* docs: add Microsoft GraphRAG to projects using LiteLLM
* docs: add arXiv paper link for GraphRAG
* docs: add GraphRAG to sidebar
* Update projects in sidebars.js
Reordered items in the projects list to include 'GraphRAG'.
Add Agent Lightning, Microsoft's open-source framework for training
AI agents with RL, APO, and SFT. Uses LiteLLM Proxy for LLM routing
and trace collection.
Both frameworks integrate with LiteLLM:
- Google ADK uses LiteLLM for model-agnostic agent building
- Harbor uses LiteLLM for agent evaluation across providers
* docs vertex tts
* place vertex ai types in file
* use VertexAITextToSpeechConfig
* use vertex_voice_dict
* refactor docs
* docs vertex ai chirp
* TestVertexAITextToSpeechConfig
* new provider vertex ai chirp3
* test_litellm_speech_vertex_ai_chirp
* add vertex_ai/chirp cost trackign
* 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>
* 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 doc for adding model pricing and context window
Co-authored-by: krrishdholakia <krrishdholakia@gmail.com>
* Refactor model pricing documentation to include sample spec and examples
Co-authored-by: krrishdholakia <krrishdholakia@gmail.com>
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Co-authored-by: Cursor Agent <cursoragent@cursor.com>
* docs: Add mini-swe-agent to projects page
Add mini-swe-agent to the documentation projects page.
mini-swe-agent is a minimal AI coding agent that resolves >70% of
GitHub issues in SWE-bench, built on LiteLLM for model flexibility.
- Added projects/mini-swe-agent.md documentation
- Updated sidebars.js to include mini-swe-agent in projects list
* docs: Update Singularity to Apptainer in mini-swe-agent.md
* feat: initial commit adding agent hub to ui
* feat: add viewable agent hub
* feat: working support for making both config + db agents public via new 'public_agent_groups' list
* fix: agents.py
fix types
* feat: working PATCH endpoint for UI changes
* feat: add new agents panel with working crud
* refactor: refactor to show created_at on be/fe
* style: align new page with the agents table
* style: more style alignment logic
* feat: return if agent is public or not in /v1/agents
* feat: initial commit adding ui flow for making agents discoverable
* feat: new batch make public endpoint
* feat(public_model_hub.tsx): show public agents on public model hub table page
* fix(public_model_hub.tsx): add code examples for using the agent in a2a
* fix: fix indicating if agent has already been made public
* docs: document expected spec for agents is A2A
* docs: add agent hub docs
* docs: document making agents discoverable
* docs: add demo video to docs
* fix: fix ui linting errors
* fix: update tests
* Add support for vector store files endpoints (#16490)
* Add base code for vector store integration
* fix azure related tests and linting error
* fix mypy errors
* Add vector store files documentation
* fix mapped tests
* Add bytedance and ideogram support in fal ai (#16636)
* Add fal ai flux pro v1.1 support (#16578)
* Add fal ai flux pro v1.1 support
* Add tests and docs
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Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
