
zoom
zoom
playback speed
01:52:28
toggle elapsed time, timecode and framecount
01:54:46
toggle duration and remaining time
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Refinement 2026-04-20.mp4
Quickllme PlayenActivityMoreJiminny …..Dratts & centi8 DirectoriesEb External connections# Starred8 jiminny-x-integrati...& platform-inner-teamE Channels# ai-chapter# alertsS hackendi# confusion-clinic# curiosity_lab# engineering# frontend# general# infra-changes# jiminny-bg# platform-tickets# product launches# random# releases# support# thank-yous# the_people_of_jimi...• Direct messages• Vasil Vasilev.P. Nikolay Nikolov. Aneliya Angelova. Galya Dimitrovaa. Stefka StoyanovaR. Stoyan Tomov3 Aneliya Angelova, .Stovan TaneyP. Nikolay IvanovP. Vesi: AppsS Jira Cloud• ToastAl Reports > Empty page design and promotion - Search#rekShow results for: Al Reports > Empty page design and promotionEnterMessageShow results in this channel for: Al Reports > Empty page design and promotionProlelag:Calva Dimitrova Direct Mescace with Galva DimitrovalJY-20372 Al Reports > Empty page design and promotionApr 16th at 11:59 AMCirckDepl.v SelectGive feedbackProject: appWhen: 04/20/2026 14:12:24View JobTodavGitHub APP 9:32 AM3 new commits pushed to master by LakyLak922c5e7e - JY-20698 handle failed field sync on playbook import activity typesc6e14fbd - Merge branch 'master' into JY-20698-fix-SF-activity-types-on-new-Dlaybookb3760452 - Merge pull request #11988 from jiminny/JY-20698-fix-SF-activity-types-on-new-playbook)jimnwlapo Added by GithubCircleCl APP 9:56 AMDeployment Successful!Project: appWhen: 04/21/202606.56-27Tho.View Jobciitlinh App 10.20 AM3 new commits pushed to master by TodorStamatovJiminny3ba7bcf9 - JY-20708: update elastic search on new activity62aoc7dh - Merge branch 'master' into JY-20708-e ashicsearch-new-activitiedc153952e - Merge pull request #11992 from jiminny/JY-20708-elasticsearch-new-activitiesjiminny/app | Added by GitHubMessage #releases+ Аa822ravountesE jiminny(* AirDrop• Recents* Applications© Documentsii lukasiCloud• iCloud Drive992 Svnc toldeLocationsO DXP4800PLUS-B5F A® Network• CRM• Orange• Red• Yellow• PurpleO All Tags...Support Daily - in 4h 9mworkv N 2026= Daily 2026-04-21.mp4Da Retinelent 2026-04-20.mp4Daily 2026-04-20.mp4Daily 2026-04-17.mp4Fu Daily 2026-04-16.mp4F™ Pannina 2026-04-15.mo4Retro 2026-04-14.mp4• Daily 2026-04-14.mp4User pilot (Adi) 2026-04-09.mp4w Daily 2026-04-00 mnЛ• Daily 2026-04-07.mp4- Refinement 2026-04-06.mo4= Daily 2026-04-06.mp4- Daily 2026-04-03.mp4lax Plannina 2026-04-01 & task split.mp4M: Datra 2026.02-21 mn/- Refinement 2026-03-30.mp4na Daily 2026-02-30.mn/- Daily 2026-03-27.mp4Daily 2026-03-26.mp4• Dailv 2026-03-24,m04• Refinement 2026-03-23.mp4** BE chapter 2026-03-20.mp4= Daily 2026-02-20 mn4sm Planing 2026-03-18-converted.mp4- Refinement 2026-02-09-converted.mp4Rя Dailv 2026-03-19.mo4- Review 2026-03-18.mp4Planing 2026-03-18.mp4F Retro 2026-03-17m04= Daily 2026-02-17 mn/ment 2026-03-16.mp4- Dally 2026-03-16.mp4c Dailv 2026-03-13.mn4с 1-1 2026-03-12.mр4xa Dallv 2026-03-11.m04•: Daily 2026-02-10 mn/nent 2026-03-09.mp4• Daily 2026-03-09.mp4Fu Daily 2026-03-06.mn4a: Planning 2026-03-04.mp4Daily 2026-03-02.mp4* Dailv 2026-02-27 mo4eN Daily 2026.02.26 malDaily 2026-02-25.movlan Opportunity-Contacts 2026-02-24.mp4ma Daily 2026-02-24 mn/Refinement 2026-02-23.mov= Daily 2026-02-20 & Ani.mp4- Dailv 2026-02-19.mo4к Review 2026-02-18.mD4Date ModifiedTodau at 10:02Yesterday at 16.56Yesterdav at 10:0617 Apr 2026 at 10:1616 Apr 2026 at 10:0015 Aor 2026 at 11:1414 Apr 2026 at 17:3714 Apr 2026 at 10:099 Apr 2026 at 14:47QAnr 2026 at 10:078 Apr 2026 at 10:137 Apr 2026 at 10:016 Aor 2026 at 17:206 Apr 2026 at 10:083 Apr 2026 at 10:211 Aor 2026 at 12:2021 Mar 2026 at 19:2031 Mar 2026 at 10:1030 Mar 2026 at 17:1220 Mar 2026 at 10:0527 Mar 2026 at 10:0926 Mar 2026 at 9:5924 Mar 2026 at 10:0022 Mar 2026 at 17:0223 Mar 2026 at 10:0020 Mar 2026 at 11:4620 Mar 2026 at 10:0619 Mar 2026 at 12:0119 Mar 2026 at 11:3519 Mar 2026 at 9:5718 Mar 2026 at 16:2018 Mar 2026 at 11:1417 Mar 2026 at 17:4017 Mar 2026 at 10:1916 Mar 2026 at 16:5516 Mar 2026 at 10:0213 Mar 2026 at 10:1212 Mar 2026 at 18:3512 Mar 2026 at 10:1011 Mar 2026 at 10:0610 Mar 2026 at 0:579 Mar 2026 at 17:049 Mar 2026 at 9:566 Mar 2026 at 9:574 Mar 2026 at 11:0927 Feb 2026 at 10:0226 Eoh 2026 at 0:5225 Feb 2026 at 9:5924 Feb 2026 at 12:0324 Feh 2026 at 10:0223 Feb 2026 at 16:3119 Feb 2026 at 9:54O CAh GAG A+ 46.0GTue 21 Apr 10:51:35v Size-- Folder567,8 MB4,25 GBMPEG-4 movie698.5 MEMPEG-4 movie1,16 GBMPEG-4 movie513,4 MBMPEG-4 movie2.75 G:MPEG-4 movie1,44 GBMPEG-4 movie924,4 MB362.6 MBMPEG-4 movie719 8MR MDEG-A movid1,04 GBMPEG-4 movie575,5 MBMPEG-4 movie4.34 G:MPEG-4 movie720,5 MB MPEG-4 movie1,02 GB4.68 G:MPEG-4 movie3,4 GBMPEG-4 movie923,6 MBMPEG-4 movie2,77 GBMPEG-4 movie6418MPMPEG-A movid884,3 MBMPEG-4 movie476,6 MBMPEG-4 movie550.8 MEMPEG-4 movie3,44 GBMDEG.A movid438,9 MBMPEG-4 movie1,68 GBMPEG-4 movie120 A MPMDEG-A movie2,38 GBMPEG-4 movie2,26 GB386.3 MEMPEG-4 movie705,8 MBMPEG-4 movie2,78 GBMPEG-4 movie1,53 GBMPEG-4 movie12 GPMDEG-A movid4,19 GBMPEG-4 movie592,2 MB1.02 GEMPEG-4 movie637.6 MBMDEC.A movid978,7 MBMPEG-4 movie798,7 MBMPEG-4 movieAOA 6MPMDSG-A movie4,16 GBMPEG-4 movie319,7 MB291.7 MEMPEG.A movid2,62 GB MPEG-4 movie768,5 MB546.8 MBMPEG-4 movieO6 GMR OT movio503,5 MBQT movie791,7 MBMPEG-4 movieMPEG-A movie2 GB QT movie234 2 MBMPEG-4 movieOEAMP MОRA A MAVid1 of 144 selected, 2,03 TB available...
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CloudWatch | us-east-2 — Work
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Workers | Datadog
Platform Sprint 2 Q2 - Platform Workers | Datadog
Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
[SRD-6793] Les Mills activity types not pulling in - Jira
[SRD-6793] Les Mills activity types not pulling in - Jira
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Symfony\Component\Debug\Exception\FatalThrowableError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line
Symfony\Component\Debug\Exception\FatalThrowableError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line
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2026-04-16T20:29:05.288Z
[IP_ADDRESS] - - [16/Apr/2026:20:29:05 +0000] 200 "GET /index.php/health_check HTTP/1.1" 36 "-" "ELB-HealthChecker/2.0" "-" rt="0.033" urt="0.032" ua="unix:/run/php-fpm-health.sock" us="200" rid="83364459354bd20da4fb1b06c90c9dcc" xrid="-"
php-app/php-app/6c7993d0e6814e478a652befada37c14 Opens in a new tab
410346195943:php-app
2026-04-16T16:29:21.934Z
[IP_ADDRESS] - - [16/Apr/2026:16:29:21 +0000] 404 "GET /api/v1/get-access-token/hubspot?appId=38484&portalId=3364459&userEmail=[EMAIL]&userId=70437797 HTTP/1.1" 12 "-" "Hubspot-UIExtensions/1.0 ReactCard" "[IP_ADDRESS], [IP_ADDRESS]" rt="0.046" urt="0.045" ua="unix:/run/php-fpm.sock" us="404" rid="44f360233af343c5f3fa5bc69cdbf38f" xrid="-"
php-app/php-app/f2dc7efdb4714f748a69327ebb9d90dc Opens in a new tab
410346195943:php-app
2026-04-16T16:29:21.934Z...
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-1950652493584006982
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8801513450341381303
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visual_change
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accessibility
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NULL
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Workers | Datadog
Platform Sprint 2 Q2 - Platform Workers | Datadog
Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
[SRD-6793] Les Mills activity types not pulling in - Jira
[SRD-6793] Les Mills activity types not pulling in - Jira
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Symfony\Component\Debug\Exception\FatalThrowableError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line
Symfony\Component\Debug\Exception\FatalThrowableError: League\Flysystem\Filesystem::has(): Argument #1 ($location) must be of type string, null given, called in /home/jiminny/vendor/laravel/framework/src/Illuminate/Filesystem/FilesystemAdapter.php on line
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Completed. Query executed for
26 log groups.
View log groups used in query
Logs (428)
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428
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Showing 428 of 428 records matched
326,991,265 records (86.4 GB) scanned in 40.6s @ 8,052,583 records/s (2.1 GB/s)
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2026-04-16T20:29:05.288Z
[IP_ADDRESS] - - [16/Apr/2026:20:29:05 +0000] 200 "GET /index.php/health_check HTTP/1.1" 36 "-" "ELB-HealthChecker/2.0" "-" rt="0.033" urt="0.032" ua="unix:/run/php-fpm-health.sock" us="200" rid="83364459354bd20da4fb1b06c90c9dcc" xrid="-"
php-app/php-app/6c7993d0e6814e478a652befada37c14 Opens in a new tab
410346195943:php-app
2026-04-16T16:29:21.934Z
[IP_ADDRESS] - - [16/Apr/2026:16:29:21 +0000] 404 "GET /api/v1/get-access-token/hubspot?appId=38484&portalId=3364459&userEmail=[EMAIL]&userId=70437797 HTTP/1.1" 12 "-" "Hubspot-UIExtensions/1.0 ReactCard" "[IP_ADDRESS], [IP_ADDRESS]" rt="0.046" urt="0.045" ua="unix:/run/php-fpm.sock" us="404" rid="44f360233af343c5f3fa5bc69cdbf38f" xrid="-"
php-app/php-app/f2dc7efdb4714f748a69327ebb9d90dc Opens in a new tab
410346195943:php-app
2026-04-16T16:29:21.934Z...
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/Users/lukas/.screenpipe/data/data/2026-04-17/1776 /Users/lukas/.screenpipe/data/data/2026-04-17/1776406416278_m2.jpg...
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CloudWatch | us-east-2 — Work
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
[SRD-6793] Les Mills activity types not pulling in - Jira
[SRD-6793] Les Mills activity types not pulling in - Jira
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Configure SSH access to multiple environment - Engineering - Confluence
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Refinement 2026-04-20.mp4
QuickTime PlayerFileEditViewWindowHelpNikolay Nikolov (Presenting, annotating), 0• Refinement 2026-04-20.mp4j Support Daily • in 4h 9 m100% C47Tue 21 Apr 10:51:318••a 8.Mon 20 Apr 16:29"eVonoes[Y-20615) No[Jv-20500) Ba x[uv-20501) Bux: x | 02:08:58- Retr x | E Jminny - Calenc x | De Meet - [PtaM inbox - nikolay.nikTogelA. LLM Leaderboard.NVmYzgxZ/YzYTFhNDNJYTg4Z/YOYT2JZGZMmVIZDUILCJwijolamlyYS1zbGFjay1pbnQIfQD T000Debug crm-sync.C3 Retine CJ Sentry CJ ES C Learn C AlChapter HomeQ SearchSpaces• Activity→ J-15971 / Д JY-20500CommentsWork logMormal texkДv.:=® % +~|oProfileCreated event fires when a new CRM profile is createdSyncProfileOpportunities listener handies itDispatches SyneOpportunities.Job with crn_profile_id parameterUses LAST_MODIFIED_BY_PROFILE_SYNC_OPPORTUNITY_STRATEGYProviders Supported (lines 51-61)• HubSpot• SalesforceBatching?No batching - Uses SyncoppoztunitiesJob which calls syncopportunáties() :• Salesforce: One-by-one (inpertOpportunity() in a loop)• HubSpot: In-memory buffer of 800, but still processes via process0pportunityßatch(xl8. 8 + Stefka Stoyanova2 + Galya Dimitrova& + Nikolay YankovQ + Anellya Angelova+ Mario Georgiev Q + Lukas KovaCancel|••)).meet google.01:27:27( Rev Prophet |( My PRS|• WorkC All Bookmarks+ CreateAsk Rovov DetailsFix versionsNoneSprintPlatform Sprint 3 Q2DaysNoneNeed QANoParentJY-15971 CRM Synching ImprovenCanny LinksOpen Canny Links• More fieldsOriginal estimateTime trackingNo time logged› Automation 4 Rule executions> featureOS Open featureOs> Sentry All Uinked Issues01:54:46Galya DimitrovaStefka Stoyanova3 othersNikotay NikolovLukas Kovalik4:29 PM | [Platform] Refinement •...
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Refinement 2026-04-20.mp4
Quickllme PlayenActivityMoreJiminny …..Dratts & centi8 DirectoriesEb External connections# Starred8 jiminny-x-integrati...& platform-inner-teamE Channels# ai-chapter# alertsS hackendi# confusion-clinic# curiosity_lab# engineering# frontend# general# infra-changes# jiminny-bg# platform-tickets# product launches# random# releases# support# thank-yous# the_people_of_jimi...• Direct messages• Vasil Vasilev.P. Nikolay Nikolov. Aneliya Angelova. Galya Dimitrovaa. Stefka StoyanovaR. Stoyan Tomov3 Aneliya Angelova, .Stovan TaneyP. Nikolay IvanovP. Vesi: AppsS Jira Cloud• ToastAl Reports > Empty page design and promotion - Search#rekShow results for: Al Reports > Empty page design and promotionEnterMessageShow results in this channel for: Al Reports > Empty page design and promotionProlelag:Calva Dimitrova Direct Mescace with Galva DimitrovalJY-20372 Al Reports > Empty page design and promotionApr 16th at 11:59 AMCirckDepl.v SelectGive feedbackProject: appWhen: 04/20/2026 14:12:24View JobTodavGitHub APP 9:32 AM3 new commits pushed to master by LakyLak922c5e7e - JY-20698 handle failed field sync on playbook import activity typesc6e14fbd - Merge branch 'master' into JY-20698-fix-SF-activity-types-on-new-Dlaybookb3760452 - Merge pull request #11988 from jiminny/JY-20698-fix-SF-activity-types-on-new-playbook)jimnwlapo Added by GithubCircleCl APP 9:56 AMDeployment Successful!Project: appWhen: 04/21/202606.56-27Tho.View Jobciitlinh App 10.20 AM3 new commits pushed to master by TodorStamatovJiminny3ba7bcf9 - JY-20708: update elastic search on new activity62aoc7dh - Merge branch 'master' into JY-20708-e ashicsearch-new-activitiedc153952e - Merge pull request #11992 from jiminny/JY-20708-elasticsearch-new-activitiesjiminny/app | Added by GitHubMessage #releases+ Аa822ravountesE jiminny(* AirDrop• Recents* Applications© Documentsii lukasiCloud• iCloud Drive992 Svnc toldeLocationsO DXP4800PLUS-B5F A® Network• CRM• Orange• Red• Yellow• PurpleO All Tags...Support Daily - in 4h 9mworkv N 2026= Daily 2026-04-21.mp4Da Retinelent 2026-04-20.mp4Daily 2026-04-20.mp4Daily 2026-04-17.mp4Fu Daily 2026-04-16.mp4F™ Pannina 2026-04-15.mo4Retro 2026-04-14.mp4• Daily 2026-04-14.mp4User pilot (Adi) 2026-04-09.mp4w Daily 2026-04-00 mnЛ• Daily 2026-04-07.mp4- Refinement 2026-04-06.mo4= Daily 2026-04-06.mp4- Daily 2026-04-03.mp4lax Plannina 2026-04-01 & task split.mp4M: Datra 2026.02-21 mn/- Refinement 2026-03-30.mp4na Daily 2026-02-30.mn/- Daily 2026-03-27.mp4Daily 2026-03-26.mp4• Dailv 2026-03-24,m04• Refinement 2026-03-23.mp4** BE chapter 2026-03-20.mp4= Daily 2026-02-20 mn4sm Planing 2026-03-18-converted.mp4- Refinement 2026-02-09-converted.mp4Rя Dailv 2026-03-19.mo4- Review 2026-03-18.mp4Planing 2026-03-18.mp4F Retro 2026-03-17m04= Daily 2026-02-17 mn/ment 2026-03-16.mp4- Dally 2026-03-16.mp4c Dailv 2026-03-13.mn4с 1-1 2026-03-12.mр4xa Dallv 2026-03-11.m04•: Daily 2026-02-10 mn/nent 2026-03-09.mp4• Daily 2026-03-09.mp4Fu Daily 2026-03-06.mn4a: Planning 2026-03-04.mp4Daily 2026-03-02.mp4* Dailv 2026-02-27 mo4eN Daily 2026.02.26 malDaily 2026-02-25.movlan Opportunity-Contacts 2026-02-24.mp4ma Daily 2026-02-24 mn/Refinement 2026-02-23.mov= Daily 2026-02-20 & Ani.mp4- Dailv 2026-02-19.mo4к Review 2026-02-18.mD4Date ModifiedTodau at 10:02Yesterday at 16.56Yesterdav at 10:0617 Apr 2026 at 10:1616 Apr 2026 at 10:0015 Aor 2026 at 11:1414 Apr 2026 at 17:3714 Apr 2026 at 10:099 Apr 2026 at 14:47QAnr 2026 at 10:078 Apr 2026 at 10:137 Apr 2026 at 10:016 Aor 2026 at 17:206 Apr 2026 at 10:083 Apr 2026 at 10:211 Aor 2026 at 12:2021 Mar 2026 at 19:2031 Mar 2026 at 10:1030 Mar 2026 at 17:1220 Mar 2026 at 10:0527 Mar 2026 at 10:0926 Mar 2026 at 9:5924 Mar 2026 at 10:0022 Mar 2026 at 17:0223 Mar 2026 at 10:0020 Mar 2026 at 11:4620 Mar 2026 at 10:0619 Mar 2026 at 12:0119 Mar 2026 at 11:3519 Mar 2026 at 9:5718 Mar 2026 at 16:2018 Mar 2026 at 11:1417 Mar 2026 at 17:4017 Mar 2026 at 10:1916 Mar 2026 at 16:5516 Mar 2026 at 10:0213 Mar 2026 at 10:1212 Mar 2026 at 18:3512 Mar 2026 at 10:1011 Mar 2026 at 10:0610 Mar 2026 at 0:579 Mar 2026 at 17:049 Mar 2026 at 9:566 Mar 2026 at 9:574 Mar 2026 at 11:0927 Feb 2026 at 10:0226 Eoh 2026 at 0:5225 Feb 2026 at 9:5924 Feb 2026 at 12:0324 Feh 2026 at 10:0223 Feb 2026 at 16:3119 Feb 2026 at 9:54O CAh GAG A+ 46.0GTue 21 Apr 10:51:31v Size-- Folder567,8 MB4,25 GBMPEG-4 movie698.5 MEMPEG-4 movie1,16 GBMPEG-4 movie513,4 MBMPEG-4 movie2.75 G:MPEG-4 movie1,44 GBMPEG-4 movie924,4 MB362.6 MBMPEG-4 movie719 8MR MDEG-A movid1,04 GBMPEG-4 movie575,5 MBMPEG-4 movie4.34 G:MPEG-4 movie720,5 MB MPEG-4 movie1,02 GB4.68 G:MPEG-4 movie3,4 GBMPEG-4 movie923,6 MBMPEG-4 movie2,77 GBMPEG-4 movie6418MPMPEG-A movid884,3 MBMPEG-4 movie476,6 MBMPEG-4 movie550.8 MEMPEG-4 movie3,44 GBMDEG.A movid438,9 MBMPEG-4 movie1,68 GBMPEG-4 movie120 A MPMDEG-A movie2,38 GBMPEG-4 movie2,26 GB386.3 MEMPEG-4 movie705,8 MBMPEG-4 movie2,78 GBMPEG-4 movie1,53 GBMPEG-4 movie12 GPMDEG-A movid4,19 GBMPEG-4 movie592,2 MB1.02 GEMPEG-4 movie637.6 MBMDEC.A movid978,7 MBMPEG-4 movie798,7 MBMPEG-4 movieAOA 6MPMDSG-A movie4,16 GBMPEG-4 movie319,7 MB291.7 MEMPEG.A movid2,62 GB MPEG-4 movie768,5 MB546.8 MBMPEG-4 movieO6 GMR OT movio503,5 MBQT movie791,7 MBMPEG-4 movieMPEG-A movie2 GB QT movie234 2 MBMPEG-4 movieOEAMP MОRA A MAVid1 of 144 selected, 2,03 TB available...
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Jy 20541 cleanup stale purged crm objects by Vasil Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app — Work...
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github.com/jiminny/app/pull/11879/changes#diff-33d github.com/jiminny/app/pull/11879/changes#diff-33db27024bef9d20cc4e1d8aea216a8ac5a37ea28bc1d07f1061629463c2db7f...
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JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {
return $this->purgeStaleRecord($crmObject);
}
$syncedObject->touch();
$this->logger->info('[StaleRecordValidator] Record synced successfully', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
]);
return $syncedObject;
} catch (HttpNotFoundException) {
return $this->purgeStaleRecord($crmObject);
} catch (Exception $e) {
$this->logger->error('[StaleRecordValidator] Failed to sync record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'error' => $e->getMessage(),
]);
return $crmObject;
}
}
private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null
{
$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmObject->getCrmProviderId(),
]);
$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));
return null;
}
}
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Jiminny\\Exceptions\\HttpNotFoundException; use Jiminny\\Models\\Account; use Jiminny\\Models\\Contact; use Jiminny\\Models\\Lead; use Jiminny\\Models\\Opportunity; use Psr\\Log\\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => 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{","depth":23,"bounds":{"left":0.14375,"top":0.57361114,"width":0.06914063,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return null;","depth":23,"bounds":{"left":0.14375,"top":0.6125,"width":0.049609374,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.14375,"top":0.6319444,"width":0.015234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (! $crmService) {","depth":23,"bounds":{"left":0.14375,"top":0.67083335,"width":0.065625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObjectCandidate;","depth":23,"bounds":{"left":0.14375,"top":0.69027776,"width":0.06484375,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.14375,"top":0.7291667,"width":0.015234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);","depth":23,"bounds":{"left":0.14375,"top":0.76805556,"width":0.0734375,"height":0.072916664},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {","depth":23,"bounds":{"left":0.14375,"top":0.84583336,"width":0.07382812,"height":0.09236111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return 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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {
return $this->purgeStaleRecord($crmObject);
}
$syncedObject->touch();
$this->logger->info('[StaleRecordValidator] Record synced successfully', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
]);
return $syncedObject;
} catch (HttpNotFoundException) {
return $this->purgeStaleRecord($crmObject);
} catch (Exception $e) {
$this->logger->error('[StaleRecordValidator] Failed to sync record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'error' => $e->getMessage(),
]);
return $crmObject;
}
}
private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null
{
$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmObject->getCrmProviderId(),
]);
$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));
return null;
}
}
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {
return $this->purgeStaleRecord($crmObject);
}
$syncedObject->touch();
$this->logger->info('[StaleRecordValidator] Record synced successfully', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
]);
return $syncedObject;
} catch (HttpNotFoundException) {
return $this->purgeStaleRecord($crmObject);
} catch (Exception $e) {
$this->logger->error('[StaleRecordValidator] Failed to sync record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'error' => $e->getMessage(),
]);
return $crmObject;
}
}
private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null
{
$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmObject->getCrmProviderId(),
]);
$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));
return null;
}
}
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use Jiminny\\Exceptions\\HttpNotFoundException; use Jiminny\\Models\\Account; use Jiminny\\Models\\Contact; use Jiminny\\Models\\Lead; use Jiminny\\Models\\Opportunity; use Psr\\Log\\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => 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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {
return $this->purgeStaleRecord($crmObject);
}
$syncedObject->touch();
$this->logger->info('[StaleRecordValidator] Record synced successfully', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
]);
return $syncedObject;
} catch (HttpNotFoundException) {
return $this->purgeStaleRecord($crmObject);
} catch (Exception $e) {
$this->logger->error('[StaleRecordValidator] Failed to sync record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'error' => $e->getMessage(),
]);
return $crmObject;
}
}
private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null
{
$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmObject->getCrmProviderId(),
]);
$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));
return null;
}
}
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Jy 20541 cleanup stale purged crm objects by Vasil Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app — Work...
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {
return $this->purgeStaleRecord($crmObject);
}
$syncedObject->touch();
$this->logger->info('[StaleRecordValidator] Record synced successfully', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
]);
return $syncedObject;
} catch (HttpNotFoundException) {
return $this->purgeStaleRecord($crmObject);
} catch (Exception $e) {
$this->logger->error('[StaleRecordValidator] Failed to sync record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'error' => $e->getMessage(),
]);
return $crmObject;
}
}
private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null
{
$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmObject->getCrmProviderId(),
]);
$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));
return null;
}
}
Expand...
|
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use Jiminny\\Exceptions\\HttpNotFoundException; use Jiminny\\Models\\Account; use Jiminny\\Models\\Contact; use Jiminny\\Models\\Lead; use Jiminny\\Models\\Opportunity; use Psr\\Log\\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exaplain <?php","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"declare(strict_types=1);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"namespace Jiminny\\Services\\Crm\\CrmObjects\\Validators;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Exception;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Carbon\\CarbonImmutable;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Illuminate\\Contracts\\Events\\Dispatcher;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Crm\\SyncableCrmObjectInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Services\\Crm\\SyncCrmEntitiesInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Events\\Crm\\RemoteCrmRecordDeleted;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Exceptions\\HttpNotFoundException;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Account;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Contact;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Lead;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Opportunity;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Psr\\Log\\LoggerInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/**","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Validate if a CRM record is stale.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* If a record hasn't been updated recently, we should test against the real CRM","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* to validate if this record still exists, or was deleted / purged.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*/","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"class 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null;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {
return $this->purgeStaleRecord($crmObject);
}
$syncedObject->touch();
$this->logger->info('[StaleRecordValidator] Record synced successfully', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
]);
return $syncedObject;
} catch (HttpNotFoundException) {
return $this->purgeStaleRecord($crmObject);
} catch (Exception $e) {
$this->logger->error('[StaleRecordValidator] Failed to sync record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'error' => $e->getMessage(),
]);
return $crmObject;
}
}
private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null
{
$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmObject->getCrmProviderId(),
]);
$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));
return null;
}
}
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Jy 20541 cleanup stale purged crm objects by Vasil Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app — Work...
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Platform Team - Backlog - Jira
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {
return $this->purgeStaleRecord($crmObject);
}
$syncedObject->touch();
$this->logger->info('[StaleRecordValidator] Record synced successfully', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
]);
return $syncedObject;
} catch (HttpNotFoundException) {
return $this->purgeStaleRecord($crmObject);
} catch (Exception $e) {
$this->logger->error('[StaleRecordValidator] Failed to sync record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'error' => $e->getMessage(),
]);
return $crmObject;
}
}
private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null
{
$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmObject->getCrmProviderId(),
]);
$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));
return null;
}
}
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button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"AI Chat settings","depth":7,"bounds":{"left":0.2171875,"top":0.047916666,"width":0.0125,"height":0.022222223},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close","depth":7,"bounds":{"left":0.23125,"top":0.047916666,"width":0.0125,"height":0.022222223},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"WORK, Google Account: lukas.kovalik@jiminny.com","depth":12,"bounds":{"left":0.228125,"top":0.090277776,"width":0.015625,"height":0.027777778},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Main menu","depth":12,"bounds":{"left":0.0984375,"top":0.090277776,"width":0.015625,"height":0.027777778},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"New Chat","depth":12,"bounds":{"left":0.1953125,"top":0.090277776,"width":0.015625,"height":0.027777778},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Open menu for conversation actions.","depth":12,"bounds":{"left":0.2109375,"top":0.090277776,"width":0.015625,"height":0.027777778},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Conversation with Gemini","depth":15,"bounds":{"left":0.09335937,"top":0.12847222,"width":0.000390625,"height":0.00069444446},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Conversation with Gemini","depth":16,"bounds":{"left":0.09335937,"top":0.13055556,"width":0.14101562,"height":0.022222223},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy prompt","depth":21,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Edit","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said Exaplain <?php declare(strict_types=1); namespace Jiminny\\Services\\Crm\\CrmObjects\\Validators; use Exception; use Carbon\\CarbonImmutable; use Illuminate\\Contracts\\Events\\Dispatcher; use Jiminny\\Contracts\\Crm\\SyncableCrmObjectInterface; use Jiminny\\Contracts\\Services\\Crm\\SyncCrmEntitiesInterface; use Jiminny\\Events\\Crm\\RemoteCrmRecordDeleted; use Jiminny\\Exceptions\\HttpNotFoundException; use Jiminny\\Models\\Account; use Jiminny\\Models\\Contact; use Jiminny\\Models\\Lead; use Jiminny\\Models\\Opportunity; use Psr\\Log\\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exaplain <?php","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"declare(strict_types=1);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"namespace Jiminny\\Services\\Crm\\CrmObjects\\Validators;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Exception;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Carbon\\CarbonImmutable;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Illuminate\\Contracts\\Events\\Dispatcher;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Crm\\SyncableCrmObjectInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Services\\Crm\\SyncCrmEntitiesInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Events\\Crm\\RemoteCrmRecordDeleted;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Exceptions\\HttpNotFoundException;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Account;","depth":23,"bounds":{"left":0.1609375,"top":0.0,"width":0.056640625,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Contact;","depth":23,"bounds":{"left":0.1609375,"top":0.0,"width":0.053515624,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Lead;","depth":23,"bounds":{"left":0.1609375,"top":0.04027778,"width":0.055859376,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Opportunity;","depth":23,"bounds":{"left":0.1609375,"top":0.09861111,"width":0.05390625,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Psr\\Log\\LoggerInterface;","depth":23,"bounds":{"left":0.1609375,"top":0.15694444,"width":0.0546875,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/**","depth":23,"bounds":{"left":0.1609375,"top":0.23472223,"width":0.0078125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Validate if a CRM record is stale.","depth":23,"bounds":{"left":0.1609375,"top":0.25416666,"width":0.05390625,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*","depth":23,"bounds":{"left":0.1609375,"top":0.29305556,"width":0.004296875,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* If a record hasn't been updated recently, we should test against the real CRM","depth":23,"bounds":{"left":0.1609375,"top":0.3125,"width":0.056640625,"height":0.09236111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* to validate if this record still exists, or was deleted / purged.","depth":23,"bounds":{"left":0.1609375,"top":0.4097222,"width":0.052734375,"height":0.072916664},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*/","depth":23,"bounds":{"left":0.1609375,"top":0.4875,"width":0.006640625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"class StaleRecordValidator","depth":23,"bounds":{"left":0.1609375,"top":0.5069444,"width":0.053515624,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"bounds":{"left":0.1609375,"top":0.56527776,"width":0.00234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/**","depth":23,"bounds":{"left":0.1609375,"top":0.5847222,"width":0.0140625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale","depth":23,"bounds":{"left":0.1609375,"top":0.6041667,"width":0.05390625,"height":0.11180556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*/","depth":23,"bounds":{"left":0.1609375,"top":0.72083336,"width":0.012890625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private const int STALE_THRESHOLD_DAYS = 120;","depth":23,"bounds":{"left":0.1609375,"top":0.74027777,"width":0.056640625,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"public function __construct(","depth":23,"bounds":{"left":0.1609375,"top":0.81805557,"width":0.048828125,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private readonly LoggerInterface $logger,","depth":23,"bounds":{"left":0.1609375,"top":0.85694444,"width":0.045703124,"height":0.072916664},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private readonly Dispatcher $dispatcher","depth":23,"bounds":{"left":0.1609375,"top":0.93472224,"width":0.033984374,"height":0.065277755},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") {","depth":23,"bounds":{"left":0.1609375,"top":1.0,"width":0.0125,"height":-0.012500048},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.1609375,"top":1.0,"width":0.00859375,"height":-0.031944394},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"public function filterStale(","depth":23,"bounds":{"left":0.1609375,"top":1.0,"width":0.048828125,"height":-0.070833325},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?SyncableCrmObjectInterface $crmObjectCandidate,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?SyncCrmEntitiesInterface $crmService","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"): ?SyncableCrmObjectInterface {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (! $crmObjectCandidate) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return null;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (! $crmService) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObjectCandidate;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObjectCandidate;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private function syncPotentiallyStaleObject(","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SyncableCrmObjectInterface $crmObject,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SyncCrmEntitiesInterface $crmService","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"): ?SyncableCrmObjectInterface {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmProviderId = $crmObject->getCrmProviderId();","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (empty($crmProviderId)) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'model' => get_class($crmObject),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'id' => $crmObject->getId(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObject;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"try {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'model' => get_class($crmObject),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'id' => $crmObject->getId(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'crm_provider_id' => $crmProviderId,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'updated_at' => $crmObject->getAttribute('updated_at'),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$syncedObject = match (true) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"};","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if ($syncedObject === null) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $this->purgeStaleRecord($crmObject);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$syncedObject->touch();","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$this->logger->info('[StaleRecordValidator] Record synced successfully', [","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'model' => get_class($crmObject),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'id' => $crmObject->getId(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'crm_provider_id' => $crmProviderId,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $syncedObject;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"} catch (HttpNotFoundException) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $this->purgeStaleRecord($crmObject);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"} catch (Exception $e) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$this->logger->error('[StaleRecordValidator] Failed to sync record', [","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'model' => get_class($crmObject),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'id' => $crmObject->getId(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'crm_provider_id' => $crmProviderId,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'error' => $e->getMessage(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObject;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'model' => get_class($crmObject),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'id' => $crmObject->getId(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'crm_provider_id' => $crmObject->getCrmProviderId(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return null;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":22,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {
return $this->purgeStaleRecord($crmObject);
}
$syncedObject->touch();
$this->logger->info('[StaleRecordValidator] Record synced successfully', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
]);
return $syncedObject;
} catch (HttpNotFoundException) {
return $this->purgeStaleRecord($crmObject);
} catch (Exception $e) {
$this->logger->error('[StaleRecordValidator] Failed to sync record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'error' => $e->getMessage(),
]);
return $crmObject;
}
}
private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null
{
$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmObject->getCrmProviderId(),
]);
$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));
return null;
}
}
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),...
|
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Jiminny\\Contracts\\Crm\\SyncableCrmObjectInterface; use Jiminny\\Contracts\\Services\\Crm\\SyncCrmEntitiesInterface; use Jiminny\\Events\\Crm\\RemoteCrmRecordDeleted; use Jiminny\\Exceptions\\HttpNotFoundException; use Jiminny\\Models\\Account; use Jiminny\\Models\\Contact; use Jiminny\\Models\\Lead; use Jiminny\\Models\\Opportunity; use Psr\\Log\\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exaplain <?php","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"declare(strict_types=1);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"namespace Jiminny\\Services\\Crm\\CrmObjects\\Validators;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Exception;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Carbon\\CarbonImmutable;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Illuminate\\Contracts\\Events\\Dispatcher;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Crm\\SyncableCrmObjectInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Services\\Crm\\SyncCrmEntitiesInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Events\\Crm\\RemoteCrmRecordDeleted;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Exceptions\\HttpNotFoundException;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Account;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Contact;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Lead;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Opportunity;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Psr\\Log\\LoggerInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/**","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Validate if a CRM record is stale.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* If a record hasn't been updated recently, we should test against the real CRM","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* to validate if this record still exists, or was deleted / purged.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*/","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"class StaleRecordValidator","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/**","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*/","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private const int STALE_THRESHOLD_DAYS = 120;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"public function __construct(","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private readonly LoggerInterface $logger,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private readonly Dispatcher $dispatcher","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"public function filterStale(","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?SyncableCrmObjectInterface $crmObjectCandidate,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?SyncCrmEntitiesInterface $crmService","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"): ?SyncableCrmObjectInterface {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (! $crmObjectCandidate) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return null;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (! $crmService) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObjectCandidate;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObjectCandidate;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private function syncPotentiallyStaleObject(","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SyncableCrmObjectInterface $crmObject,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SyncCrmEntitiesInterface $crmService","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"): ?SyncableCrmObjectInterface {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmProviderId = $crmObject->getCrmProviderId();","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (empty($crmProviderId)) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'model' => get_class($crmObject),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'id' => $crmObject->getId(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObject;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"try {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'model' => get_class($crmObject),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'id' => $crmObject->getId(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'crm_provider_id' => $crmProviderId,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'updated_at' => $crmObject->getAttribute('updated_at'),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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8798980973368525420
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click
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accessibility
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),...
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/Users/lukas/.screenpipe/data/data/2026-04-16/1776 /Users/lukas/.screenpipe/data/data/2026-04-16/1776321697471_m2.jpg...
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Firefox
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app/app/Services/Crm/ProspectCache.php at e93e7b74 app/app/Services/Crm/ProspectCache.php at e93e7b7433974694bbc9876b07a0cd5d9cc25c07 · jiminny/app — Work...
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github.com/jiminny/app/blob/e93e7b7433974694bbc987 github.com/jiminny/app/blob/e93e7b7433974694bbc9876b07a0cd5d9cc25c07/app/Services/Crm/ProspectCache.php...
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JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
Jiminny
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app/app/Services/Crm/ProspectCache.php at e93e7b7433974694bbc9876b07a0cd5d9cc25c07 · jiminny/app
app/app/Services/Crm/ProspectCache.php at e93e7b7433974694bbc9876b07a0cd5d9cc25c07 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {
return $this->purgeStaleRecord($crmObject);
}
$syncedObject->touch();
$this->logger->info('[StaleRecordValidator] Record synced successfully', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
]);
return $syncedObject;
} catch (HttpNotFoundException) {
return $this->purgeStaleRecord($crmObject);
} catch (Exception $e) {
$this->logger->error('[StaleRecordValidator] Failed to sync record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'error' => $e->getMessage(),
]);
return $crmObject;
}
}
private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null
{
$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmObject->getCrmProviderId(),
]);
$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));
return null;
}
}
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Jiminny\\Exceptions\\HttpNotFoundException; use Jiminny\\Models\\Account; use Jiminny\\Models\\Contact; use Jiminny\\Models\\Lead; use Jiminny\\Models\\Opportunity; use Psr\\Log\\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => 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$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exaplain <?php","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"declare(strict_types=1);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"namespace Jiminny\\Services\\Crm\\CrmObjects\\Validators;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Exception;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Carbon\\CarbonImmutable;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Illuminate\\Contracts\\Events\\Dispatcher;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Crm\\SyncableCrmObjectInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Services\\Crm\\SyncCrmEntitiesInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Events\\Crm\\RemoteCrmRecordDeleted;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Exceptions\\HttpNotFoundException;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Account;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Contact;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Lead;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Opportunity;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Psr\\Log\\LoggerInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/**","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Validate if a CRM record is 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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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app/app/Services/Crm/ProspectCache.php at e93e7b7433974694bbc9876b07a0cd5d9cc25c07 · jiminny/app
app/app/Services/Crm/ProspectCache.php at e93e7b7433974694bbc9876b07a0cd5d9cc25c07 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {
return $this->purgeStaleRecord($crmObject);
}
$syncedObject->touch();
$this->logger->info('[StaleRecordValidator] Record synced successfully', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
]);
return $syncedObject;
} catch (HttpNotFoundException) {
return $this->purgeStaleRecord($crmObject);
} catch (Exception $e) {
$this->logger->error('[StaleRecordValidator] Failed to sync record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'error' => $e->getMessage(),
]);
return $crmObject;
}
}
private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null
{
$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmObject->getCrmProviderId(),
]);
$this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject));
return null;
}
}
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Jy 20541 cleanup stale purged crm objects by Vasil Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app — Work...
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}...
|
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Jiminny\\Exceptions\\HttpNotFoundException; use Jiminny\\Models\\Account; use Jiminny\\Models\\Contact; use Jiminny\\Models\\Lead; use Jiminny\\Models\\Opportunity; use Psr\\Log\\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => 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$this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exaplain <?php","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"declare(strict_types=1);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"namespace Jiminny\\Services\\Crm\\CrmObjects\\Validators;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Exception;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Carbon\\CarbonImmutable;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Illuminate\\Contracts\\Events\\Dispatcher;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Crm\\SyncableCrmObjectInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Services\\Crm\\SyncCrmEntitiesInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Events\\Crm\\RemoteCrmRecordDeleted;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Exceptions\\HttpNotFoundException;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Account;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Contact;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Lead;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Opportunity;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Psr\\Log\\LoggerInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/**","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Validate if a CRM record is stale.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* If a record hasn't been updated recently, we should test against the real CRM","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* to validate if this record still exists, or was deleted / purged.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*/","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"class 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stale","depth":23,"bounds":{"left":0.14375,"top":0.0,"width":0.07265625,"height":0.072916664},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*/","depth":23,"bounds":{"left":0.14375,"top":0.068055555,"width":0.012890625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private const int STALE_THRESHOLD_DAYS = 120;","depth":23,"bounds":{"left":0.14375,"top":0.0875,"width":0.07070313,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"public function __construct(","depth":23,"bounds":{"left":0.14375,"top":0.16527778,"width":0.048828125,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private readonly LoggerInterface $logger,","depth":23,"bounds":{"left":0.14375,"top":0.20416667,"width":0.07070313,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private readonly Dispatcher $dispatcher","depth":23,"bounds":{"left":0.14375,"top":0.24305555,"width":0.06679688,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") {","depth":23,"bounds":{"left":0.14375,"top":0.28194445,"width":0.0125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.14375,"top":0.3013889,"width":0.00859375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"public function filterStale(","depth":23,"bounds":{"left":0.14375,"top":0.3402778,"width":0.048828125,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?SyncableCrmObjectInterface $crmObjectCandidate,","depth":23,"bounds":{"left":0.14375,"top":0.37916666,"width":0.072265625,"height":0.072916664},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?SyncCrmEntitiesInterface $crmService","depth":23,"bounds":{"left":0.14375,"top":0.45694444,"width":0.072265625,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"): ?SyncableCrmObjectInterface {","depth":23,"bounds":{"left":0.14375,"top":0.5152778,"width":0.072265625,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (! $crmObjectCandidate) {","depth":23,"bounds":{"left":0.14375,"top":0.57361114,"width":0.06914063,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return null;","depth":23,"bounds":{"left":0.14375,"top":0.6125,"width":0.049609374,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.14375,"top":0.6319444,"width":0.015234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (! $crmService) {","depth":23,"bounds":{"left":0.14375,"top":0.67083335,"width":0.065625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObjectCandidate;","depth":23,"bounds":{"left":0.14375,"top":0.69027776,"width":0.06484375,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.14375,"top":0.7291667,"width":0.015234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);","depth":23,"bounds":{"left":0.14375,"top":0.76805556,"width":0.0734375,"height":0.072916664},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {","depth":23,"bounds":{"left":0.14375,"top":0.84583336,"width":0.07382812,"height":0.09236111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObjectCandidate;","depth":23,"bounds":{"left":0.14375,"top":0.94305557,"width":0.06484375,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.14375,"top":0.98194444,"width":0.015234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);","depth":23,"bounds":{"left":0.14375,"top":1.0,"width":0.0734375,"height":-0.020833373},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.14375,"top":1.0,"width":0.00859375,"height":-0.09861112},"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}...
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Jy 20541 cleanup stale purged crm objects by Vasil Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app — Work...
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github.com/jiminny/app/pull/11879/changes#diff-735 github.com/jiminny/app/pull/11879/changes#diff-73569194b1c17e5c3f07beaeed832015d6bef3503e89b32a959ea44b2a24a034...
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {...
|
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Jiminny\\Contracts\\Crm\\SyncableCrmObjectInterface; use Jiminny\\Contracts\\Services\\Crm\\SyncCrmEntitiesInterface; use Jiminny\\Events\\Crm\\RemoteCrmRecordDeleted; use Jiminny\\Exceptions\\HttpNotFoundException; use Jiminny\\Models\\Account; use Jiminny\\Models\\Contact; use Jiminny\\Models\\Lead; use Jiminny\\Models\\Opportunity; use Psr\\Log\\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exaplain <?php","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"declare(strict_types=1);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"namespace Jiminny\\Services\\Crm\\CrmObjects\\Validators;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Exception;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Carbon\\CarbonImmutable;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Illuminate\\Contracts\\Events\\Dispatcher;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Crm\\SyncableCrmObjectInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Contracts\\Services\\Crm\\SyncCrmEntitiesInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Events\\Crm\\RemoteCrmRecordDeleted;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Exceptions\\HttpNotFoundException;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Account;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Contact;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Lead;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Jiminny\\Models\\Opportunity;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"use Psr\\Log\\LoggerInterface;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/**","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Validate if a CRM record is stale.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* If a record hasn't been updated recently, we should test against the real CRM","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* to validate if this record still exists, or was deleted / purged.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*/","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"class StaleRecordValidator","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/**","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*/","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private const int STALE_THRESHOLD_DAYS = 120;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"public function __construct(","depth":23,"bounds":{"left":0.1609375,"top":0.0,"width":0.048828125,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private readonly LoggerInterface $logger,","depth":23,"bounds":{"left":0.1609375,"top":0.0,"width":0.045703124,"height":0.072916664},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private readonly Dispatcher $dispatcher","depth":23,"bounds":{"left":0.1609375,"top":0.02638889,"width":0.033984374,"height":0.072916664},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") {","depth":23,"bounds":{"left":0.1609375,"top":0.104166664,"width":0.0125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.1609375,"top":0.12361111,"width":0.00859375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"public function filterStale(","depth":23,"bounds":{"left":0.1609375,"top":0.1625,"width":0.048828125,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?SyncableCrmObjectInterface $crmObjectCandidate,","depth":23,"bounds":{"left":0.1609375,"top":0.2013889,"width":0.0546875,"height":0.09236111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?SyncCrmEntitiesInterface $crmService","depth":23,"bounds":{"left":0.1609375,"top":0.2986111,"width":0.055859376,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"): ?SyncableCrmObjectInterface {","depth":23,"bounds":{"left":0.1609375,"top":0.35694444,"width":0.0546875,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (! $crmObjectCandidate) {","depth":23,"bounds":{"left":0.1609375,"top":0.41527778,"width":0.05390625,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return null;","depth":23,"bounds":{"left":0.1609375,"top":0.47361112,"width":0.049609374,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.1609375,"top":0.49305555,"width":0.015234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (! $crmService) {","depth":23,"bounds":{"left":0.1609375,"top":0.53194445,"width":0.0421875,"height":0.034027778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObjectCandidate;","depth":23,"bounds":{"left":0.1609375,"top":0.5708333,"width":0.05390625,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.1609375,"top":0.62916666,"width":0.015234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);","depth":23,"bounds":{"left":0.1609375,"top":0.66805553,"width":0.05625,"height":0.13125},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {","depth":23,"bounds":{"left":0.1609375,"top":0.8041667,"width":0.05546875,"height":0.11180556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObjectCandidate;","depth":23,"bounds":{"left":0.1609375,"top":0.92083335,"width":0.05390625,"height":0.05347222},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"bounds":{"left":0.1609375,"top":0.9791667,"width":0.015234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);","depth":23,"bounds":{"left":0.1609375,"top":1.0,"width":0.056640625,"height":-0.018055558},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private function syncPotentiallyStaleObject(","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SyncableCrmObjectInterface $crmObject,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SyncCrmEntitiesInterface $crmService","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"): ?SyncableCrmObjectInterface {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmProviderId = $crmObject->getCrmProviderId();","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if (empty($crmProviderId)) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'model' => get_class($crmObject),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'id' => $crmObject->getId(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return $crmObject;","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"try {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'model' => get_class($crmObject),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'id' => $crmObject->getId(),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'crm_provider_id' => $crmProviderId,","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'updated_at' => $crmObject->getAttribute('updated_at'),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]);","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$syncedObject = match (true) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"};","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"if ($syncedObject === null) {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
Jy 20541 cleanup stale purged crm objects by Vasil-Jiminny · Pull Request #11879 · jiminny/app
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You said Exaplain <?php declare(strict_types=1); namespace Jiminny\Services\Crm\CrmObjects\Validators; use Exception; use Carbon\CarbonImmutable; use Illuminate\Contracts\Events\Dispatcher; use Jiminny\Contracts\Crm\SyncableCrmObjectInterface; use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface; use Jiminny\Events\Crm\RemoteCrmRecordDeleted; use Jiminny\Exceptions\HttpNotFoundException; use Jiminny\Models\Account; use Jiminny\Models\Contact; use Jiminny\Models\Lead; use Jiminny\Models\Opportunity; use Psr\Log\LoggerInterface; /** * Validate if a CRM record is stale. * * If a record hasn't been updated recently, we should test against the real CRM * to validate if this record still exists, or was deleted / purged. */ class StaleRecordValidator { /** * If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale */ private const int STALE_THRESHOLD_DAYS = 120; public function __construct( private readonly LoggerInterface $logger, private readonly Dispatcher $dispatcher ) { } public function filterStale( ?SyncableCrmObjectInterface $crmObjectCandidate, ?SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { if (! $crmObjectCandidate) { return null; } if (! $crmService) { return $crmObjectCandidate; } $thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS); if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) { return $crmObjectCandidate; } return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService); } private function syncPotentiallyStaleObject( SyncableCrmObjectInterface $crmObject, SyncCrmEntitiesInterface $crmService ): ?SyncableCrmObjectInterface { $crmProviderId = $crmObject->getCrmProviderId(); if (empty($crmProviderId)) { $this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), ]); return $crmObject; } try { $this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'updated_at' => $crmObject->getAttribute('updated_at'), ]); $syncedObject = match (true) { $crmObject instanceof Lead => $crmService->syncLead($crmProviderId), $crmObject instanceof Account => $crmService->syncAccount($crmProviderId), $crmObject instanceof Contact => $crmService->syncContact($crmProviderId), $crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId), }; if ($syncedObject === null) { return $this->purgeStaleRecord($crmObject); } $syncedObject->touch(); $this->logger->info('[StaleRecordValidator] Record synced successfully', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, ]); return $syncedObject; } catch (HttpNotFoundException) { return $this->purgeStaleRecord($crmObject); } catch (Exception $e) { $this->logger->error('[StaleRecordValidator] Failed to sync record', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmProviderId, 'error' => $e->getMessage(), ]); return $crmObject; } } private function purgeStaleRecord(SyncableCrmObjectInterface $crmObject): null { $this->logger->info('[StaleRecordValidator] Record not found in remote CRM', [ 'model' => get_class($crmObject), 'id' => $crmObject->getId(), 'crm_provider_id' => $crmObject->getCrmProviderId(), ]); $this->dispatcher->dispatch(new RemoteCrmRecordDeleted($crmObject)); return null; } }
You said
Exaplain <?php
declare(strict_types=1);
namespace Jiminny\Services\Crm\CrmObjects\Validators;
use Exception;
use Carbon\CarbonImmutable;
use Illuminate\Contracts\Events\Dispatcher;
use Jiminny\Contracts\Crm\SyncableCrmObjectInterface;
use Jiminny\Contracts\Services\Crm\SyncCrmEntitiesInterface;
use Jiminny\Events\Crm\RemoteCrmRecordDeleted;
use Jiminny\Exceptions\HttpNotFoundException;
use Jiminny\Models\Account;
use Jiminny\Models\Contact;
use Jiminny\Models\Lead;
use Jiminny\Models\Opportunity;
use Psr\Log\LoggerInterface;
/**
* Validate if a CRM record is stale.
*
* If a record hasn't been updated recently, we should test against the real CRM
* to validate if this record still exists, or was deleted / purged.
*/
class StaleRecordValidator
{
/**
* If a CRM entity hasn't been updated in more than 120 days, the object may be potentially stale
*/
private const int STALE_THRESHOLD_DAYS = 120;
public function __construct(
private readonly LoggerInterface $logger,
private readonly Dispatcher $dispatcher
) {
}
public function filterStale(
?SyncableCrmObjectInterface $crmObjectCandidate,
?SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
if (! $crmObjectCandidate) {
return null;
}
if (! $crmService) {
return $crmObjectCandidate;
}
$thresholdDate = CarbonImmutable::now()->subDays(self::STALE_THRESHOLD_DAYS);
if ($thresholdDate->isBefore($crmObjectCandidate->getAttribute('updated_at'))) {
return $crmObjectCandidate;
}
return $this->syncPotentiallyStaleObject($crmObjectCandidate, $crmService);
}
private function syncPotentiallyStaleObject(
SyncableCrmObjectInterface $crmObject,
SyncCrmEntitiesInterface $crmService
): ?SyncableCrmObjectInterface {
$crmProviderId = $crmObject->getCrmProviderId();
if (empty($crmProviderId)) {
$this->logger->warning('[StaleRecordValidator] CRM object has empty crm_provider_id', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
]);
return $crmObject;
}
try {
$this->logger->info('[StaleRecordValidator] Syncing potentially stale record', [
'model' => get_class($crmObject),
'id' => $crmObject->getId(),
'crm_provider_id' => $crmProviderId,
'updated_at' => $crmObject->getAttribute('updated_at'),
]);
$syncedObject = match (true) {
$crmObject instanceof Lead => $crmService->syncLead($crmProviderId),
$crmObject instanceof Account => $crmService->syncAccount($crmProviderId),
$crmObject instanceof Contact => $crmService->syncContact($crmProviderId),
$crmObject instanceof Opportunity => $crmService->syncOpportunity($crmProviderId),
};
if ($syncedObject === null) {...
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/Users/lukas/.screenpipe/data/data/2026-04-15/1776 /Users/lukas/.screenpipe/data/data/2026-04-15/1776243781385_m2.jpg...
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JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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User Pilot introduction Adi 2026-04-23.mp4
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User Pilot introduction Adi 2026-04-23.mp4...
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User Pilot introduction Adi 2026-04-23.mp4
QuickTime PlayerFileEditViewWindowHelpAdelina Petrova (Presenting, annotating)# Userpilot Introducti... 29 m left• User Pilot introduction Adi 2026-04-23.mp4 ~100% <47Thu 23 Apr 12:01:5318+ Al DashboardsPeople8 Usersl colpanies© SegmentsQ Search Engugement, Feedback, Reports, Users And MorePop out thiнаи 21. 2028Ner 22, 2038Nо 22.3070Adelina PetrovaMihail Mihaylov& DashboardFeedtackAрr 0O6, 2020Ape 13, 2026Mar 21, 2026E PlaylistsMar 30, 2026Apr 06, 2026Aрe 13, 202813 othersStefka StoyanovaVн 30 2261Ner 08, 2028Ase 12, 2026Мa 23, 2026Мar 30,2020Aor 06, 2028""))06:44»Her 13, 202827:3327m 33s724 MBLukas Kovalik11:37 AM Userpilot Introduction...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
[SRD-6787] Issue with reconnecting Zoho - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Pipelines - jiminny/app
Feed — jiminny — Sentry
Sandbox: Verify your identity in Salesforce - [EMAIL] - Jiminny Mail
Jiminny x Shiji - Reconnecting the platform
Jiminny x Shiji - Reconnecting the platform
For you - Confluence
For you - Confluence
Lukas Kovalik - Time Off
Lukas Kovalik - Time Off
Product Growth Platform | Userpilot
Product Growth Platform | Userpilot
Userpilot
Userpilot
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
[SRD-6787] Issue with reconnecting Zoho - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Pipelines - jiminny/app
Feed — jiminny — Sentry
Sandbox: Verify your identity in Salesforce - [EMAIL] - Jiminny Mail
Jiminny x Shiji - Reconnecting the platform
Jiminny x Shiji - Reconnecting the platform
For you - Confluence
For you - Confluence
Lukas Kovalik - Time Off
Lukas Kovalik - Time Off
Product Growth Platform | Userpilot
Product Growth Platform | Userpilot
Userpilot
Userpilot
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
fix(security): composer dependency updates – 2026-04-15 by github-actions[bot] · Pull Request #11970 · jiminny/app
Jiminny
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© 2026 Salesforce, Inc. All rights reserved....
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Last login: Sat Apr 11 12:38:35 on ttys007
Poetry Last login: Sat Apr 11 12:38:35 on ttys007
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Merge branch 'JY-18909-automated-reports-ask-jiminny' of github.com:jiminny/app into JY-18909-automated-reports-ask-jiminny
# Please enter a commit message to explain why this merge is necessary,
# especially if it merges an updated upstream into a topic branch.
#
# Lines starting with '#' will be ignored, and an empty message aborts
# the commit.
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"~/jiminny/app/.git/MERGE_MSG" 6L, 350B
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APP (vi)...
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Last login: Sat Apr 11 12:38:35 on ttys007
Poetry Last login: Sat Apr 11 12:38:35 on ttys007
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Merge branch 'JY-18909-automated-reports-ask-jiminny' of github.com:jiminny/app into JY-18909-automated-reports-ask-jiminny
# Please enter a commit message to explain why this merge is necessary,
# especially if it merges an updated upstream into a topic branch.
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"~/jiminny/app/.git/MERGE_MSG" 6L, 350B
DOCKER
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DEV (docker)
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APP (vi)
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ec2-user@ip-10-30-93-249:~ (nc)
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✳ Unable to access screenpipe activity data (claude)
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APP (vi)...
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/Users/lukas/.screenpipe/data/data/2026-04-17/1776 /Users/lukas/.screenpipe/data/data/2026-04-17/1776424993369_m2.jpg...
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Jiminny · Membrane
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Configure SSH access to multiple environment - Engineering - Confluence
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fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
[JY-20692] Issue with reconnecting Zoho - Jira
[JY-20692] Issue with reconnecting Zoho - Jira
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fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
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[JY-20692] Issue with reconnecting Zoho - Jira
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DEL","depth":15,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Delete connector file","depth":17,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"DEL","depth":16,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Delete connector directory DEL","depth":15,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
[JY-20692] Issue with reconnecting Zoho - Jira
[JY-20692] Issue with reconnecting Zoho - Jira
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Connections Show subpages for Connections
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PUT
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POST
Get connection logs GET
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Get connection dependencies GET
Get connection dependencies
GET
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Export connection
GET
Restore connection POST
Restore connection
POST
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Archive connection
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Connectors Hide subpages for Connectors
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Connector Types Hide subpages for Connector Types
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List connectors GET
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Get connector GET
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Create connector POST
Create connector
POST
Patch connector PATCH
Patch connector
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Delete connector DEL
Delete connector
DEL
Download connector GET
Download connector
GET
Upload connector POST
Upload connector
POST
Import connector POST
Import connector
POST
Clone connector POST
Clone connector
POST
Get connector versions GET
Get connector versions
GET
Publish connector version POST
Publish connector version
POST
Update connector completely PUT
Update connector completely
PUT
Get a list of connector files GET
Get a list of connector files
GET
Get connector file by path GET
Get connector file by path
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Update connector file PUT
Update connector file
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Delete connector file DEL
Delete connector file
DEL
Delete connector directory DEL...
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2026-04-16T12:49:35.198701+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-16/1776 /Users/lukas/.screenpipe/data/data/2026-04-16/1776343775198_m1.jpg...
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Last login: Thu Apr 16 15:48:10 on ttys008
Poetry Last login: Thu Apr 16 15:48:10 on ttys008
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $ sqlite3 ~/.screenpipe/db.sqlite "SELECT app_name, window_name FROM ocr_text WHERE app_name LIKE '%Safari%' OR window_name LIKE '%Boosteroid%' ORDER BY created_at DESC LIMIT 20;"
Error: in prepare, no such column: created_at
ari%' OR window_name LIKE '%Boosteroid%' ORDER BY created_at DESC LIMIT 20;
error here ---^
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $ sp-start
[1] 10835
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-04-16T15:49:34.042032Z INFO screenpipe_engine::cli: api auth enabled — key loaded
checking permissions...
screen recording: ok
accessibility: ok
2026-04-16T15:49:34.112749Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-04-16T15:49:34.594897Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-04-16T15:49:34.596610Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-04-16T15:49:34.596593Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-04-16T15:49:34.596791Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-04-16T15:49:34.596806Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-04-16T15:49:34.596807Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-04-16T15:49:34.596885Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-04-16T15:49:34.596870Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-04-16T15:49:34.597351Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-04-16T15:49:34.606273Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))
2026-04-16T15:49:34.618378Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-04-16T15:49:34.618584Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-04-16T15:49:34.619192Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-04-16T15:49:34.619360Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-04-16T15:49:34.619514Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-04-16T15:49:34.620079Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-04-16T15:49:34.620094Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
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power AI by everything you've seen, said or heard
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ true │
│ 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 │
2026-04-16T15:49:34.621492Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
2026-04-16T15:49:34.624911Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh
│ encrypt secrets │ disabled │
│ retention days │ 14 │
├────────────────────────┼────────────────────────────────────┤
│ languages │ │
│ │ all languages │
├────────────────────────┼────────────────────────────────────┤
│ monitors │ │
│ │ id: 1 │
│ │ id: 2 │
├────────────────────────┼────────────────────────────────────┤
│ audio devices │ │
│ │ disabled │
└────────────────────────┴────────────────────────────────────┘
you are using local processing. all your data stays on your computer.
warning: telemetry is enabled. only error-level data will be sent.
to disable, use the --disable-telemetry flag.
check latest changes here: https://github.com/screenpipe/screenpipe/releases
2026-04-16T15:49:34.635508Z INFO screenpipe: starting UI event capture
2026-04-16T15:49:34.650182Z INFO screenpipe_engine::ui_recorder: Starting UI event capture
2026-04-16T15:49:34.664835Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)
2026-04-16T15:49:34.664920Z INFO screenpipe_engine::ui_recorder: UI recording session started: 9b7c5415-eda0-4db6-9d45-49e7670207bb
2026-04-16T15:49:34.665040Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-04-15 12:49:34.665038 UTC to 2026-04-16 12:49:34.665038 UTC)
2026-04-16T15:49:34.665532Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)
2026-04-16T15:49:34.671502Z INFO screenpipe_engine::server: Server listening on [IP_ADDRESS]:3030
2026-04-16T15:49:34.675785Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030
2026-04-16T15:49:34.697836Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)
2026-04-16T15:49:34.697951Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)
2026-04-16T15:49:34.698000Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)
2026-04-16T15:49:34.738391Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (2560x1440)
2026-04-16T15:49:34.738421Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)
2026-04-16T15:49:34.738434Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (polling every 5 seconds)
2026-04-16T15:49:34.738437Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)
2026-04-16T15:49:35.348337Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
DOCKER
Close Tab
DEV (-zsh)
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APP (-zsh)
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-zsh
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⌥⌘1
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|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Thu Apr 16 15:48:10 on ttys008\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $ sqlite3 ~/.screenpipe/db.sqlite \"SELECT app_name, window_name FROM ocr_text WHERE app_name LIKE '%Safari%' OR window_name LIKE '%Boosteroid%' ORDER BY created_at DESC LIMIT 20;\"\nError: in prepare, no such column: created_at\n ari%' OR window_name LIKE '%Boosteroid%' ORDER BY created_at DESC LIMIT 20;\n error here ---^\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $ sp-start\n[1] 10835\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-04-16T15:49:34.042032Z INFO screenpipe_engine::cli: api auth enabled — key loaded\nchecking permissions...\n screen recording: ok\n accessibility: ok\n2026-04-16T15:49:34.112749Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-04-16T15:49:34.594897Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-04-16T15:49:34.596610Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-04-16T15:49:34.596593Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-04-16T15:49:34.596791Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-04-16T15:49:34.596806Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-04-16T15:49:34.596807Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-04-16T15:49:34.596885Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-04-16T15:49:34.596870Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-04-16T15:49:34.597351Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-04-16T15:49:34.606273Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-04-16T15:49:34.618378Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-04-16T15:49:34.618584Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-04-16T15:49:34.619192Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-04-16T15:49:34.619360Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-04-16T15:49:34.619514Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-04-16T15:49:34.620079Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-04-16T15:49:34.620094Z 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\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 │ true │\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 │\n2026-04-16T15:49:34.621492Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n2026-04-16T15:49:34.624911Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ disabled │\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\n2026-04-16T15:49:34.635508Z INFO screenpipe: starting UI event capture\n2026-04-16T15:49:34.650182Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-04-16T15:49:34.664835Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-04-16T15:49:34.664920Z INFO screenpipe_engine::ui_recorder: UI recording session started: 9b7c5415-eda0-4db6-9d45-49e7670207bb\n2026-04-16T15:49:34.665040Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-04-15 12:49:34.665038 UTC to 2026-04-16 12:49:34.665038 UTC)\n2026-04-16T15:49:34.665532Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-04-16T15:49:34.671502Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-04-16T15:49:34.675785Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-04-16T15:49:34.697836Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-04-16T15:49:34.697951Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-04-16T15:49:34.698000Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-04-16T15:49:34.738391Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (2560x1440)\n2026-04-16T15:49:34.738421Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-04-16T15:49:34.738434Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (polling every 5 seconds)\n2026-04-16T15:49:34.738437Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-04-16T15:49:35.348337Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)","depth":4,"value":"Last login: Thu Apr 16 15:48:10 on ttys008\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $ sqlite3 ~/.screenpipe/db.sqlite \"SELECT app_name, window_name FROM ocr_text WHERE app_name LIKE '%Safari%' OR window_name LIKE '%Boosteroid%' ORDER BY created_at DESC LIMIT 20;\"\nError: in prepare, no such column: created_at\n ari%' OR window_name LIKE '%Boosteroid%' ORDER BY created_at DESC LIMIT 20;\n error here ---^\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $ sp-start\n[1] 10835\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-04-16T15:49:34.042032Z INFO screenpipe_engine::cli: api auth enabled — key loaded\nchecking permissions...\n screen recording: ok\n accessibility: ok\n2026-04-16T15:49:34.112749Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-04-16T15:49:34.594897Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-04-16T15:49:34.596610Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-04-16T15:49:34.596593Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-04-16T15:49:34.596791Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-04-16T15:49:34.596806Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-04-16T15:49:34.596807Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-04-16T15:49:34.596885Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-04-16T15:49:34.596870Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-04-16T15:49:34.597351Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-04-16T15:49:34.606273Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-04-16T15:49:34.618378Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-04-16T15:49:34.618584Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-04-16T15:49:34.619192Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-04-16T15:49:34.619360Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-04-16T15:49:34.619514Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-04-16T15:49:34.620079Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-04-16T15:49:34.620094Z 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\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 │ true │\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 │\n2026-04-16T15:49:34.621492Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n2026-04-16T15:49:34.624911Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ disabled │\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\n2026-04-16T15:49:34.635508Z INFO screenpipe: starting UI event capture\n2026-04-16T15:49:34.650182Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-04-16T15:49:34.664835Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-04-16T15:49:34.664920Z INFO screenpipe_engine::ui_recorder: UI recording session started: 9b7c5415-eda0-4db6-9d45-49e7670207bb\n2026-04-16T15:49:34.665040Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-04-15 12:49:34.665038 UTC to 2026-04-16 12:49:34.665038 UTC)\n2026-04-16T15:49:34.665532Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-04-16T15:49:34.671502Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-04-16T15:49:34.675785Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-04-16T15:49:34.697836Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-04-16T15:49:34.697951Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-04-16T15:49:34.698000Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-04-16T15:49:34.738391Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (2560x1440)\n2026-04-16T15:49:34.738421Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-04-16T15:49:34.738434Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (polling every 5 seconds)\n2026-04-16T15:49:34.738437Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-04-16T15:49:35.348337Z 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":0.20069444,"height":0.026666667},"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},"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.20069444,"top":0.05888889,"width":0.20034721,"height":0.026666667},"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":0.2048611,"top":0.06333333,"width":0.011111111,"height":0.017777778},"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.40104166,"top":0.05888889,"width":0.20034721,"height":0.026666667},"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":0.40520832,"top":0.06333333,"width":0.011111111,"height":0.017777778},"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.6013889,"top":0.05888889,"width":0.20034721,"height":0.026666667},"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":0.60555553,"top":0.06333333,"width":0.011111111,"height":0.017777778},"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.8017361,"top":0.05888889,"width":0.19826388,"height":0.026666667},"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":0.8059028,"top":0.06333333,"width":0.011111111,"height":0.017777778},"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.9736111,"top":0.032222223,"width":0.026388884,"height":0.018888889},"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"-zsh","depth":1,"bounds":{"left":0.49791667,"top":0.033333335,"width":0.022916667,"height":0.017777778},"role_description":"text"}]...
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8846152518528864609
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8770504107326362693
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manual
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accessibility
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NULL
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Last login: Thu Apr 16 15:48:10 on ttys008
Poetry Last login: Thu Apr 16 15:48:10 on ttys008
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $ sqlite3 ~/.screenpipe/db.sqlite "SELECT app_name, window_name FROM ocr_text WHERE app_name LIKE '%Safari%' OR window_name LIKE '%Boosteroid%' ORDER BY created_at DESC LIMIT 20;"
Error: in prepare, no such column: created_at
ari%' OR window_name LIKE '%Boosteroid%' ORDER BY created_at DESC LIMIT 20;
error here ---^
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $ sp-start
[1] 10835
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-04-16T15:49:34.042032Z INFO screenpipe_engine::cli: api auth enabled — key loaded
checking permissions...
screen recording: ok
accessibility: ok
2026-04-16T15:49:34.112749Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-04-16T15:49:34.594897Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-04-16T15:49:34.596610Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-04-16T15:49:34.596593Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-04-16T15:49:34.596791Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-04-16T15:49:34.596806Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-04-16T15:49:34.596807Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-04-16T15:49:34.596885Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-04-16T15:49:34.596870Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-04-16T15:49:34.597351Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-04-16T15:49:34.606273Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))
2026-04-16T15:49:34.618378Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-04-16T15:49:34.618584Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-04-16T15:49:34.619192Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-04-16T15:49:34.619360Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-04-16T15:49:34.619514Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-04-16T15:49:34.620079Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-04-16T15:49:34.620094Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ true │
│ 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 │
2026-04-16T15:49:34.621492Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
2026-04-16T15:49:34.624911Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh
│ encrypt secrets │ disabled │
│ retention days │ 14 │
├────────────────────────┼────────────────────────────────────┤
│ languages │ │
│ │ all languages │
├────────────────────────┼────────────────────────────────────┤
│ monitors │ │
│ │ id: 1 │
│ │ id: 2 │
├────────────────────────┼────────────────────────────────────┤
│ audio devices │ │
│ │ disabled │
└────────────────────────┴────────────────────────────────────┘
you are using local processing. all your data stays on your computer.
warning: telemetry is enabled. only error-level data will be sent.
to disable, use the --disable-telemetry flag.
check latest changes here: https://github.com/screenpipe/screenpipe/releases
2026-04-16T15:49:34.635508Z INFO screenpipe: starting UI event capture
2026-04-16T15:49:34.650182Z INFO screenpipe_engine::ui_recorder: Starting UI event capture
2026-04-16T15:49:34.664835Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)
2026-04-16T15:49:34.664920Z INFO screenpipe_engine::ui_recorder: UI recording session started: 9b7c5415-eda0-4db6-9d45-49e7670207bb
2026-04-16T15:49:34.665040Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-04-15 12:49:34.665038 UTC to 2026-04-16 12:49:34.665038 UTC)
2026-04-16T15:49:34.665532Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)
2026-04-16T15:49:34.671502Z INFO screenpipe_engine::server: Server listening on [IP_ADDRESS]:3030
2026-04-16T15:49:34.675785Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030
2026-04-16T15:49:34.697836Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)
2026-04-16T15:49:34.697951Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)
2026-04-16T15:49:34.698000Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)
2026-04-16T15:49:34.738391Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (2560x1440)
2026-04-16T15:49:34.738421Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)
2026-04-16T15:49:34.738434Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (polling every 5 seconds)
2026-04-16T15:49:34.738437Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)
2026-04-16T15:49:35.348337Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
DOCKER
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iTerm2ShellEditViewSessionScriptsProfilesWindowHelp• 0.laln]• Tech Day Review - in 10 mA•DOCKERAPP (-zsh)- 881DEV (docker)APP (-zsh)|../raw_sql_query.sql../tests/Unit/Policies/CanAccessAiReportsTest.phpX3-zshX4-zsh• ₴5* Review screenp...• ₴6ec2-user@ip-10-...• ₴7no changes added tocommit(use "git add" and/or "git commit -a")lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app/front-end (master)$ git pullremote: Enumerating objects: 15,done.remote: Counting objects: 100% (15/15), done.remote: Compressing objects: 100% (15/15), done.remote: Total 15 (delta 5), reused 0 (delta 0),pack-reused 0 (from 0)Unpacking objects: 100% (15/15), 12.86 KiB | 731.00 KiB/s, done.From github.com:jiminny/appc04e334173..eb5bb80e5bmaster-> origin/master08ed383c5b..da535e5554JY-18909-automated-reports-ask-jiminny• -> origin/JY-18909-automated-reports-ask-jiminny4b59984896..a8959a0497JY-20695-handle-no-raw-transcript-> origin/JY-20695-handle-no-raw-transcriptUpdating 5bb8fefcba..eb5bb80e5bFast-forwardapp/Component/Activity/ActivityProcessingStateManager.php+++++++app/Component/Activity/ActivityProcessingStateRepository.phpapp/Component/Datadog/Constants.phpapp/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.phpdatabase/migrations/2026_04_16_141800_move_ai_call_scoring_to_scale_tier.phptests/Unit/Component/Activity/ActivityProcessingStateManagerTest.php1 2591 +116 +t+++++++++-8674+++++++6 files changed, 205 insertions(+), 6 deletions(-)create mode 100644 database/migrations/2026_04_16_141800_move_ai_call_scoring_to_scale_tier.phplukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app/front-end (master) $co -b JY-20698-fix-SF-activity-types-on-new-playbookSwitched to a new branch 'JY-20698-fix-SF-activity-types-on-new-playbook'lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app/front-end (JY-20698-fix-SF-activity-types-on-new-playbook) $ csfixmake: *** No rule to make target'cs-fix'.Stop.lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app/front-end (JY-20698-fix-SF-activity-types-on-new-playbook) $ cd ..lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20698-fix-SF-activity-types-on-new-playbook) $ csfixdocker exec -it docker_lamp_1./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diffPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminskiandcontributors.PHP runtime: 8.3.30Running analysis on 7 cores with 10 files per process.Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!Loadedconfig default from ".php-cs-fixer.dist.php".5596/5596 [8831 100%+[PASSWORD_DOTS]++++++++++++++++++++-100% <78Fri 17 Apr 16:50:311₴81ec2-user@ip-10-...O ₴8APPFixed 0 of 5596 files in 49.418 seconds, 67.00 MB memory usedWhat's next:Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1Learn more at https://docs.docker.com/go/debug-cli/lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20698-fix-SF-activity-types-on-new-playbook) $ U...
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PhostormcodeProiect v(c) Field.onp© Fie Force Push
PhostormcodeProiect v(c) Field.onp© FieldRepository.phpD Audio© AskJiminnyReportActivityService.php• AutomatedReports• kecuestGenerateaskJiminnykkequestGeneratekeporJoo.orAskJiminnyReporiscontroller.php©)ActivityActualDate.ong© SendReportJob.phpc) senckeponmallJob.ong0 CalendarC) AutomatedReportsCommand.php(c) AutomatedReportsRepository.php(C) AutomatedReportsService.phob ermC) CreateHeldActivityEvent.phpC) TrackProviderInstalledEvent.phpC) CreateActivityLoqgedEvent.phpC) UserPilotActivitvListener.ohv© ActivityLogged.php(C)AutomatedReportsCallbackService.ohvC) ReauestGenerateAsk.JiminnvReport.Job.ohv X (C) AutomatedReportResult.ohv© AutomatedReport.phpclass RequestGenerateAskJiminnyReportJob implements ShouldQueue, ShouldBeUniquepublic function handle(l TreamTelenhonv'status' => AutomatedReportResult::STATUS_DEFAULT,Use'media_type' => AutomatedReportsService::MEDIA_TYPE_PDF,© BaseProcessingJob.phpC) Dummv.lob.oho© ImportRecallAlRecordingsJob.php© ImportRemoteTrackJob.phpG Job.php© JobDispatcher.phpSactivityIds = $activityService->getActivityIdsForSavedSearch(savedsearch. ssavedsearch,user. screacor© JobDispatcherInterface.phpfrequency: $automatedReport->qetFrequencyOl© PurgeSoftDeletedOpportunityJob 101SqsVisibilityControl.phpLocal chancesSheliConsoleLO0XChanges 12 files, updating.Side-by-side viewerDo not ignoreHighlight words"E.env.local app© ActivityController.php app/Http/Controllers/API© AskJiminnyReportActivityService.php app/Services/Kiosk/AutomatedReports© AskJiminnyReportActivitvServiceTest.php tests/Unit/Services/Kiosk/Automatedi®a72e71cc app/Jobs/Au© AutomatedReportsService.php app/Services/Kiosk/AutomatedReports$activityIds = $activityService->getActivityIdsForSavedSearchCsavedSearch: SsavedSearch.© AutomatedReportsServiceTest.php tests/Unit/Services/Kiosk/AutomatedReportsusen: Screator)© JiminnyDebugCommand.php app/Console/Commandsphp loaaina.php confic€ PlavbackService.phv app/Services$logger->info(self::LOG_PREFIX . ' Fetched activity IDs', [C) Requestcenerateask.iminnvRevoroo,ono aoo/oos AutomatedReoortsilautomatedPenontlluad' =s Cthic-snenontllusidi@ SvncTolntercom.ohp app/.Jobs/Teamphp web.oho routedUnversioned Files 8 files= env.nikilocal aooE.env.other appc CanAccossAiRenortstlest.nhn tests/Unit/Policies(C) CreateMockAsk.liminnvRenortRecultCommand.nhnann/Console/Commands/ReE ids tyt and"2 raw sal querv sal anniC) SimulateWehhooksCommand.nhnann/Console/Commands/Crm/HubsnotMLWERHOOK FIL TERING IMPI EMENTATION md and= custom.log=laravel.log4 SF [jiminny@localhost] XA HS_local (jiminny@localhost]& console [PKol)A console [EU]A console [STAGING]11421144159155Tx: Autovdojiminny vB10 BI2 XLY4AANSERI INO activity search tultersiC'activity_search_idactivity search. id 1977.( activity_search_id 1978,filter "aroup id'.activity search id 1979value") VALUES443f2608-8512-437e-a9f9-7e75f8025c22'0.•443f26b8-8512-437e-a9f9-7e75f8025c22')443f2608-8512-437e-a9f9-7e75f8025c22').select * from crm_configurations where id = 39;Duch Commits to appselece x tholl cedlllsselect * from team fsK- minny • olcil sclo orzauonhercoors-aska llmllalayselect x tron teacon update & include activity tiltenv D 5 filesSELECT * FROM activiSELECT * FROM activiv aoo 3 tilesv M Jobs/AutomatedReports 1 fileSELECT * FROM autoSELECT * FROM automa(C) RequestGenerateAskJiminnvReport.Job.ohov O Services/Kiosk/AutomatedReports 2 files(C) AskJiminnvReportActivitvService.onv© AutomatedRenortsService.ohnSELElI * rrum aurom.SELECT * FROM automacolont & Gnom ontiudvMtests/Unit/Services/Kiosk/AutomatedRenorts 2 files© AskJiminnyReportActivityServiceTest.php(c) AutomatedRenortsServiceTlest.oho100% LMon 20 Apr 12:38:31RequestGenerateAskJimCascadeGroup Photo UrL RevRetactor UserPilot TraFixing Expiration Date+O •Fix alse the tests for this changeThe test uses 2099-01-01 which is clearly more than 1 year away — that still works fine after the fix. The fix only changes theboundary case (same anniversary day, different time). No existing tests break.However, there's a missing test: the boundary case where expires on is exactly 1 year from today with a time componentlater in the day (the scenario that was broken). Let me check if the testValidateAskJiminnyReportDataExpiresTooFar test isThe existing tests are fine — 2099-01-01 still fails correctly. What's missing is a test proving that a date exactly 1 year fromnow (with a late time component is accepted, not rejected. Let me look at the end of the test tile to tind where to append:eporisservicelest.pho #4100-4142let me check the imoorts at the too to see what carbon alias is used.AutomatedReportsServiceTest.oho #L1-30AutomatedReportsServiceTest.phpView alls/Unit/Services/Kiosk/AutomatedRenorts/M AutomatedRenortcServiceTest.nhv +55Reiect alllAccent allianvthina (84-D1• CoddS Adaptive1 differenceMitvldsForSavedSearchdv For Commit and Push to non-protected branches, preview commits before pushlencv Ou^ Push taasiCancolPustodactivity Thct'automatedReportUuid' => $this->reportUuid.Po 4 spaces...
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iTerm2ShellEditViewSessionScriptsProfil Force Push
iTerm2ShellEditViewSessionScriptsProfilesWindowHelpAPP (-zsh)883‹$0screenpipe*DOCKERO 81DEV (docker)882raw_sql_query.sqltests/Unit/Policies/CanAccessAiReportsTest.phpAPP (-zsh)-zsh• 84no changes added to commit (use "gitadd"and/or "git commit -a")lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $ git pullremote: Enumerating objects: 49,done.remote: Counting objects:100% (49/49),done.remote: Compressing objects: 100% (16/16),done.remote: Total 49 (delta 33), reused 49 (delta 33), pack-reused 0 (from 0)reused o (from 0)Unpacking objects: 100% (49/49), 9.18 KiB | 284.00 KiB/s, done.From github.com:jiminny/app1d10796eec..fec25f3343JY-20701-reschedule-HubSpot-processing -› origin/JY-20701-reschedule-HubSpot-processingAlready up to date.lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $ csfixdocker exec-it docker_lamp_1./vendor/bin/php-cs-fixer fix--config=.php-cs-fixer.dist.php -v --using-cache=no --diffPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.PHPruntime:8.3.30Running analysis on 7 cores with 10 files perprocess.Parallelrunner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!Loadedconfig default from-php-cs-fixer.dist.php".5603/5603100%+++@@1) app/Http/Controllers/API/V2/AskJiminnyReportsController.php (single_quote)begin diff/home.iminny/app/Http/Controllers/API/V2/AskJiminnyReportsController.php/home/jiminny/app/Http/Controllers/AP1/V2/AskJiminnyReportsController.php-89,7 +89,7 00*/public function update(Request Srequest, string Suuid): JsonResponse\Illuminate\Support\Facades\Log::channel('custom_channel')->info("UPDATE");(Illuminate|Support\Facades\Log::channel('custom_channel')->info('UPDATE');/** @var User Suser */Suser = Srequest->user();О ₴85100% C47 8 Mon 20 Apr 12:38:31T₴1-zsh₴6APPend diffFixed 1 of 5603 files in 42.363 seconds, 60.00 MB memory usedWhat's next:Try Docker Debug for seamless, persistent debugging tools in any container or image » docker debug docker_1amp_1Learn more at https://docs.docker.com/go/debug-cli/lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-18909-automated-reports-ask-jiminny) $D...
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Jiminny · Membrane
console.getmembrane.com
Workers Jiminny · Membrane
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Workers | Datadog
Developers | HubSpot
Developers | HubSpot
Inbox (1,576) - [EMAIL] - Jiminny Mail
Inbox (1,576) - [EMAIL] - Jiminny Mail
120216 is your HubSpot Log In Code - [EMAIL] - Jiminny Mail
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Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
[JY-20692] Issue with reconnecting Zoho - Jira
[JY-20692] Issue with reconnecting Zoho - Jira
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Configure SSH access to multiple environment - Engineering - Confluence
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fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
[JY-20692] Issue with reconnecting Zoho - Jira
[JY-20692] Issue with reconnecting Zoho - Jira
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fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
[JY-20692] Issue with reconnecting Zoho - Jira
[JY-20692] Issue with reconnecting Zoho - Jira
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fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
[JY-20692] Issue with reconnecting Zoho - Jira
[JY-20692] Issue with reconnecting Zoho - Jira
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fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
[JY-20692] Issue with reconnecting Zoho - Jira
[JY-20692] Issue with reconnecting Zoho - Jira
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Configure SSH access to multiple environment - Engineering - Confluence
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fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
fix-cache-for-business-processes by ilian-jiminny · Pull Request #11985 · jiminny/app
[JY-20692] Issue with reconnecting Zoho - Jira
[JY-20692] Issue with reconnecting Zoho - Jira
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2026-04-16T13:59:53.748294+00:00
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8735654862450359688
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visual_change
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accessibility
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NULL
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Search
Lukas Kovalik, Apple ID
1
1
Wi‑Fi
Bluetooth Search
Lukas Kovalik, Apple ID
1
1
Wi‑Fi
Bluetooth
Network
VPN
Notifications
Sound
Focus
Screen Time
General
Appearance
Accessibility
Control Centre
Siri & Spotlight
Privacy & Security
Desktop & Dock
Displays
Wallpaper
Screen Saver
Battery
Lock Screen
Touch ID & Password
Users & Groups
Passwords
Internet Accounts
Game Center
Wallet & Apple Pay
Keyboard
Mouse
Trackpad
Printers & Scanners
Privacy
Location Services
Contacts
Calendars
Reminders
Photos
Bluetooth
Microphone
Camera
Motion & Fitness
HomeKit
Speech Recognition
Media & Apple Music
Files and Folders
Full Disk Access
Focus
Accessibility
Input Monitoring
Remote Desktop
Screen & System Audio Recording
Passkeys Access for Web Browsers
Automation
App Management
Developer Tools
Sensitive Content Warning, Off
Analytics & Improvements
Apple Advertising
Security
Allow applications downloaded from
App Store
App Store and identified developers
Warning This setting has been configured by a profile.
Allow accessories to connect
FileVault, On
Lockdown Mode, Off
Others
Extensions
Profiles
Advanced…
Help
Privacy & Security...
|
NULL
|
|
39713
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808
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11
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2026-04-16T14:03:35.512435+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-16/1776 /Users/lukas/.screenpipe/data/data/2026-04-16/1776348215512_m1.jpg...
|
System Settings
|
Privacy & Security
|
1
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NULL
|
monitor_1
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NULL
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NULL
|
NULL
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NULL
|
Search
Lukas Kovalik, Apple ID
1
1
Wi‑Fi
Bluetooth Search
Lukas Kovalik, Apple ID
1
1
Wi‑Fi
Bluetooth
Network
VPN
Notifications
Sound
Focus
Screen Time
General
Appearance
Accessibility
Control Centre
Siri & Spotlight
Privacy & Security
Desktop & Dock
Displays
Wallpaper
Screen Saver
Battery
Lock Screen
Touch ID & Password
Users & Groups
Passwords
Internet Accounts
Game Center
Wallet & Apple Pay
Keyboard
Mouse
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Privacy
Location Services
Contacts
Calendars
Reminders
Photos
Bluetooth
Microphone
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Motion & Fitness
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Speech Recognition
Media & Apple Music
Files and Folders
Full Disk Access
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Remote Desktop
Screen & System Audio Recording
Passkeys Access for Web Browsers
Automation
App Management
Developer Tools
Sensitive Content Warning, Off
Analytics & Improvements
Apple Advertising
Security
Allow applications downloaded from
App Store
App Store and identified developers
Warning This setting has been configured by a profile.
Allow accessories to connect
FileVault, On
Lockdown Mode, Off
Others
Extensions
Profiles
Advanced…
Help
Privacy & Security...
|
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8735654862450359688
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click
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accessibility
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NULL
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Search
Lukas Kovalik, Apple ID
1
1
Wi‑Fi
Bluetooth Search
Lukas Kovalik, Apple ID
1
1
Wi‑Fi
Bluetooth
Network
VPN
Notifications
Sound
Focus
Screen Time
General
Appearance
Accessibility
Control Centre
Siri & Spotlight
Privacy & Security
Desktop & Dock
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Battery
Lock Screen
Touch ID & Password
Users & Groups
Passwords
Internet Accounts
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Mouse
Trackpad
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Location Services
Contacts
Calendars
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM...
|
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19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":22,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"Gemini said","depth":20,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This Python script defines the","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AiActivityTypeEvaluator","depth":25,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Core Functionality","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Core Functionality","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Data Collection (","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"collect_test_set","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"):","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Supports fetching raw samples from","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Elasticsearch (ES)","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or loading them from","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"local JSON files","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Implements a","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"replayability check","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": It probes the live API endpoint to ensure the activity exists before including it in the dataset.","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Filters data based on request body size, language, and the presence of an original response.","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ground Truth Management:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Saves inputs and \"gold standard\" responses to a local directory structure (","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"eval_output/ai_activity_type/...","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":").","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Features an optional mode to populate ground truth using a high-order LLM (e.g.,","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gpt-5_2","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") if the","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POPULATE_GROUND_TRUTH_LLM","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM...
|
8622
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
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Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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are there soem issues with this PR
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Gemini said
Gemini said
Yes, there are several issues and code smells in this Pull Request, ranging from performance bottlenecks to architectural anti-patterns.
Here is a breakdown of the most notable issues, categorized by impact:
Performance & Async Anti-Patterns
Performance & Async Anti-Patterns
Sequential Requests Defeating Async (Lines 86-106):
Inside
_collect_from_es
, the code loops through
raw_samples
and
await
s a
session.post
request for each sample one by one. This means the script waits for one HTTP request to finish before starting the next, completely defeating the purpose of using
aiohttp
for asynchronous concurrency.
Fix:
Collect these coroutines into a list and use
asyncio.gather()
(ideally wrapped in an
asyncio.Semaphore
to avoid overwhelming the endpoint) to run the replayability probes concurrently.
Blocking File I/O in Async Functions (Lines 110-114, 184-188, 268-269):
Standard synchronous file operations (
with open(...)
,
json.dump
,
json.load
) are used inside
async def
functions. In Python, this blocks the entire event loop while the disk is reading/writing.
Fix:
Use an asynchronous file I/O library like
aiofiles
, or run the blocking I/O operations in a separate thread using
asyncio.to_thread()
.
Architecture & State Management
Architecture & State Management
Mutating Class-Level Variables (Lines 323-328):
The script parses CLI arguments and directly mutates the class attributes (e.g.,
AiActivityTypeEvaluator.DATA_SET = args.data_set
). This is a major anti-pattern. If you ever try to run tests in parallel or create multiple instances of this evaluator in a single process, the state will bleed across them.
Fix:
Pass these arguments into the
__init__
constructor of the instance (
self.data_set = args.data_set
) rather than modifying the class definition globally.
Code Quality & Edge Cases
Code Quality & Edge Cases
Broad Exception Catching (Line 107):
Using a bare
except Exception:
during the replayability probe is dangerous. It will catch
aiohttp.ClientError
(which is intended), but it will also silently swallow
TimeoutError
or even memory errors, making debugging incredibly difficult if the endpoint goes down.
Fix:
Scope the exception to specific expected errors, like
except (aiohttp.ClientError, asyncio.TimeoutError):
.
Inefficient Size Calculation (Line 95):
len(json.dumps(request_body)) < min_size
requires serializing the entire dictionary to a string
just
to check its length. Since
min_size
defaults to
0
, the
if min_size
short-circuit saves it for now, but if anyone sets a minimum size, this will become an unnecessary CPU bottleneck on large datasets.
Potential Path Traversal Risk (Lines 110, 113, 251):
The script writes and reads files directly using
f"{es_id}.json"
and
f"gt_{req_id}.json"
. If
es_id
or
req_id
originate from a database and ever contain characters like
../
, it could result in files being read from or written to unintended directories.
Fix:
Sanitize the IDs or strictly enforce that they only contain alphanumeric characters.
Would you like me to rewrite the
_collect_from_es
method to show how to fix the sequential async loop and blocking file I/O?
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“<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":22,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"Gemini said","depth":20,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This Python script defines the","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AiActivityTypeEvaluator","depth":25,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Core Functionality","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Core Functionality","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Data Collection (","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"collect_test_set","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"):","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Supports fetching raw samples from","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Elasticsearch (ES)","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or loading them from","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"local JSON files","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Implements a","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"replayability check","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": It probes the live API endpoint to ensure the activity exists before including it in the dataset.","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Filters data based on request body size, language, and the presence of an original response.","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ground Truth Management:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Saves inputs and \"gold standard\" responses to a local directory structure (","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"eval_output/ai_activity_type/...","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":").","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Features an optional mode to populate ground truth using a high-order LLM (e.g.,","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gpt-5_2","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") if 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8732321575042068887
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
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Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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You said are there soem issues with this PR
You said
are there soem issues with this PR
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Gemini said
Gemini said
Yes, there are several issues and code smells in this Pull Request, ranging from performance bottlenecks to architectural anti-patterns.
Here is a breakdown of the most notable issues, categorized by impact:
Performance & Async Anti-Patterns
Performance & Async Anti-Patterns
Sequential Requests Defeating Async (Lines 86-106):
Inside
_collect_from_es
, the code loops through
raw_samples
and
await
s a
session.post
request for each sample one by one. This means the script waits for one HTTP request to finish before starting the next, completely defeating the purpose of using
aiohttp
for asynchronous concurrency.
Fix:
Collect these coroutines into a list and use
asyncio.gather()
(ideally wrapped in an
asyncio.Semaphore
to avoid overwhelming the endpoint) to run the replayability probes concurrently.
Blocking File I/O in Async Functions (Lines 110-114, 184-188, 268-269):
Standard synchronous file operations (
with open(...)
,
json.dump
,
json.load
) are used inside
async def
functions. In Python, this blocks the entire event loop while the disk is reading/writing.
Fix:
Use an asynchronous file I/O library like
aiofiles
, or run the blocking I/O operations in a separate thread using
asyncio.to_thread()
.
Architecture & State Management
Architecture & State Management
Mutating Class-Level Variables (Lines 323-328):
The script parses CLI arguments and directly mutates the class attributes (e.g.,
AiActivityTypeEvaluator.DATA_SET = args.data_set
). This is a major anti-pattern. If you ever try to run tests in parallel or create multiple instances of this evaluator in a single process, the state will bleed across them.
Fix:
Pass these arguments into the
__init__
constructor of the instance (
self.data_set = args.data_set
) rather than modifying the class definition globally.
Code Quality & Edge Cases
Code Quality & Edge Cases
Broad Exception Catching (Line 107):
Using a bare
except Exception:
during the replayability probe is dangerous. It will catch
aiohttp.ClientError
(which is intended), but it will also silently swallow
TimeoutError
or even memory errors, making debugging incredibly difficult if the endpoint goes down.
Fix:
Scope the exception to specific expected errors, like
except (aiohttp.ClientError, asyncio.TimeoutError):
.
Inefficient Size Calculation (Line 95):
len(json.dumps(request_body)) < min_size
requires serializing the entire dictionary to a string
just
to check its length. Since
min_size
defaults to
0
, the
if min_size
short-circuit saves it for now, but if anyone sets a minimum size, this will become an unnecessary CPU bottleneck on large datasets.
Potential Path Traversal Risk (Lines 110, 113, 251):
The script writes and reads files directly using
f"{es_id}.json"
and
f"gt_{req_id}.json"
. If
es_id
or
req_id
originate from a database and ever contain characters like
../
, it could result in files being read from or written to unintended directories.
Fix:
Sanitize the IDs or strictly enforce that they only contain alphanumeric characters.
Would you like me to rewrite the
_collect_from_es
method to show how to fix the sequential async loop and blocking file I/O?
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
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Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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are there soem issues with this PR
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Gemini said
Gemini said
Yes, there are several issues and code smells in this Pull Request, ranging from performance bottlenecks to architectural anti-patterns.
Here is a breakdown of the most notable issues, categorized by impact:
Performance & Async Anti-Patterns
Performance & Async Anti-Patterns
Sequential Requests Defeating Async (Lines 86-106):
Inside
_collect_from_es
, the code loops through
raw_samples
and
await
s a
session.post
request for each sample one by one. This means the script waits for one HTTP request to finish before starting the next, completely defeating the purpose of using
aiohttp
for asynchronous concurrency.
Fix:
Collect these coroutines into a list and use
asyncio.gather()
(ideally wrapped in an
asyncio.Semaphore
to avoid overwhelming the endpoint) to run the replayability probes concurrently.
Blocking File I/O in Async Functions (Lines 110-114, 184-188, 268-269):
Standard synchronous file operations (
with open(...)
,
json.dump
,
json.load
) are used inside
async def
functions. In Python, this blocks the entire event loop while the disk is reading/writing.
Fix:
Use an asynchronous file I/O library like
aiofiles
, or run the blocking I/O operations in a separate thread using
asyncio.to_thread()
.
Architecture & State Management
Architecture & State Management
Mutating Class-Level Variables (Lines 323-328):
The script parses CLI arguments and directly mutates the class attributes (e.g.,
AiActivityTypeEvaluator.DATA_SET = args.data_set
). This is a major anti-pattern. If you ever try to run tests in parallel or create multiple instances of this evaluator in a single process, the state will bleed across them.
Fix:
Pass these arguments into the
__init__
constructor of the instance (
self.data_set = args.data_set
) rather than modifying the class definition globally.
Code Quality & Edge Cases
Code Quality & Edge Cases
Broad Exception Catching (Line 107):
Using a bare
except Exception:
during the replayability probe is dangerous. It will catch
aiohttp.ClientError
(which is intended), but it will also silently swallow
TimeoutError
or even memory errors, making debugging incredibly difficult if the endpoint goes down.
Fix:
Scope the exception to specific expected errors, like
except (aiohttp.ClientError, asyncio.TimeoutError):
.
Inefficient Size Calculation (Line 95):
len(json.dumps(request_body)) < min_size
requires serializing the entire dictionary to a string
just
to check its length. Since
min_size
defaults to
0
, the
if min_size
short-circuit saves it for now, but if anyone sets a minimum size, this will become an unnecessary CPU bottleneck on large datasets.
Potential Path Traversal Risk (Lines 110, 113, 251):
The script writes and reads files directly using
f"{es_id}.json"
and
f"gt_{req_id}.json"
. If
es_id
or
req_id
originate from a database and ever contain characters like
../
, it could result in files being read from or written to unintended directories.
Fix:
Sanitize the IDs or strictly enforce that they only contain alphanumeric characters....
|
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Gemini","depth":15,"bounds":{"left":0.09335937,"top":0.14791666,"width":0.000390625,"height":0.00069444446},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Conversation with Gemini","depth":16,"bounds":{"left":0.09335937,"top":0.15,"width":0.14101562,"height":0.022222223},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy prompt","depth":21,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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(ES)","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or loading them from","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"local JSON files","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Implements a","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"replayability check","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": It probes the live API endpoint to ensure the activity exists before including it in the dataset.","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Filters data based on request body size, language, and the presence of an 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phases.","depth":26,"bounds":{"left":0.1171875,"top":0.18402778,"width":0.11289062,"height":0.06875},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy prompt","depth":21,"bounds":{"left":0.1203125,"top":0.3013889,"width":0.015625,"height":0.027777778},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Edit","depth":21,"bounds":{"left":0.1375,"top":0.3013889,"width":0.015625,"height":0.027777778},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said are there soem issues with this PR","depth":21,"bounds":{"left":0.1609375,"top":0.30972221,"width":0.072265625,"height":0.03888889},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You 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86-106):","depth":26,"bounds":{"left":0.11757813,"top":0.5659722,"width":0.11601563,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Inside","depth":26,"bounds":{"left":0.16289063,"top":0.58402777,"width":0.019921875,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"_collect_from_es","depth":27,"bounds":{"left":0.11992188,"top":0.60347223,"width":0.05234375,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", the code loops 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a","depth":26,"bounds":{"left":0.21757813,"top":0.6201389,"width":0.009765625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"session.post","depth":27,"bounds":{"left":0.11992188,"top":0.63958335,"width":0.039453126,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"request for each sample one by one. This means the script waits for one HTTP request to finish before starting the next, completely defeating the purpose of using","depth":26,"bounds":{"left":0.11757813,"top":0.63819444,"width":0.11640625,"height":0.08680555},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aiohttp","depth":27,"bounds":{"left":0.18046875,"top":0.7118056,"width":0.023046875,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"for asynchronous concurrency.","depth":26,"bounds":{"left":0.11757813,"top":0.7104167,"width":0.09921875,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Fix:","depth":28,"bounds":{"left":0.1296875,"top":0.75208336,"width":0.009765625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Collect these coroutines into a list and use","depth":28,"bounds":{"left":0.1296875,"top":0.75208336,"width":0.09921875,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"asyncio.gather()","depth":29,"bounds":{"left":0.16601562,"top":0.77152777,"width":0.05234375,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(ideally wrapped in an","depth":28,"bounds":{"left":0.1296875,"top":0.77013886,"width":0.09257813,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"asyncio.Semaphore","depth":29,"bounds":{"left":0.13203125,"top":0.8076389,"width":0.055859376,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to avoid overwhelming the endpoint) to run the replayability probes concurrently.","depth":28,"bounds":{"left":0.1296875,"top":0.80625,"width":0.10546875,"height":0.050694443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Blocking File I/O in Async Functions (Lines 110-114, 184-188, 268-269):","depth":26,"bounds":{"left":0.11757813,"top":0.8659722,"width":0.10976563,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Standard synchronous file operations (","depth":26,"bounds":{"left":0.11757813,"top":0.8840278,"width":0.107421875,"height":0.050694443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"with open(...)","depth":27,"bounds":{"left":0.12226562,"top":0.9215278,"width":0.045703124,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":0.1703125,"top":0.9201389,"width":0.003515625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json.dump","depth":27,"bounds":{"left":0.17617187,"top":0.9215278,"width":0.029296875,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":0.2078125,"top":0.9201389,"width":0.003125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json.load","depth":27,"bounds":{"left":0.11992188,"top":0.93958336,"width":0.0296875,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") are used inside","depth":26,"bounds":{"left":0.15195313,"top":0.93819445,"width":0.048046876,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"async def","depth":27,"bounds":{"left":0.20234375,"top":0.93958336,"width":0.0296875,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"functions. In Python, this blocks the entire event loop while the disk is reading/writing.","depth":26,"bounds":{"left":0.11757813,"top":0.93819445,"width":0.11875,"height":0.061805546},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Fix:","depth":28,"bounds":{"left":0.1296875,"top":1.0,"width":0.009765625,"height":-0.015972257},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Use an asynchronous file I/O library like","depth":28,"bounds":{"left":0.1296875,"top":1.0,"width":0.09335937,"height":-0.015972257},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aiofiles","depth":29,"bounds":{"left":0.1625,"top":1.0,"width":0.0265625,"height":-0.035416722},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", or run the blocking I/O operations in a separate thread using","depth":28,"bounds":{"left":0.1296875,"top":1.0,"width":0.10585938,"height":-0.034027815},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"asyncio.to_thread()","depth":29,"bounds":{"left":0.16914062,"top":1.0,"width":0.0625,"height":-0.07152772},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":28,"bounds":{"left":0.23398438,"top":1.0,"width":0.0015625,"height":-0.07013893},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Architecture & State Management","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Architecture & State Management","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Mutating Class-Level Variables (Lines 323-328):","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The script parses CLI arguments and directly mutates the class attributes (e.g.,","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AiActivityTypeEvaluator.DATA_SET = args.data_set","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"). This is a major anti-pattern. If you ever try to run tests in parallel or create multiple instances of this evaluator in a single process, the state will bleed across them.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Fix:","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Pass these arguments into the","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"__init__","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"constructor of the instance (","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"self.data_set = args.data_set","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") rather than modifying the class definition globally.","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Code Quality & Edge Cases","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Code Quality & Edge Cases","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Broad Exception Catching (Line 107):","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Using a bare","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"except Exception:","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"during the replayability probe is dangerous. It will catch","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aiohttp.ClientError","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(which is intended), but it will also silently swallow","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"TimeoutError","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or even memory errors, making debugging incredibly difficult if the endpoint goes down.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Fix:","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Scope the exception to specific expected errors, like","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"except (aiohttp.ClientError, asyncio.TimeoutError):","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Inefficient Size Calculation (Line 95):","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"len(json.dumps(request_body)) < min_size","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requires serializing the entire dictionary to a string","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"just","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to check its length. 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If","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"es_id","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"req_id","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"originate from a database and ever contain characters like","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"../","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", it could result in files being read from or written to unintended directories.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Fix:","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Sanitize the IDs or strictly enforce that they only contain alphanumeric characters.","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
Copy table
Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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You said are there soem issues with this PR
You said
are there soem issues with this PR
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Gemini said
Gemini said
Yes, there are several issues and code smells in this Pull Request, ranging from performance bottlenecks to architectural anti-patterns.
Here is a breakdown of the most notable issues, categorized by impact:
Performance & Async Anti-Patterns
Performance & Async Anti-Patterns
Sequential Requests Defeating Async (Lines 86-106):
Inside
_collect_from_es
, the code loops through
raw_samples
and
await
s a
session.post
request for each sample one by one. This means the script waits for one HTTP request to finish before starting the next, completely defeating the purpose of using
aiohttp
for asynchronous concurrency.
Fix:
Collect these coroutines into a list and use
asyncio.gather()
(ideally wrapped in an
asyncio.Semaphore
to avoid overwhelming the endpoint) to run the replayability probes concurrently.
Blocking File I/O in Async Functions (Lines 110-114, 184-188, 268-269):
Standard synchronous file operations (
with open(...)
,
json.dump
,
json.load
) are used inside
async def
functions. In Python, this blocks the entire event loop while the disk is reading/writing.
Fix:
Use an asynchronous file I/O library like
aiofiles
, or run the blocking I/O operations in a separate thread using
asyncio.to_thread()
.
Architecture & State Management
Architecture & State Management
Mutating Class-Level Variables (Lines 323-328):
The script parses CLI arguments and directly mutates the class attributes (e.g.,
AiActivityTypeEvaluator.DATA_SET = args.data_set
). This is a major anti-pattern. If you ever try to run tests in parallel or create multiple instances of this evaluator in a single process, the state will bleed across them.
Fix:
Pass these arguments into the
__init__
constructor of the instance (
self.data_set = args.data_set
) rather than modifying the class definition globally.
Code Quality & Edge Cases
Code Quality & Edge Cases
Broad Exception Catching (Line 107):
Using a bare
except Exception:
during the replayability probe is dangerous. It will catch
aiohttp.ClientError
(which is intended), but it will also silently swallow
TimeoutError
or even memory errors, making debugging incredibly difficult if the endpoint goes down.
Fix:
Scope the exception to specific expected errors, like
except (aiohttp.ClientError, asyncio.TimeoutError):
.
Inefficient Size Calculation (Line 95):
len(json.dumps(request_body)) < min_size
requires serializing the entire dictionary to a string
just
to check its length. Since
min_size
defaults to
0
, the
if min_size
short-circuit saves it for now, but if anyone sets a minimum size, this will become an unnecessary CPU bottleneck on large datasets.
Potential Path Traversal Risk (Lines 110, 113, 251):
The script writes and reads files directly using
f"{es_id}.json"
and
f"gt_{req_id}.json"
. If
es_id
or
req_id
originate from a database and ever contain characters like
../
, it could result in files being read from or written to unintended directories.
Fix:
Sanitize the IDs or strictly enforce that they only contain alphanumeric characters....
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
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Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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are there soem issues with this PR
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Gemini said
Gemini said
Yes, there are several issues and code smells in this Pull Request, ranging from performance bottlenecks to architectural anti-patterns.
Here is a breakdown of the most notable issues, categorized by impact:
Performance & Async Anti-Patterns
Performance & Async Anti-Patterns
Sequential Requests Defeating Async (Lines 86-106):
Inside
_collect_from_es
, the code loops through
raw_samples
and
await
s a
session.post
request for each sample one by one. This means the script waits for one HTTP request to finish before starting the next, completely defeating the purpose of using
aiohttp
for asynchronous concurrency.
Fix:
Collect these coroutines into a list and use
asyncio.gather()
(ideally wrapped in an
asyncio.Semaphore
to avoid overwhelming the endpoint) to run the replayability probes concurrently.
Blocking File I/O in Async Functions (Lines 110-114, 184-188, 268-269):
Standard synchronous file operations (
with open(...)
,
json.dump
,
json.load
) are used inside
async def
functions. In Python, this blocks the entire event loop while the disk is reading/writing.
Fix:
Use an asynchronous file I/O library like
aiofiles
, or run the blocking I/O operations in a separate thread using
asyncio.to_thread()
.
Architecture & State Management
Architecture & State Management
Mutating Class-Level Variables (Lines 323-328):
The script parses CLI arguments and directly mutates the class attributes (e.g.,
AiActivityTypeEvaluator.DATA_SET = args.data_set
). This is a major anti-pattern. If you ever try to run tests in parallel or create multiple instances of this evaluator in a single process, the state will bleed across them.
Fix:
Pass these arguments into the
__init__
constructor of the instance (
self.data_set = args.data_set
) rather than modifying the class definition globally.
Code Quality & Edge Cases
Code Quality & Edge Cases
Broad Exception Catching (Line 107):
Using a bare
except Exception:
during the replayability probe is dangerous. It will catch
aiohttp.ClientError
(which is intended), but it will also silently swallow
TimeoutError
or even memory errors, making debugging incredibly difficult if the endpoint goes down.
Fix:
Scope the exception to specific expected errors, like
except (aiohttp.ClientError, asyncio.TimeoutError):
.
Inefficient Size Calculation (Line 95):
len(json.dumps(request_body)) < min_size
requires serializing the entire dictionary to a string
just
to check its length. Since
min_size
defaults to
0
, the
if min_size
short-circuit saves it for now, but if anyone sets a minimum size, this will become an unnecessary CPU bottleneck on large datasets.
Potential Path Traversal Risk (Lines 110, 113, 251):
The script writes and reads files directly using
f"{es_id}.json"
and
f"gt_{req_id}.json"
. If
es_id
or
req_id
originate from a database and ever contain characters like
../
, it could result in files being read from or written to unintended directories.
Fix:
Sanitize the IDs or strictly enforce that they only contain alphanumeric characters.
Would you like me to rewrite the
_collect_from_es
method to show how to fix the sequential async loop and blocking file I/O?
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src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Core Functionality","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Core Functionality","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Data Collection (","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"collect_test_set","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"):","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Supports fetching raw samples from","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Elasticsearch 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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
Copy table
Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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You said are there soem issues with this PR
You said
are there soem issues with this PR
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Gemini said
Gemini said
Yes, there are several issues and code smells in this Pull Request, ranging from performance bottlenecks to architectural anti-patterns.
Here is a breakdown of the most notable issues, categorized by impact:
Performance & Async Anti-Patterns
Performance & Async Anti-Patterns
Sequential Requests Defeating Async (Lines 86-106):
Inside
_collect_from_es
, the code loops through
raw_samples
and
await
s a
session.post
request for each sample one by one. This means the script waits for one HTTP request to finish before starting the next, completely defeating the purpose of using
aiohttp
for asynchronous concurrency.
Fix:
Collect these coroutines into a list and use
asyncio.gather()
(ideally wrapped in an
asyncio.Semaphore
to avoid overwhelming the endpoint) to run the replayability probes concurrently.
Blocking File I/O in Async Functions (Lines 110-114, 184-188, 268-269):
Standard synchronous file operations (
with open(...)
,
json.dump
,
json.load
) are used inside
async def
functions. In Python, this blocks the entire event loop while the disk is reading/writing.
Fix:
Use an asynchronous file I/O library like
aiofiles
, or run the blocking I/O operations in a separate thread using
asyncio.to_thread()
.
Architecture & State Management
Architecture & State Management
Mutating Class-Level Variables (Lines 323-328):
The script parses CLI arguments and directly mutates the class attributes (e.g.,
AiActivityTypeEvaluator.DATA_SET = args.data_set
). This is a major anti-pattern. If you ever try to run tests in parallel or create multiple instances of this evaluator in a single process, the state will bleed across them.
Fix:
Pass these arguments into the
__init__
constructor of the instance (
self.data_set = args.data_set
) rather than modifying the class definition globally.
Code Quality & Edge Cases
Code Quality & Edge Cases
Broad Exception Catching (Line 107):
Using a bare
except Exception:
during the replayability probe is dangerous. It will catch
aiohttp.ClientError
(which is intended), but it will also silently swallow
TimeoutError
or even memory errors, making debugging incredibly difficult if the endpoint goes down.
Fix:
Scope the exception to specific expected errors, like
except (aiohttp.ClientError, asyncio.TimeoutError):
.
Inefficient Size Calculation (Line 95):
len(json.dumps(request_body)) < min_size
requires serializing the entire dictionary to a string
just
to check its length. Since
min_size
defaults to
0
, the
if min_size
short-circuit saves it for now, but if anyone sets a minimum size, this will become an unnecessary CPU bottleneck on large datasets.
Potential Path Traversal Risk (Lines 110, 113, 251):
The script writes and reads files directly using
f"{es_id}.json"
and
f"gt_{req_id}.json"
. If
es_id
or
req_id
originate from a database and ever contain characters like
../
, it could result in files being read from or written to unintended directories.
Fix:
Sanitize the IDs or strictly enforce that they only contain alphanumeric characters.
Would you like me to rewrite the
_collect_from_es
method to show how to fix the sequential async loop and blocking file I/O?
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Jy 19798 evaluation for ai activity types by nikol Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet — Work...
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
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Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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Gemini","depth":15,"bounds":{"left":0.09335937,"top":0.12847222,"width":0.000390625,"height":0.00069444446},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Conversation with Gemini","depth":16,"bounds":{"left":0.09335937,"top":0.13055556,"width":0.14101562,"height":0.022222223},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy prompt","depth":21,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":22,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"Gemini said","depth":20,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This Python script defines the","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AiActivityTypeEvaluator","depth":25,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"class, a specialized tool for evaluating AI-driven activity type classification. 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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
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Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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Jy 19798 evaluation for ai activity types by nikol Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet — Work...
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github.com/jiminny/prophet/pull/468/changes#diff-d github.com/jiminny/prophet/pull/468/changes#diff-d2f9fea9bc428b119ae26a66453e8eab7dd0782d4a4d93075ca5ce05903d77e8...
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
Copy table
Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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Edit
You said are there soem issues with this PR
You said
are there soem issues with this PR
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Gemini said
Gemini said
Yes,
there are several issues and code smells in this Pull Request,
ranging from performance bottlenecks to architectural anti-patterns.
Here is a breakdown of the most notable issues,
categorized by impact:
Performance & Async Anti-Patterns
Performance & Async Anti-Patterns
Sequential Requests Defeating Async (Lines 86-106):
Inside
_collect_from_es
,
the code loops through
raw_samples
and
await
s a
session.post
request for each sample one by one.
This means the script waits for one HTTP request to finish before starting the next,
completely defeating the purpose of using
aiohttp
for asynchronous concurrency.
Fix:
Collect these coroutines into a list and use...
|
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Gemini","depth":16,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy prompt","depth":21,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":22,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"Gemini said","depth":20,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This Python script defines the","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AiActivityTypeEvaluator","depth":25,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Core Functionality","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Core Functionality","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Data Collection (","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"collect_test_set","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"):","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Supports fetching raw samples from","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Elasticsearch (ES)","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or loading them from","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"local JSON files","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Implements a","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"replayability check","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": It probes the live API endpoint to ensure the activity exists before including it in the dataset.","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Filters data based on request body size, language, and the presence of an original response.","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ground Truth Management:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Saves inputs and \"gold standard\" responses to a local directory structure (","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"eval_output/ai_activity_type/...","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":").","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Features an optional mode to populate ground truth using a high-order LLM (e.g.,","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gpt-5_2","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") if 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truths based on the selected dataset name.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Run:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Executes the evaluation via","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"asyncio.run(run_evaluation(...))","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", which orchestrates the collection, endpoint calling, and result scoring phases.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy prompt","depth":21,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Edit","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":false,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said are there soem issues with this PR","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"are there soem issues with this PR","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Show more options","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":20,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yes,","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"there are several issues and code smells in this Pull Request,","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ranging from performance bottlenecks to architectural anti-patterns.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a breakdown of the most notable issues,","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"categorized by 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through","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"raw_samples","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"await","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"s a","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"session.post","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"request for each sample one by one.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This means the script waits for one HTTP request to finish before starting the next,","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"completely defeating the purpose of using","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aiohttp","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"for asynchronous concurrency.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Fix:","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Collect these coroutines into a list and use","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
Expand
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
Copy table
Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
Copy prompt
Edit
You said are there soem issues with this PR
You said
are there soem issues with this PR
Show more options
Show thinking
Gemini said
Gemini said
Yes,
there are several issues and code smells in this Pull Request,
ranging from performance bottlenecks to architectural anti-patterns.
Here is a breakdown of the most notable issues,
categorized by impact:
Performance & Async Anti-Patterns
Performance & Async Anti-Patterns
Sequential Requests Defeating Async (Lines 86-106):
Inside
_collect_from_es
,
the code loops through
raw_samples
and
await
s a
session.post
request for each sample one by one.
This means the script waits for one HTTP request to finish before starting the next,
completely defeating the purpose of using
aiohttp
for asynchronous concurrency.
Fix:
Collect these coroutines into a list and use...
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Jiminny — Work
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app.staging.jiminny.com
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
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Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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Edit
You said are there soem issues with this PR
You said
are there soem issues with this PR
Listen
Show more options
Show thinking
Gemini said
Gemini said
Yes, there are several issues and code smells in this Pull Request, ranging from performance bottlenecks to architectural anti-patterns.
Here is a breakdown of the most notable issues, categorized by impact:
Performance & Async Anti-Patterns
Performance & Async Anti-Patterns
Sequential Requests Defeating Async (Lines 86-106):
Inside
_collect_from_es
, the code loops through
raw_samples
and
await
s a
session.post
request for each sample one by one. This means the script waits for one HTTP request to finish before starting the next, completely defeating the purpose of using
aiohttp
for asynchronous concurrency.
Fix:...
|
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AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\\nExpected: {gt_label}\\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. 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It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Core Functionality","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Core Functionality","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Data Collection (","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"collect_test_set","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"):","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Supports fetching raw samples from","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Elasticsearch 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truths based on the selected dataset name.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Run:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Executes the evaluation via","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"asyncio.run(run_evaluation(...))","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", which orchestrates the collection, endpoint calling, and result scoring phases.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy prompt","depth":21,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Edit","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said are there soem issues with this PR","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"are there soem issues with this PR","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":22,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":20,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yes, there are several issues and code smells in this Pull Request, ranging from performance bottlenecks to architectural anti-patterns.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a breakdown of the most notable issues, categorized by impact:","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Performance & Async Anti-Patterns","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Performance & Async Anti-Patterns","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Sequential Requests Defeating Async (Lines 86-106):","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Inside","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"_collect_from_es","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", the code loops through","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"raw_samples","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"await","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"s a","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"session.post","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"request for each sample one by one. This means the script waits for one HTTP request to finish before starting the next, completely defeating the purpose of using","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aiohttp","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"for asynchronous concurrency.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Fix:","depth":28,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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You said I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected. Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
You said
I’m on page “<tabTitle>Jy 19798 evaluation for ai activity types by nikol</tabTitle>” with “<selection>@@ -0,0 +1,330 @@1+#!/usr/bin/env python32+import asyncio3+import json4+import os5+from pathlib import Path6+from typing import Any, Dict, List7+8+import aiohttp9+10+from src.component.call_processing.schemes.ai_activity_type_request import AiActivityTypeRequest11+from src.component.call_processing.schemes.ai_activity_type_response import AiActivityTypeResponse12+from src.eval.abstract_evaluator import AbstractEvaluator13+from src.eval.collectors import collect_test_set as es_collect_test_set14+from src.eval.common_evaluator_runner import create_parser, run_evaluation15+from src.eval.endpoints import run_endpoint as run_endpoint_http16+from src.eval.models import EvaluationResult17+18+19+class AiActivityTypeEvaluator(AbstractEvaluator):20+ENDPOINT_PATH = "call/ai-activity-type"21+REQUEST_MODEL = AiActivityTypeRequest22+RESPONSE_MODEL = AiActivityTypeResponse23+OUTPUT_SUBFOLDER = "ai_activity_type"24+USES_LLM_EVALUATION = False25+26+READS_FROM_DATASET_FOLDER = True27+28+DATA_SET: str = "initial"29+30+MINIMUM_REQUEST_BODY_SIZE: int = 031+32+SKIP_UNREPLAYABLE_ON_COLLECT: bool = True33+REPLAYABILITY_CHECK_TIMEOUT_SECONDS: float = 20.034+35+POPULATE_GROUND_TRUTH_LLM: bool = False36+GROUND_TRUTH_LLM_ENDPOINT: str = "OPENAI:gpt-5_2"37+38+COMPARE_TO_GROUND_TRUTH: str = "es"39+40+def __init__(self, **kwargs: Any) -> None:41+super().__init__(**kwargs)42+_repo_root = Path(__file__).parents[2]43+_datasets_root = _repo_root / "eval_output" / self.OUTPUT_SUBFOLDER / "eval_datasets"44+_dataset_dir = _datasets_root / self.__class__.DATA_SET45+self._dataset_dir = _dataset_dir46+self._inputs_dir = _dataset_dir / "input"47+self._ground_truths_dir = _dataset_dir / "ground_truth"48+49+async def collect_test_set(self) -> List[Dict[str, Any]]:50+if self.es_host_name:51+return await self._collect_from_es()52+return await self._collect_from_files()53+54+async def _collect_from_es(self) -> List[Dict[str, Any]]:55+if self._inputs_dir.exists() or self._ground_truths_dir.exists():56+raise FileExistsError(57+f"Dataset folder already exists: {self._inputs_dir.parent}. "58+"Choose a different --data-set name or remove the folder manually."59+ )60+61+raw_samples = await es_collect_test_set(62+es_host_name=self.es_host_name,63+es_port=self.es_port,64+endpoint_path=self.ENDPOINT_PATH,65+limit=self.limit,66+language_filter=self.language_filter,67+min_prompt_length=self.min_prompt_length,68+is_json_response=self.IS_JSON_RESPONSE,69+exclude_languages=self.exclude_languages,70+ )71+72+self._inputs_dir.mkdir(parents=True, exist_ok=True)73+self._ground_truths_dir.mkdir(parents=True, exist_ok=True)74+75+min_size = self.MINIMUM_REQUEST_BODY_SIZE76+samples: List[Dict[str, Any]] = []77+skipped_no_response = 078+skipped_too_small = 079+skipped_unreplayable = 080+skipped_probe_errors = 081+82+endpoint_url = f"{self.api_host}/{self.ENDPOINT_PATH}"83+84+timeout = aiohttp.ClientTimeout(total=self.REPLAYABILITY_CHECK_TIMEOUT_SECONDS)85+async with aiohttp.ClientSession(timeout=timeout) as session:86+for sample in raw_samples:87+es_id = sample["id"]88+request_body = sample["request_body"]89+original_response = sample.get("original_response")90+91+if not original_response:92+skipped_no_response += 193+continue94+95+if min_size and len(json.dumps(request_body)) < min_size:96+skipped_too_small += 197+continue98+99+if self.SKIP_UNREPLAYABLE_ON_COLLECT:100+try:101+async with session.post(endpoint_url, json=request_body) as resp:102+if resp.status != 200:103+body_text = await resp.text()104+if "Cannot find activity" in body_text:105+skipped_unreplayable += 1106+continue107+except Exception:108+skipped_probe_errors += 1109+110+with open(self._inputs_dir / f"{es_id}.json", "w") as f:111+json.dump(request_body, f, indent=2)112+113+with open(self._ground_truths_dir / f"gt_{es_id}.json", "w") as f:114+json.dump(original_response, f, indent=2)115+116+samples.append(117+ {118+"id": es_id,119+"request_body": request_body,120+"original_response": original_response,121+"ground_truth": original_response,122+ }123+ )124+125+print(f"Wrote {len(samples)} samples to {self._inputs_dir.parent}")126+if skipped_no_response:127+print(f"Skipped {skipped_no_response} records with no response body")128+if skipped_too_small:129+print(130+f"Skipped {skipped_too_small} records whose request body was smaller "131+f"than {min_size} characters"132+ )133+if skipped_unreplayable:134+print(f"Skipped {skipped_unreplayable} records that are not replayable (missing activity in ES)")135+if skipped_probe_errors:136+print(f"Warning: replayability probe errored for {skipped_probe_errors} records (kept those records)")137+138+if self.__class__.POPULATE_GROUND_TRUTH_LLM:139+label_results = await run_endpoint_http(140+test_set=samples,141+endpoint_url=endpoint_url,142+request_model=self.REQUEST_MODEL,143+force_llm_endpoint=self.__class__.GROUND_TRUTH_LLM_ENDPOINT,144+is_streaming_response=self.IS_STREAMING_RESPONSE,145+timeout_seconds=300.0,146+parallel_requests=self.parallel_requests,147+return_prompt_in_run=self.RETURN_PROMPT_IN_RUN,148+ )149+150+for i, r in enumerate(label_results):151+forced = self.__class__.GROUND_TRUTH_LLM_ENDPOINT152+model = forced.split(":", 1)[1] if ":" in forced else forced153+samples[i]["ground_truth_llm_model"] = model154+155+if not r.get("success", True):156+samples[i]["ground_truth_llm"] = None157+samples[i]["ground_truth_llm_reasoning"] = None158+samples[i]["ground_truth_llm_error_type"] = r.get("error_type")159+samples[i]["ground_truth_llm_error_message"] = r.get("error_message")160+continue161+162+resp = r.get("new_response") or {}163+samples[i]["ground_truth_llm"] = resp.get("ai_activity_type")164+samples[i]["ground_truth_llm_reasoning"] = resp.get("ai_activity_type_reasoning")165+166+return samples167+168+async def _collect_from_files(self) -> List[Dict[str, Any]]:169+if not self._inputs_dir.exists():170+raise FileNotFoundError(171+f"Dataset folder not found: {self._inputs_dir}. "172+"Run --steps collect first or check your --data-set name."173+ )174+175+samples: List[Dict[str, Any]] = []176+for filename in sorted(os.listdir(self._inputs_dir)):177+input_path = self._inputs_dir / filename178+gt_path = self._ground_truths_dir / f"gt_{filename}"179+180+if not gt_path.exists():181+print(f"Warning: ground truth not found for {filename}, skipping")182+continue183+184+with open(input_path, "r") as f:185+request_body: Dict[str, Any] = json.load(f)186+187+with open(gt_path, "r") as f:188+ground_truth: Dict[str, Any] = json.load(f)189+190+samples.append(191+ {192+"id": Path(filename).stem,193+"request_body": request_body,194+"original_response": None,195+"ground_truth": ground_truth,196+ }197+ )198+199+print(f"Loaded {len(samples)} samples from {self._inputs_dir.parent}")200+return samples201+202+async def evaluate_against_ground_truth(self, results: List[Dict[str, Any]]) -> List[EvaluationResult]:203+evaluation_results: List[EvaluationResult] = []204+compare_to = self.__class__.COMPARE_TO_GROUND_TRUTH205+206+for res in results:207+req_id = res["request_id"]208+is_success = res.get("success", True)209+210+if not is_success:211+evaluation_results.append(212+EvaluationResult(213+request_id=req_id,214+request_body=res["request_body"],215+new_response=res.get("new_response"),216+valid_schema=False,217+quality_score=0.0,218+quality_feedback=f"Request failed: {res.get('error_type')} - {res.get('error_message')}",219+response_time=res.get("response_time"),220+success=False,221+error_type=res.get("error_type"),222+error_message=res.get("error_message"),223+ground_truth_match=False,224+ )225+ )226+continue227+228+pred = (res.get("new_response") or {}).get("ai_activity_type")229+230+if compare_to == "llm":231+if "ground_truth_llm" not in res:232+evaluation_results.append(233+EvaluationResult(234+request_id=req_id,235+request_body=res["request_body"],236+new_response=res.get("new_response"),237+valid_schema=res.get("valid_schema", True),238+quality_score=0.0,239+quality_feedback=(240+"Missing ground_truth_llm in run results. Ensure collect step populated it and "241+"endpoints.py passes it through."242+ ),243+response_time=res.get("response_time"),244+success=True,245+ground_truth_match=False,246+ )247+ )248+continue249+gt_label = res.get("ground_truth_llm")250+else:251+gt_path = self._ground_truths_dir / f"gt_{req_id}.json"252+if not gt_path.exists():253+evaluation_results.append(254+EvaluationResult(255+request_id=req_id,256+request_body=res["request_body"],257+new_response=res.get("new_response"),258+valid_schema=res.get("valid_schema", True),259+quality_score=0.0,260+quality_feedback=f"Ground truth file not found: {gt_path}",261+response_time=res.get("response_time"),262+success=True,263+ground_truth_match=False,264+ )265+ )266+continue267+268+with open(gt_path, "r") as f:269+ground_truth_dict: Dict[str, Any] = json.load(f)270+271+gt_label = (ground_truth_dict or {}).get("ai_activity_type")272+273+matched = pred == gt_label274+275+evaluation_results.append(276+EvaluationResult(277+request_id=req_id,278+request_body=res["request_body"],279+new_response=res.get("new_response"),280+valid_schema=res.get("valid_schema", True),281+quality_score=1.0 if matched else 0.0,282+quality_feedback="PASS" if matched else f"FAIL\nExpected: {gt_label}\nGot: {pred}",283+response_time=res.get("response_time"),284+success=True,285+ground_truth_match=matched,286+ )287+ )288+289+return evaluation_results290+291+292+if __name__ == "__main__":293+parser = create_parser(AiActivityTypeEvaluator)294+parser.add_argument(295+"--data-set",296+type=str,297+default="initial",298+dest="data_set",299+help="Dataset folder under eval_output/ai_activity_type/eval_datasets/ (default: initial)",300+ )301+302+parser.add_argument(303+"--populate-ground-truth-llm",304+action="store_true",305+dest="populate_ground_truth_llm",306+ )307+parser.add_argument(308+"--ground-truth-llm-endpoint",309+type=str,310+default="OPENAI:gpt-5_2",311+dest="ground_truth_llm_endpoint",312+ )313+314+parser.add_argument(315+"--compare-to-ground-truth",316+type=str,317+choices=["es", "llm"],318+default="es",319+dest="compare_to_ground_truth",320+ )321+322+args = parser.parse_args()323+AiActivityTypeEvaluator.DATA_SET = args.data_set324+325+AiActivityTypeEvaluator.POPULATE_GROUND_TRUTH_LLM = bool(args.populate_ground_truth_llm)326+AiActivityTypeEvaluator.GROUND_TRUTH_LLM_ENDPOINT = args.ground_truth_llm_endpoint327+328+AiActivityTypeEvaluator.COMPARE_TO_GROUND_TRUTH = args.compare_to_ground_truth329+330+asyncio.run(run_evaluation(AiActivityTypeEvaluator, args))</selection>” selected.
Please summarize the selection using precise and concise language. Use headers and bulleted lists in the summary, to make it scannable. Maintain the meaning and factual accuracy.
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Gemini said
Gemini said
This Python script defines the
AiActivityTypeEvaluator
class, a specialized tool for evaluating AI-driven activity type classification. It extends a base evaluation framework to handle data collection, ground-truth comparison, and performance scoring.
Core Functionality
Core Functionality
Data Collection (
collect_test_set
):
* Supports fetching raw samples from
Elasticsearch (ES)
or loading them from
local JSON files
.
Implements a
replayability check
: It probes the live API endpoint to ensure the activity exists before including it in the dataset.
Filters data based on request body size, language, and the presence of an original response.
Ground Truth Management:
Saves inputs and "gold standard" responses to a local directory structure (
eval_output/ai_activity_type/...
).
Features an optional mode to populate ground truth using a high-order LLM (e.g.,
gpt-5_2
) if the
POPULATE_GROUND_TRUTH_LLM
flag is set.
Evaluation Logic (
evaluate_against_ground_truth
):
Compares the model's predicted
ai_activity_type
against either the original ES response or the LLM-generated ground truth.
Assigns a
quality_score
of
1.0
for a match and
0.0
for a mismatch or request failure.
Key Configuration Constants
Key Configuration Constants
Constant
Purpose
ENDPOINT_PATH
The specific API route being tested:
call/ai-activity-type
.
COMPARE_TO_GROUND_TRUTH
Determines if the baseline is the original data (
es
) or an
llm
.
SKIP_UNREPLAYABLE_ON_COLLECT
If
True
, discards records where the API returns "Cannot find activity."
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Limits the probe request to 20 seconds.
Constant
ENDPOINT_PATH
COMPARE_TO_GROUND_TRUTH
SKIP_UNREPLAYABLE_ON_COLLECT
REPLAYABILITY_CHECK_TIMEOUT_SECONDS
Purpose
The specific API route being tested:
call/ai-activity-type
.
Determines if the baseline is the original data (
es
) or an
llm
.
If
True
, discards records where the API returns "Cannot find activity."
Limits the probe request to 20 seconds.
Copy table
Execution Workflow
Execution Workflow
Parsing:
The script uses
create_parser
to handle CLI arguments like
--data-set
,
--populate-ground-truth-llm
, and
--compare-to-ground-truth
.
Initialization:
Sets up directory paths for inputs and ground truths based on the selected dataset name.
Run:
Executes the evaluation via
asyncio.run(run_evaluation(...))
, which orchestrates the collection, endpoint calling, and result scoring phases.
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You said are there soem issues with this PR
You said
are there soem issues with this PR
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Gemini said
Gemini said
Yes, there are several issues and code smells in this Pull Request, ranging from performance bottlenecks to architectural anti-patterns.
Here is a breakdown of the most notable issues, categorized by impact:
Performance & Async Anti-Patterns
Performance & Async Anti-Patterns
Sequential Requests Defeating Async (Lines 86-106):
Inside
_collect_from_es
, the code loops through
raw_samples
and
await
s a
session.post
request for each sample one by one. This means the script waits for one HTTP request to finish before starting the next, completely defeating the purpose of using
aiohttp
for asynchronous concurrency.
Fix:...
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meet.google.com/mie-gawc-dsi
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
CloudWatch | us-east-2
CloudWatch | us-east-2
Meet - Daily - Platform
Meet - Daily - Platform
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
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Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
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8731697523133232206
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visual_change
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accessibility
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NULL
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
CloudWatch | us-east-2
CloudWatch | us-east-2
Meet - Daily - Platform
Meet - Daily - Platform
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
Open upload file menu
Tools
Open mode picker
Pro
Send message
Your Jiminny chats aren’t used to improve our models. Gemini is AI and can make mistakes, including about people.
Your privacy & Gemini Opens in a new window
Your privacy & Gemini
Opens in a new window
Summarize page
Summarize page
Backgrounds and effects
Backgrounds and effects
Turn off visual effects
Back
Generate a background
No scene
No scene
Describe your idea
Create samples
Create samples
Learn more about generating backgrounds
Learn more about generating backgrounds
Close...
|
10061
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10066
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195
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35
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2026-04-14T08:10:03.883667+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-14/1776 /Users/lukas/.screenpipe/data/data/2026-04-14/1776154203883_m2.jpg...
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Firefox
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Meet - Daily - Platform — Work
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meet.google.com/mie-gawc-dsi
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
CloudWatch | us-east-2
CloudWatch | us-east-2
Meet - Daily - Platform
Meet - Daily - Platform
Close tab
Settings
Settings
New Tab
Customize sidebar
Close Google Gemini (⌃X)
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WORK, Google Account: [EMAIL]
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Conversation with Gemini
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Copy prompt
Edit
You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
Open upload file menu
Tools
Open mode picker
Pro
Send message
Your Jiminny chats aren’t used to improve our models. Gemini is AI and can make mistakes, including about people.
Your privacy & Gemini Opens in a new window
Your privacy & Gemini
Opens in a new window
Summarize page
Summarize page
Backgrounds and effects
Backgrounds and effects
Turn off visual effects
Back
Generate a background
No scene
No scene
Describe your idea
Create samples
Create samples
Learn more about generating backgrounds
Learn more about generating backgrounds
Close...
|
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
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Summarize page
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Backgrounds and effects
Turn off visual effects
Back
Generate a background
No scene
No scene
Describe your idea
Create samples
Create samples
Learn more about generating backgrounds
Learn more about generating backgrounds
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
CloudWatch | us-east-2
CloudWatch | us-east-2
Meet - Daily - Platform
Meet - Daily - Platform
Close tab
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
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encrypted
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said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"why I can't see speaker data on meemt in firefox. ho wto set it up","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Listen","depth":22,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":20,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Dealing with missing features right when you need them is incredibly frustrating. Assuming \"meemt\" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Since \"speaker data\" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. You Need \"Speaker Notes\" for Google Slides","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. You Need \"Speaker Notes\" for Google Slides","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Reality:","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"However, this relies on a specific \"Present a Tab\" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Google Workspace Updates. Opens side panel.","depth":24,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"How to set it up (The Firefox Workaround):","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can still present and read your notes in Firefox by manually managing your windows.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open your Google Slides presentation in a standard Firefox window.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Click the dropdown arrow next to the","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Slideshow","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"button in the top right corner.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Select","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Presenter view","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to pop your speaker notes out into a separate, smaller window.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Skywork. Opens side panel.","depth":26,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Join your Google Meet in a different Firefox window.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Click","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Present now","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and choose the","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Window","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"option.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Select the window displaying your main slides (do not select your separate speaker notes window).","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. 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Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How to set it up:","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Turn on built-in captions:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CC","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"button at the bottom of your Meet screen to toggle them on.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Search for a Firefox add-on:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Fellow.ai. Opens side panel.","depth":26,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Switch browsers temporarily:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Sources","depth":23,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Sources","depth":25,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"Enter a prompt for Gemini\nencrypted","depth":20,"value":"Enter a prompt for Gemini\nencrypted","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Enter a prompt for Gemini","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"encrypted","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Open upload file menu","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Tools","depth":18,"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,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Pro","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Microphone","depth":19,"role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Your Jiminny chats aren’t used to improve our models. Gemini is AI and can make mistakes, including about people.","depth":17,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Your privacy & Gemini Opens in a new window","depth":17,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Your privacy & Gemini","depth":18,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Opens in a new window","depth":19,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Summarize page","depth":7,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Summarize page","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Return to home screen","depth":10,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"lukas.kovalik@jiminny.com","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Switch account","depth":11,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Switch account","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Lukas Kovalik","depth":14,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"More options","depth":13,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Turn off microphone","depth":14,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Turn off camera","depth":14,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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8731688727032609870
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accessibility
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
CloudWatch | us-east-2
CloudWatch | us-east-2
Meet - Daily - Platform
Meet - Daily - Platform
Close tab
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Settings
New Tab
Customize sidebar
Close Google Gemini (⌃X)
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WORK, Google Account: [EMAIL]
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Conversation with Gemini
Conversation with Gemini
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Edit
You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
Enter a prompt for Gemini
encrypted
Enter a prompt for Gemini
encrypted
Open upload file menu
Tools
Open mode picker
Pro
Microphone
Your Jiminny chats aren’t used to improve our models. Gemini is AI and can make mistakes, including about people.
Your privacy & Gemini Opens in a new window
Your privacy & Gemini
Opens in a new window
Summarize page
Summarize page
Return to home screen
[EMAIL]
Switch account
Switch account
Lukas Kovalik
More options
Turn off microphone
Turn off camera...
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
CloudWatch | us-east-2
CloudWatch | us-east-2
Meet - Daily - Platform
Mute tab
Meet - Daily - Platform
Close tab
Settings
Settings
New Tab
Customize sidebar
Close Google Gemini (⌃X)
Tabs from other devices
Open history (⇧⌘H)
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WORK, Google Account: [EMAIL]
Main menu
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Conversation with Gemini
Conversation with Gemini
Copy prompt
Edit
You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
Open upload file menu
Tools
Open mode picker
Pro
Send message
Your Jiminny chats aren’t used to improve our models. Gemini is AI and can make mistakes, including about people.
Your privacy & Gemini Opens in a new window
Your privacy & Gemini
Opens in a new window
Summarize page
Summarize page
Return to home screen
[EMAIL]
Switch account
Switch account
Lukas Kovalik
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Turn off microphone
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Assuming \"meemt\" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.","depth":24,"bounds":{"left":0.10390625,"top":0.30069444,"width":0.13046876,"height":0.10486111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Since \"speaker data\" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.","depth":24,"bounds":{"left":0.10390625,"top":0.4201389,"width":0.13125,"height":0.06875},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. You Need \"Speaker Notes\" for Google Slides","depth":23,"bounds":{"left":0.10390625,"top":0.52152777,"width":0.13242188,"height":0.033333335},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. You Need \"Speaker Notes\" for Google Slides","depth":24,"bounds":{"left":0.10390625,"top":0.5229167,"width":0.12070312,"height":0.03125},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Reality:","depth":24,"bounds":{"left":0.10390625,"top":0.5625,"width":0.036328126,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.","depth":24,"bounds":{"left":0.10390625,"top":0.5625,"width":0.13242188,"height":0.050694443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"However, this relies on a specific \"Present a Tab\" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.","depth":24,"bounds":{"left":0.10390625,"top":0.5986111,"width":0.12539062,"height":0.10486111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Google Workspace Updates. 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Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How to set it up:","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Turn on built-in captions:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CC","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"button at the bottom of your Meet screen to toggle them on.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Search for a Firefox add-on:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Fellow.ai. Opens side panel.","depth":26,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Switch browsers temporarily:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Sources","depth":23,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Sources","depth":25,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"I men in dia (arc) I can see my headphones in both microphone and speakers","depth":20,"bounds":{"left":0.109375,"top":0.8020833,"width":0.125,"height":0.05},"value":"I men in dia (arc) I can see my headphones in both microphone and speakers","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"I men in dia (arc) I can see my headphones in both microphone and speakers","depth":22,"bounds":{"left":0.109375,"top":0.8034722,"width":0.10625,"height":0.047916666},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Open upload file menu","depth":20,"bounds":{"left":0.1046875,"top":0.86527777,"width":0.015625,"height":0.027777778},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Tools","depth":18,"bounds":{"left":0.1234375,"top":0.86527777,"width":0.015625,"height":0.027777778},"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,"bounds":{"left":0.190625,"top":0.8645833,"width":0.03046875,"height":0.027777778},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Pro","depth":23,"bounds":{"left":0.196875,"top":0.87222224,"width":0.00859375,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Send message","depth":19,"bounds":{"left":0.22265625,"top":0.86388886,"width":0.01640625,"height":0.029166667},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Your Jiminny chats aren’t used to improve our models. Gemini is AI and can make mistakes, including about people.","depth":17,"bounds":{"left":0.10039063,"top":0.9097222,"width":0.14296874,"height":0.022222223},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Your privacy & Gemini Opens in a new window","depth":17,"bounds":{"left":0.1484375,"top":0.93194443,"width":0.046875,"height":0.011111111},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Your privacy & Gemini","depth":18,"bounds":{"left":0.1484375,"top":0.93194443,"width":0.046875,"height":0.011111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Opens in a new window","depth":19,"bounds":{"left":0.09335937,"top":0.93125,"width":0.05078125,"height":0.011111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Summarize page","depth":7,"bounds":{"left":0.1,"top":0.96319443,"width":0.06289063,"height":0.022222223},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Summarize page","depth":9,"bounds":{"left":0.10664062,"top":0.9673611,"width":0.049609374,"height":0.013888889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Return to home screen","depth":10,"bounds":{"left":0.259375,"top":0.05625,"width":0.041015625,"height":0.027777778},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"lukas.kovalik@jiminny.com","depth":12,"bounds":{"left":0.9097656,"top":0.057638887,"width":0.06523438,"height":0.011805556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Switch account","depth":11,"bounds":{"left":0.94023436,"top":0.06875,"width":0.034765624,"height":0.011805556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Switch account","depth":12,"bounds":{"left":0.94023436,"top":0.06875,"width":0.034765624,"height":0.011805556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Lukas Kovalik","depth":14,"bounds":{"left":0.39765626,"top":0.36319444,"width":0.03515625,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"More options","depth":13,"bounds":{"left":0.6578125,"top":0.35277778,"width":0.01875,"height":0.033333335},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Turn off microphone","depth":14,"bounds":{"left":0.496875,"top":0.59097224,"width":0.021875,"height":0.033333335},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Turn off camera","depth":14,"bounds":{"left":0.525,"top":0.59097224,"width":0.021875,"height":0.033333335},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Turn on background blur","depth":13,"bounds":{"left":0.553125,"top":0.59097224,"width":0.021875,"height":0.033333335},"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Microphone: soundcore AeroClip","depth":12,"bounds":{"left":0.39140624,"top":0.6493056,"width":0.06992187,"height":0.022222223},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Speaker: Playing…","depth":13,"bounds":{"left":0.46445313,"top":0.6493056,"width":0.06992187,"height":0.022222223},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Camera: FaceTime HD Camera","depth":13,"bounds":{"left":0.5375,"top":0.6493056,"width":0.06992187,"height":0.022222223},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Backgrounds and effects","depth":12,"bounds":{"left":0.6105469,"top":0.6493056,"width":0.06992187,"height":0.022222223},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Enhance your appearance","depth":14,"bounds":{"left":0.5679687,"top":0.5138889,"width":0.07539062,"height":0.016666668},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enhance your appearance","depth":15,"bounds":{"left":0.5679687,"top":0.51458335,"width":0.07539062,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Meet can adjust your image sharpness and lighting so others can see you better. To change how you look, use the Appearance tab.","depth":15,"bounds":{"left":0.55546874,"top":0.53333336,"width":0.10507812,"height":0.05486111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Not now","depth":15,"bounds":{"left":0.590625,"top":0.6,"width":0.03046875,"height":0.027777778},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Try now","depth":15,"bounds":{"left":0.62578124,"top":0.6,"width":0.0390625,"height":0.027777778},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":true,"is_selected":false},{"role":"AXStaticText","text":"Try now","depth":17,"bounds":{"left":0.6351563,"top":0.60694444,"width":0.0203125,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Daily - Platform","depth":11,"bounds":{"left":0.68671876,"top":0.3888889,"width":0.175,"height":0.025},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Daily - Platform","depth":14,"bounds":{"left":0.7363281,"top":0.38819444,"width":0.07578125,"height":0.025694445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Scheduled for","depth":12,"bounds":{"left":0.7601563,"top":0.425,"width":0.035546876,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thu, Apr 16","depth":12,"bounds":{"left":0.73164064,"top":0.43888888,"width":0.046484374,"height":0.021527778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"9:45 AM","depth":12,"bounds":{"left":0.7828125,"top":0.43888888,"width":0.033984374,"height":0.021527778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Use Gemini to take notes Share notes and transcript","depth":11,"bounds":{"left":0.71132815,"top":0.4722222,"width":0.12578125,"height":0.044444446},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Use Gemini to take notes","depth":12,"bounds":{"left":0.73476565,"top":0.48194444,"width":0.06328125,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Share notes and transcript","depth":12,"bounds":{"left":0.73476565,"top":0.49583334,"width":0.056640625,"height":0.011111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Start","depth":12,"bounds":{"left":0.8011719,"top":0.48055556,"width":0.03125,"height":0.027777778},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Start","depth":14,"bounds":{"left":0.8105469,"top":0.4875,"width":0.0125,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Join anyway","depth":12,"bounds":{"left":0.72734374,"top":0.5277778,"width":0.09375,"height":0.03888889},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Join anyway","depth":14,"bounds":{"left":0.75859374,"top":0.5402778,"width":0.03125,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Other ways to join","depth":12,"bounds":{"left":0.7378906,"top":0.5861111,"width":0.07265625,"height":0.027777778},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Gemini is available in Meet as your personal in-meeting assistant. It can analyze conversation via temporary access to meeting captions. Using Ask Gemini won't create a recording or store meeting data. The meeting host can turn it off.","depth":12,"bounds":{"left":0.50273436,"top":0.9375,"width":0.26328126,"height":0.035416666},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Learn more","depth":12,"bounds":{"left":0.64453125,"top":0.9611111,"width":0.027734375,"height":0.011805556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Learn more","depth":13,"bounds":{"left":0.64453125,"top":0.9611111,"width":0.027734375,"height":0.011805556},"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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-2250905463257490131
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8731661789005347918
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visual_change
|
accessibility
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NULL
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
CloudWatch | us-east-2
CloudWatch | us-east-2
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
Open upload file menu
Tools
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Pro
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Your Jiminny chats aren’t used to improve our models. Gemini is AI and can make mistakes, including about people.
Your privacy & Gemini Opens in a new window
Your privacy & Gemini
Opens in a new window
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Summarize page
Return to home screen
[EMAIL]
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Switch account
Lukas Kovalik
More options
Turn off microphone
Turn off camera
Turn on background blur
Microphone: soundcore AeroClip
Speaker: Playing…
Camera: FaceTime HD Camera
Backgrounds and effects
Enhance your appearance
Enhance your appearance
Meet can adjust your image sharpness and lighting so others can see you better. To change how you look, use the Appearance tab.
Not now
Try now
Try now
Daily - Platform
Daily - Platform
Scheduled for
Thu, Apr 16
9:45 AM
Use Gemini to take notes Share notes and transcript
Use Gemini to take notes
Share notes and transcript
Start
Start
Join anyway
Join anyway
Other ways to join
Gemini is available in Meet as your personal in-meeting assistant. It can analyze conversation via temporary access to meeting captions. Using Ask Gemini won't create a recording or store meeting data. The meeting host can turn it off.
Learn more
Learn more...
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/Users/lukas/.screenpipe/data/data/2026-04-14/1776 /Users/lukas/.screenpipe/data/data/2026-04-14/1776156395135_m1.jpg...
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Jiminny — Work
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app.staging.jiminny.com/ondemand?topic_id[]=e02f09 app.staging.jiminny.com/ondemand?topic_id[]=e02f0932-cb76-41b6-ac4f-6b8db1392146&include_internal_conversations=1&sequence_number=3...
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Close tab
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
CloudWatch | us-east-2
CloudWatch | us-east-2
New Tab
Customize sidebar
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
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I men in dia (arc) I can see my headphones in both microphone and speakers
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JY-18909-automated-reports-ask-jiminny ■ 869720
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
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Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
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JY-18909-automated-reports-ask-jiminny ■ 869720
28
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Transcript
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Select option Said by
Select option
Said by
Select option Anyone
Select option...
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2026-04-14T08:54:35.667922+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-14/1776 /Users/lukas/.screenpipe/data/data/2026-04-14/1776156875667_m2.jpg...
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Firefox
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CloudWatch | us-east-2 — Work
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1
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us-east-2.console.aws.amazon.com/cloudwatch/home?r us-east-2.console.aws.amazon.com/cloudwatch/home?region=us-east-2#logsV2:logs-insights$3FqueryDetail$3D~(end~0~start~-3600~timeType~'RELATIVE~tz~'UTC~unit~'seconds~editorString~'fields*20*40timestamp*2c*20*40message*2c*20*40logStream*2c*20*40log*0a*7c*20filter*20*40message*20like*20*22*5bAskJiminnyReport*3aGenerate*5d*22*20*0a*7c*20filter*20*40message*20not*20like*20*2fAnalytic*2f*20*7c*20filter*20*40message*20not*20like*20*2fTranscript*2f*0a*7c*20filter*20*40message*20not*20like*20*2fWebhook*2f*20*7c*20filter*20*40message*20not*20like*20*2fMeetingBot*2f*20*0a*7c*20limit*2010000~queryId~'0551e814-f51a-4339-8372-80d7ba4cef27~source~(~'*2a)~lang~'CWLI~logClass~'STANDARD~accountIDs~(~'All)~queryBy~'allLogGroups)...
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
Open upload file menu
Tools
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Your Jiminny chats aren’t used to improve our models. Gemini is AI and can make mistakes, including about people.
Your privacy & Gemini Opens in a new window
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Summarize page
Summarize page
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accessibility
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NULL
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
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2026-04-14T08:12:45.872468+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-14/1776 /Users/lukas/.screenpipe/data/data/2026-04-14/1776154365872_m2.jpg...
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Settings — Work
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
CloudWatch | us-east-2
CloudWatch | us-east-2
Settings
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
Open upload file menu
Tools
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Pro
Send message
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accessibility
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
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Find in Settings
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General
Default browser
Default browser
Psst, Firefox isn’t your default.
Make default
Make default
Startup
Startup
Open previous windows and tabs
Open previous windows and tabs
Always check if Firefox is your default browser
Always check if Firefox is your default browser
Import browser data
Import browser data
Bring your bookmarks, passwords, history, extensions, and autofill data from another browser.
Import data
Import data
Profiles
Profiles...
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jiminny
Jiminny
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
CloudWatch | us-east-2
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Settings
Settings
Close tab
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WORK, Google Account: [EMAIL]
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Conversation with Gemini
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
Show more options
Show thinking
Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
Open upload file menu
Tools
Open mode picker
Pro
Send message
Your Jiminny chats aren’t used to improve our models. Gemini is AI and can make mistakes, including about people.
Your privacy & Gemini Opens in a new window
Your privacy & Gemini
Opens in a new window
Summarize page
Summarize page
General
Home
Search
Privacy & Security
Sync
AI Controls
Firefox Labs
More from Mozilla
Extensions & Themes
Extensions & Themes
Firefox Support
Firefox Support
Your browser is being managed by your organization.
Your browser is being managed by your organization.
Find in Settings
General
General
Default browser
Default browser
Psst, Firefox isn’t your default.
Make default
Make default
Startup
Startup
Open previous windows and tabs
Open previous windows and tabs
Always check if Firefox is your default browser
Always check if Firefox is your default browser
Import browser data
Import browser data
Bring your bookmarks, passwords, history, extensions, and autofill data from another browser.
Import data
Import data
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Profiles
Each profile has separate browsing data and settings, including history, passwords, and more.
Learn more
Learn more
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When you open a link, image or media in a new tab, switch to it immediately
When you open a link, image or media in a new tab, switch to it immediately
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options","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":20,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Dealing with missing features right when you need them is incredibly frustrating. Assuming \"meemt\" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Since \"speaker data\" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. You Need \"Speaker Notes\" for Google Slides","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. You Need \"Speaker Notes\" for Google Slides","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Reality:","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"However, this relies on a specific \"Present a Tab\" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Google Workspace Updates. Opens side panel.","depth":24,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"How to set it up (The Firefox Workaround):","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can still present and read your notes in Firefox by manually managing your windows.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open your Google Slides presentation in a standard Firefox window.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Click the dropdown arrow next to the","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Slideshow","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"button in the top right corner.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Select","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Presenter view","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to pop your speaker notes out into a separate, smaller window.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Skywork. Opens side panel.","depth":26,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Join your Google Meet in a different Firefox window.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Click","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Present now","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and choose the","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Window","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"option.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Select the window displaying your main slides (do not select your separate speaker notes window).","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. 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Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How to set it up:","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Turn on built-in captions:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CC","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"button at the bottom of your Meet screen to toggle them on.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Search for a Firefox add-on:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Fellow.ai. 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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
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Configure SSH access to multiple environment - Engineering - Confluence
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SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
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Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
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Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
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Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
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Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
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Assuming \"meemt\" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.","depth":24,"bounds":{"left":0.10390625,"top":0.30069444,"width":0.13046876,"height":0.10486111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Since \"speaker data\" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.","depth":24,"bounds":{"left":0.10390625,"top":0.4201389,"width":0.13125,"height":0.06875},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. You Need \"Speaker Notes\" for Google Slides","depth":23,"bounds":{"left":0.10390625,"top":0.52152777,"width":0.13242188,"height":0.033333335},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. You Need \"Speaker Notes\" for Google Slides","depth":24,"bounds":{"left":0.10390625,"top":0.5229167,"width":0.12070312,"height":0.03125},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Reality:","depth":24,"bounds":{"left":0.10390625,"top":0.5625,"width":0.036328126,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.","depth":24,"bounds":{"left":0.10390625,"top":0.5625,"width":0.13242188,"height":0.050694443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"However, this relies on a specific \"Present a Tab\" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.","depth":24,"bounds":{"left":0.10390625,"top":0.5986111,"width":0.12539062,"height":0.10486111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Google Workspace Updates. Opens side panel.","depth":24,"bounds":{"left":0.13710937,"top":0.68958336,"width":0.01015625,"height":0.013888889},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"How to set it up (The Firefox Workaround):","depth":24,"bounds":{"left":0.10390625,"top":0.71805555,"width":0.12851563,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can still present and read your notes in Firefox by manually managing your windows.","depth":24,"bounds":{"left":0.10390625,"top":0.7361111,"width":0.12617187,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open your Google Slides presentation in a standard Firefox window.","depth":26,"bounds":{"left":0.11796875,"top":0.7777778,"width":0.115625,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Click the dropdown arrow next to the","depth":26,"bounds":{"left":0.11796875,"top":0.8194444,"width":0.10703125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Slideshow","depth":26,"bounds":{"left":0.11796875,"top":0.8375,"width":0.03125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"button in the top right corner.","depth":26,"bounds":{"left":0.14921875,"top":0.8375,"width":0.08515625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Select","depth":26,"bounds":{"left":0.11796875,"top":0.8611111,"width":0.01953125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Presenter view","depth":26,"bounds":{"left":0.1375,"top":0.8611111,"width":0.0453125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to pop your speaker notes out into a separate, smaller window.","depth":26,"bounds":{"left":0.11796875,"top":0.8611111,"width":0.10078125,"height":0.050694443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Skywork. Opens side panel.","depth":26,"bounds":{"left":0.16523437,"top":0.8979167,"width":0.01015625,"height":0.013888889},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Join your Google Meet in a different Firefox window.","depth":26,"bounds":{"left":0.11796875,"top":0.92083335,"width":0.103125,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Click","depth":26,"bounds":{"left":0.11796875,"top":0.9625,"width":0.015234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Present now","depth":26,"bounds":{"left":0.13320312,"top":0.9625,"width":0.037890624,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and choose the","depth":26,"bounds":{"left":0.17109375,"top":0.9625,"width":0.047265626,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Window","depth":26,"bounds":{"left":0.11796875,"top":0.98055553,"width":0.02421875,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"option.","depth":26,"bounds":{"left":0.1421875,"top":0.98055553,"width":0.02109375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Select the window displaying your main slides (do not select your separate speaker notes window).","depth":26,"bounds":{"left":0.11796875,"top":1.0,"width":0.11328125,"height":-0.0041667223},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.","depth":26,"bounds":{"left":0.11796875,"top":1.0,"width":0.11835937,"height":-0.06388891},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. You Need \"Speaker Labels\" or Transcripts","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. You Need \"Speaker Labels\" or Transcripts","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Reality:","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How to set it up:","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Turn on built-in captions:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CC","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"button at the bottom of your Meet screen to toggle them on.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Search for a Firefox add-on:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Fellow.ai. Opens side panel.","depth":26,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Switch browsers temporarily:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Sources","depth":23,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Sources","depth":25,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"Enter a prompt for Gemini\nencrypted","depth":20,"bounds":{"left":0.109375,"top":0.8354167,"width":0.125,"height":0.016666668},"value":"Enter a prompt for Gemini\nencrypted","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Enter a prompt for Gemini","depth":21,"bounds":{"left":0.1171875,"top":0.8354167,"width":0.08203125,"height":0.016666668},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"encrypted","depth":21,"bounds":{"left":0.10820313,"top":0.8354167,"width":0.0078125,"height":0.016666668},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Open upload file menu","depth":20,"bounds":{"left":0.1046875,"top":0.86527777,"width":0.015625,"height":0.027777778},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Tools","depth":18,"bounds":{"left":0.1234375,"top":0.86527777,"width":0.015625,"height":0.027777778},"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,"bounds":{"left":0.190625,"top":0.8645833,"width":0.03046875,"height":0.027777778},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Pro","depth":23,"bounds":{"left":0.196875,"top":0.87222224,"width":0.00859375,"height":0.013194445},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Microphone","depth":19,"bounds":{"left":0.2234375,"top":0.8645833,"width":0.015625,"height":0.027777778},"role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Your Jiminny chats aren’t used to improve our models. 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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
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Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 1 Q2 - Platform Team - Scrum Board - Jira
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
Console Home | Console Home | us-east-2
Console Home | Console Home | us-east-2
SecurityGroup | EC2 | us-east-2
SecurityGroup | EC2 | us-east-2
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
SRD-6779 | JY-20632 | Unable to log in to Sidekick with SSO by yalokin-jiminny · Pull Request #11935 · jiminny/app
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
Jy 19798 evaluation for ai activity types by nikolaybiaivanov · Pull Request #468 · jiminny/prophet
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Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
Configure SSH access to multiple environment - Engineering - Confluence
Configure SSH access to multiple environment - Engineering - Confluence
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
Listen
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Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
Sources
Sources
I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
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Assuming \"meemt\" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.","depth":24,"bounds":{"left":0.10390625,"top":0.30069444,"width":0.13046876,"height":0.10486111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Since \"speaker data\" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.","depth":24,"bounds":{"left":0.10390625,"top":0.4201389,"width":0.13125,"height":0.06875},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. You Need \"Speaker Notes\" for Google Slides","depth":23,"bounds":{"left":0.10390625,"top":0.52152777,"width":0.13242188,"height":0.033333335},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. You Need \"Speaker Notes\" for Google Slides","depth":24,"bounds":{"left":0.10390625,"top":0.5229167,"width":0.12070312,"height":0.03125},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The Reality:","depth":24,"bounds":{"left":0.10390625,"top":0.5625,"width":0.036328126,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.","depth":24,"bounds":{"left":0.10390625,"top":0.5625,"width":0.13242188,"height":0.050694443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"However, this relies on a specific \"Present a Tab\" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.","depth":24,"bounds":{"left":0.10390625,"top":0.5986111,"width":0.12539062,"height":0.10486111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Google Workspace Updates. Opens side panel.","depth":24,"bounds":{"left":0.13710937,"top":0.68958336,"width":0.01015625,"height":0.013888889},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"How to set it up (The Firefox Workaround):","depth":24,"bounds":{"left":0.10390625,"top":0.71805555,"width":0.12851563,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can still present and read your notes in Firefox by manually managing your windows.","depth":24,"bounds":{"left":0.10390625,"top":0.7361111,"width":0.12617187,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open your Google Slides presentation in a standard Firefox window.","depth":26,"bounds":{"left":0.11796875,"top":0.7777778,"width":0.115625,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Click the dropdown arrow next to the","depth":26,"bounds":{"left":0.11796875,"top":0.8194444,"width":0.10703125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Slideshow","depth":26,"bounds":{"left":0.11796875,"top":0.8375,"width":0.03125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"button in the top right corner.","depth":26,"bounds":{"left":0.14921875,"top":0.8375,"width":0.08515625,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Select","depth":26,"bounds":{"left":0.11796875,"top":0.8611111,"width":0.01953125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Presenter view","depth":26,"bounds":{"left":0.1375,"top":0.8611111,"width":0.0453125,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to pop your speaker notes out into a separate, smaller window.","depth":26,"bounds":{"left":0.11796875,"top":0.8611111,"width":0.10078125,"height":0.050694443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View source details for citation from Skywork. Opens side panel.","depth":26,"bounds":{"left":0.16523437,"top":0.8979167,"width":0.01015625,"height":0.013888889},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Join your Google Meet in a different Firefox window.","depth":26,"bounds":{"left":0.11796875,"top":0.92083335,"width":0.103125,"height":0.03263889},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Click","depth":26,"bounds":{"left":0.11796875,"top":0.9625,"width":0.015234375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Present now","depth":26,"bounds":{"left":0.13320312,"top":0.9625,"width":0.037890624,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and choose the","depth":26,"bounds":{"left":0.17109375,"top":0.9625,"width":0.047265626,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Window","depth":26,"bounds":{"left":0.11796875,"top":0.98055553,"width":0.02421875,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"option.","depth":26,"bounds":{"left":0.1421875,"top":0.98055553,"width":0.02109375,"height":0.014583333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Select the window displaying your main slides (do not select your separate speaker notes window).","depth":26,"bounds":{"left":0.11796875,"top":1.0,"width":0.11328125,"height":-0.0041667223},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.","depth":26,"bounds":{"left":0.11796875,"top":1.0,"width":0.11835937,"height":-0.06388891},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. 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Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How to set it up:","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Turn on built-in captions:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Google Meet has its own live captions that natively identify who is speaking, even in Firefox. 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JY-20543 add AJ reports User pilot tracking by Lak JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
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JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
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Ask Jiminny test report - 8 Apr 2026 - Ask Jiminny test report - 13 Apr 2026.pdf
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Service-Desk - Queues - Platform team - Service space - Jira
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JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
JY-20543 add AJ reports User pilot tracking by LakyLak · Pull Request #11932 · jiminny/app
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You said why I can't see speaker data on meemt in firefox. ho wto set it up
You said
why I can't see speaker data on meemt in firefox. ho wto set it up
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Gemini said
Gemini said
Dealing with missing features right when you need them is incredibly frustrating. Assuming "meemt" means Google Meet, the reason you can't see your speaker data comes down to how Firefox interacts with Google's platform compared to Chrome.
Since "speaker data" can mean a couple of different things in a meeting, here are the two most likely causes for your issue and exactly how to get things working.
1. You Need "Speaker Notes" for Google Slides
1. You Need "Speaker Notes" for Google Slides
The Reality:
Google Meet has a native feature that lets you see your presentation's speaker notes right inside the video call interface.
However, this relies on a specific "Present a Tab" technology built exclusively for Google Chrome. Firefox handles screen sharing differently, so that native integration simply won't load.
View source details for citation from Google Workspace Updates. Opens side panel.
How to set it up (The Firefox Workaround):
You can still present and read your notes in Firefox by manually managing your windows.
Open your Google Slides presentation in a standard Firefox window.
Click the dropdown arrow next to the
Slideshow
button in the top right corner.
Select
Presenter view
to pop your speaker notes out into a separate, smaller window.
View source details for citation from Skywork. Opens side panel.
Join your Google Meet in a different Firefox window.
Click
Present now
and choose the
Window
option.
Select the window displaying your main slides (do not select your separate speaker notes window).
Resize your windows on your monitor so you can comfortably read the notes window while keeping an eye on the Meet window.
2. You Need "Speaker Labels" or Transcripts
2. You Need "Speaker Labels" or Transcripts
The Reality:
If you are trying to use a third-party AI note-taker (like Otter.ai, Tactiq, or tl;dv) to capture transcriptions and see who is speaking, Firefox is likely the roadblock. Firefox has strict privacy guardrails that prevent extensions from capturing internal browser audio easily, so most developers only build these tools for Chrome.
How to set it up:
Turn on built-in captions:
Google Meet has its own live captions that natively identify who is speaking, even in Firefox. Click the
CC
button at the bottom of your Meet screen to toggle them on.
Search for a Firefox add-on:
Check the Mozilla Add-ons store to see if your preferred tool actually has a supported Firefox version (for example, Fellow.ai offers one).
View source details for citation from Fellow.ai. Opens side panel.
Switch browsers temporarily:
If your specific transcription tool is explicitly Chrome-only, you will unfortunately need to join that specific meeting using a Chromium-based browser like Chrome, Edge, or Brave to capture the data.
Using Meet's built-in closed captions or the manual Presenter view workaround will get your speaker data back on track without forcing you to completely abandon Firefox.
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I men in dia (arc) I can see my headphones in both microphone and speakers
I men in dia (arc) I can see my headphones in both microphone and speakers
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