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JY-20676 delete AJ reports related objects by Laky JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app — Work...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
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LakyLak commented 2 days ago •
LakyLak
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
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LakyLak commented 2 days ago •
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Tabs from other devices
Open history (⇧⌘H)
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SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
jiminny.sentry.io
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app...
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SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
jiminny.sentry.io
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app...
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JY-20915 add alias for EU by LakyLak · Pull Reques JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app — Work...
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github.com/jiminny/app/pull/12098
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app...
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JY-20915 add alias for EU by LakyLak · Pull Reques JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app — Work...
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github.com/jiminny/app/pull/12105
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JY-20676 delete AJ reports related objects by Laky JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app — Work...
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github.com/jiminny/app/pull/12098
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2...
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JY-20676 delete AJ reports related objects by Laky JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app — Work...
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github.com/jiminny/app/pull/12098
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
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JY-20676 delete AJ reports related objects #12098 Edit title
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visual_change
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
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JY-20676 delete AJ reports related objects #12098 Edit title
JY-20676 delete AJ reports related objects
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12098
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JY-20676 delete AJ reports related objects by Laky JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app — Work...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
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JY-20676 delete AJ reports related objects by Laky JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app — Work...
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
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LakyLak commented 2 days ago •
LakyLak
LakyLak
commented
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edited by nikolay-yankov...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
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JY-20676 delete AJ reports related objects by Laky JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app — Work...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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JY-20676 delete AJ reports related objects #12098 Edit title
JY-20676 delete AJ reports related objects
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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JY-20676 delete AJ reports related objects #12098 Edit title
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JY-20676 delete AJ reports related objects by Laky JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app — Work...
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github.com/jiminny/app/pull/12098
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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Pipelines - jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
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JY-20676 delete AJ reports related objects #12098 Edit title
JY-20676 delete AJ reports related objects
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
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org avatar Current organization: jiminny
Home
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Dashboard All Pipelines...
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New Device Logged In From Firefox Extension - kova New Device Logged In From Firefox Extension - kovaliklukas@gmail.com - Gmail — Personal...
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mail.google.com/mail/u/0/#inbox/FMfcgzQgLsBnWDSZHL mail.google.com/mail/u/0/#inbox/FMfcgzQgLsBnWDSZHLwxGzsLfnHRkbzk...
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PostmanFileEditViewWindowHelp(MySQL 11.4.9-MariaDB PostmanFileEditViewWindowHelp(MySQL 11.4.9-MariaDB-log) PROD/jiminny/playbooksQ plTABLESactivity_playsactivity_upload_settingsai_crm_template_fieldsai_crm_template_filtersai_crm_template_logai_crm_template_runsai_crm_template_write_logsai_crm_templatesplayback_theme_topic_triggersplayback_theme_topicsplayback_themesactivity_field_ididuuid3502 JPK&V¾q5yäY3503 FZE"Áýpù2i3505 N*Àº|3/W[s=V÷3506 B¾zE1Pp£]ÏYUk3507@ãGX,« .=OÌR3520 @°Ã|оù_ñ[3"3522 F®ÇüÄ¿©ú)¿803523 EVL%À5cT6lq4777 D.Ü}) ·C=j°Â5328 CÔHPcÔBuj£:a'PSjiminnySelect DatabaseStructure>0 lolContentRelationsTriggersTable InfoQueryC IS NULLteam_idactivity_type531 task531 © event531 • task531 • event531 • event531 • task531 • task531 • event938 task1106 taskactivity_field_idnameNULL RoofSnap Sales TeamNULL RoofSnap SalesNULL TESTNULL TEST ENULL TESTENULL RoofSnap Sales TeamNULL TESTNULL TEST ENULL Sales PlaybookNULL Sales Team | Taskis_selectable$131100% <78• Thu 21 May 17:59:57Table HistoryUsersConsole+Filterai_activity_type_detection_enabledcreated_at0 2022-05-13 1.0 2022-05-13 1.0 2022-05-16 1.0 2022-05-16 10 2022-05-16 1,0 2022-05-20 10 2022-05-20 10 2022-05-20 10 2024-05-0310 2025-10-17 14'141.11SlackIII+17 rows of 2 228 match filter...
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PostmanFileEditViewWindowHelp(MySQL 11.4.9-MariaDB PostmanFileEditViewWindowHelp(MySQL 11.4.9-MariaDB-log) PROD/jiminny/playbooksQ plTABLESactivity_playsactivity_upload_settingsai_crm_template_fieldsai_crm_template_filtersai_crm_template_logai_crm_template_runsai_crm_template_write_logsai_crm_templatesplayback_theme_topic_triggersplayback_theme_topicsplayback_themesactivity_field_ididuuid3502 JPK&V¾q5yäY3503 FZE"Áýpù2i3505 N*Àº|3/W[s=V÷3506 B¾zE1Pp£]ÏYUk3507@ãGX,« .=OÌR3520 @°Ã|оù_ñ[3"3522 F®ÇüÄ¿©ú)¿803523 EVL%À5cT6lq4777 D.Ü}) ·C=j°Â5328 CÔHPcÔBuj£:a'PSjiminnySelect DatabaseStructure>0 lolContentRelationsTriggersTable InfoQueryC IS NULLteam_idactivity_type531 task531 © event531 • task531 • event531 • event531 • task531 • task531 • event938 task1106 taskactivity_field_idnameNULL RoofSnap Sales TeamNULL RoofSnap SalesNULL TESTNULL TEST ENULL TESTENULL RoofSnap Sales TeamNULL TESTNULL TEST ENULL Sales PlaybookNULL Sales Team | Taskis_selectable$131100% <78• Thu 21 May 17:59:57Table HistoryUsersConsole+Filterai_activity_type_detection_enabledcreated_at0 2022-05-13 1.0 2022-05-13 1.0 2022-05-16 1.0 2022-05-16 10 2022-05-16 1,0 2022-05-20 10 2022-05-20 10 2022-05-20 10 2024-05-0310 2025-10-17 14'141.11SlackIII+17 rows of 2 228 match filter...
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375616248_m1.jpg...
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Firefox
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New Device Logged In From Firefox Extension - kova New Device Logged In From Firefox Extension - kovaliklukas@gmail.com - Gmail — Personal...
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1
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mail.google.com/mail/u/0/#inbox/FMfcgzQgLsBnWDSZHL mail.google.com/mail/u/0/#inbox/FMfcgzQgLsBnWDSZHLwxGzsLfnHRkbzk...
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Close tab
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins...
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Close tab
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins...
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68758
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2026-05-21T15:00:20.444778+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375620444_m1.jpg...
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Firefox
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Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Ге Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа — Personal...
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1
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desktop.bg/mini_pcs-apple-Mac_Studio_M4-apple_mac_ desktop.bg/mini_pcs-apple-Mac_Studio_M4-apple_mac_studio_m4_max_mu963zea_upgrade_z1cd_40GPU?conf[]=106391&conf[]=113420&conf[]=126083...
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PostmanFileEditViewWindowHelp(MySQL 11.4.9-MariaDB PostmanFileEditViewWindowHelp(MySQL 11.4.9-MariaDB-log) PROD/jiminny/playbooksQ plTABLESactivity_playsactivity_upload_settingsai_crm_template_fieldsai_crm_template_filtersai_crm_template_logai_crm_template_runsai_crm_template_write_logsai_crm_templatesplayback_theme_topic_triggersplayback_theme_topicsplayback_themesplaybook_categoriesplaybook_layoutsplaybooksplaylist_activitiesplaylist_sharesplaylistsVactivity_field_ididuuid3502 JPK&V¾q5yäY3503 FZE"Áýpù2i3505 N*Àº|3/W[s=V÷3506 B¾zE1Pp£]ÏYUk3507@ãGX, « .=OIR3520 @°Ã|оù_ñ[3"3522 F®ÇüÄ¿©ú)¿803523 EVL%À5cT6lq4777 D.Ü)) ·C=°Â5328 CÔHPcÔBuj£:a'5329 B.=iXI#°áîy»½'s5344 ЕCхЗÁ«JÊ>>5346 D·¾\U;/CámæL^5355 HPulÜc®?GpüZ5363 MvùË}i°H50f5365 MöeA,ùc Sa5462 FẢõuBmÓé/9xªÛjiminnySelect DatabaseStructure>0.ldlolО.ContentRelationsTriggersTable InfoC IS NULLteam_idactivity_type531 • task531 © event531 • task531 • event531 • event531 • task531 • task531 • event938 task1106 task1106 • event1108 © task1108 task1108 task1108 task1108 task1121 © taskactivity_field_idnameNULL RoofSnap Sales TeamNULL RoofSnap SalesNULL TESTNULL TEST ENULL TESTENULL RoofSnap Sales TeamNULL TESTNULL TESTENULL Sales PlaybookNULL Sales Team | TaskNULL Sales Team | EventNULL Sales PlaybackNULL Sales testNULL testNULL testNULL testNULL Salesis_selectable1100% C8• Thu 21 May 18:00:20QueryTable HistoryUsersConsoleFilterai_activity_type_detection_enabledcreated_at0 2022-05-13 1.0 2022-05-13 1.0 2022-05-16 1.0 2022-05-16 1.0 2022-05-16 1,0 2022-05-20 10 2022-05-20 10 2022-05-20 10 2024-05-0310 2025-10-17 140 2025-10-17 140 2025-10-28 10 2025-10-28 1.0 2025-11-05 00 2025-11-05 140 2025-11-06 110 2026-02-26 1+III|+-17 rows of 2 228 match filter...
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2091115884683753725
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click
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PostmanFileEditViewWindowHelp(MySQL 11.4.9-MariaDB PostmanFileEditViewWindowHelp(MySQL 11.4.9-MariaDB-log) PROD/jiminny/playbooksQ plTABLESactivity_playsactivity_upload_settingsai_crm_template_fieldsai_crm_template_filtersai_crm_template_logai_crm_template_runsai_crm_template_write_logsai_crm_templatesplayback_theme_topic_triggersplayback_theme_topicsplayback_themesplaybook_categoriesplaybook_layoutsplaybooksplaylist_activitiesplaylist_sharesplaylistsVactivity_field_ididuuid3502 JPK&V¾q5yäY3503 FZE"Áýpù2i3505 N*Àº|3/W[s=V÷3506 B¾zE1Pp£]ÏYUk3507@ãGX, « .=OIR3520 @°Ã|оù_ñ[3"3522 F®ÇüÄ¿©ú)¿803523 EVL%À5cT6lq4777 D.Ü)) ·C=°Â5328 CÔHPcÔBuj£:a'5329 B.=iXI#°áîy»½'s5344 ЕCхЗÁ«JÊ>>5346 D·¾\U;/CámæL^5355 HPulÜc®?GpüZ5363 MvùË}i°H50f5365 MöeA,ùc Sa5462 FẢõuBmÓé/9xªÛjiminnySelect DatabaseStructure>0.ldlolО.ContentRelationsTriggersTable InfoC IS NULLteam_idactivity_type531 • task531 © event531 • task531 • event531 • event531 • task531 • task531 • event938 task1106 task1106 • event1108 © task1108 task1108 task1108 task1108 task1121 © taskactivity_field_idnameNULL RoofSnap Sales TeamNULL RoofSnap SalesNULL TESTNULL TEST ENULL TESTENULL RoofSnap Sales TeamNULL TESTNULL TESTENULL Sales PlaybookNULL Sales Team | TaskNULL Sales Team | EventNULL Sales PlaybackNULL Sales testNULL testNULL testNULL testNULL Salesis_selectable1100% C8• Thu 21 May 18:00:20QueryTable HistoryUsersConsoleFilterai_activity_type_detection_enabledcreated_at0 2022-05-13 1.0 2022-05-13 1.0 2022-05-16 1.0 2022-05-16 1.0 2022-05-16 1,0 2022-05-20 10 2022-05-20 10 2022-05-20 10 2024-05-0310 2025-10-17 140 2025-10-17 140 2025-10-28 10 2025-10-28 1.0 2025-11-05 00 2025-11-05 140 2025-11-06 110 2026-02-26 1+III|+-17 rows of 2 228 match filter...
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68759
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2462
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28
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2026-05-21T15:00:23.082612+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375623082_m1.jpg...
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Firefox
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Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Ге Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа — Personal...
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1
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desktop.bg
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desktop.bg
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Close tab
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins
Завеждане на щета онлайн | Euroins
Screenpipe — Archive
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Reminders
Reminders
Photos - Google Photos
Photos - Google Photos
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
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Nginx Proxy Manager
Nginx Proxy Manager
Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
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Преоценени продукти
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Доставка
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Плащане
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Условия за сервизно обслужване
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02 490 1112
02 490 1112
Компютри от desktop.bg
Компютри от desktop.bg
Продукти
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ТЪРСЕНЕ
ТЪРСЕНЕ
ТЪРСИ
Моят профил
Моят профил
Начало
Начало
Всички Mini PC
Всички
Mini PC
Всички mini pc Apple
Всички mini pc
Apple
Всички mini pc Mac Studio M4
Всички mini pc
Mac Studio M4
Apple Mac Studio M4 Max
Apple Mac Studio M4 Max
Apple Mac Studio M4 Max
Вземи на лизинг за 150.34 € / 294.05 лв. за 48 месеца.
Вижте повече
Вижте повече
Кратко описание
Кратко описание
Снимки
Снимки
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
НАПРЕД
НАПРЕД
Изпращане
Изпращане
Публикуване
Публикуване
СРОК НА ДОСТАВКА 90 ДНИ
Цена:
4876
€
9536
.66
лв.
ВИЕ ПОЛУЧАВАТЕ
ВИЕ ПОЛУЧАВАТЕ
Apple Mac Studio M4 Max
3149
€
6158
.93
лв.
128GB (131072MB) +1319 €/+2579.75 лв.
1319
€
2579
.75
лв.
1TB SSD Apple +269 €/+526.12 лв.
269
€
526
.12
лв.
10 Gigabit Ethernet +139 €/+271.86 лв.
139
€
271
.86
лв.
Безплатна доставка до офис Спиди
Безплатна доставка до офис Спиди
за поръчки над 25 € / 48.90 лв.
Количество:
НАМАЛЯВАНЕ
НАМАЛЯВАНЕ
1
УВЕЛИЧАВАНЕ
УВЕЛИЧАВАНЕ
ДОБАВИ В КОЛИЧКАТА
ДОБАВИ В КОЛИЧКАТА
Добави за сравнение
Добави
за сравнение
Вземи на лизинг за 150.34 € / 294.05 лв. за 48 месеца виж лизинговите схеми
Вземи на лизинг за
150.34 € / 294.05 лв. за 48 месеца
виж лизинговите схеми
ОСНОВНИ ХАРАКТЕРИСТИКИ
ОСНОВНИ ХАРАКТЕРИСТИКИ
С възможност за ъпгрейд
Apple M4 Max (16-ядрен)
Apple M4 Max (40-ядрен графичен процесор)
от 48GB до 128GB
от 512GB SSD до 8TB SSD
пълни характеристики
пълни характеристики
Продукт с предварителна поръчка
Продукт с предварителна поръчка
Този продукт може да бъде доставен по поръчка на клиента. Срокът за доставка е 90 дни.
Кратко описание
Кратко описание
Технически характеристики
Технически характеристики
Характеристики
Характеристики
СЕРИЯ
Mac Studio M4
Mac Studio M4...
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Gigabit Ethernet +139 €/+271.86 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(16-ядрен)","depth":12,"bounds":{"left":0.7152593,"top":0.4688747,"width":0.04488032,"height":0.033918597},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"","depth":12,"bounds":{"left":0.70794547,"top":0.5151636,"width":0.005319149,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Apple M4 Max (40-ядрен графичен процесор)","depth":12,"bounds":{"left":0.7152593,"top":0.5139665,"width":0.04488032,"height":0.05347167},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"","depth":12,"bounds":{"left":0.70794547,"top":0.5798085,"width":0.005319149,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"от 48GB до 128GB","depth":12,"bounds":{"left":0.7152593,"top":0.5786113,"width":0.045877658,"height":0.014365523},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"","depth":12,"bounds":{"left":0.70794547,"top":0.60614526,"width":0.005319149,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"от 512GB SSD до 8TB SSD","depth":12,"bounds":{"left":0.7152593,"top":0.6049481,"width":0.054521278,"height":0.033918597},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"пълни характеристики","depth":10,"bounds":{"left":0.70794547,"top":0.65163606,"width":0.0631649,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"пълни характеристики","depth":11,"bounds":{"left":0.70794547,"top":0.6528332,"width":0.048204787,"height":0.012769354},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"","depth":11,"bounds":{"left":0.75731385,"top":0.6552275,"width":0.0039893617,"height":0.009976057},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"","depth":9,"bounds":{"left":0.61452794,"top":1.0,"width":0.008643617,"height":-0.059457302},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Продукт с предварителна поръчка","depth":9,"bounds":{"left":0.62948805,"top":1.0,"width":0.32446808,"height":-0.05267358},"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Продукт с предварителна поръчка","depth":10,"bounds":{"left":0.62948805,"top":1.0,"width":0.09591091,"height":-0.053471684},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Този продукт може да бъде доставен по поръчка на клиента. Срокът за доставка е 90 дни.","depth":10,"bounds":{"left":0.62948805,"top":1.0,"width":0.1966423,"height":-0.076217055},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Кратко описание","depth":12,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Кратко описание","depth":13,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Технически характеристики","depth":12,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Технически характеристики","depth":13,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Характеристики","depth":9,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Характеристики","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"СЕРИЯ","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Mac Studio M4","depth":12,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Mac Studio M4","depth":13,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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4623080765912876997
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5359033547890298731
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visual_change
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NULL
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💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
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Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
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Продукти
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ТЪРСЕНЕ
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Всички mini pc Mac Studio M4
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Mac Studio M4
Apple Mac Studio M4 Max
Apple Mac Studio M4 Max
Apple Mac Studio M4 Max
Вземи на лизинг за 150.34 € / 294.05 лв. за 48 месеца.
Вижте повече
Вижте повече
Кратко описание
Кратко описание
Снимки
Снимки
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
Mini PC Apple Mac Studio M4 Max
НАПРЕД
НАПРЕД
Изпращане
Изпращане
Публикуване
Публикуване
СРОК НА ДОСТАВКА 90 ДНИ
Цена:
4876
€
9536
.66
лв.
ВИЕ ПОЛУЧАВАТЕ
ВИЕ ПОЛУЧАВАТЕ
Apple Mac Studio M4 Max
3149
€
6158
.93
лв.
128GB (131072MB) +1319 €/+2579.75 лв.
1319
€
2579
.75
лв.
1TB SSD Apple +269 €/+526.12 лв.
269
€
526
.12
лв.
10 Gigabit Ethernet +139 €/+271.86 лв.
139
€
271
.86
лв.
Безплатна доставка до офис Спиди
Безплатна доставка до офис Спиди
за поръчки над 25 € / 48.90 лв.
Количество:
НАМАЛЯВАНЕ
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1
УВЕЛИЧАВАНЕ
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Добави за сравнение
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за сравнение
Вземи на лизинг за 150.34 € / 294.05 лв. за 48 месеца виж лизинговите схеми
Вземи на лизинг за
150.34 € / 294.05 лв. за 48 месеца
виж лизинговите схеми
ОСНОВНИ ХАРАКТЕРИСТИКИ
ОСНОВНИ ХАРАКТЕРИСТИКИ
С възможност за ъпгрейд
Apple M4 Max (16-ядрен)
Apple M4 Max (40-ядрен графичен процесор)
от 48GB до 128GB
от 512GB SSD до 8TB SSD
пълни характеристики
пълни характеристики
Продукт с предварителна поръчка
Продукт с предварителна поръчка
Този продукт може да бъде доставен по поръчка на клиента. Срокът за доставка е 90 дни.
Кратко описание
Кратко описание
Технически характеристики
Технически характеристики
Характеристики
Характеристики
СЕРИЯ
Mac Studio M4
Mac Studio M4...
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68762
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2462
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Firefox
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Ambulatory sheet - Paperless-ngx — Personal
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1
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💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа...
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
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Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
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💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
Close tab
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
Close tab
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Close tab
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
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💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
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[JY-20879] Enable users to use their new activity types - Jira
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[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
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[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Git Branch JY-20676-delete-report-related-objects
JY-20676-delete-report-related-objects
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Pipelines app #58666
app #58666
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6h ago
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ARM X-Large
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JY-20676-delete-report-related-objects
JY-20676-delete-report-related-objects
PR /
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#12098
#
12098
/
Open commit on version control site
a6ed8e9
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& Message
Avatar of Lukas Kovalik
Merge branch 'master' into JY-20676-delete-report-related-objects
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Status Passed Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2
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Status Passed Create mappings table in db for ElasticSearch indexes 4s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Failed Run PHPunit tests 7m 33s Find in Step Output Open step output in new tab Open raw step output in new tab
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Fix error (Beta)
Explain error
#!/bin/bash -eo pipefail
export
SYMFONY_DEPRECATIONS_HELPER=weak
echo
-e
"\nxdebug.mode=coverage\nxdebug.coverage_output_dir=/home/circleci/project\nzend_extension=xdebug.so\n"
>> /usr/
local
/etc/php/conf.d/docker-php-ext-xdebug.ini
vendor/bin/paratest --coverage-clover coverage.xml --log-junit execution.xml
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Merge branch 'master' into JY-20676-delete-report-related-objects
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Status Passed Spin up environment 44s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Spin up environment
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44s
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Status Passed Container cimg/mariadb:10.9.7 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container cimg/mariadb:10.9.7
Container cimg/mariadb:10.9.7
9m 22s
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Status Passed Container redis:5 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container redis:5
Container redis:5
9m 22s
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Status Passed Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2
Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2
9m 22s
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Status Passed Preparing environment variables 0s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Preparing environment variables
Preparing environment variables
0s
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Status Passed Attaching workspace 8s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Attaching workspace
Attaching workspace
8s
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Status Passed Restore Cache - Composer vendor cache (composer.lock) 5s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Restore Cache - Composer vendor cache (composer.lock)
Restore Cache - Composer vendor cache (composer.lock)
5s
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Status Passed Restore Cache - frontend build output (public/, this SHA) 0s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Restore Cache - frontend build output (public/, this SHA)
Restore Cache - frontend build output (public/, this SHA)
0s
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Status Passed Restore Cache - backend workspace cache 0s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Restore Cache - backend workspace cache
Restore Cache - backend workspace cache
0s
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Status Passed Restore Cache - MySQL test DB snapshot cache (this SHA) 0s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Restore Cache - MySQL test DB snapshot cache (this SHA)
Restore Cache - MySQL test DB snapshot cache (this SHA)
0s
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Status Passed Edit hosts file 2s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Edit hosts file
Edit hosts file
2s
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Status Passed composer install /w dev dependencies 34s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed composer install /w dev dependencies
composer install /w dev dependencies
34s
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Status Passed Cache .env file 3s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Cache .env file
Cache .env file
3s
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Status Passed Create jobs table migration 3s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Create jobs table migration
Create jobs table migration
3s
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Status Passed Run database migrations 6s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Run database migrations
Run database migrations
6s
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Status Passed Run database seeders 9s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Run database seeders
Run database seeders
9s
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Status Passed Run passport:install migrations 12s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Run passport:install migrations
Run passport:install migrations
12s
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Status Passed Wait for mysql to become online 2s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Wait for mysql to become online
Wait for mysql to become online
2s
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Open step output in new tab
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Status Passed Create mappings table in db for ElasticSearch indexes 4s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Create mappings table in db for ElasticSearch indexes
Create mappings table in db for ElasticSearch indexes
4s
Find in Step Output
Open step output in new tab
Open raw step output in new tab
Status Passed Create ElasticSearch schema 5s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Create ElasticSearch schema
Create ElasticSearch schema
5s
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Open raw step output in new tab
Status Passed Cache .env file 3s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Cache .env file
Cache .env file
3s
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Status Failed Run PHPunit tests 7m 33s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Failed Run PHPunit tests
Run PHPunit tests
7m 33s
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Fix error (Beta)
Explain error
#!/bin/bash -eo pipefail
export
SYMFONY_DEPRECATIONS_HELPER=weak
echo
-e
"\nxdebug.mode=coverage\nxdebug.coverage_output_dir=/home/circleci/project\nzend_extension=xdebug.so\n"
>> /usr/
local
/etc/php/conf.d/docker-php-ext-xdebug.ini
vendor/bin/paratest --coverage-clover coverage.xml --log-junit execution.xml
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2026-05-21T15:00:56.544178+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375656544_m2.jpg...
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Firefox
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test (891125) - jiminny/app — Work
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app.circleci.com/pipelines/github/jiminny/app/5866 app.circleci.com/pipelines/github/jiminny/app/58666/workflows/792a5739-75fa-4e5d-8655-68b7ef18914e/jobs/891125...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
New Tab
Customize sidebar
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org avatar Current organization: jiminny
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Git Branch JY-20676-delete-report-related-objects
JY-20676-delete-report-related-objects
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Pipelines app #58666
app #58666
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Workflows build_accept_deploy
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Jobs test (891125)
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test
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10m 5s
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6h ago
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0s
Executor / Resource Class
Docker
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ARM X-Large
Info Outline
Branch
JY-20676-delete-report-related-objects
JY-20676-delete-report-related-objects
PR /
Commit
#12098
#
12098
/
Open commit on version control site
a6ed8e9
Author
& Message
Avatar of Lukas Kovalik
Merge branch 'master' into JY-20676-delete-report-related-objects
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Status Passed Spin up environment 44s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Container cimg/mariadb:10.9.7 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container cimg/mariadb:10.9.7
Container cimg/mariadb:10.9.7
9m 22s
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Status Passed Container redis:5 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2
Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2
9m 22s
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Status Passed Preparing environment variables 0s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Attaching workspace 8s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Restore Cache - Composer vendor cache (composer.lock) 5s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Restore Cache - Composer vendor cache (composer.lock)
Restore Cache - Composer vendor cache (composer.lock)
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Status Passed Restore Cache - frontend build output (public/, this SHA) 0s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Restore Cache - backend workspace cache 0s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Restore Cache - MySQL test DB snapshot cache (this SHA) 0s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Restore Cache - MySQL test DB snapshot cache (this SHA)
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Status Passed Edit hosts file 2s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed composer install /w dev dependencies 34s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed composer install /w dev dependencies
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Status Passed Cache .env file 3s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Create jobs table migration 3s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Create jobs table migration
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Status Passed Run database migrations 6s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Run passport:install migrations 12s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Wait for mysql to become online 2s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Create mappings table in db for ElasticSearch indexes 4s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Create mappings table in db for ElasticSearch indexes
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4s
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Status Passed Create ElasticSearch schema 5s Find in Step Output Open step output in new tab Open raw step output in new tab
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Status Passed Cache .env file 3s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Cache .env file
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Status Failed Run PHPunit tests 7m 33s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Failed Run PHPunit tests
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7m 33s
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#!/bin/bash -eo pipefail
export
SYMFONY_DEPRECATIONS_HELPER=weak...
|
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raw step output in new tab","depth":13,"bounds":{"left":0.9690825,"top":0.3084597,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"Status Passed Cache .env file 3s Find in Step Output Open step output in new tab Open raw step output in new tab","depth":12,"bounds":{"left":0.117519945,"top":0.3547486,"width":0.87017953,"height":0.044692736},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXButton","text":"Status Passed Cache .env file","depth":13,"bounds":{"left":0.117519945,"top":0.35794094,"width":0.80950797,"height":0.03830806},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Cache .env 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tests","depth":16,"bounds":{"left":0.1434508,"top":0.4225858,"width":0.039893616,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"7m 33s","depth":14,"bounds":{"left":0.9183843,"top":0.4217877,"width":0.018783245,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Find in Step Output","depth":13,"bounds":{"left":0.9424867,"top":0.41380686,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Open step output in new tab","depth":13,"bounds":{"left":0.95578456,"top":0.41380686,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Open raw step output in new tab","depth":13,"bounds":{"left":0.9690825,"top":0.41380686,"width":0.013297873,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Fix error (Beta)","depth":13,"bounds":{"left":0.8756649,"top":0.46488428,"width":0.0546875,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Explain error","depth":13,"bounds":{"left":0.93301195,"top":0.46488428,"width":0.04936835,"height":0.031923383},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"#!/bin/bash -eo pipefail","depth":15,"bounds":{"left":0.12583111,"top":0.51755786,"width":0.06732048,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"export","depth":15,"bounds":{"left":0.12583111,"top":0.5319234,"width":0.016788565,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SYMFONY_DEPRECATIONS_HELPER=weak","depth":15,"bounds":{"left":0.14261968,"top":0.5319234,"width":0.092586435,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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5898202392568655670
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8036234059028396064
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visual_change
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accessibility
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NULL
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
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JY-20676-delete-report-related-objects
JY-20676-delete-report-related-objects
PR /
Commit
#12098
#
12098
/
Open commit on version control site
a6ed8e9
Author
& Message
Avatar of Lukas Kovalik
Merge branch 'master' into JY-20676-delete-report-related-objects
Steps
Steps
Tests tests
Tests
Timing timing
Timing
Artifacts artifacts
Artifacts
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Resources
Status Passed Spin up environment 44s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Spin up environment
Spin up environment
44s
Find in Step Output
Open step output in new tab
Open raw step output in new tab
Status Passed Container cimg/mariadb:10.9.7 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container cimg/mariadb:10.9.7
Container cimg/mariadb:10.9.7
9m 22s
Find in Step Output
Open step output in new tab
Open raw step output in new tab
Status Passed Container redis:5 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container redis:5
Container redis:5
9m 22s
Find in Step Output
Open step output in new tab
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Status Passed Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2
Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2
9m 22s
Find in Step Output
Open step output in new tab
Open raw step output in new tab
Status Passed Preparing environment variables 0s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Preparing environment variables
Preparing environment variables
0s
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Open step output in new tab
Open raw step output in new tab
Status Passed Attaching workspace 8s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Attaching workspace
Attaching workspace
8s
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Status Passed Restore Cache - Composer vendor cache (composer.lock) 5s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Restore Cache - Composer vendor cache (composer.lock)
Restore Cache - Composer vendor cache (composer.lock)
5s
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Status Passed Restore Cache - frontend build output (public/, this SHA) 0s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Restore Cache - frontend build output (public/, this SHA)
Restore Cache - frontend build output (public/, this SHA)
0s
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Status Passed Restore Cache - backend workspace cache 0s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Restore Cache - backend workspace cache
Restore Cache - backend workspace cache
0s
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Status Passed Restore Cache - MySQL test DB snapshot cache (this SHA) 0s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Restore Cache - MySQL test DB snapshot cache (this SHA)
Restore Cache - MySQL test DB snapshot cache (this SHA)
0s
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Status Passed Edit hosts file 2s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Edit hosts file
Edit hosts file
2s
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Status Passed composer install /w dev dependencies 34s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed composer install /w dev dependencies
composer install /w dev dependencies
34s
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Status Passed Cache .env file 3s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Cache .env file
Cache .env file
3s
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Status Passed Create jobs table migration 3s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Create jobs table migration
Create jobs table migration
3s
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Status Passed Run database migrations 6s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Run database migrations
Run database migrations
6s
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Status Passed Run database seeders 9s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Run database seeders
Run database seeders
9s
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Status Passed Run passport:install migrations 12s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Run passport:install migrations
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12s
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Status Passed Wait for mysql to become online 2s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Wait for mysql to become online
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2s
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Status Passed Create mappings table in db for ElasticSearch indexes 4s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Create mappings table in db for ElasticSearch indexes
Create mappings table in db for ElasticSearch indexes
4s
Find in Step Output
Open step output in new tab
Open raw step output in new tab
Status Passed Create ElasticSearch schema 5s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Create ElasticSearch schema
Create ElasticSearch schema
5s
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Open step output in new tab
Open raw step output in new tab
Status Passed Cache .env file 3s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Cache .env file
Cache .env file
3s
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Status Failed Run PHPunit tests 7m 33s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Failed Run PHPunit tests
Run PHPunit tests
7m 33s
Find in Step Output
Open step output in new tab
Open raw step output in new tab
Fix error (Beta)
Explain error
#!/bin/bash -eo pipefail
export
SYMFONY_DEPRECATIONS_HELPER=weak...
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68771
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NULL
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NULL
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NULL
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68775
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2463
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69
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2026-05-21T15:00:59.583995+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375659583_m2.jpg...
|
Firefox
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test (891125) - jiminny/app — Work
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1
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app.circleci.com/pipelines/github/jiminny/app/5866 app.circleci.com/pipelines/github/jiminny/app/58666/workflows/792a5739-75fa-4e5d-8655-68b7ef18914e/jobs/891125...
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monitor_2
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NULL
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NULL
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CloudWatch | us-east-2
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us-east-2.console.aws.amazon.com
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
Close tab
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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6h ago
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/
Learn more about resource classes in the docs (opens in new tab)
ARM X-Large
Info Outline
Branch
JY-20676-delete-report-related-objects
JY-20676-delete-report-related-objects
PR /
Commit
#12098
#
12098
/
Open commit on version control site
a6ed8e9
Author
& Message
Avatar of Lukas Kovalik
Merge branch 'master' into JY-20676-delete-report-related-objects
Steps
Steps
Tests tests
Tests
Timing timing
Timing
Artifacts artifacts
Artifacts
Resources resources
Resources
Status Passed Spin up environment 44s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Spin up environment
Spin up environment
44s
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Status Passed Container cimg/mariadb:10.9.7 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container cimg/mariadb:10.9.7
Container cimg/mariadb:10.9.7
9m 22s
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Open raw step output in new tab
Status Passed Container redis:5 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container redis:5
Container redis:5
9m 22s
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Status Passed Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2 9m 22s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2
Container docker.elastic.co/elasticsearch/elasticsearch:7.10.2
9m 22s
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Status Passed Preparing environment variables 0s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Preparing environment variables
Preparing environment variables
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Status Passed Attaching workspace 8s Find in Step Output Open step output in new tab Open raw step output in new tab
Status Passed Attaching workspace
Attaching workspace
8s
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Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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CloudWatch | us-east-2
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Git Branch JY-20676-delete-report-related-objects
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JY-20676-delete-report-related-objects
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Merge branch 'master' into JY-20676-delete-report-related-objects
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SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT — Work...
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jiminny.sentry.io/issues/7007366572/?environment=p jiminny.sentry.io/issues/7007366572/?environment=production-eu&environment=production&project=82419&query=is%3Aunresolved&referrer=issue-stream&sort=freq&statsPeriod=14d...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
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/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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content","depth":13,"bounds":{"left":0.10954122,"top":0.34836394,"width":0.028922873,"height":0.025538707},"on_screen":true,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Events","depth":15,"bounds":{"left":0.11353058,"top":0.35434955,"width":0.01761968,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Previous Event","depth":13,"bounds":{"left":0.7250665,"top":0.3499601,"width":0.00930851,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Next Event","depth":13,"bounds":{"left":0.734375,"top":0.3499601,"width":0.00930851,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":false,"is_focused":false,"is_selected":false},{"role":"AXRadioButton","text":"First","depth":14,"bounds":{"left":0.74601066,"top":0.3499601,"width":0.013630319,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"First","depth":15,"bounds":{"left":0.74601066,"top":0.3507582,"width":0.013630319,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"First","depth":17,"bounds":{"left":0.7486702,"top":0.3567438,"width":0.00831117,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Latest","depth":14,"bounds":{"left":0.7609708,"top":0.3499601,"width":0.017121011,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Latest","depth":15,"bounds":{"left":0.7609708,"top":0.3507582,"width":0.017121011,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Latest","depth":17,"bounds":{"left":0.76363033,"top":0.3567438,"width":0.011801862,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Recommended","depth":14,"bounds":{"left":0.77942157,"top":0.3499601,"width":0.033410903,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":true},{"role":"AXStaticText","text":"Recommended","depth":17,"bounds":{"left":0.7820811,"top":0.3567438,"width":0.028091755,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"View More Events","depth":13,"bounds":{"left":0.81416225,"top":0.3499601,"width":0.0390625,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"View More Events","depth":15,"bounds":{"left":0.8168218,"top":0.35514766,"width":0.03374335,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy as","depth":13,"bounds":{"left":0.85455453,"top":0.3499601,"width":0.03174867,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Copy as","depth":15,"bounds":{"left":0.86319816,"top":0.35514766,"width":0.01512633,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ID: c4ba69ae","depth":15,"bounds":{"left":0.11386303,"top":0.38906625,"width":0.029421542,"height":0.012370312},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3 days ago","depth":15,"bounds":{"left":0.15392287,"top":0.38906625,"width":0.023105053,"height":0.012370312},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"JSON","depth":14,"bounds":{"left":0.1818484,"top":0.38826814,"width":0.012300532,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"JSON","depth":15,"bounds":{"left":0.1818484,"top":0.38906625,"width":0.012300532,"height":0.012370312},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Highlights","depth":17,"bounds":{"left":0.7787567,"top":0.38387868,"width":0.024268618,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Highlights","depth":19,"bounds":{"left":0.78141624,"top":0.38986433,"width":0.018949468,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
|
-9015381144704544724
|
-3292835497546088228
|
click
|
accessibility
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NULL
|
Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Close tab
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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SevenShores\Hubspot\Exceptions\BadRequest
View events
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Level: Error
Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
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/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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release 69% 874599
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3 days ago
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2026-05-21T15:01:01.725183+00:00
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SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT — Work...
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jiminny.sentry.io/issues/7007366572/?environment=p jiminny.sentry.io/issues/7007366572/?environment=production-eu&environment=production&project=82419&query=is%3Aunresolved&referrer=issue-stream&sort=freq&statsPeriod=14d...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Close tab
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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SevenShores\Hubspot\Exceptions\BadRequest
View events
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Users (90d)
Level: Error
Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
17K
0
Ongoing
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Lukas Kovalik
production-eu, production
production-eu, production
14D
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Add a search term
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Toggle graph series - Events
Events
28
Toggle graph series - Users
Users
0
release 69% 874599
release
69%
874599
environment 91% production
environment
91%
production
runtime.name 100% php
runtime.name
100%
php
os.name 100% Linux
os.name
100%
Linux
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ID: c4ba69ae
3 days ago
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php
8.3.30
Linux
6.1.164-196.303.amzn2023.aarch64
888860
888860
production
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handled
yes
level
error
transaction
--
url
--
Trace: Trace ID
2528654a7d7845f79e93b877fd68c9ad
2528654a7d7845f79e93b877fd68c9ad
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There are 2 chained exceptions in this event.
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
Client error: `POST
https://api.hubapi.com/crm/v3/objects/contact/search
https://api.hubapi.com/crm/v3/objects/contact/search
` resulted in a `429 Too Many Requests` response:
{"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
mechanism
generic
handled
true
code
429
Crashed in non-app
:
/vendor/hubspot/hubspot-php/src/Exceptions/HubspotException.php
:24
in
SevenShores\Hubspot\Exceptions\HubspotException::create
Show 1 more frame
Show 1 more frame
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:163
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Open this line in GitHub
In App
158
}
159
160
private
function
executeSearchRequest
(
Client
$client
,
string
$endpoint
,
array
$payload
,
PaginationState
$state
)
:
array
161
{
162
try
{
163
$response
=
$client
->
getInstance
(
)
->
getClient
(
)
->
request
(
'POST'
,
$endpoint
,
[
'json'
=>
$payload
]
)
;
164
165
return
$response
->
toArray
(
)
;
166
}
catch
(
\
Exception
$e
)
{
167
if
(
$client
->
isUnauthorizedException
(
$e
)
)
{
168
$this
->
logger
->
warning
(
'[Hubspot] Got 401 during pagination, attempting token refresh'
,
[
client
Object Jiminny\Services\Crm\Hubspot\Client
endpoint
https://api.hubapi.com/crm/v3/objects/contact/search
Open link
payload
Collapse
{
Collapse
filterGroups
:
[
Expand
{
1 item
1 item
}
,
Expand
{
1 item
1 item
}
]
,
Expand
properties
:
[
14 items
14 items
]
,
Collapse
sorts
:
[
Expand
{
2 items
2 items
}
]
}
state
Object Jiminny\Services\Crm\Hubspot\Pagination\PaginationState
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:51
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::getPaginatedDataGenerator
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Jiminny\Services\Crm\Hubspot\Client::getPaginatedData
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Jiminny\Services\Crm\Hubspot\Service::Jiminny\Services\Crm\Hubspot\{closure}
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Illuminate\Cache\Repository::remember
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Jiminny\Services\Crm\Hubspot\Service::matchByName...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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SevenShores\Hubspot\Exceptions\BadRequest
View events
Events (total)
Users (90d)
Level: Error
Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
17K
0
Ongoing
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Lukas Kovalik
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production-eu, production
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release 69% 874599
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os.name 100% Linux
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ID: c4ba69ae
3 days ago
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php
8.3.30
Linux
6.1.164-196.303.amzn2023.aarch64
888860
888860
production
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Edit
Edit
handled
yes
level
error
transaction
--
url
--
Trace: Trace ID
2528654a7d7845f79e93b877fd68c9ad
2528654a7d7845f79e93b877fd68c9ad
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There are 2 chained exceptions in this event.
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
Client error: `POST
https://api.hubapi.com/crm/v3/objects/contact/search
https://api.hubapi.com/crm/v3/objects/contact/search
` resulted in a `429 Too Many Requests` response:
{"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
mechanism
generic
handled
true
code
429
Crashed in non-app
:
/vendor/hubspot/hubspot-php/src/Exceptions/HubspotException.php
:24
in
SevenShores\Hubspot\Exceptions\HubspotException::create
Show 1 more frame
Show 1 more frame
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:163
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
Copy file path
Open this line in GitHub
In App
158
}
159
160
private
function
executeSearchRequest
(
Client
$client
,
string
$endpoint
,
array
$payload
,
PaginationState
$state
)
:
array
161
{
162
try
{
163
$response
=
$client
->
getInstance
(
)
->
getClient
(
)
->
request
(
'POST'
,
$endpoint
,
[
'json'
=>
$payload
]
)
;
164
165
return
$response
->
toArray
(
)
;
166
}
catch
(
\
Exception
$e
)
{
167
if
(
$client
->
isUnauthorizedException
(
$e
)
)
{
168
$this
->
logger
->
warning
(
'[Hubspot] Got 401 during pagination, attempting token refresh'
,
[
client
Object Jiminny\Services\Crm\Hubspot\Client
endpoint
https://api.hubapi.com/crm/v3/objects/contact/search
Open link
payload
Collapse
{
Collapse
filterGroups
:
[
Expand
{
1 item
1 item
}
,
Expand
{
1 item
1 item
}
]
,
Expand
properties
:
[
14 items
14 items
]
,
Collapse
sorts
:
[
Expand
{
2 items
2 items
}
]
}
state
Object Jiminny\Services\Crm\Hubspot\Pagination\PaginationState
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:51
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::getPaginatedDataGenerator
In App
/app/Services/Crm/Hubspot/Client.php
:94
in
Jiminny\Services\Crm\Hubspot\Client::getPaginatedData
In App
/app/Services/Crm/Hubspot/Service.php
:1314
in
Jiminny\Services\Crm\Hubspot\Service::Jiminny\Services\Crm\Hubspot\{closure}
In App
Called from
:
/vendor/laravel/framework/src/Illuminate/Cache/Repository.php
:564
in
Illuminate\Cache\Repository::remember
Show 2 more frames
Show 2 more frames
/app/Services/Crm/Hubspot/Service.php
:1308
in
Jiminny\Services\Crm\Hubspot\Service::matchByName...
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2026-05-21T15:01:02.584582+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375662584_m2.jpg...
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Firefox
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SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT — Work...
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1
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jiminny.sentry.io/issues/7007366572/?environment=p jiminny.sentry.io/issues/7007366572/?environment=production-eu&environment=production&project=82419&query=is%3Aunresolved&referrer=issue-stream&sort=freq&statsPeriod=14d...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Close tab
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
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CloudWatch | us-east-2
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SevenShores\Hubspot\Exceptions\BadRequest
View events
Events (total)
Users (90d)
Level: Error
Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
17K
0
Ongoing
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Lukas Kovalik
production-eu, production
production-eu, production
14D
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28
Toggle graph series - Users
Users
0
release 69% 874599
release
69%
874599
environment 91% production
environment
91%
production
runtime.name 100% php
runtime.name
100%
php
os.name 100% Linux
os.name
100%
Linux
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ID: c4ba69ae
3 days ago
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Trace
Tags
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Context
Context
php
8.3.30
Linux
6.1.164-196.303.amzn2023.aarch64
888860
888860
production
Collapse Highlights Section
Highlights
Edit
Edit
handled
yes
level
error
transaction
--
url
--
Trace: Trace ID
2528654a7d7845f79e93b877fd68c9ad
2528654a7d7845f79e93b877fd68c9ad
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Stack Trace
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There are 2 chained exceptions in this event.
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
Client error: `POST
https://api.hubapi.com/crm/v3/objects/contact/search
https://api.hubapi.com/crm/v3/objects/contact/search
` resulted in a `429 Too Many Requests` response:
{"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
mechanism
generic
handled
true
code
429
Crashed in non-app
:
/vendor/hubspot/hubspot-php/src/Exceptions/HubspotException.php
:24
in
SevenShores\Hubspot\Exceptions\HubspotException::create
Show 1 more frame
Show 1 more frame
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:163
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
Copy file path
Open this line in GitHub
In App
158
}
159
160
private
function
executeSearchRequest
(
Client
$client
,
string
$endpoint
,
array
$payload
,
PaginationState
$state
)
:
array
161
{
162
try
{
163
$response
=
$client
->
getInstance
(
)
->
getClient
(
)
->
request
(
'POST'
,
$endpoint
,
[
'json'
=>
$payload
]
)
;
164
165
return
$response
->
toArray
(
)
;
166
}
catch
(
\
Exception
$e
)
{
167
if
(
$client
->
isUnauthorizedException
(
$e
)
)
{
168
$this
->
logger
->
warning
(
'[Hubspot] Got 401 during pagination, attempting token refresh'
,
[
client
Object Jiminny\Services\Crm\Hubspot\Client
endpoint
https://api.hubapi.com/crm/v3/objects/contact/search
Open link...
|
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Got 401 during pagination, attempting token refresh'","depth":19,"bounds":{"left":0.24019282,"top":0.9796488,"width":0.15076463,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":19,"bounds":{"left":0.39095744,"top":0.9796488,"width":0.002493351,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"[","depth":19,"bounds":{"left":0.3957779,"top":0.9796488,"width":0.0023271276,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"client","depth":20,"bounds":{"left":0.1341423,"top":1.0,"width":0.014295213,"height":-0.0019952059},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Object 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|
2507203170009303191
|
-986992531284148028
|
visual_change
|
accessibility
|
NULL
|
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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[JY-20879] Enable users to use their new activity types - Jira
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[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
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SevenShores\Hubspot\Exceptions\BadRequest
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Level: Error
Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
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/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Lukas Kovalik
production-eu, production
production-eu, production
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release 69% 874599
release
69%
874599
environment 91% production
environment
91%
production
runtime.name 100% php
runtime.name
100%
php
os.name 100% Linux
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Linux
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ID: c4ba69ae
3 days ago
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Context
php
8.3.30
Linux
6.1.164-196.303.amzn2023.aarch64
888860
888860
production
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handled
yes
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error
transaction
--
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Trace: Trace ID
2528654a7d7845f79e93b877fd68c9ad
2528654a7d7845f79e93b877fd68c9ad
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There are 2 chained exceptions in this event.
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
Client error: `POST
https://api.hubapi.com/crm/v3/objects/contact/search
https://api.hubapi.com/crm/v3/objects/contact/search
` resulted in a `429 Too Many Requests` response:
{"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
mechanism
generic
handled
true
code
429
Crashed in non-app
:
/vendor/hubspot/hubspot-php/src/Exceptions/HubspotException.php
:24
in
SevenShores\Hubspot\Exceptions\HubspotException::create
Show 1 more frame
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/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:163
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Open this line in GitHub
In App
158
}
159
160
private
function
executeSearchRequest
(
Client
$client
,
string
$endpoint
,
array
$payload
,
PaginationState
$state
)
:
array
161
{
162
try
{
163
$response
=
$client
->
getInstance
(
)
->
getClient
(
)
->
request
(
'POST'
,
$endpoint
,
[
'json'
=>
$payload
]
)
;
164
165
return
$response
->
toArray
(
)
;
166
}
catch
(
\
Exception
$e
)
{
167
if
(
$client
->
isUnauthorizedException
(
$e
)
)
{
168
$this
->
logger
->
warning
(
'[Hubspot] Got 401 during pagination, attempting token refresh'
,
[
client
Object Jiminny\Services\Crm\Hubspot\Client
endpoint
https://api.hubapi.com/crm/v3/objects/contact/search
Open link...
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NULL
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NULL
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NULL
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NULL
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68779
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2463
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72
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2026-05-21T15:01:05.600812+00:00
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jiminny.sentry.io/issues/7007366572/?environment=p jiminny.sentry.io/issues/7007366572/?environment=production-eu&environment=production&project=82419&query=is%3Aunresolved&referrer=issue-stream&sort=freq&statsPeriod=14d...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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2056694201054179723
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visual_change
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accessibility
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NULL
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
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test (891125) - jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
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[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375668633_m2.jpg...
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SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT — Work...
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jiminny.sentry.io/issues/7007366572/?environment=p jiminny.sentry.io/issues/7007366572/?environment=production-eu&environment=production&project=82419&query=is%3Aunresolved&referrer=issue-stream&sort=freq&statsPeriod=14d...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
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test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
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[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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SevenShores\Hubspot\Exceptions\BadRequest
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Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
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/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Lukas Kovalik
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ID: c4ba69ae
3 days ago
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php
8.3.30
Linux
6.1.164-196.303.amzn2023.aarch64
888860
888860
production
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Trace: Trace ID
2528654a7d7845f79e93b877fd68c9ad
2528654a7d7845f79e93b877fd68c9ad
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There are 2 chained exceptions in this event.
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
Client error: `POST
https://api.hubapi.com/crm/v3/objects/contact/search
https://api.hubapi.com/crm/v3/objects/contact/search
` resulted in a `429 Too Many Requests` response:
{"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
mechanism
generic
handled
true
code
429
Crashed in non-app
:
/vendor/hubspot/hubspot-php/src/Exceptions/HubspotException.php
:24
in
SevenShores\Hubspot\Exceptions\HubspotException::create
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/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:163
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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In App
158
}
159
160
private
function
executeSearchRequest
(
Client
$client
,
string
$endpoint
,
array
$payload
,...
|
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(truncated...)","depth":17,"bounds":{"left":0.13115026,"top":0.67318434,"width":0.35006648,"height":0.029130088},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"mechanism","depth":16,"bounds":{"left":0.1341423,"top":0.71668,"width":0.021609042,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"generic","depth":17,"bounds":{"left":0.16140293,"top":0.71548283,"width":0.016788565,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"handled","depth":16,"bounds":{"left":0.18683511,"top":0.71668,"width":0.014960106,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"true","depth":17,"bounds":{"left":0.20711437,"top":0.71548283,"width":0.009474734,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"code","depth":16,"bounds":{"left":0.2252327,"top":0.71668,"width":0.009142287,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"429","depth":17,"bounds":{"left":0.2400266,"top":0.71548283,"width":0.0071476065,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Crashed in non-app","depth":20,"bounds":{"left":0.1341423,"top":0.75259376,"width":0.03673537,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":20,"bounds":{"left":0.17087767,"top":0.75259376,"width":0.0009973404,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/vendor/hubspot/hubspot-php/src/Exceptions/HubspotException.php","depth":20,"bounds":{"left":0.17253989,"top":0.75259376,"width":0.13297872,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":24","depth":20,"bounds":{"left":0.30551863,"top":0.75259376,"width":0.005817819,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"in","depth":20,"bounds":{"left":0.31333113,"top":0.75139666,"width":0.004488032,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"SevenShores\\Hubspot\\Exceptions\\HubspotException::create","depth":20,"bounds":{"left":0.31981382,"top":0.75259376,"width":0.1143617,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Show 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|
8676267898683626028
|
-3292835506136006460
|
visual_change
|
accessibility
|
NULL
|
Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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SevenShores\Hubspot\Exceptions\BadRequest
View events
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Users (90d)
Level: Error
Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
17K
0
Ongoing
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Lukas Kovalik
production-eu, production
production-eu, production
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release 69% 874599
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environment 91% production
environment
91%
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handled
100%
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server_name 5% 1afcc19ab21f
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1afcc19ab21f
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ID: c4ba69ae
3 days ago
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php
8.3.30
Linux
6.1.164-196.303.amzn2023.aarch64
888860
888860
production
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handled
yes
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--
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Trace: Trace ID
2528654a7d7845f79e93b877fd68c9ad
2528654a7d7845f79e93b877fd68c9ad
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There are 2 chained exceptions in this event.
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
Client error: `POST
https://api.hubapi.com/crm/v3/objects/contact/search
https://api.hubapi.com/crm/v3/objects/contact/search
` resulted in a `429 Too Many Requests` response:
{"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
mechanism
generic
handled
true
code
429
Crashed in non-app
:
/vendor/hubspot/hubspot-php/src/Exceptions/HubspotException.php
:24
in
SevenShores\Hubspot\Exceptions\HubspotException::create
Show 1 more frame
Show 1 more frame
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:163
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
Copy file path
Open this line in GitHub
In App
158
}
159
160
private
function
executeSearchRequest
(
Client
$client
,
string
$endpoint
,
array
$payload
,...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
68781
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2462
|
36
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2026-05-21T15:01:19.750690+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375679750_m1.jpg...
|
Firefox
|
SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT — Work...
|
1
|
jiminny.sentry.io/issues/7007366572/?environment=p jiminny.sentry.io/issues/7007366572/?environment=production-eu&environment=production&project=82419&query=is%3Aunresolved&referrer=issue-stream&sort=freq&statsPeriod=14d...
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monitor_1
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NULL
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NULL
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NULL
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NULL
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Close tab
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
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CloudWatch | us-east-2
CloudWatch | us-east-2
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SevenShores\Hubspot\Exceptions\BadRequest
View events
Events (total)
Users (90d)
Level: Error
Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
17K
0
Ongoing
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Lukas Kovalik
production-eu, production
production-eu, production
14D
14D
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27
Toggle graph series - Users
Users
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release 69% 874599
release
69%
874599
environment 91% production
environment
91%
production
handled 100% yes
handled
100%
yes
server_name 5% 1afcc19ab21f
server_name
5%
1afcc19ab21f
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ID: c4ba69ae
3 days ago
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Trace
Tags
Tags
Context
Context
php
8.3.30
Linux
6.1.164-196.303.amzn2023.aarch64
888860
888860
production
Collapse Highlights Section
Highlights
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Edit
handled
yes
level
error
transaction
--
url
--
Trace: Trace ID
2528654a7d7845f79e93b877fd68c9ad
2528654a7d7845f79e93b877fd68c9ad
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There are 2 chained exceptions in this event.
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
Client error: `POST
https://api.hubapi.com/crm/v3/objects/contact/search
https://api.hubapi.com/crm/v3/objects/contact/search
` resulted in a `429 Too Many Requests` response:
{"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
mechanism
generic
handled
true
code
429
Crashed in non-app
:
/vendor/hubspot/hubspot-php/src/Exceptions/HubspotException.php
:24
in
SevenShores\Hubspot\Exceptions\HubspotException::create
Show 1 more frame
Show 1 more frame
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:163
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
Copy file path
Open this line in GitHub
In App
158
}
159
160
private
function
executeSearchRequest
(
Client
$client
,
string
$endpoint
,
array
$payload
,
PaginationState
$state
)
:
array
161
{
162
try
{
163
$response
=
$client
->
getInstance
(
)
->
getClient
(
)
->
request
(
'POST'
,
$endpoint
,
[
'json'
=>
$payload
]
)
;
164
165
return
$response
->
toArray
(
)
;
166
}
catch
(
\
Exception
$e
)
{
167
if
(
$client
->
isUnauthorizedException
(
$e
)
)
{
168
$this
->
logger
->
warning
(
'[Hubspot] Got 401 during pagination, attempting token refresh'
,
[
client
Object Jiminny\Services\Crm\Hubspot\Client
endpoint
https://api.hubapi.com/crm/v3/objects/contact/search
Open link
payload
Collapse
{
Collapse
filterGroups
:
[
Expand
{
1 item
1 item
}
,
Expand
{
1 item
1 item
}
]
,
Expand
properties
:
[
14 items
14 items
]
,
Collapse
sorts
:
[
Expand
{
2 items
2 items
}
]
}
state
Object Jiminny\Services\Crm\Hubspot\Pagination\PaginationState
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:51
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::getPaginatedDataGenerator
In App
/app/Services/Crm/Hubspot/Client.php
:94
in
Jiminny\Services\Crm\Hubspot\Client::getPaginatedData
In App
/app/Services/Crm/Hubspot/Service.php
:1314
in
Jiminny\Services\Crm\Hubspot\Service::Jiminny\Services\Crm\Hubspot\{closure}
In App
Called from
:
/vendor/laravel/framework/src/Illuminate/Cache/Repository.php
:564
in
Illuminate\Cache\Repository::remember
Show 2 more frames
Show 2 more frames
/app/Services/Crm/Hubspot/Service.php
:1308
in
Jiminny\Services\Crm\Hubspot\Service::matchByName
In App
/app/Services/Crm/CachedCrmServiceDecorator.php
:167
in
Jiminny\Services\Crm\CachedCrmServiceDecorator::matchByName
In App
/app/Services/Crm/CrmActivityService.php
:227
in
Jiminny\Services\Crm\CrmActivityService::findCrmRecords
In App...
|
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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SevenShores\Hubspot\Exceptions\BadRequest
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Level: Error
Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
17K
0
Ongoing
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Lukas Kovalik
production-eu, production
production-eu, production
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release 69% 874599
release
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environment 91% production
environment
91%
production
handled 100% yes
handled
100%
yes
server_name 5% 1afcc19ab21f
server_name
5%
1afcc19ab21f
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ID: c4ba69ae
3 days ago
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Context
Context
php
8.3.30
Linux
6.1.164-196.303.amzn2023.aarch64
888860
888860
production
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handled
yes
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error
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Trace: Trace ID
2528654a7d7845f79e93b877fd68c9ad
2528654a7d7845f79e93b877fd68c9ad
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There are 2 chained exceptions in this event.
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
SevenShores\Hubspot\Exceptions\BadRequest
Client error: `POST
https://api.hubapi.com/crm/v3/objects/contact/search
https://api.hubapi.com/crm/v3/objects/contact/search
` resulted in a `429 Too Many Requests` response:
{"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
mechanism
generic
handled
true
code
429
Crashed in non-app
:
/vendor/hubspot/hubspot-php/src/Exceptions/HubspotException.php
:24
in
SevenShores\Hubspot\Exceptions\HubspotException::create
Show 1 more frame
Show 1 more frame
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:163
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
Copy file path
Open this line in GitHub
In App
158
}
159
160
private
function
executeSearchRequest
(
Client
$client
,
string
$endpoint
,
array
$payload
,
PaginationState
$state
)
:
array
161
{
162
try
{
163
$response
=
$client
->
getInstance
(
)
->
getClient
(
)
->
request
(
'POST'
,
$endpoint
,
[
'json'
=>
$payload
]
)
;
164
165
return
$response
->
toArray
(
)
;
166
}
catch
(
\
Exception
$e
)
{
167
if
(
$client
->
isUnauthorizedException
(
$e
)
)
{
168
$this
->
logger
->
warning
(
'[Hubspot] Got 401 during pagination, attempting token refresh'
,
[
client
Object Jiminny\Services\Crm\Hubspot\Client
endpoint
https://api.hubapi.com/crm/v3/objects/contact/search
Open link
payload
Collapse
{
Collapse
filterGroups
:
[
Expand
{
1 item
1 item
}
,
Expand
{
1 item
1 item
}
]
,
Expand
properties
:
[
14 items
14 items
]
,
Collapse
sorts
:
[
Expand
{
2 items
2 items
}
]
}
state
Object Jiminny\Services\Crm\Hubspot\Pagination\PaginationState
/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
:51
in
Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::getPaginatedDataGenerator
In App
/app/Services/Crm/Hubspot/Client.php
:94
in
Jiminny\Services\Crm\Hubspot\Client::getPaginatedData
In App
/app/Services/Crm/Hubspot/Service.php
:1314
in
Jiminny\Services\Crm\Hubspot\Service::Jiminny\Services\Crm\Hubspot\{closure}
In App
Called from
:
/vendor/laravel/framework/src/Illuminate/Cache/Repository.php
:564
in
Illuminate\Cache\Repository::remember
Show 2 more frames
Show 2 more frames
/app/Services/Crm/Hubspot/Service.php
:1308
in
Jiminny\Services\Crm\Hubspot\Service::matchByName
In App
/app/Services/Crm/CachedCrmServiceDecorator.php
:167
in
Jiminny\Services\Crm\CachedCrmServiceDecorator::matchByName
In App
/app/Services/Crm/CrmActivityService.php
:227
in
Jiminny\Services\Crm\CrmActivityService::findCrmRecords
In App...
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375699120_m2.jpg...
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Firefox
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SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT — Work...
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1
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jiminny.sentry.io/issues/7007366572/?environment=p jiminny.sentry.io/issues/7007366572/?environment=production-eu&environment=production&project=82419&query=is%3Aunresolved&referrer=issue-stream&sort=freq&statsPeriod=14d...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Close tab
Jiminny
Jiminny
Close tab
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
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test (891125) - jiminny/app
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JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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[JY-20879] Enable users to use their new activity types - Jira
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[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT — Work...
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jiminny.sentry.io/issues/7007366572/?environment=p jiminny.sentry.io/issues/7007366572/?environment=production-eu&environment=production&project=82419&query=is%3Aunresolved&referrer=issue-stream&sort=freq&statsPeriod=14d...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
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JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
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[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
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/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
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/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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release 69% 874599
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874599
environment 91% production
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91%
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yes
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ID: c4ba69ae
3 days ago
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2026-05-21T15:01:40.800536+00:00
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SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT — Work...
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jiminny.sentry.io/issues/7007366572/?environment=p jiminny.sentry.io/issues/7007366572/?environment=production-eu&environment=production&project=82419&query=is%3Aunresolved&referrer=issue-stream&sort=freq&statsPeriod=14d...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
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Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
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/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019e3d8c-d (truncated...)
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/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php in Jiminny\Services\Crm\Hubspot\Pagination\HubspotPaginationService::executeSearchRequest
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SevenShores\Hubspot\Exceptions\BadRequest: Client SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT — Work...
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jiminny.sentry.io/issues/7007366572/?environment=p jiminny.sentry.io/issues/7007366572/?environment=production-eu&environment=production&project=82419&query=is%3Aunresolved&referrer=issue-stream&sort=freq&statsPeriod=14d...
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Close tab
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Close tab
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
Pipelines - jiminny/app
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
Jiminny
[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
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github.com/jiminny/app/pull/12115
github.com/jiminny/app/pull/12115
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3815363198317249551
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Platform Sprint 4 Q2 - Platform Team - Scrum Board Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 4 Q2 - Platform Team - Scrum Board - Jira
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
JY-20676 delete AJ reports related objects by LakyLak · Pull Request #12098 · jiminny/app
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
test (891125) - jiminny/app
test (891125) - jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
JY-20915 add alias for EU by LakyLak · Pull Request #12105 · jiminny/app
Pipelines - jiminny/app
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Jiminny
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[JY-20879] Enable users to use their new activity types - Jira
[JY-20879] Enable users to use their new activity types - Jira
Unnamed Group
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
[SRD-6871] Sensi.Ai - Call data not logging to HubSpot activity - Jira
Jiminny
Jiminny
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
[JY-20879] Ensure Activity types are being synchronised with the CRM - Jira
CloudWatch | us-east-2
CloudWatch | us-east-2
CloudWatch | us-east-2
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Ollama API Setup 💻 • Open WebUI — Personal
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ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371 ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfa...
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Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Today at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
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Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
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Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
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Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(
"Generated Response:"
)
print
(
result
.
get
(
"response"
))
except
requests
.
exceptions
.
RequestException
as
e
:
print
(
f"An error occurred:
{
e
}
"
)
4. The Role of Open WebUI
4. The Role of Open WebUI
Open WebUI
is a powerful frontend tool that provides a graphical interface for chatting.
Does it expose an API?
Generally,
no
, not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates
with
the backend (Ollama).
How to use it in your setup:
You set up Ollama
(running the model).
You set up Open WebUI
(to chat with the model visually).
You use the Ollama API directly
(using
curl
or Python) if you need to integrate the model into a custom application, script, or website.
Summary Checklist
Summary Checklist
GOAL
TOOL TO USE
ENDPOINT
ACCESS METHOD
Self-hosted Model Access
Ollama
http://[IP]:11434
REST API (POST requests)
Graphical Chatting
Open WebUI
(Web Interface)
Browser
Programmatic API Calls
curl
or
Python (
requests
)
/api/chat
or
/api/generate
HTTP Request
GOAL
Self-hosted Model Access
Graphical Chatting
Programmatic API Calls
TOOL TO USE
Ollama
Open WebUI
curl
or
Python (
requests
)
ENDPOINT
http://[IP]:11434
(Web Interface)
/api/chat
or
/api/generate
ACCESS METHOD
REST API (POST requests)
Browser
HTTP Request
Edit
Copy
Read Aloud
Good Response
Bad Response
Continue Response
Regenerate
Follow up
Follow up: What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
Follow up: How can I handle streaming responses from the Ollama API instead of waiting for the full response?
How can I handle streaming responses from the Ollama API instead of waiting for the full response?
Follow up: What are the specific API endpoints for generating embeddings or other advanced features?
What are the specific API endpoints for generating embeddings or other advanced features?
Follow up: How do I use this API connection to build a custom application or web service?
How do I use this API connection to build a custom application or web service?
Send a Message
Send a Message
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Conversation","depth":16,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gemma4:e2b","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Today at 9:33 PM","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thought for 2 minutes","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is the service that exposes the REST API, while","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is primarily a graphical user interface (GUI) for chatting with those models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a complete guide on how you can access and interact with your self-hosted model via API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Understanding Ollama as the API Endpoint","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Understanding Ollama as the API Endpoint","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"A. Default API URL","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A. Default API URL","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, Ollama runs on:","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"URL:","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://localhost:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if running on the same machine)","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://[Your_Server_IP]:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if you are accessing it from another device on your local network).","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"B. API Methods","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"B. API Methods","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama uses standard HTTP methods (","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") to interact with its endpoints. The most common endpoints for generating text are:","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating a single response based on a prompt.","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For multi-turn conversations (simulating a chat interface).","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/embeddings","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating vector embeddings.","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How to Make the REST API Call (Using curl)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How to Make the REST API Call (Using","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can use command-line tools like","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to test and interact with the Ollama API directly.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 1: Single Generation Call (/api/generate)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 1: Single Generation Call (","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This example sends a prompt to the model and waits for the generated response.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","depth":24,"on_screen":true,"value":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/generate","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral)","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\": \"Write a short poem about self-hosting AI.\",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 2: Chat Completion Call (/api/chat)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 2: Chat Completion Call (","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is better for conversational use, as it maintains context.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","depth":24,"on_screen":true,"value":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST 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models?\"}","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"],","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. Using Programming Languages (The Professional Way)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. Using Programming Languages (The Professional Way)","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Python Example (Recommended)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python Example (Recommended)","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python, with the","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"library, is the easiest way to interact with the Ollama API.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"python","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Run","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Run","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","depth":24,"on_screen":true,"value":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"import","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"import","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 1. Define the API endpoint","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"http://localhost:11434/api/generate\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 2. 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WebUI","depth":27,"bounds":{"left":0.9458333,"top":0.77555555,"width":0.050694443,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Web Interface)","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Browser","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Programmatic API 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(","depth":27,"bounds":{"left":0.98506945,"top":0.81222224,"width":0.014930546,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":28,"bounds":{"left":1.0,"top":0.815,"width":-0.024305582,"height":0.013333334},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":27,"bounds":{"left":1.0,"top":0.81222224,"width":-0.063194394,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HTTP Request","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"GOAL","depth":26,"bounds":{"left":0.79097223,"top":0.7022222,"width":0.023263888,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Self-hosted Model Access","depth":27,"bounds":{"left":0.79236114,"top":0.73888886,"width":0.10694444,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Graphical Chatting","depth":27,"bounds":{"left":0.79236114,"top":0.77555555,"width":0.07673611,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Programmatic API Calls","depth":27,"bounds":{"left":0.79236114,"top":0.81222224,"width":0.09618056,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"TOOL TO USE","depth":26,"bounds":{"left":0.9444444,"top":0.7022222,"width":0.055555582,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama","depth":27,"bounds":{"left":0.9458333,"top":0.73888886,"width":0.028472222,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":27,"bounds":{"left":0.9458333,"top":0.77555555,"width":0.050694443,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":28,"bounds":{"left":0.95034724,"top":0.815,"width":0.017013889,"height":0.013333334},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":26,"bounds":{"left":0.9722222,"top":0.81222224,"width":0.012847222,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python (","depth":27,"bounds":{"left":0.98506945,"top":0.81222224,"width":0.014930546,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":28,"bounds":{"left":1.0,"top":0.815,"width":-0.024305582,"height":0.013333334},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":27,"bounds":{"left":1.0,"top":0.81222224,"width":-0.063194394,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ENDPOINT","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://[IP]:11434","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Web Interface)","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ACCESS METHOD","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"REST API (POST requests)","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Browser","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HTTP Request","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Edit","depth":20,"bounds":{"left":0.78402776,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":20,"bounds":{"left":0.8034722,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Read Aloud","depth":20,"bounds":{"left":0.8229167,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Good Response","depth":20,"bounds":{"left":0.86180556,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Bad Response","depth":20,"bounds":{"left":0.88125,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Continue Response","depth":20,"bounds":{"left":0.90069443,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Regenerate","depth":19,"bounds":{"left":0.9201389,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Follow up","depth":20,"bounds":{"left":0.78402776,"top":0.9,"width":0.04375,"height":0.018888889},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Follow up: What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?","depth":20,"bounds":{"left":0.78402776,"top":0.92722225,"width":0.21597224,"height":0.035555556},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?","depth":22,"bounds":{"left":0.78402776,"top":0.9355556,"width":0.21597224,"height":0.018888889},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Follow up: How can I handle streaming responses from the Ollama API instead of waiting for the full response?","depth":20,"bounds":{"left":0.78402776,"top":0.9727778,"width":0.21597224,"height":0.027222216},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"How can I handle streaming responses from the Ollama API instead of waiting for the full response?","depth":22,"bounds":{"left":0.78402776,"top":0.9811111,"width":0.21597224,"height":0.018888889},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Follow up: What are the specific API endpoints for generating embeddings or other advanced features?","depth":20,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.018333316},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"What are the specific API endpoints for generating embeddings or other advanced features?","depth":22,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.026666641},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Follow up: How do I use this API connection to build a custom application or web service?","depth":20,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.06388891},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"How do I use this API connection to build a custom application or web service?","depth":22,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.07222223},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"Send a Message","depth":17,"on_screen":true,"value":"Send a Message","help_text":"","role_description":"text entry area","subrole":"AXApplicationGroup","is_enabled":true,"is_focused":true,"is_selected":false},{"role":"AXStaticText","text":"Send a Message","depth":19,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Voice Input","depth":17,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Voice mode","depth":17,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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Open Sidebar New Chat Search Notes Workspace
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New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
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Add Model
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How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Today at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(
"Generated Response:"
)
print
(
result
.
get
(
"response"
))
except
requests
.
exceptions
.
RequestException
as
e
:
print
(
f"An error occurred:
{
e
}
"
)
4. The Role of Open WebUI
4. The Role of Open WebUI
Open WebUI
is a powerful frontend tool that provides a graphical interface for chatting.
Does it expose an API?
Generally,
no
, not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates
with
the backend (Ollama).
How to use it in your setup:
You set up Ollama
(running the model).
You set up Open WebUI
(to chat with the model visually).
You use the Ollama API directly
(using
curl
or Python) if you need to integrate the model into a custom application, script, or website.
Summary Checklist
Summary Checklist
GOAL
TOOL TO USE
ENDPOINT
ACCESS METHOD
Self-hosted Model Access
Ollama
http://[IP]:11434
REST API (POST requests)
Graphical Chatting
Open WebUI
(Web Interface)
Browser
Programmatic API Calls
curl
or
Python (
requests
)
/api/chat
or
/api/generate
HTTP Request
GOAL
Self-hosted Model Access
Graphical Chatting
Programmatic API Calls
TOOL TO USE
Ollama
Open WebUI
curl
or
Python (
requests
)
ENDPOINT
http://[IP]:11434
(Web Interface)
/api/chat
or
/api/generate
ACCESS METHOD
REST API (POST requests)
Browser
HTTP Request
Edit
Copy
Read Aloud
Good Response
Bad Response
Continue Response
Regenerate
Follow up
Follow up: What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
Follow up: How can I handle streaming responses from the Ollama API instead of waiting for the full response?
How can I handle streaming responses from the Ollama API instead of waiting for the full response?
Follow up: What are the specific API endpoints for generating embeddings or other advanced features?
What are the specific API endpoints for generating embeddings or other advanced features?
Follow up: How do I use this API connection to build a custom application or web service?
How do I use this API connection to build a custom application or web service?
Send a Message
Send a Message
Voice Input
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Welcome to authentik! - authentik
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Ollama API Setup 💻 • Open WebUI
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Close tab
New Tab
Customize sidebar
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Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
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Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
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Run
Run
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import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(
"Generated Response:"
)
print
(
result
.
get
(
"response"
))
except
requests
.
exceptions
.
RequestException
as
e
:
print
(
f"An error occurred:
{
e
}
"
)
4. The Role of Open WebUI
4. The Role of Open WebUI
Open WebUI
is a powerful frontend tool that provides a graphical interface for chatting.
Does it expose an API?
Generally,
no
, not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates
with
the backend (Ollama).
How to use it in your setup:
You set up Ollama
(running the model).
You set up Open WebUI
(to chat with the model visually).
You use the Ollama API directly
(using
curl
or Python) if you need to integrate the model into a custom application, script, or website.
Summary Checklist
Summary Checklist
GOAL
TOOL TO USE
ENDPOINT
ACCESS METHOD
Self-hosted Model Access
Ollama
http://[IP]:11434
REST API (POST requests)
Graphical Chatting
Open WebUI
(Web Interface)
Browser
Programmatic API Calls
curl
or
Python (
requests
)
/api/chat
or
/api/generate
HTTP Request
GOAL
Self-hosted Model Access
Graphical Chatting
Programmatic API Calls
TOOL TO USE
Ollama
Open WebUI
curl
or
Python (
requests
)
ENDPOINT
http://[IP]:11434
(Web Interface)
/api/chat
or
/api/generate
ACCESS METHOD
REST API (POST requests)
Browser
HTTP Request
Edit
Copy
Read Aloud
Good Response
Bad Response
Continue Response
Regenerate
Follow up
Follow up: What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
Follow up: How can I handle streaming responses from the Ollama API instead of waiting for the full response?
How can I handle streaming responses from the Ollama API instead of waiting for the full response?
Follow up: What are the specific API endpoints for generating embeddings or other advanced features?
What are the specific API endpoints for generating embeddings or other advanced features?
Follow up: How do I use this API connection to build a custom application or web service?
How do I use this API connection to build a custom application or web service?
Send a Message
Send a Message
Voice Input
Voice mode...
|
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Conversation","depth":16,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gemma4:e2b","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thought for 2 minutes","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is the service that exposes the REST API, while","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is primarily a graphical user interface (GUI) for chatting with those models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a complete guide on how you can access and interact with your self-hosted model via API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Understanding Ollama as the API Endpoint","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Understanding Ollama as the API Endpoint","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"A. Default API URL","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A. Default API URL","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, Ollama runs on:","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"URL:","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://localhost:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if running on the same machine)","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://[Your_Server_IP]:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if you are accessing it from another device on your local network).","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"B. API Methods","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"B. API Methods","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama uses standard HTTP methods (","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") to interact with its endpoints. The most common endpoints for generating text are:","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating a single response based on a prompt.","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For multi-turn conversations (simulating a chat interface).","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/embeddings","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating vector embeddings.","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How to Make the REST API Call (Using curl)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How to Make the REST API Call (Using","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can use command-line tools like","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to test and interact with the Ollama API directly.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 1: Single Generation Call (/api/generate)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 1: Single Generation Call (","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This example sends a prompt to the model and waits for the generated response.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","depth":24,"on_screen":true,"value":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/generate","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral)","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\": \"Write a short poem about self-hosting AI.\",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 2: Chat Completion Call (/api/chat)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 2: Chat Completion Call (","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is better for conversational use, as it maintains context.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","depth":24,"on_screen":true,"value":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/chat","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"messages\": [","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"}","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"],","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. Using Programming Languages (The Professional Way)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. Using Programming Languages (The Professional Way)","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Python Example (Recommended)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python Example (Recommended)","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python, with the","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"library, is the easiest way to interact with the Ollama API.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"python","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Run","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Run","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","depth":24,"on_screen":true,"value":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"import","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"import","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 1. Define the API endpoint","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"http://localhost:11434/api/generate\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 2. Define the request payload (what you are sending)","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"llama3\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Explain the difference between Ollama and Open WebUI.\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"False","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":26,"bounds":{"left":0.81319445,"top":0.0,"width":0.005902778,"height":0.018333333},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 3. Make the POST request","depth":26,"bounds":{"left":0.81319445,"top":0.0,"width":0.15243055,"height":0.018333333},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"try","depth":26,"bounds":{"left":0.81319445,"top":0.0,"width":0.017708333,"height":0.018333333},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.83090276,"top":0.0,"width":0.005902778,"height":0.018333333},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"bounds":{"left":0.8368056,"top":0.003888889,"width":0.046875,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.8892361,"top":0.003888889,"width":0.005902778,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"bounds":{"left":0.9010417,"top":0.003888889,"width":0.046875,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"bounds":{"left":0.9479167,"top":0.003888889,"width":0.005902778,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"post","depth":26,"bounds":{"left":0.95381945,"top":0.003888889,"width":0.023263888,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"bounds":{"left":0.9770833,"top":0.003888889,"width":0.005902778,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"bounds":{"left":0.9829861,"top":0.003888889,"width":0.017013907,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":1.0,"top":0.003888889,"width":-0.0006943941,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"bounds":{"left":1.0,"top":0.003888889,"width":-0.012500048,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":1.0,"top":0.003888889,"width":-0.03576386,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"bounds":{"left":1.0,"top":0.003888889,"width":-0.041666627,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":26,"bounds":{"left":1.0,"top":0.003888889,"width":-0.08263886,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"bounds":{"left":0.8368056,"top":0.025555555,"width":0.046875,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"bounds":{"left":0.8836806,"top":0.025555555,"width":0.0055555557,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"raise_for_status","depth":26,"bounds":{"left":0.8892361,"top":0.025555555,"width":0.09375,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"()","depth":26,"bounds":{"left":0.9829861,"top":0.025555555,"width":0.017013907,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# Raise an exception for bad status codes (4xx or 5xx)","depth":26,"bounds":{"left":1.0,"top":0.025555555,"width":-0.0065972805,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 4. Parse the JSON 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Print the generated text","depth":26,"bounds":{"left":0.8368056,"top":0.13444445,"width":0.15208334,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"print","depth":26,"bounds":{"left":0.8368056,"top":0.15666667,"width":0.029166667,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"bounds":{"left":0.8659722,"top":0.15666667,"width":0.005902778,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Generated 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The Role of Open WebUI","depth":21,"bounds":{"left":0.78402776,"top":0.3061111,"width":0.21597224,"height":0.035555556},"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"4. The Role of Open WebUI","depth":22,"bounds":{"left":0.78402776,"top":0.3077778,"width":0.20173611,"height":0.032222223},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"bounds":{"left":0.78402776,"top":0.3511111,"width":0.065625,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is a powerful frontend tool that provides a graphical interface for chatting.","depth":22,"bounds":{"left":0.84965277,"top":0.3511111,"width":0.15034723,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Does it expose an API?","depth":23,"bounds":{"left":0.78402776,"top":0.3911111,"width":0.119791664,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Generally,","depth":22,"bounds":{"left":0.78402776,"top":0.42222223,"width":0.05277778,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"no","depth":23,"bounds":{"left":0.8368056,"top":0.42222223,"width":0.013194445,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates","depth":22,"bounds":{"left":0.85,"top":0.42222223,"width":0.14999998,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"with","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the backend (Ollama).","depth":22,"bounds":{"left":0.78402776,"top":0.42222223,"width":0.21597224,"height":0.052222222},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How to use it in your setup:","depth":23,"bounds":{"left":0.78402776,"top":0.49333334,"width":0.14375,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You set up Ollama","depth":24,"bounds":{"left":0.80625,"top":0.52444446,"width":0.094791666,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(running the model).","depth":23,"bounds":{"left":0.9010417,"top":0.52444446,"width":0.09895831,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You set up Open WebUI","depth":24,"bounds":{"left":0.80625,"top":0.5555556,"width":0.123958334,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(to chat with the model visually).","depth":23,"bounds":{"left":0.9302083,"top":0.5555556,"width":0.069791675,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You use the Ollama API directly","depth":24,"bounds":{"left":0.80625,"top":0.58666664,"width":0.16458334,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(using","depth":23,"bounds":{"left":0.97083336,"top":0.58666664,"width":0.029166639,"height":0.02111111},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":24,"bounds":{"left":1.0,"top":0.58944446,"width":-0.012847185,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or Python) if you need to integrate the model into a custom application, script, or website.","depth":23,"bounds":{"left":0.80625,"top":0.58666664,"width":0.19375002,"height":0.052222222},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Summary Checklist","depth":21,"bounds":{"left":0.78402776,"top":0.6527778,"width":0.21597224,"height":0.035555556},"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Summary Checklist","depth":22,"bounds":{"left":0.78402776,"top":0.65444446,"width":0.14722222,"height":0.032222223},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"GOAL","depth":26,"bounds":{"left":0.79097223,"top":0.7022222,"width":0.023263888,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"TOOL TO USE","depth":26,"bounds":{"left":0.9444444,"top":0.7022222,"width":0.055555582,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ENDPOINT","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ACCESS METHOD","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Self-hosted Model 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(","depth":27,"bounds":{"left":0.98506945,"top":0.81222224,"width":0.014930546,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":28,"bounds":{"left":1.0,"top":0.815,"width":-0.024305582,"height":0.013333334},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":27,"bounds":{"left":1.0,"top":0.81222224,"width":-0.063194394,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HTTP 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(","depth":27,"bounds":{"left":0.98506945,"top":0.81222224,"width":0.014930546,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":28,"bounds":{"left":1.0,"top":0.815,"width":-0.024305582,"height":0.013333334},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":27,"bounds":{"left":1.0,"top":0.81222224,"width":-0.063194394,"height":0.016666668},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ENDPOINT","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://[IP]:11434","depth":27,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Web 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Response","depth":20,"bounds":{"left":0.86180556,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Bad Response","depth":20,"bounds":{"left":0.88125,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Continue Response","depth":20,"bounds":{"left":0.90069443,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Regenerate","depth":19,"bounds":{"left":0.9201389,"top":0.84944445,"width":0.019444445,"height":0.031111112},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Follow up","depth":20,"bounds":{"left":0.78402776,"top":0.9,"width":0.04375,"height":0.018888889},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Follow up: What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?","depth":20,"bounds":{"left":0.78402776,"top":0.92722225,"width":0.21597224,"height":0.035555556},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?","depth":22,"bounds":{"left":0.78402776,"top":0.9355556,"width":0.21597224,"height":0.018888889},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Follow up: How can I handle streaming responses from the Ollama API instead of waiting for the full response?","depth":20,"bounds":{"left":0.78402776,"top":0.9727778,"width":0.21597224,"height":0.027222216},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"How can I handle streaming responses from the Ollama API instead of waiting for the full response?","depth":22,"bounds":{"left":0.78402776,"top":0.9811111,"width":0.21597224,"height":0.018888889},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Follow up: What are the specific API endpoints for generating embeddings or other advanced features?","depth":20,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.018333316},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"What are the specific API endpoints for generating embeddings or other advanced features?","depth":22,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.026666641},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Follow up: How do I use this API connection to build a custom application or web service?","depth":20,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.06388891},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"How do I use this API connection to build a custom application or web service?","depth":22,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.07222223},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"Send a Message","depth":17,"on_screen":true,"value":"Send a Message","help_text":"","role_description":"text entry area","subrole":"AXApplicationGroup","is_enabled":true,"is_focused":true,"is_selected":false},{"role":"AXStaticText","text":"Send a Message","depth":19,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Voice Input","depth":17,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Voice mode","depth":17,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
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Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
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Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
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Run
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import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(
"Generated Response:"
)
print
(
result
.
get
(
"response"
))
except
requests
.
exceptions
.
RequestException
as
e
:
print
(
f"An error occurred:
{
e
}
"
)
4. The Role of Open WebUI
4. The Role of Open WebUI
Open WebUI
is a powerful frontend tool that provides a graphical interface for chatting.
Does it expose an API?
Generally,
no
, not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates
with
the backend (Ollama).
How to use it in your setup:
You set up Ollama
(running the model).
You set up Open WebUI
(to chat with the model visually).
You use the Ollama API directly
(using
curl
or Python) if you need to integrate the model into a custom application, script, or website.
Summary Checklist
Summary Checklist
GOAL
TOOL TO USE
ENDPOINT
ACCESS METHOD
Self-hosted Model Access
Ollama
http://[IP]:11434
REST API (POST requests)
Graphical Chatting
Open WebUI
(Web Interface)
Browser
Programmatic API Calls
curl
or
Python (
requests
)
/api/chat
or
/api/generate
HTTP Request
GOAL
Self-hosted Model Access
Graphical Chatting
Programmatic API Calls
TOOL TO USE
Ollama
Open WebUI
curl
or
Python (
requests
)
ENDPOINT
http://[IP]:11434
(Web Interface)
/api/chat
or
/api/generate
ACCESS METHOD
REST API (POST requests)
Browser
HTTP Request
Edit
Copy
Read Aloud
Good Response
Bad Response
Continue Response
Regenerate
Follow up
Follow up: What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
Follow up: How can I handle streaming responses from the Ollama API instead of waiting for the full response?
How can I handle streaming responses from the Ollama API instead of waiting for the full response?
Follow up: What are the specific API endpoints for generating embeddings or other advanced features?
What are the specific API endpoints for generating embeddings or other advanced features?
Follow up: How do I use this API connection to build a custom application or web service?
How do I use this API connection to build a custom application or web service?
Send a Message
Send a Message
Voice Input
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Ollama API Setup 💻 • Open WebUI — Personal
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ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371 ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfa...
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
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Ambulatory sheet - Paperless-ngx
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💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
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Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
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Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins
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Screenpipe — Archive
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Reminders
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DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
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Nginx Proxy Manager
Nginx Proxy Manager
Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(
"Generated Response:"
)
print
(
result
.
get
(
"response"
))
except
requests
.
exceptions
.
RequestException
as
e
:
print
(
f"An error occurred:
{
e
}
"
)
4. The Role of Open WebUI
4. The Role of Open WebUI
Open WebUI
is a powerful frontend tool that provides a graphical interface for chatting.
Does it expose an API?
Generally,
no
, not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates
with
the backend (Ollama).
How to use it in your setup:
You set up Ollama
(running the model).
You set up Open WebUI
(to chat with the model visually).
You use the Ollama API directly
(using
curl
or Python) if you need to integrate the model into a custom application, script, or website.
Summary Checklist
Summary Checklist
GOAL
TOOL TO USE
ENDPOINT
ACCESS METHOD
Self-hosted Model Access
Ollama
http://[IP]:11434
REST API (POST requests)
Graphical Chatting
Open WebUI
(Web Interface)
Browser
Programmatic API Calls
curl
or
Python (
requests
)
/api/chat
or
/api/generate
HTTP Request
GOAL
Self-hosted Model Access
Graphical Chatting
Programmatic API Calls
TOOL TO USE
Ollama
Open WebUI
curl
or
Python (
requests
)
ENDPOINT
http://[IP]:11434
(Web Interface)
/api/chat
or
/api/generate
ACCESS METHOD
REST API (POST requests)
Browser
HTTP Request
Edit
Copy
Read Aloud
Good Response
Bad Response
Continue Response
Regenerate
Follow up
Follow up: What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
Follow up: How can I handle streaming responses from the Ollama API instead of waiting for the full response?
How can I handle streaming responses from the Ollama API instead of waiting for the full response?
Follow up: What are the specific API endpoints for generating embeddings or other advanced features?
What are the specific API endpoints for generating embeddings or other advanced features?
Follow up: How do I use this API connection to build a custom application or web service?
How do I use this API connection to build a custom application or web service?
ok I am
ok I am
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API Methods","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"B. API Methods","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama uses standard HTTP methods (","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") to interact with its endpoints. The most common endpoints for generating text are:","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating a single response based on a prompt.","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For multi-turn conversations (simulating a chat interface).","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/embeddings","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating vector embeddings.","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How to Make the REST API Call (Using curl)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How to Make the REST API Call (Using","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can use command-line tools like","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to test and interact with the Ollama API directly.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 1: Single Generation Call (/api/generate)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 1: Single Generation Call (","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This example sends a prompt to the model and waits for the generated response.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","depth":24,"on_screen":true,"value":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/generate","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral)","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\": \"Write a short poem about self-hosting AI.\",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 2: Chat Completion Call (/api/chat)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 2: Chat Completion Call (","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is better for conversational use, as it maintains context.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","depth":24,"on_screen":true,"value":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/chat","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"messages\": [","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"}","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"],","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. Using Programming Languages (The Professional Way)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. Using Programming Languages (The Professional Way)","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Python Example (Recommended)","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python Example (Recommended)","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python, with the","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"library, is the easiest way to interact with the Ollama API.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"python","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Run","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Run","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","depth":24,"on_screen":true,"value":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"import","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"import","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 1. Define the API endpoint","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"http://localhost:11434/api/generate\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 2. Define the request payload (what you are sending)","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"llama3\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Explain the difference between Ollama and Open WebUI.\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"False","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":26,"bounds":{"left":0.81319445,"top":0.0,"width":0.005902778,"height":0.018333333},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 3. Make the POST request","depth":26,"bounds":{"left":0.81319445,"top":0.0,"width":0.15243055,"height":0.018333333},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"try","depth":26,"bounds":{"left":0.81319445,"top":0.0,"width":0.017708333,"height":0.018333333},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.83090276,"top":0.0,"width":0.005902778,"height":0.018333333},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"bounds":{"left":0.8368056,"top":0.003888889,"width":0.046875,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.8892361,"top":0.003888889,"width":0.005902778,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"bounds":{"left":0.9010417,"top":0.003888889,"width":0.046875,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"bounds":{"left":0.9479167,"top":0.003888889,"width":0.005902778,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"post","depth":26,"bounds":{"left":0.95381945,"top":0.003888889,"width":0.023263888,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"bounds":{"left":0.9770833,"top":0.003888889,"width":0.005902778,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"bounds":{"left":0.9829861,"top":0.003888889,"width":0.017013907,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":1.0,"top":0.003888889,"width":-0.0006943941,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"bounds":{"left":1.0,"top":0.003888889,"width":-0.012500048,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":1.0,"top":0.003888889,"width":-0.03576386,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"bounds":{"left":1.0,"top":0.003888889,"width":-0.041666627,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":26,"bounds":{"left":1.0,"top":0.003888889,"width":-0.08263886,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"bounds":{"left":0.8368056,"top":0.025555555,"width":0.046875,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"bounds":{"left":0.8836806,"top":0.025555555,"width":0.0055555557,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"raise_for_status","depth":26,"bounds":{"left":0.8892361,"top":0.025555555,"width":0.09375,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"()","depth":26,"bounds":{"left":0.9829861,"top":0.025555555,"width":0.017013907,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# Raise an exception for bad status codes (4xx or 5xx)","depth":26,"bounds":{"left":1.0,"top":0.025555555,"width":-0.0065972805,"height":0.018333333},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 4. Parse the JSON 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the Ollama API instead of waiting for the full response?","depth":22,"bounds":{"left":0.78402776,"top":0.9811111,"width":0.21597224,"height":0.018888889},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Follow up: What are the specific API endpoints for generating embeddings or other advanced features?","depth":20,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.018333316},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"What are the specific API endpoints for generating embeddings or other advanced features?","depth":22,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.026666641},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Follow up: How do I use this API connection to build a custom application or web service?","depth":20,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.06388891},"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"How do I use this API connection to build a custom application or web service?","depth":22,"bounds":{"left":0.78402776,"top":1.0,"width":0.21597224,"height":-0.07222223},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"ok I am","depth":17,"on_screen":true,"value":"ok I am","help_text":"","role_description":"text entry area","subrole":"AXApplicationGroup","is_enabled":true,"is_focused":true,"is_selected":false},{"role":"AXStaticText","text":"ok I am","depth":19,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Voice Input","depth":17,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
|
-2838248782540931965
|
-7073484169920002769
|
visual_change
|
accessibility
|
NULL
|
New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins
Завеждане на щета онлайн | Euroins
Screenpipe — Archive
Screenpipe — Archive
Reminders
Reminders
Photos - Google Photos
Photos - Google Photos
DXP4800PLUS-B5F8
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Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
Close tab
New Tab
Customize sidebar
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Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(
"Generated Response:"
)
print
(
result
.
get
(
"response"
))
except
requests
.
exceptions
.
RequestException
as
e
:
print
(
f"An error occurred:
{
e
}
"
)
4. The Role of Open WebUI
4. The Role of Open WebUI
Open WebUI
is a powerful frontend tool that provides a graphical interface for chatting.
Does it expose an API?
Generally,
no
, not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates
with
the backend (Ollama).
How to use it in your setup:
You set up Ollama
(running the model).
You set up Open WebUI
(to chat with the model visually).
You use the Ollama API directly
(using
curl
or Python) if you need to integrate the model into a custom application, script, or website.
Summary Checklist
Summary Checklist
GOAL
TOOL TO USE
ENDPOINT
ACCESS METHOD
Self-hosted Model Access
Ollama
http://[IP]:11434
REST API (POST requests)
Graphical Chatting
Open WebUI
(Web Interface)
Browser
Programmatic API Calls
curl
or
Python (
requests
)
/api/chat
or
/api/generate
HTTP Request
GOAL
Self-hosted Model Access
Graphical Chatting
Programmatic API Calls
TOOL TO USE
Ollama
Open WebUI
curl
or
Python (
requests
)
ENDPOINT
http://[IP]:11434
(Web Interface)
/api/chat
or
/api/generate
ACCESS METHOD
REST API (POST requests)
Browser
HTTP Request
Edit
Copy
Read Aloud
Good Response
Bad Response
Continue Response
Regenerate
Follow up
Follow up: What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
What are the necessary prerequisites and steps to install Ollama and set up a self-hosted model?
Follow up: How can I handle streaming responses from the Ollama API instead of waiting for the full response?
How can I handle streaming responses from the Ollama API instead of waiting for the full response?
Follow up: What are the specific API endpoints for generating embeddings or other advanced features?
What are the specific API endpoints for generating embeddings or other advanced features?
Follow up: How do I use this API connection to build a custom application or web service?
How do I use this API connection to build a custom application or web service?
ok I am
ok I am
Voice Input...
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68794
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2463
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77
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2026-05-21T15:02:52.068152+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375772068_m2.jpg...
|
Firefox
|
Ollama API Setup 💻 • Open WebUI — Personal
|
1
|
ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371 ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfa...
|
monitor_2
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NULL
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NULL
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NULL
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NULL
|
rireroxVIewMistorPlatform Sprint 4 Q2 - Platform T rireroxVIewMistorPlatform Sprint 4 Q2 - Platform TeService-Desk - Queues - Platfc Xtest (891125) - jimilJY-20915 adalias for EU by LakPipelines - jiminny/appSevenShores|Hubspot\Exceptions8 Jiminny(JY-20879] Enable users to use thLY (SRD-6871] Sensi.Ai - Call data n8 Jiminn57 |JY-208791 Ensure Activitv tvpes(a CloudWatch I us-east-2CloudWatch | us-east-2CloudWatch I us-east-2Add Jira ticket context fetching to— New TalbookmarksProtllesToolsWindowmelpJ JIMINNYg For you(• RecentSpaces / Service-Desk / QueuesPlatform team* Starred0* Apps|#= List +Q Spaces+ ***Q Search workJiminny (New)work lems14 Service-DeskKey@ SummarySRD-6871E Queues+ **v leam PrioritySRD-68485 All open tickets 15j Unassigned t... 2•, Support tea...E Raised by meEj Assigned to …•, Service requ...61 Platform teamj Processing t..•, Site reliabilitv... o=i New features... 0j InfoSec issues 0•1 Ready for Cu... 4#, Resolved ti... 999+= View all quienesE) Service requestsA Incidentsiul ReportsC: Operations• Knowledae Base0 CuctomordÇ Channels• Email loas⅘> Developer escalationsil: Slack integration• Search |Request tvpe vStatus vAssianee vSummarySensi.Al - Call data not logging to Hubspot activitysidekick sms issuelMore tilters vPriority levelP2 MediumPe MediumNew Device Logged In FromAmbulatory sheet - Paperles@1 - Apple MacBook Pro 14d Apple Mac Studio M4 MaxWelcome to authentik! - autiЗавеждане на щета онлай,@ Screenpipe — Archive(* RemindersPhotos - Gooale Photos( DXP4800PLUS-B5F8New Tab0) Nainx Proxy Manaaeo1 Ollama API Setup • 0, x— New Tab• • ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfagemma4:e2b v +19 y ury:python# 4. Parse the JSON responseresulr = resoonse.ison.22# Print the generated textPrant seneraued nesponse.orint.result.det"response"25 v except nequests eroe oicurrRea lstelests.excentions.Requestzxcention as e4. The Role of Open WebUlOpen WebUl is a powerful frontend tool that provides a graphical interface for chatting.Does it expose an APl?Generally, no, not as a primary source for programmatic API calls. Open WebUl acts as a client that communicates with thebackend (Ollama)How to use it in your setup:1. You set up Ollama (runnina the model)2. You set up Open Webul (to chat with the model visually).3. You use the Ollama API directiy (usina curl or Python) if vou need to intearate the model into a custom application.script, or website.Summary ChecklistGOALTOOL TO USEENDPOINTACCESS METHODSelf-hocted Model AccaceOllamalhttp://[IP]:11434REST API (POST requests)Graphical ChattingOpen WebUWeb Intertace)BrowserProgrammatic API Callscurl or Pyinon requests/api/chat or /api/generateHTTP Requestok l am using gemma4:ezb create crul request tor me100% S2e Inu z1 May 10.02'01*Collapse Run Save Coovgemma4:e2bSend a MessageA new version (v0.9.5) is now available. Update Xfor the latest features and imorovements...
|
NULL
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8509812686157296801
|
NULL
|
visual_change
|
ocr
|
NULL
|
rireroxVIewMistorPlatform Sprint 4 Q2 - Platform T rireroxVIewMistorPlatform Sprint 4 Q2 - Platform TeService-Desk - Queues - Platfc Xtest (891125) - jimilJY-20915 adalias for EU by LakPipelines - jiminny/appSevenShores|Hubspot\Exceptions8 Jiminny(JY-20879] Enable users to use thLY (SRD-6871] Sensi.Ai - Call data n8 Jiminn57 |JY-208791 Ensure Activitv tvpes(a CloudWatch I us-east-2CloudWatch | us-east-2CloudWatch I us-east-2Add Jira ticket context fetching to— New TalbookmarksProtllesToolsWindowmelpJ JIMINNYg For you(• RecentSpaces / Service-Desk / QueuesPlatform team* Starred0* Apps|#= List +Q Spaces+ ***Q Search workJiminny (New)work lems14 Service-DeskKey@ SummarySRD-6871E Queues+ **v leam PrioritySRD-68485 All open tickets 15j Unassigned t... 2•, Support tea...E Raised by meEj Assigned to …•, Service requ...61 Platform teamj Processing t..•, Site reliabilitv... o=i New features... 0j InfoSec issues 0•1 Ready for Cu... 4#, Resolved ti... 999+= View all quienesE) Service requestsA Incidentsiul ReportsC: Operations• Knowledae Base0 CuctomordÇ Channels• Email loas⅘> Developer escalationsil: Slack integration• Search |Request tvpe vStatus vAssianee vSummarySensi.Al - Call data not logging to Hubspot activitysidekick sms issuelMore tilters vPriority levelP2 MediumPe MediumNew Device Logged In FromAmbulatory sheet - Paperles@1 - Apple MacBook Pro 14d Apple Mac Studio M4 MaxWelcome to authentik! - autiЗавеждане на щета онлай,@ Screenpipe — Archive(* RemindersPhotos - Gooale Photos( DXP4800PLUS-B5F8New Tab0) Nainx Proxy Manaaeo1 Ollama API Setup • 0, x— New Tab• • ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfagemma4:e2b v +19 y ury:python# 4. Parse the JSON responseresulr = resoonse.ison.22# Print the generated textPrant seneraued nesponse.orint.result.det"response"25 v except nequests eroe oicurrRea lstelests.excentions.Requestzxcention as e4. The Role of Open WebUlOpen WebUl is a powerful frontend tool that provides a graphical interface for chatting.Does it expose an APl?Generally, no, not as a primary source for programmatic API calls. Open WebUl acts as a client that communicates with thebackend (Ollama)How to use it in your setup:1. You set up Ollama (runnina the model)2. You set up Open Webul (to chat with the model visually).3. You use the Ollama API directiy (usina curl or Python) if vou need to intearate the model into a custom application.script, or website.Summary ChecklistGOALTOOL TO USEENDPOINTACCESS METHODSelf-hocted Model AccaceOllamalhttp://[IP]:11434REST API (POST requests)Graphical ChattingOpen WebUWeb Intertace)BrowserProgrammatic API Callscurl or Pyinon requests/api/chat or /api/generateHTTP Requestok l am using gemma4:ezb create crul request tor me100% S2e Inu z1 May 10.02'01*Collapse Run Save Coovgemma4:e2bSend a MessageA new version (v0.9.5) is now available. Update Xfor the latest features and imorovements...
|
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NULL
|
NULL
|
NULL
|
|
68795
|
2462
|
46
|
2026-05-21T15:02:55.219716+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375775219_m1.jpg...
|
Firefox
|
Ollama API Setup 💻 • Open WebUI — Personal
|
1
|
ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371 ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfa...
|
monitor_1
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NULL
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NULL
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NULL
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NULL
|
New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins
Завеждане на щета онлайн | Euroins
Screenpipe — Archive
Screenpipe — Archive
Reminders
Reminders
Photos - Google Photos
Photos - Google Photos
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
New Tab
Nginx Proxy Manager
Nginx Proxy Manager
Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(
"Generated Response:"
)
print
(
result
.
get
(
"response"
))
except
requests
.
exceptions
.
RequestException
as
e
:
print
(
f"An error occurred:
{
e
}
"
)
4. The Role of Open WebUI
4. The Role of Open WebUI
Open WebUI
is a powerful frontend tool that provides a graphical interface for chatting.
Does it expose an API?
Generally,
no
, not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates
with
the backend (Ollama).
How to use it in your setup:
You set up Ollama
(running the model).
You set up Open WebUI
(to chat with the model visually).
You use the Ollama API directly
(using
curl
or Python) if you need to integrate the model into a custom application, script, or website.
Summary Checklist
Summary Checklist
GOAL
TOOL TO USE
ENDPOINT
ACCESS METHOD
Self-hosted Model Access
Ollama
http://[IP]:11434
REST API (POST requests)
Graphical Chatting
Open WebUI
(Web Interface)
Browser
Programmatic API Calls
curl
or
Python (
requests
)
/api/chat
or
/api/generate
HTTP Request
GOAL
Self-hosted Model Access
Graphical Chatting
Programmatic API Calls
TOOL TO USE
Ollama
Open WebUI
curl
or
Python (
requests
)
ENDPOINT
http://[IP]:11434
(Web Interface)
/api/chat
or
/api/generate
ACCESS METHOD
REST API (POST requests)
Browser
HTTP Request
ok I am using gemma4:e2b create crul request for me
gemma4:e2b
Send a Message
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that","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is the service that exposes the REST API, while","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is primarily a graphical user interface (GUI) for chatting with those models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a complete guide on how you can access and interact with your self-hosted model via API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. 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Default API URL","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, Ollama runs on:","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"URL:","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://localhost:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if running on the same machine)","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://[Your_Server_IP]:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if you are accessing it from another device on your local network).","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"B. API Methods","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"B. API Methods","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama uses standard HTTP methods (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") to interact with its endpoints. The most common endpoints for generating text are:","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating a single response based on a prompt.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For multi-turn conversations (simulating a chat interface).","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/embeddings","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating vector embeddings.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How to Make the REST API Call (Using curl)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How to Make the REST API Call (Using","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can use command-line tools like","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to test and interact with the Ollama API directly.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 1: Single Generation Call (/api/generate)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 1: Single Generation Call (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This example sends a prompt to the model and waits for the generated 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http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","depth":24,"on_screen":false,"value":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/generate","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral)","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\": \"Write a short poem about self-hosting AI.\",","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": 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context.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","depth":24,"on_screen":false,"value":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/chat","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\",","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"messages\": [","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"}","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"],","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. Using Programming Languages (The Professional Way)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. Using Programming Languages (The Professional Way)","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Python Example (Recommended)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python Example (Recommended)","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python, with the","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"library, is the easiest way to interact with the Ollama API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"python","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Run","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Run","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","depth":24,"on_screen":true,"value":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"import","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"import","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 1. Define the API endpoint","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"http://localhost:11434/api/generate\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 2. Define the request payload (what you are sending)","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"llama3\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Explain the difference between Ollama and Open WebUI.\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"False","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 3. Make the POST request","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"try","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"post","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"raise_for_status","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"()","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# Raise an exception for bad status codes (4xx or 5xx)","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 4. Parse the JSON response","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"result","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"()","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# Print the generated text","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"print","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Generated Response:\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"print","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"result","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"get","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"response\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"))","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"except","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"exceptions","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"RequestException","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"as","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"e","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"print","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"f\"An error occurred:","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"e","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"4. 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The Role of Open WebUI","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is a powerful frontend tool that provides a graphical interface for chatting.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Does it expose an API?","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Generally,","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"no","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"with","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the backend (Ollama).","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How to use it in your setup:","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You set up Ollama","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(running the model).","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You set up Open 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Request","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ok I am using gemma4:e2b create crul request for me","depth":21,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gemma4:e2b","depth":21,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"Send a Message","depth":17,"on_screen":true,"value":"Send a Message","help_text":"","role_description":"text entry area","subrole":"AXApplicationGroup","is_enabled":true,"is_focused":true,"is_selected":false},{"role":"AXStaticText","text":"Send a Message","depth":19,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(
"Generated Response:"
)
print
(
result
.
get
(
"response"
))
except
requests
.
exceptions
.
RequestException
as
e
:
print
(
f"An error occurred:
{
e
}
"
)
4. The Role of Open WebUI
4. The Role of Open WebUI
Open WebUI
is a powerful frontend tool that provides a graphical interface for chatting.
Does it expose an API?
Generally,
no
, not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates
with
the backend (Ollama).
How to use it in your setup:
You set up Ollama
(running the model).
You set up Open WebUI
(to chat with the model visually).
You use the Ollama API directly
(using
curl
or Python) if you need to integrate the model into a custom application, script, or website.
Summary Checklist
Summary Checklist
GOAL
TOOL TO USE
ENDPOINT
ACCESS METHOD
Self-hosted Model Access
Ollama
http://[IP]:11434
REST API (POST requests)
Graphical Chatting
Open WebUI
(Web Interface)
Browser
Programmatic API Calls
curl
or
Python (
requests
)
/api/chat
or
/api/generate
HTTP Request
GOAL
Self-hosted Model Access
Graphical Chatting
Programmatic API Calls
TOOL TO USE
Ollama
Open WebUI
curl
or
Python (
requests
)
ENDPOINT
http://[IP]:11434
(Web Interface)
/api/chat
or
/api/generate
ACCESS METHOD
REST API (POST requests)
Browser
HTTP Request
ok I am using gemma4:e2b create crul request for me
gemma4:e2b
Send a Message
Send a Message...
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2026-05-21T15:03:23.060841+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375803060_m2.jpg...
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Firefox
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Ollama API Setup 💻 • Open WebUI — Personal
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ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371 ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfa...
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins
Завеждане на щета онлайн | Euroins
Screenpipe — Archive
Screenpipe — Archive
Reminders
Reminders
Photos - Google Photos
Photos - Google Photos
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
New Tab
Nginx Proxy Manager
Nginx Proxy Manager
Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,...
|
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Chat","depth":12,"bounds":{"left":0.57147604,"top":0.0905826,"width":0.011968086,"height":0.028731046},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Search","depth":12,"bounds":{"left":0.57147604,"top":0.11931365,"width":0.011968086,"height":0.028731046},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Notes","depth":12,"bounds":{"left":0.57147604,"top":0.14804469,"width":0.011968086,"height":0.028731046},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Workspace","depth":12,"bounds":{"left":0.57147604,"top":0.17677574,"width":0.011968086,"height":0.028731046},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Open User Profile Menu","depth":10,"bounds":{"left":0.5728058,"top":0.9648843,"width":0.00930851,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Selected model: gemma4:e2b","depth":16,"bounds":{"left":0.5909242,"top":0.05905826,"width":0.043550532,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"gemma4:e2b","depth":18,"bounds":{"left":0.5915891,"top":0.061851557,"width":0.03557181,"height":0.01715882},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Add Model","depth":16,"bounds":{"left":0.6371343,"top":0.06424581,"width":0.004654255,"height":0.011173184},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Controls","depth":14,"bounds":{"left":0.97207445,"top":0.055067837,"width":0.011968086,"height":0.028731046},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"User menu","depth":13,"bounds":{"left":0.9840425,"top":0.055067837,"width":0.011968086,"height":0.028731046},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"User menu","depth":15,"bounds":{"left":0.9896942,"top":0.061053474,"width":0.010305822,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Chat Conversation","depth":15,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Chat Conversation","depth":16,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gemma4:e2b","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yesterday at 9:33 PM","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thought for 2 minutes","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is the service that exposes the REST API, while","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is primarily a graphical user interface (GUI) for chatting with those models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a complete guide on how you can access and interact with your self-hosted model via API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Understanding Ollama as the API Endpoint","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Understanding Ollama as the API Endpoint","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"A. Default API URL","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A. Default API URL","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, Ollama runs on:","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"URL:","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://localhost:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if running on the same machine)","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://[Your_Server_IP]:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if you are accessing it from another device on your local network).","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"B. API Methods","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"B. API Methods","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama uses standard HTTP methods (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") to interact with its endpoints. The most common endpoints for generating text are:","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating a single response based on a prompt.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For multi-turn conversations (simulating a chat interface).","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/embeddings","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating vector embeddings.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How to Make the REST API Call (Using curl)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How to Make the REST API Call (Using","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can use command-line tools like","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to test and interact with the Ollama API directly.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 1: Single Generation Call (/api/generate)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 1: Single Generation Call (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This example sends a prompt to the model and waits for the generated response.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","depth":24,"on_screen":false,"value":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/generate","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral)","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\": \"Write a short poem about self-hosting AI.\",","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 2: Chat Completion Call (/api/chat)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 2: Chat Completion Call (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is better for conversational use, as it maintains context.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","depth":24,"on_screen":false,"value":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/chat","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\",","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"messages\": [","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"}","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"],","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. Using Programming Languages (The Professional Way)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. Using Programming Languages (The Professional Way)","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Python Example (Recommended)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python Example (Recommended)","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python, with the","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"library, is the easiest way to interact with the Ollama API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"python","depth":25,"bounds":{"left":0.6499335,"top":0.08739027,"width":0.012965426,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.88680184,"top":0.08539505,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.8941157,"top":0.08739027,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Run","depth":22,"bounds":{"left":0.91306514,"top":0.08539505,"width":0.011303191,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Run","depth":24,"bounds":{"left":0.91505986,"top":0.08739027,"width":0.00731383,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.08539505,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.08539505,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","depth":24,"on_screen":true,"value":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"import","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"import","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 1. Define the API endpoint","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"bounds":{"left":0.65957445,"top":0.0,"width":0.008477394,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.67087764,"top":0.0,"width":0.0026595744,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"http://localhost:11434/api/generate\"","depth":26,"bounds":{"left":0.67636305,"top":0.0,"width":0.10372341,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 2. 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-311749228398505574
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-2451173570642720437
|
idle
|
accessibility
|
NULL
|
New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
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Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
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Welcome to authentik! - authentik
Welcome to authentik! - authentik
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Reminders
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Photos - Google Photos
Photos - Google Photos
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
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Nginx Proxy Manager
Nginx Proxy Manager
Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,...
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47
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|
/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375805448_m1.jpg...
|
Firefox
|
Ollama API Setup 💻 • Open WebUI — Personal
|
1
|
ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371 ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfa...
|
monitor_1
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|
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|
New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins
Завеждане на щета онлайн | Euroins
Screenpipe — Archive
Screenpipe — Archive
Reminders
Reminders
Photos - Google Photos
Photos - Google Photos
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
New Tab
Nginx Proxy Manager
Nginx Proxy Manager
Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(
"Generated Response:"
)
print
(
result
.
get
(
"response"
))
except
requests
.
exceptions
.
RequestException
as
e
:
print
(
f"An error occurred:
{
e
}
"
)
4. The Role of Open WebUI
4. The Role of Open WebUI
Open WebUI
is a powerful frontend tool that provides a graphical interface for chatting.
Does it expose an API?
Generally,
no
, not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates
with
the backend (Ollama).
How to use it in your setup:
You set up Ollama
(running the model).
You set up Open WebUI
(to chat with the model visually).
You use the Ollama API directly
(using
curl
or Python) if you need to integrate the model into a custom application, script, or website.
Summary Checklist
Summary Checklist
GOAL
TOOL TO USE
ENDPOINT
ACCESS METHOD
Self-hosted Model Access
Ollama
http://[IP]:11434
REST API (POST requests)
Graphical Chatting
Open WebUI
(Web Interface)
Browser
Programmatic API Calls
curl
or
Python (
requests
)
/api/chat
or
/api/generate
HTTP Request
GOAL
Self-hosted Model Access
Graphical Chatting
Programmatic API Calls
TOOL TO USE
Ollama
Open WebUI
curl
or
Python (
requests
)
ENDPOINT
http://[IP]:11434
(Web Interface)
/api/chat
or
/api/generate
ACCESS METHOD
REST API (POST requests)
Browser
HTTP Request
Edit
Copy
Read Aloud
Good Response
Bad Response
Regenerate
ok I am using gemma4:e2b create crul request for me
gemma4:e2b
Send a Message
Send a Message...
|
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Conversation","depth":16,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gemma4:e2b","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yesterday at 9:33 PM","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thought for 2 minutes","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is the service that exposes the REST API, while","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is primarily a graphical user interface (GUI) for chatting with those models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a complete guide on how you can access and interact with your self-hosted model via API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Understanding Ollama as the API Endpoint","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Understanding Ollama as the API Endpoint","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"A. Default API URL","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A. Default API URL","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, Ollama runs on:","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"URL:","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://localhost:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if running on the same machine)","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://[Your_Server_IP]:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if you are accessing it from another device on your local network).","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"B. API Methods","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"B. API Methods","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama uses standard HTTP methods (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") to interact with its endpoints. The most common endpoints for generating text are:","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating a single response based on a prompt.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For multi-turn conversations (simulating a chat interface).","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/embeddings","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating vector embeddings.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How to Make the REST API Call (Using curl)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How to Make the REST API Call (Using","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can use command-line tools like","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to test and interact with the Ollama API directly.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 1: Single Generation Call (/api/generate)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 1: Single Generation Call (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This example sends a prompt to the model and waits for the generated response.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","depth":24,"on_screen":false,"value":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/generate","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral)","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\": \"Write a short poem about self-hosting AI.\",","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 2: Chat Completion Call (/api/chat)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 2: Chat Completion Call (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is better for conversational use, as it maintains context.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","depth":24,"on_screen":false,"value":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST 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models?\"}","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"],","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. Using Programming Languages (The Professional Way)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. Using Programming Languages (The Professional Way)","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Python Example (Recommended)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python Example (Recommended)","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python, with the","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"library, is the easiest way to interact with the Ollama API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"python","depth":25,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Run","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Run","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","depth":24,"on_screen":true,"value":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"import","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"import","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 1. Define the API endpoint","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"http://localhost:11434/api/generate\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 2. Define the request payload (what you are sending)","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"llama3\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Explain the difference between Ollama and Open WebUI.\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"False","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 3. Make the POST request","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"try","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"post","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"raise_for_status","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"()","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# Raise an exception for bad status codes (4xx or 5xx)","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 4. Parse the JSON response","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"result","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"()","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# Print the generated text","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"print","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Generated Response:\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"print","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"result","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"get","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"response\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"))","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"except","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"exceptions","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"RequestException","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"as","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"e","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"print","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"f\"An error occurred:","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"e","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"4. The Role of Open WebUI","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"4. The Role of Open WebUI","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is a powerful frontend tool that provides a graphical interface for chatting.","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Does it expose an API?","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Generally,","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"no","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"with","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the backend (Ollama).","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How to use it in your setup:","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You set up Ollama","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(running the model).","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You set up Open WebUI","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(to chat with the model visually).","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You use the Ollama API directly","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(using","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":24,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or Python) if you need to integrate the model into a custom application, script, or website.","depth":23,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Summary Checklist","depth":21,"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Summary Checklist","depth":22,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"GOAL","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"TOOL TO USE","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ENDPOINT","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"ACCESS METHOD","depth":26,"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Self-hosted Model 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How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
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Save
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curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
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curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
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Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(
"Generated Response:"
)
print
(
result
.
get
(
"response"
))
except
requests
.
exceptions
.
RequestException
as
e
:
print
(
f"An error occurred:
{
e
}
"
)
4. The Role of Open WebUI
4. The Role of Open WebUI
Open WebUI
is a powerful frontend tool that provides a graphical interface for chatting.
Does it expose an API?
Generally,
no
, not as a primary source for programmatic API calls. Open WebUI acts as a client that communicates
with
the backend (Ollama).
How to use it in your setup:
You set up Ollama
(running the model).
You set up Open WebUI
(to chat with the model visually).
You use the Ollama API directly
(using
curl
or Python) if you need to integrate the model into a custom application, script, or website.
Summary Checklist
Summary Checklist
GOAL
TOOL TO USE
ENDPOINT
ACCESS METHOD
Self-hosted Model Access
Ollama
http://[IP]:11434
REST API (POST requests)
Graphical Chatting
Open WebUI
(Web Interface)
Browser
Programmatic API Calls
curl
or
Python (
requests
)
/api/chat
or
/api/generate
HTTP Request
GOAL
Self-hosted Model Access
Graphical Chatting
Programmatic API Calls
TOOL TO USE
Ollama
Open WebUI
curl
or
Python (
requests
)
ENDPOINT
http://[IP]:11434
(Web Interface)
/api/chat
or
/api/generate
ACCESS METHOD
REST API (POST requests)
Browser
HTTP Request
Edit
Copy
Read Aloud
Good Response
Bad Response
Regenerate
ok I am using gemma4:e2b create crul request for me
gemma4:e2b
Send a Message
Send a Message...
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68795
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NULL
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NULL
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68798
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2026-05-21T15:03:28.322077+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375808322_m2.jpg...
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Firefox
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Ollama API Setup 💻 • Open WebUI — Personal
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ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371 ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfa...
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins
Завеждане на щета онлайн | Euroins
Screenpipe — Archive
Screenpipe — Archive
Reminders
Reminders
Photos - Google Photos
Photos - Google Photos
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
New Tab
Nginx Proxy Manager
Nginx Proxy Manager
Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(...
|
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menu","depth":15,"bounds":{"left":0.9896942,"top":0.061053474,"width":0.010305822,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Chat Conversation","depth":15,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Chat Conversation","depth":16,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gemma4:e2b","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yesterday at 9:33 PM","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thought for 2 minutes","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is the service that exposes the REST API, while","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is primarily a graphical user interface (GUI) for chatting with those models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a complete guide on how you can access and interact with your self-hosted model via API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Understanding Ollama as the API Endpoint","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Understanding Ollama as the API Endpoint","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"A. Default API URL","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A. Default API URL","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, Ollama runs on:","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"URL:","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://localhost:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if running on the same machine)","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://[Your_Server_IP]:11434","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if you are accessing it from another device on your local network).","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"B. API Methods","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"B. API Methods","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama uses standard HTTP methods (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") to interact with its endpoints. The most common endpoints for generating text are:","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating a single response based on a prompt.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For multi-turn conversations (simulating a chat interface).","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/embeddings","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating vector embeddings.","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How to Make the REST API Call (Using curl)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How to Make the REST API Call (Using","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can use command-line tools like","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to test and interact with the Ollama API directly.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 1: Single Generation Call (/api/generate)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 1: Single Generation Call (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This example sends a prompt to the model and waits for the generated response.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","depth":24,"on_screen":false,"value":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/generate","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral)","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\": \"Write a short poem about self-hosting AI.\",","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 2: Chat Completion Call (/api/chat)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 2: Chat Completion Call (","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is better for conversational use, as it maintains context.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"bounds":{"left":0.6499335,"top":0.017956903,"width":0.008976064,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.89877,"top":0.015961692,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.90608376,"top":0.017956903,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.015961692,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.015961692,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","depth":24,"bounds":{"left":0.6559175,"top":0.0,"width":0.30053192,"height":0.11572227},"on_screen":true,"value":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"bounds":{"left":0.65791225,"top":0.0,"width":0.011303191,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"bounds":{"left":0.67204124,"top":0.0,"width":0.005485372,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/chat","depth":26,"bounds":{"left":0.6775266,"top":0.0,"width":0.1065492,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"bounds":{"left":0.7840758,"top":0.0,"width":0.0056515955,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"bounds":{"left":0.7925532,"top":0.0,"width":0.0056515955,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\",","depth":26,"bounds":{"left":0.65791225,"top":0.0,"width":0.05618351,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"messages\": [","depth":26,"bounds":{"left":0.65791225,"top":0.0,"width":0.042054523,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"}","depth":26,"bounds":{"left":0.65791225,"top":0.0,"width":0.23836437,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"],","depth":26,"bounds":{"left":0.65791225,"top":0.0,"width":0.011303191,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"bounds":{"left":0.65791225,"top":0.0035913808,"width":0.047706116,"height":0.0131683955},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"bounds":{"left":0.65791225,"top":0.01915403,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. Using Programming Languages (The Professional Way)","depth":21,"bounds":{"left":0.6456117,"top":0.06384677,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. Using Programming Languages (The Professional Way)","depth":22,"bounds":{"left":0.6456117,"top":0.0650439,"width":0.20711437,"height":0.023144454},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.","depth":22,"bounds":{"left":0.6456117,"top":0.096169196,"width":0.30618352,"height":0.037509978},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Python Example (Recommended)","depth":21,"bounds":{"left":0.6456117,"top":0.14365523,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python Example (Recommended)","depth":22,"bounds":{"left":0.6456117,"top":0.14684756,"width":0.10239362,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python, with the","depth":22,"bounds":{"left":0.6456117,"top":0.17597765,"width":0.040724736,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":23,"bounds":{"left":0.68866354,"top":0.17797287,"width":0.021775266,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"library, is the easiest way to interact with the Ollama API.","depth":22,"bounds":{"left":0.71276593,"top":0.17597765,"width":0.13813165,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"python","depth":25,"bounds":{"left":0.6499335,"top":0.20869912,"width":0.012965426,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.88680184,"top":0.20670392,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.8941157,"top":0.20869912,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Run","depth":22,"bounds":{"left":0.91306514,"top":0.20670392,"width":0.011303191,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Run","depth":24,"bounds":{"left":0.91505986,"top":0.20869912,"width":0.00731383,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.20670392,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.20670392,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","depth":24,"bounds":{"left":0.6575798,"top":0.22266561,"width":0.29886967,"height":0.42897046},"on_screen":true,"value":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"import","depth":26,"bounds":{"left":0.65957445,"top":0.22705507,"width":0.016788565,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"bounds":{"left":0.67918885,"top":0.22705507,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"import","depth":26,"bounds":{"left":0.65957445,"top":0.24261771,"width":0.016788565,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"bounds":{"left":0.67918885,"top":0.24261771,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 1. Define the API endpoint","depth":26,"bounds":{"left":0.65957445,"top":0.27414206,"width":0.078457445,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"bounds":{"left":0.65957445,"top":0.2897047,"width":0.008477394,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.67087764,"top":0.2897047,"width":0.0026595744,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"http://localhost:11434/api/generate\"","depth":26,"bounds":{"left":0.67636305,"top":0.2897047,"width":0.10372341,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 2. Define the request payload (what you are sending)","depth":26,"bounds":{"left":0.65957445,"top":0.32083002,"width":0.15142952,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"bounds":{"left":0.65957445,"top":0.3367917,"width":0.019614361,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.68201464,"top":0.3367917,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":26,"bounds":{"left":0.68484044,"top":0.3367917,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\"","depth":26,"bounds":{"left":0.67087764,"top":0.35235435,"width":0.019614361,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.69049203,"top":0.35235435,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"llama3\"","depth":26,"bounds":{"left":0.6959774,"top":0.35235435,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":0.7184175,"top":0.35235435,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\"","depth":26,"bounds":{"left":0.67087764,"top":0.367917,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.69331783,"top":0.367917,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Explain the difference between Ollama and Open WebUI.\"","depth":26,"bounds":{"left":0.6988032,"top":0.367917,"width":0.15425532,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":0.8530585,"top":0.367917,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\"","depth":26,"bounds":{"left":0.67087764,"top":0.38347965,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.69331783,"top":0.38347965,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"False","depth":26,"bounds":{"left":0.6988032,"top":0.38347965,"width":0.01412899,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":26,"bounds":{"left":0.65957445,"top":0.3990423,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 3. Make the POST request","depth":26,"bounds":{"left":0.65957445,"top":0.43056664,"width":0.072972074,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"try","depth":26,"bounds":{"left":0.65957445,"top":0.4461293,"width":0.008477394,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.66805184,"top":0.4461293,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"bounds":{"left":0.67087764,"top":0.46169195,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.6959774,"top":0.46169195,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"bounds":{"left":0.701629,"top":0.46169195,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"bounds":{"left":0.7240692,"top":0.46169195,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"post","depth":26,"bounds":{"left":0.726895,"top":0.46169195,"width":0.011136968,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"bounds":{"left":0.7380319,"top":0.46169195,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"bounds":{"left":0.7408577,"top":0.46169195,"width":0.008477394,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":0.7493351,"top":0.46169195,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"bounds":{"left":0.7549867,"top":0.46169195,"width":0.011136968,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.76612365,"top":0.46169195,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"bounds":{"left":0.76894945,"top":0.46169195,"width":0.019614361,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":26,"bounds":{"left":0.78856385,"top":0.46169195,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"bounds":{"left":0.67087764,"top":0.4772546,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"bounds":{"left":0.69331783,"top":0.4772546,"width":0.0026595744,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"raise_for_status","depth":26,"bounds":{"left":0.6959774,"top":0.4772546,"width":0.04488032,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"()","depth":26,"bounds":{"left":0.7408577,"top":0.4772546,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# Raise an exception for bad status codes (4xx or 5xx)","depth":26,"bounds":{"left":0.7521609,"top":0.4772546,"width":0.15142952,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 4. Parse the JSON response","depth":26,"bounds":{"left":0.67087764,"top":0.5087789,"width":0.078457445,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"result","depth":26,"bounds":{"left":0.67087764,"top":0.5243416,"width":0.016788565,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.69049203,"top":0.5243416,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"bounds":{"left":0.6959774,"top":0.5243416,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"bounds":{"left":0.7184175,"top":0.5243416,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"bounds":{"left":0.7212433,"top":0.5243416,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"()","depth":26,"bounds":{"left":0.73254657,"top":0.5243416,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# Print the generated text","depth":26,"bounds":{"left":0.67087764,"top":0.5554669,"width":0.07280585,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"print","depth":26,"bounds":{"left":0.67087764,"top":0.5714286,"width":0.013962766,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"bounds":{"left":0.68484044,"top":0.5714286,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
|
-241525858201414733
|
-8215781093675939509
|
visual_change
|
accessibility
|
NULL
|
New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
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A new version (v0.9.5) is now available.
Update for the latest features and improvements.
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Open Sidebar New Chat Search Notes Workspace
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Open User Profile Menu
Selected model: gemma4:e2b
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How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url
,
json
=
payload
)
response
.
raise_for_status
()
# Raise an exception for bad status codes (4xx or 5xx)
# 4. Parse the JSON response
result
=
response
.
json
()
# Print the generated text
print
(...
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2463
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80
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2026-05-21T15:03:31.341318+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375811341_m2.jpg...
|
Firefox
|
Ollama API Setup 💻 • Open WebUI — Personal
|
1
|
ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371 ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfa...
|
monitor_2
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NULL
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NULL
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NULL
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
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Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
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Welcome to authentik! - authentik
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Reminders
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DXP4800PLUS-B5F8
New Tab
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Nginx Proxy Manager
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Ollama API Setup 💻 • Open WebUI
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Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response...
|
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PM","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thought for 2 minutes","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is the service that exposes the REST API, while","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is primarily a graphical user 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Default API URL","depth":21,"bounds":{"left":0.6456117,"top":0.0622506,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A. 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API Methods","depth":21,"bounds":{"left":0.6456117,"top":0.16440542,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"B. API Methods","depth":22,"bounds":{"left":0.6456117,"top":0.16759777,"width":0.046875,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama uses standard HTTP methods (","depth":22,"bounds":{"left":0.6456117,"top":0.19672786,"width":0.093417555,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":23,"bounds":{"left":0.7413564,"top":0.19872306,"width":0.010804521,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") to interact with its endpoints. The most common endpoints for generating text are:","depth":22,"bounds":{"left":0.6456117,"top":0.19672786,"width":0.30103058,"height":0.037509978},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":25,"bounds":{"left":0.6584109,"top":0.24980047,"width":0.035405584,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating a single response based on a prompt.","depth":23,"bounds":{"left":0.6959774,"top":0.24780527,"width":0.1306516,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":25,"bounds":{"left":0.6584109,"top":0.27214685,"width":0.02443484,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For multi-turn conversations (simulating a chat interface).","depth":23,"bounds":{"left":0.68517286,"top":0.27015164,"width":0.1419548,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/embeddings","depth":25,"bounds":{"left":0.6584109,"top":0.29449323,"width":0.04089096,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating vector embeddings.","depth":23,"bounds":{"left":0.70146275,"top":0.292498,"width":0.087932184,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How to Make the REST API Call (Using curl)","depth":21,"bounds":{"left":0.6456117,"top":0.31763768,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How to Make the REST API Call (Using","depth":22,"bounds":{"left":0.6456117,"top":0.31883478,"width":0.14694148,"height":0.023144454},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"bounds":{"left":0.7947141,"top":0.32242617,"width":0.016289894,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"bounds":{"left":0.8133311,"top":0.31883478,"width":0.0029920214,"height":0.023144454},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can use command-line tools like","depth":22,"bounds":{"left":0.6456117,"top":0.3499601,"width":0.08976064,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"bounds":{"left":0.7375333,"top":0.3519553,"width":0.010970744,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to test and interact with the Ollama API directly.","depth":22,"bounds":{"left":0.7506649,"top":0.3499601,"width":0.1165226,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 1: Single Generation Call (/api/generate)","depth":21,"bounds":{"left":0.6456117,"top":0.37509975,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 1: Single Generation Call (","depth":22,"bounds":{"left":0.6456117,"top":0.3782921,"width":0.10605053,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":23,"bounds":{"left":0.75398934,"top":0.3810854,"width":0.044215426,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"bounds":{"left":0.8005319,"top":0.3782921,"width":0.002493351,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This example sends a prompt to the model and waits for the generated response.","depth":22,"bounds":{"left":0.6456117,"top":0.40742218,"width":0.19630983,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"bounds":{"left":0.6499335,"top":0.44014364,"width":0.008976064,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.89877,"top":0.43814844,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.90608376,"top":0.44014364,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.43814844,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.43814844,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","depth":24,"bounds":{"left":0.6559175,"top":0.45411015,"width":0.30053192,"height":0.08459697},"on_screen":true,"value":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"bounds":{"left":0.65791225,"top":0.4584996,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"bounds":{"left":0.67204124,"top":0.4584996,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/generate","depth":26,"bounds":{"left":0.6775266,"top":0.4584996,"width":0.1178524,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"bounds":{"left":0.795379,"top":0.4584996,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"bounds":{"left":0.80369014,"top":0.4584996,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral)","depth":26,"bounds":{"left":0.65791225,"top":0.47406226,"width":0.2551529,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\": \"Write a short poem about self-hosting AI.\",","depth":26,"bounds":{"left":0.65791225,"top":0.4896249,"width":0.15708111,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"bounds":{"left":0.65791225,"top":0.5051876,"width":0.047706116,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"bounds":{"left":0.65791225,"top":0.5211492,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 2: Chat Completion Call (/api/chat)","depth":21,"bounds":{"left":0.6456117,"top":0.54588985,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 2: Chat Completion Call (","depth":22,"bounds":{"left":0.6456117,"top":0.5490822,"width":0.10405585,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":23,"bounds":{"left":0.75199467,"top":0.5518755,"width":0.030585106,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"bounds":{"left":0.7849069,"top":0.5490822,"width":0.002493351,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is better for conversational use, as it maintains context.","depth":22,"bounds":{"left":0.6456117,"top":0.57821226,"width":0.14478059,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"bounds":{"left":0.6499335,"top":0.6109338,"width":0.008976064,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.89877,"top":0.6089386,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.90608376,"top":0.6109338,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.6089386,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.6089386,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","depth":24,"bounds":{"left":0.6559175,"top":0.6249002,"width":0.30053192,"height":0.11572227},"on_screen":true,"value":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"bounds":{"left":0.65791225,"top":0.6292897,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"bounds":{"left":0.67204124,"top":0.6292897,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/chat","depth":26,"bounds":{"left":0.6775266,"top":0.6292897,"width":0.1065492,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"bounds":{"left":0.7840758,"top":0.6292897,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"bounds":{"left":0.7925532,"top":0.6292897,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\",","depth":26,"bounds":{"left":0.65791225,"top":0.64485234,"width":0.05618351,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"messages\": [","depth":26,"bounds":{"left":0.65791225,"top":0.660415,"width":0.042054523,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"}","depth":26,"bounds":{"left":0.65791225,"top":0.67597765,"width":0.23836437,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"],","depth":26,"bounds":{"left":0.65791225,"top":0.69193935,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"bounds":{"left":0.65791225,"top":0.707502,"width":0.047706116,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"bounds":{"left":0.65791225,"top":0.72306466,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. Using Programming Languages (The Professional Way)","depth":21,"bounds":{"left":0.6456117,"top":0.76775736,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. Using Programming Languages (The Professional Way)","depth":22,"bounds":{"left":0.6456117,"top":0.7689545,"width":0.20711437,"height":0.023144454},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.","depth":22,"bounds":{"left":0.6456117,"top":0.8000798,"width":0.30618352,"height":0.037509978},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Python Example (Recommended)","depth":21,"bounds":{"left":0.6456117,"top":0.8475658,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python Example (Recommended)","depth":22,"bounds":{"left":0.6456117,"top":0.8507582,"width":0.10239362,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python, with the","depth":22,"bounds":{"left":0.6456117,"top":0.8798883,"width":0.040724736,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":23,"bounds":{"left":0.68866354,"top":0.8818835,"width":0.021775266,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"library, is the easiest way to interact with the Ollama API.","depth":22,"bounds":{"left":0.71276593,"top":0.8798883,"width":0.13813165,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"python","depth":25,"bounds":{"left":0.6499335,"top":0.91260976,"width":0.012965426,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.88680184,"top":0.91061455,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.8941157,"top":0.91260976,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Run","depth":22,"bounds":{"left":0.91306514,"top":0.91061455,"width":0.011303191,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Run","depth":24,"bounds":{"left":0.91505986,"top":0.91260976,"width":0.00731383,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.91061455,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.91061455,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","depth":24,"bounds":{"left":0.6575798,"top":0.9265762,"width":0.29886967,"height":0.0734238},"on_screen":true,"value":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"import","depth":26,"bounds":{"left":0.65957445,"top":0.93096566,"width":0.016788565,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"bounds":{"left":0.67918885,"top":0.93096566,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"import","depth":26,"bounds":{"left":0.65957445,"top":0.9465283,"width":0.016788565,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"bounds":{"left":0.67918885,"top":0.9465283,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 1. Define the API endpoint","depth":26,"bounds":{"left":0.65957445,"top":0.9780527,"width":0.078457445,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"bounds":{"left":0.65957445,"top":0.9936153,"width":0.008477394,"height":0.0063846707},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.67087764,"top":0.9936153,"width":0.0026595744,"height":0.0063846707},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"http://localhost:11434/api/generate\"","depth":26,"bounds":{"left":0.67636305,"top":0.9936153,"width":0.10372341,"height":0.0063846707},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 2. Define the request payload (what you are sending)","depth":26,"bounds":{"left":0.65957445,"top":1.0,"width":0.15142952,"height":-0.024740577},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"bounds":{"left":0.65957445,"top":1.0,"width":0.019614361,"height":-0.040702343},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.68201464,"top":1.0,"width":0.0028257978,"height":-0.040702343},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":26,"bounds":{"left":0.68484044,"top":1.0,"width":0.0056515955,"height":-0.040702343},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\"","depth":26,"bounds":{"left":0.67087764,"top":1.0,"width":0.019614361,"height":-0.056264997},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.69049203,"top":1.0,"width":0.005485372,"height":-0.056264997},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"llama3\"","depth":26,"bounds":{"left":0.6959774,"top":1.0,"width":0.02244016,"height":-0.056264997},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":0.7184175,"top":1.0,"width":0.0028257978,"height":-0.056264997},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\"","depth":26,"bounds":{"left":0.67087764,"top":1.0,"width":0.02244016,"height":-0.07182765},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.69331783,"top":1.0,"width":0.005485372,"height":-0.07182765},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Explain the difference between Ollama and Open WebUI.\"","depth":26,"bounds":{"left":0.6988032,"top":1.0,"width":0.15425532,"height":-0.07182765},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":0.8530585,"top":1.0,"width":0.0028257978,"height":-0.07182765},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\"","depth":26,"bounds":{"left":0.67087764,"top":1.0,"width":0.02244016,"height":-0.0873903},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.69331783,"top":1.0,"width":0.005485372,"height":-0.0873903},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"False","depth":26,"bounds":{"left":0.6988032,"top":1.0,"width":0.01412899,"height":-0.0873903},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 3. Make the POST request","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"try","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
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Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
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Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
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Welcome to authentik! - authentik
Welcome to authentik! - authentik
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New Tab
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Ollama API Setup 💻 • Open WebUI
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Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
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Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response...
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2026-05-21T15:03:34.349867+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375814349_m2.jpg...
|
Firefox
|
Ollama API Setup 💻 • Open WebUI — Personal
|
1
|
ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371 ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfa...
|
monitor_2
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New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins
Завеждане на щета онлайн | Euroins
Screenpipe — Archive
Screenpipe — Archive
Reminders
Reminders
Photos - Google Photos
Photos - Google Photos
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
New Tab
Nginx Proxy Manager
Nginx Proxy Manager
Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"...
|
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User Profile Menu","depth":10,"bounds":{"left":0.5728058,"top":0.9648843,"width":0.00930851,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Selected model: gemma4:e2b","depth":16,"bounds":{"left":0.5909242,"top":0.05905826,"width":0.043550532,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"gemma4:e2b","depth":18,"bounds":{"left":0.5915891,"top":0.061851557,"width":0.03557181,"height":0.01715882},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Add Model","depth":16,"bounds":{"left":0.6371343,"top":0.06424581,"width":0.004654255,"height":0.011173184},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Controls","depth":14,"bounds":{"left":0.97207445,"top":0.055067837,"width":0.011968086,"height":0.028731046},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"User menu","depth":13,"bounds":{"left":0.9840425,"top":0.055067837,"width":0.011968086,"height":0.028731046},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"User menu","depth":15,"bounds":{"left":0.9896942,"top":0.061053474,"width":0.010305822,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Chat Conversation","depth":15,"bounds":{"left":0.5859375,"top":0.07980846,"width":0.0003324468,"height":0.0007980846},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Chat Conversation","depth":16,"bounds":{"left":0.5859375,"top":0.08180367,"width":0.04454787,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model","depth":21,"bounds":{"left":0.69298536,"top":0.10175578,"width":0.2584774,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gemma4:e2b","depth":21,"bounds":{"left":0.6456117,"top":0.16241021,"width":0.033410903,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yesterday at 9:33 PM","depth":22,"bounds":{"left":0.6810173,"top":0.16480447,"width":0.04105718,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thought for 2 minutes","depth":23,"bounds":{"left":0.6456117,"top":0.18316041,"width":0.053690158,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that","depth":22,"bounds":{"left":0.6456117,"top":0.20550679,"width":0.30452126,"height":0.037509978},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama","depth":23,"bounds":{"left":0.6565825,"top":0.22785315,"width":0.017453458,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is the service that exposes the REST API, while","depth":22,"bounds":{"left":0.6740359,"top":0.22785315,"width":0.11619016,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"bounds":{"left":0.79022604,"top":0.22785315,"width":0.03158245,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is primarily a graphical user interface (GUI) for chatting with those models.","depth":22,"bounds":{"left":0.6456117,"top":0.22785315,"width":0.31050533,"height":0.037509978},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a complete guide on how you can access and interact with your self-hosted model via API.","depth":22,"bounds":{"left":0.6456117,"top":0.27893057,"width":0.23670213,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Understanding Ollama as the API Endpoint","depth":21,"bounds":{"left":0.6456117,"top":0.32402235,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Understanding Ollama as the API Endpoint","depth":22,"bounds":{"left":0.6456117,"top":0.32521948,"width":0.16023937,"height":0.023144454},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.","depth":22,"bounds":{"left":0.6456117,"top":0.35634476,"width":0.30950797,"height":0.037509978},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"A. Default API URL","depth":21,"bounds":{"left":0.6456117,"top":0.4038308,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A. Default API URL","depth":22,"bounds":{"left":0.6456117,"top":0.40702313,"width":0.05668218,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, Ollama runs on:","depth":22,"bounds":{"left":0.6456117,"top":0.43615323,"width":0.06499335,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"URL:","depth":24,"bounds":{"left":0.65625,"top":0.4584996,"width":0.011968086,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://localhost:11434","depth":24,"bounds":{"left":0.67204124,"top":0.46049482,"width":0.059840426,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if running on the same machine)","depth":23,"bounds":{"left":0.7340425,"top":0.4584996,"width":0.08128324,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":24,"bounds":{"left":0.65625,"top":0.48084596,"width":0.0051529254,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://[Your_Server_IP]:11434","depth":24,"bounds":{"left":0.66522604,"top":0.4828412,"width":0.0787899,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if you are accessing it from another device on your local network).","depth":23,"bounds":{"left":0.7463431,"top":0.48084596,"width":0.1627327,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"B. API Methods","depth":21,"bounds":{"left":0.6456117,"top":0.5059856,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"B. API Methods","depth":22,"bounds":{"left":0.6456117,"top":0.509178,"width":0.046875,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama uses standard HTTP methods (","depth":22,"bounds":{"left":0.6456117,"top":0.5383081,"width":0.093417555,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":23,"bounds":{"left":0.7413564,"top":0.5403033,"width":0.010804521,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") to interact with its endpoints. The most common endpoints for generating text are:","depth":22,"bounds":{"left":0.6456117,"top":0.5383081,"width":0.30103058,"height":0.037509978},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":25,"bounds":{"left":0.6584109,"top":0.5913807,"width":0.035405584,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating a single response based on a prompt.","depth":23,"bounds":{"left":0.6959774,"top":0.58938545,"width":0.1306516,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":25,"bounds":{"left":0.6584109,"top":0.61372703,"width":0.02443484,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For multi-turn conversations (simulating a chat interface).","depth":23,"bounds":{"left":0.68517286,"top":0.6117318,"width":0.1419548,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/embeddings","depth":25,"bounds":{"left":0.6584109,"top":0.6360734,"width":0.04089096,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating vector embeddings.","depth":23,"bounds":{"left":0.70146275,"top":0.6340782,"width":0.087932184,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How to Make the REST API Call (Using curl)","depth":21,"bounds":{"left":0.6456117,"top":0.6592179,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How to Make the REST API Call (Using","depth":22,"bounds":{"left":0.6456117,"top":0.660415,"width":0.14694148,"height":0.023144454},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"bounds":{"left":0.7947141,"top":0.6640064,"width":0.016289894,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"bounds":{"left":0.8133311,"top":0.660415,"width":0.0029920214,"height":0.023144454},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can use command-line tools like","depth":22,"bounds":{"left":0.6456117,"top":0.6915403,"width":0.08976064,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"bounds":{"left":0.7375333,"top":0.6935355,"width":0.010970744,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to test and interact with the Ollama API directly.","depth":22,"bounds":{"left":0.7506649,"top":0.6915403,"width":0.1165226,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 1: Single Generation Call (/api/generate)","depth":21,"bounds":{"left":0.6456117,"top":0.71668,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 1: Single Generation Call (","depth":22,"bounds":{"left":0.6456117,"top":0.7198723,"width":0.10605053,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":23,"bounds":{"left":0.75398934,"top":0.7226656,"width":0.044215426,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"bounds":{"left":0.8005319,"top":0.7198723,"width":0.002493351,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This example sends a prompt to the model and waits for the generated response.","depth":22,"bounds":{"left":0.6456117,"top":0.7490024,"width":0.19630983,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"bounds":{"left":0.6499335,"top":0.78172386,"width":0.008976064,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.89877,"top":0.77972865,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.90608376,"top":0.78172386,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.77972865,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.77972865,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","depth":24,"bounds":{"left":0.6559175,"top":0.79569036,"width":0.30053192,"height":0.08459697},"on_screen":true,"value":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"bounds":{"left":0.65791225,"top":0.8000798,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"bounds":{"left":0.67204124,"top":0.8000798,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/generate","depth":26,"bounds":{"left":0.6775266,"top":0.8000798,"width":0.1178524,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"bounds":{"left":0.795379,"top":0.8000798,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"bounds":{"left":0.80369014,"top":0.8000798,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral)","depth":26,"bounds":{"left":0.65791225,"top":0.8156425,"width":0.2551529,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\": \"Write a short poem about self-hosting AI.\",","depth":26,"bounds":{"left":0.65791225,"top":0.8312051,"width":0.15708111,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"bounds":{"left":0.65791225,"top":0.8467678,"width":0.047706116,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"bounds":{"left":0.65791225,"top":0.86272943,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 2: Chat Completion Call (/api/chat)","depth":21,"bounds":{"left":0.6456117,"top":0.88747007,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 2: Chat Completion Call (","depth":22,"bounds":{"left":0.6456117,"top":0.89066243,"width":0.10405585,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":23,"bounds":{"left":0.75199467,"top":0.8934557,"width":0.030585106,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"bounds":{"left":0.7849069,"top":0.89066243,"width":0.002493351,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is better for conversational use, as it maintains context.","depth":22,"bounds":{"left":0.6456117,"top":0.9197925,"width":0.14478059,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"bounds":{"left":0.6499335,"top":0.952514,"width":0.008976064,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.89877,"top":0.9505187,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.90608376,"top":0.952514,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.9505187,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.9505187,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","depth":24,"bounds":{"left":0.6559175,"top":0.96648043,"width":0.30053192,"height":0.033519566},"on_screen":true,"value":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"bounds":{"left":0.65791225,"top":0.9708699,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"bounds":{"left":0.67204124,"top":0.9708699,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/chat","depth":26,"bounds":{"left":0.6775266,"top":0.9708699,"width":0.1065492,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"bounds":{"left":0.7840758,"top":0.9708699,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"bounds":{"left":0.7925532,"top":0.9708699,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\",","depth":26,"bounds":{"left":0.65791225,"top":0.98643255,"width":0.05618351,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"messages\": [","depth":26,"bounds":{"left":0.65791225,"top":1.0,"width":0.042054523,"height":-0.0019952059},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"}","depth":26,"bounds":{"left":0.65791225,"top":1.0,"width":0.23836437,"height":-0.01755786},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"],","depth":26,"bounds":{"left":0.65791225,"top":1.0,"width":0.011303191,"height":-0.033519506},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"bounds":{"left":0.65791225,"top":1.0,"width":0.047706116,"height":-0.04908216},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"bounds":{"left":0.65791225,"top":1.0,"width":0.0056515955,"height":-0.06464481},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. Using Programming Languages (The Professional Way)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. Using Programming Languages (The Professional Way)","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Python Example (Recommended)","depth":21,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python Example (Recommended)","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python, with the","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"library, is the easiest way to interact with the Ollama API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"python","depth":25,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Run","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Run","depth":24,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","depth":24,"on_screen":false,"value":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"import","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"import","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 1. Define the API endpoint","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"http://localhost:11434/api/generate\"","depth":26,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
|
1626352969782686001
|
-2459054869990618805
|
visual_change
|
accessibility
|
NULL
|
New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins
Завеждане на щета онлайн | Euroins
Screenpipe — Archive
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Reminders
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Photos - Google Photos
Photos - Google Photos
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
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Nginx Proxy Manager
Nginx Proxy Manager
Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"...
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2463
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82
|
2026-05-21T15:03:37.380398+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-21/1779 /Users/lukas/.screenpipe/data/data/2026-05-21/1779375817380_m2.jpg...
|
Firefox
|
Ollama API Setup 💻 • Open WebUI — Personal
|
1
|
ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371 ai.chat.lakylak.xyz/c/ac2a9877-420f-403e-bc4f-4371a1766cfa...
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
New Device Logged In From Firefox Extension - [EMA New Device Logged In From Firefox Extension - [EMAIL] - Gmail
New Device Logged In From Firefox Extension - [EMAIL] - Gmail
Ambulatory sheet - Paperless-ngx
Ambulatory sheet - Paperless-ngx
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
💬1 - Apple MacBook Pro 14" Space Black M5 Max | Laptop.bg - Технологията с теб
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа
Welcome to authentik! - authentik
Welcome to authentik! - authentik
Завеждане на щета онлайн | Euroins
Завеждане на щета онлайн | Euroins
Screenpipe — Archive
Screenpipe — Archive
Reminders
Reminders
Photos - Google Photos
Photos - Google Photos
DXP4800PLUS-B5F8
DXP4800PLUS-B5F8
New Tab
New Tab
Nginx Proxy Manager
Nginx Proxy Manager
Ollama API Setup 💻 • Open WebUI
Ollama API Setup 💻 • Open WebUI
Close tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden [9+]
A new version (v0.9.5) is now available.
Update for the latest features and improvements.
Update for the latest features and improvements.
Open Sidebar New Chat Search Notes Workspace
Open Sidebar
New Chat
Search
Notes
Workspace
Open User Profile Menu
Selected model: gemma4:e2b
gemma4:e2b
Add Model
Controls
User menu
User menu
Chat Conversation
Chat Conversation
How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
Collapse
Collapse
Save
Copy
curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
Collapse
Collapse
Run
Run
Save
Copy
import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url...
|
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Paperless-ngx","depth":5,"bounds":{"left":0.51329786,"top":0.09577015,"width":0.059507977,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"💬1 - Apple MacBook Pro 14\" Space Black M5 Max | Laptop.bg - Технологията с теб","depth":4,"bounds":{"left":0.5,"top":0.11731844,"width":0.06881649,"height":0.032721467},"on_screen":true,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"💬1 - Apple MacBook Pro 14\" Space Black M5 Max | Laptop.bg - Технологията с теб","depth":5,"bounds":{"left":0.51329786,"top":0.12849163,"width":0.14727394,"height":0.011572227},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа","depth":4,"bounds":{"left":0.5,"top":0.15003991,"width":0.06881649,"height":0.032721467},"on_screen":true,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Apple Mac Studio M4 Max | Desktop.bg - Мощни PC Гейминг конфигурации, Персонални компютри на изплащане за игри и работа","depth":5,"bounds":{"left":0.51329786,"top":0.16121309,"width":0.2365359,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Welcome to authentik! - authentik","depth":4,"bounds":{"left":0.5,"top":0.18276137,"width":0.06881649,"height":0.032721467},"on_screen":true,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Welcome to authentik! - authentik","depth":5,"bounds":{"left":0.51329786,"top":0.19393456,"width":0.05900931,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Завеждане на щета онлайн | Euroins","depth":4,"bounds":{"left":0.5,"top":0.21548285,"width":0.06881649,"height":0.032721467},"on_screen":true,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Завеждане на щета онлайн | Euroins","depth":5,"bounds":{"left":0.51329786,"top":0.22665602,"width":0.0653258,"height":0.010774142},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Screenpipe — 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User Profile Menu","depth":10,"bounds":{"left":0.5728058,"top":0.9648843,"width":0.00930851,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Selected model: gemma4:e2b","depth":16,"bounds":{"left":0.5909242,"top":0.05905826,"width":0.043550532,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"gemma4:e2b","depth":18,"bounds":{"left":0.5915891,"top":0.061851557,"width":0.03557181,"height":0.01715882},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Add Model","depth":16,"bounds":{"left":0.6371343,"top":0.06424581,"width":0.004654255,"height":0.011173184},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Controls","depth":14,"bounds":{"left":0.97207445,"top":0.055067837,"width":0.011968086,"height":0.028731046},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"User menu","depth":13,"bounds":{"left":0.9840425,"top":0.055067837,"width":0.011968086,"height":0.028731046},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"User menu","depth":15,"bounds":{"left":0.9896942,"top":0.061053474,"width":0.010305822,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Chat Conversation","depth":15,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Chat Conversation","depth":16,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"gemma4:e2b","depth":21,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Yesterday at 9:33 PM","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thought for 2 minutes","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is the service that exposes the REST API, while","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open WebUI","depth":23,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"is primarily a graphical user interface (GUI) for chatting with those models.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a complete guide on how you can access and interact with your self-hosted model via API.","depth":22,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Understanding Ollama as the API Endpoint","depth":21,"bounds":{"left":0.6456117,"top":0.0,"width":0.31117022,"height":0.025538707},"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Understanding Ollama as the API Endpoint","depth":22,"bounds":{"left":0.6456117,"top":0.0,"width":0.16023937,"height":0.023144454},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.","depth":22,"bounds":{"left":0.6456117,"top":0.0,"width":0.30950797,"height":0.037509978},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"A. Default API URL","depth":21,"bounds":{"left":0.6456117,"top":0.0,"width":0.31117022,"height":0.025538707},"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A. Default API URL","depth":22,"bounds":{"left":0.6456117,"top":0.0,"width":0.05668218,"height":0.01915403},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, Ollama runs on:","depth":22,"bounds":{"left":0.6456117,"top":0.019553073,"width":0.06499335,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"URL:","depth":24,"bounds":{"left":0.65625,"top":0.041899443,"width":0.011968086,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://localhost:11434","depth":24,"bounds":{"left":0.67204124,"top":0.043894652,"width":0.059840426,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if running on the same machine)","depth":23,"bounds":{"left":0.7340425,"top":0.041899443,"width":0.08128324,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or","depth":24,"bounds":{"left":0.65625,"top":0.06424581,"width":0.0051529254,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"http://[Your_Server_IP]:11434","depth":24,"bounds":{"left":0.66522604,"top":0.06624102,"width":0.0787899,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(if you are accessing it from another device on your local network).","depth":23,"bounds":{"left":0.7463431,"top":0.06424581,"width":0.1627327,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"B. API Methods","depth":21,"bounds":{"left":0.6456117,"top":0.08938547,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"B. API Methods","depth":22,"bounds":{"left":0.6456117,"top":0.092577815,"width":0.046875,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ollama uses standard HTTP methods (","depth":22,"bounds":{"left":0.6456117,"top":0.1217079,"width":0.093417555,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":23,"bounds":{"left":0.7413564,"top":0.123703115,"width":0.010804521,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":") to interact with its endpoints. The most common endpoints for generating text are:","depth":22,"bounds":{"left":0.6456117,"top":0.1217079,"width":0.30103058,"height":0.037509978},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":25,"bounds":{"left":0.6584109,"top":0.17478053,"width":0.035405584,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating a single response based on a prompt.","depth":23,"bounds":{"left":0.6959774,"top":0.17278531,"width":0.1306516,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":25,"bounds":{"left":0.6584109,"top":0.1971269,"width":0.02443484,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For multi-turn conversations (simulating a chat interface).","depth":23,"bounds":{"left":0.68517286,"top":0.19513169,"width":0.1419548,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/embeddings","depth":25,"bounds":{"left":0.6584109,"top":0.21947326,"width":0.04089096,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": For generating vector embeddings.","depth":23,"bounds":{"left":0.70146275,"top":0.21747805,"width":0.087932184,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"2. How to Make the REST API Call (Using curl)","depth":21,"bounds":{"left":0.6456117,"top":0.24261771,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2. How to Make the REST API Call (Using","depth":22,"bounds":{"left":0.6456117,"top":0.24381484,"width":0.14694148,"height":0.023144454},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"bounds":{"left":0.7947141,"top":0.24740623,"width":0.016289894,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"bounds":{"left":0.8133311,"top":0.24381484,"width":0.0029920214,"height":0.023144454},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can use command-line tools like","depth":22,"bounds":{"left":0.6456117,"top":0.27494013,"width":0.08976064,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curl","depth":23,"bounds":{"left":0.7375333,"top":0.27693537,"width":0.010970744,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to test and interact with the Ollama API directly.","depth":22,"bounds":{"left":0.7506649,"top":0.27494013,"width":0.1165226,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 1: Single Generation Call (/api/generate)","depth":21,"bounds":{"left":0.6456117,"top":0.30007982,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 1: Single Generation Call (","depth":22,"bounds":{"left":0.6456117,"top":0.30327216,"width":0.10605053,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/generate","depth":23,"bounds":{"left":0.75398934,"top":0.30606544,"width":0.044215426,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"bounds":{"left":0.8005319,"top":0.30327216,"width":0.002493351,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This example sends a prompt to the model and waits for the generated response.","depth":22,"bounds":{"left":0.6456117,"top":0.33240223,"width":0.19630983,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"bounds":{"left":0.6499335,"top":0.3651237,"width":0.008976064,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.89877,"top":0.36312848,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.90608376,"top":0.3651237,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.36312848,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.36312848,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","depth":24,"bounds":{"left":0.6559175,"top":0.3790902,"width":0.30053192,"height":0.08459697},"on_screen":true,"value":"curl -X POST http://localhost:11434/api/generate -d '{ \"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral) \"prompt\": \"Write a short poem about self-hosting AI.\", \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"bounds":{"left":0.65791225,"top":0.38347965,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"bounds":{"left":0.67204124,"top":0.38347965,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/generate","depth":26,"bounds":{"left":0.6775266,"top":0.38347965,"width":0.1178524,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"bounds":{"left":0.795379,"top":0.38347965,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"bounds":{"left":0.80369014,"top":0.38347965,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\", // Replace with the model you have downloaded (e.g., llama3, mistral)","depth":26,"bounds":{"left":0.65791225,"top":0.3990423,"width":0.2551529,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\": \"Write a short poem about self-hosting AI.\",","depth":26,"bounds":{"left":0.65791225,"top":0.41460496,"width":0.15708111,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"bounds":{"left":0.65791225,"top":0.4301676,"width":0.047706116,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"bounds":{"left":0.65791225,"top":0.4461293,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Example 2: Chat Completion Call (/api/chat)","depth":21,"bounds":{"left":0.6456117,"top":0.4708699,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example 2: Chat Completion Call (","depth":22,"bounds":{"left":0.6456117,"top":0.47406226,"width":0.10405585,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/api/chat","depth":23,"bounds":{"left":0.75199467,"top":0.47685555,"width":0.030585106,"height":0.016360734},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":")","depth":22,"bounds":{"left":0.7849069,"top":0.47406226,"width":0.002493351,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is better for conversational use, as it maintains context.","depth":22,"bounds":{"left":0.6456117,"top":0.50319237,"width":0.14478059,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"bash","depth":25,"bounds":{"left":0.6499335,"top":0.5359138,"width":0.008976064,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.89877,"top":0.5339186,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.90608376,"top":0.5359138,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.5339186,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.5339186,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","depth":24,"bounds":{"left":0.6559175,"top":0.54988027,"width":0.30053192,"height":0.11572227},"on_screen":true,"value":"curl -X POST http://localhost:11434/api/chat -d '{ \"model\": \"llama3\", \"messages\": [ {\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"} ], \"stream\": false}'","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"curl","depth":26,"bounds":{"left":0.65791225,"top":0.55426973,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-X","depth":26,"bounds":{"left":0.67204124,"top":0.55426973,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST http://localhost:11434/api/chat","depth":26,"bounds":{"left":0.6775266,"top":0.55426973,"width":0.1065492,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"-d","depth":26,"bounds":{"left":0.7840758,"top":0.55426973,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"'{","depth":26,"bounds":{"left":0.7925532,"top":0.55426973,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\": \"llama3\",","depth":26,"bounds":{"left":0.65791225,"top":0.5698324,"width":0.05618351,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"messages\": [","depth":26,"bounds":{"left":0.65791225,"top":0.58539504,"width":0.042054523,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{\"role\": \"user\", \"content\": \"What are the benefits of using self-hosted models?\"}","depth":26,"bounds":{"left":0.65791225,"top":0.6009577,"width":0.23836437,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"],","depth":26,"bounds":{"left":0.65791225,"top":0.6169194,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\": false","depth":26,"bounds":{"left":0.65791225,"top":0.63248205,"width":0.047706116,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}'","depth":26,"bounds":{"left":0.65791225,"top":0.6480447,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"3. Using Programming Languages (The Professional Way)","depth":21,"bounds":{"left":0.6456117,"top":0.6927374,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"3. Using Programming Languages (The Professional Way)","depth":22,"bounds":{"left":0.6456117,"top":0.69393456,"width":0.20711437,"height":0.023144454},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.","depth":22,"bounds":{"left":0.6456117,"top":0.72505987,"width":0.30618352,"height":0.037509978},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Python Example (Recommended)","depth":21,"bounds":{"left":0.6456117,"top":0.7725459,"width":0.31117022,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python Example (Recommended)","depth":22,"bounds":{"left":0.6456117,"top":0.77573824,"width":0.10239362,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Python, with the","depth":22,"bounds":{"left":0.6456117,"top":0.80486834,"width":0.040724736,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":23,"bounds":{"left":0.68866354,"top":0.80686355,"width":0.021775266,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"library, is the easiest way to interact with the Ollama API.","depth":22,"bounds":{"left":0.71276593,"top":0.80486834,"width":0.13813165,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"python","depth":25,"bounds":{"left":0.6499335,"top":0.8375898,"width":0.012965426,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Collapse","depth":22,"bounds":{"left":0.88680184,"top":0.8355946,"width":0.025598405,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Collapse","depth":24,"bounds":{"left":0.8941157,"top":0.8375898,"width":0.016289894,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Run","depth":22,"bounds":{"left":0.91306514,"top":0.8355946,"width":0.011303191,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Run","depth":24,"bounds":{"left":0.91505986,"top":0.8375898,"width":0.00731383,"height":0.011971269},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Save","depth":22,"bounds":{"left":0.9250333,"top":0.8355946,"width":0.012965426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy","depth":22,"bounds":{"left":0.93866354,"top":0.8355946,"width":0.013796543,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextArea","text":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","depth":24,"bounds":{"left":0.6575798,"top":0.85155624,"width":0.29886967,"height":0.14844376},"on_screen":true,"value":"import requestsimport json\n# 1. Define the API endpointurl = \"http://localhost:11434/api/generate\"\n# 2. Define the request payload (what you are sending)payload = { \"model\": \"llama3\", \"prompt\": \"Explain the difference between Ollama and Open WebUI.\", \"stream\": False}\n# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print(\"Generated Response:\") print(result.get(\"response\"))\nexcept requests.exceptions.RequestException as e: print(f\"An error occurred: {e}\")","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"import","depth":26,"bounds":{"left":0.65957445,"top":0.8559457,"width":0.016788565,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"bounds":{"left":0.67918885,"top":0.8559457,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"import","depth":26,"bounds":{"left":0.65957445,"top":0.87150836,"width":0.016788565,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"json","depth":26,"bounds":{"left":0.67918885,"top":0.87150836,"width":0.011303191,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 1. Define the API endpoint","depth":26,"bounds":{"left":0.65957445,"top":0.9030327,"width":0.078457445,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"bounds":{"left":0.65957445,"top":0.9185954,"width":0.008477394,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.67087764,"top":0.9185954,"width":0.0026595744,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"http://localhost:11434/api/generate\"","depth":26,"bounds":{"left":0.67636305,"top":0.9185954,"width":0.10372341,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 2. Define the request payload (what you are sending)","depth":26,"bounds":{"left":0.65957445,"top":0.9497207,"width":0.15142952,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"payload","depth":26,"bounds":{"left":0.65957445,"top":0.9656824,"width":0.019614361,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.68201464,"top":0.9656824,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":26,"bounds":{"left":0.68484044,"top":0.9656824,"width":0.0056515955,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"model\"","depth":26,"bounds":{"left":0.67087764,"top":0.98124504,"width":0.019614361,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.69049203,"top":0.98124504,"width":0.005485372,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"llama3\"","depth":26,"bounds":{"left":0.6959774,"top":0.98124504,"width":0.02244016,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":0.7184175,"top":0.98124504,"width":0.0028257978,"height":0.0131683955},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"prompt\"","depth":26,"bounds":{"left":0.67087764,"top":0.99680763,"width":0.02244016,"height":0.0031923652},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.69331783,"top":0.99680763,"width":0.005485372,"height":0.0031923652},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Explain the difference between Ollama and Open WebUI.\"","depth":26,"bounds":{"left":0.6988032,"top":0.99680763,"width":0.15425532,"height":0.0031923652},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":26,"bounds":{"left":0.8530585,"top":0.99680763,"width":0.0028257978,"height":0.0031923652},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stream\"","depth":26,"bounds":{"left":0.67087764,"top":1.0,"width":0.02244016,"height":-0.012370348},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.69331783,"top":1.0,"width":0.005485372,"height":-0.012370348},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"False","depth":26,"bounds":{"left":0.6988032,"top":1.0,"width":0.01412899,"height":-0.012370348},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":26,"bounds":{"left":0.65957445,"top":1.0,"width":0.0028257978,"height":-0.027933002},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"# 3. Make the POST request","depth":26,"bounds":{"left":0.65957445,"top":1.0,"width":0.072972074,"height":-0.059457302},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"try","depth":26,"bounds":{"left":0.65957445,"top":1.0,"width":0.008477394,"height":-0.075019956},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":26,"bounds":{"left":0.66805184,"top":1.0,"width":0.0028257978,"height":-0.075019956},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"response","depth":26,"bounds":{"left":0.67087764,"top":1.0,"width":0.02244016,"height":-0.09058261},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"=","depth":26,"bounds":{"left":0.6959774,"top":1.0,"width":0.0028257978,"height":-0.09058261},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"requests","depth":26,"bounds":{"left":0.701629,"top":1.0,"width":0.02244016,"height":-0.09058261},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":26,"bounds":{"left":0.7240692,"top":1.0,"width":0.0028257978,"height":-0.09058261},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"post","depth":26,"bounds":{"left":0.726895,"top":1.0,"width":0.011136968,"height":-0.09058261},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(","depth":26,"bounds":{"left":0.7380319,"top":1.0,"width":0.0028257978,"height":-0.09058261},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"url","depth":26,"bounds":{"left":0.7408577,"top":1.0,"width":0.008477394,"height":-0.09058261},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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How can I access api via url and make rest api call to ollama or open web ui. i want to use selfhosted model
gemma4:e2b
Yesterday at 9:33 PM
Thought for 2 minutes
This is a very common setup when deploying self-hosted LLMs. The key to accessing your self-hosted model is to understand that
Ollama
is the service that exposes the REST API, while
Open WebUI
is primarily a graphical user interface (GUI) for chatting with those models.
Here is a complete guide on how you can access and interact with your self-hosted model via API.
1. Understanding Ollama as the API Endpoint
1. Understanding Ollama as the API Endpoint
When you install Ollama, it automatically runs a service that exposes a fully compatible REST API. This is the direct endpoint you need to interact with your models.
A. Default API URL
A. Default API URL
By default, Ollama runs on:
URL:
http://localhost:11434
(if running on the same machine)
or
http://[Your_Server_IP]:11434
(if you are accessing it from another device on your local network).
B. API Methods
B. API Methods
Ollama uses standard HTTP methods (
POST
) to interact with its endpoints. The most common endpoints for generating text are:
/api/generate
: For generating a single response based on a prompt.
/api/chat
: For multi-turn conversations (simulating a chat interface).
/api/embeddings
: For generating vector embeddings.
2. How to Make the REST API Call (Using curl)
2. How to Make the REST API Call (Using
curl
)
You can use command-line tools like
curl
to test and interact with the Ollama API directly.
Example 1: Single Generation Call (/api/generate)
Example 1: Single Generation Call (
/api/generate
)
This example sends a prompt to the model and waits for the generated response.
bash
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curl -X POST http://localhost:11434/api/generate -d '{ "model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral) "prompt": "Write a short poem about self-hosting AI.", "stream": false}'
curl
-X
POST http://localhost:11434/api/generate
-d
'{
"model": "llama3", // Replace with the model you have downloaded (e.g., llama3, mistral)
"prompt": "Write a short poem about self-hosting AI.",
"stream": false
}'
Example 2: Chat Completion Call (/api/chat)
Example 2: Chat Completion Call (
/api/chat
)
This is better for conversational use, as it maintains context.
bash
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curl -X POST http://localhost:11434/api/chat -d '{ "model": "llama3", "messages": [ {"role": "user", "content": "What are the benefits of using self-hosted models?"} ], "stream": false}'
curl
-X
POST http://localhost:11434/api/chat
-d
'{
"model": "llama3",
"messages": [
{"role": "user", "content": "What are the benefits of using self-hosted models?"}
],
"stream": false
}'
3. Using Programming Languages (The Professional Way)
3. Using Programming Languages (The Professional Way)
For robust applications, you will typically use a programming language like Python to handle the HTTP requests, JSON parsing, and error handling.
Python Example (Recommended)
Python Example (Recommended)
Python, with the
requests
library, is the easiest way to interact with the Ollama API.
python
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import requestsimport json
# 1. Define the API endpointurl = "http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)payload = { "model": "llama3", "prompt": "Explain the difference between Ollama and Open WebUI.", "stream": False}
# 3. Make the POST requesttry: response = requests.post(url, json=payload) response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx) # 4. Parse the JSON response result = response.json() # Print the generated text print("Generated Response:") print(result.get("response"))
except requests.exceptions.RequestException as e: print(f"An error occurred: {e}")
import
requests
import
json
# 1. Define the API endpoint
url
=
"http://localhost:11434/api/generate"
# 2. Define the request payload (what you are sending)
payload
=
{
"model"
:
"llama3"
,
"prompt"
:
"Explain the difference between Ollama and Open WebUI."
,
"stream"
:
False
}
# 3. Make the POST request
try
:
response
=
requests
.
post
(
url...
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