* Support for Custom Vertex AI Models via PSC Endpoint with api_base
* Add docs related psc
* remove not needed files
* remove print statemnt
* fix mypy errors
* refactor(generic_guardrail_api.py): refactor to update to new guardrail api logic
* refactor: refactor llm api integrations to support passing in text as a list[str] instead of one at a time
* refactor: fix linting errors
* refactor: pass request type to guardrail api
allows request vs. response processing to occur
* feat: pass user api key dict information to the guardrail api
* fix: pass user api key dict information to the guardrail api
* feat: pass litellm call id + trace id, if present
* docs: update docs
* feat(generic_guardrail_api.py): new generic api for guardrails
Allows guardrail providers to work with litellm for guardrails without needing to make a PR to LiteLLM
* docs(generic_guardrail_api.md): document new generic guardrail api
* Fix: Improve PII detection and guardrail API integration
Co-authored-by: krrishdholakia <krrishdholakia@gmail.com>
* feat: correctly extract raw request from guardrail api
* docs(generic_guardrail_api.md): document this is a beta feature
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Co-authored-by: Cursor Agent <cursoragent@cursor.com>
* feat: allow fetching OIDC user info
* test: use test_auth_builder_with_oidc_userinfo_enabled gets user info when enabled
* fix tool permission doc
* docs fix diagram
* store and fetch lasso-conversation id from cache
* include gateway/v# in the baseUrl to allow simpler version migrations in the future
* add tests for cached conversation ID
* docs: add OpenAI Agents SDK to projects
Add documentation for OpenAI Agents SDK which has an official
LiteLLM extension enabling 100+ LLM providers in multi-agent workflows.
* Update project items in sidebars.js
* feat(generic_api_callback.py): make generic api OSS + support multiple generic API's
Enables https://github.com/BerriAI/litellm/pull/17094#discussion_r2562832967
* feat(callback_utils.py): support custom generic api callbacks
* feat(generic_api_callback.py): support specifying which event types to run the generic api for
* fix(litellm_logging.py): log system prompt for anthropic messages
* feat(generic_api_callback.py): support generic api compatible api's - e.g. rubrik agent cloud
* docs(sidebars.js): document new OSS generic api
* docs(generic_api.md): document new OSS Generic API
* docs(custom_webhook_api.md): document custom webhook api integration tutorial
* docs(custom_webhook_api.md): cleanup
* docs(custom_webhook_api.md): document what get's logged to custom webhook api
* Refactor: Pass callback config to GenericAPILogger
Co-authored-by: krrishdholakia <krrishdholakia@gmail.com>
* Fix: Handle empty messages list in logging payload
Co-authored-by: krrishdholakia <krrishdholakia@gmail.com>
* Checkpoint before follow-up message
Co-authored-by: krrishdholakia <krrishdholakia@gmail.com>
* feat: Cache GenericAPILogger instances to improve performance
Co-authored-by: krrishdholakia <krrishdholakia@gmail.com>
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Co-authored-by: Cursor Agent <cursoragent@cursor.com>
- Add model identifier to FLASH_IMAGE_PREVIEW_MODEL_IDENTIFIERS
- Add imageSize parameter support (1K, 2K, 4K) with GeminiImageSize type
- Add tests for imageSize parameter transformation
- Update documentation with new model
* Added tool search support for anthropic
* Add programtic tool calling support
* Add tool use input examples support
* Add anthropic effort param support
* Add anthropic effort param support
* Add blog for new features
* fix mypy and lint errors
* fix mypy and lint errors
* fix mypy and lint errors
* fix mypy and lint errors
* Add better handling
* Add better handling
Sameer Kankute