* feat(llm_passthrough_endpoints.py): support milvus passthrough api
* fix(llm_passthrough_endpoints.py): move streaming request value to the top of the function
* docs: document new milvus vector store passthrough flow
* feat: change guardrail_information to list type to support displaying multiple guardrails
* fix: add missing commit and revert auto-format changes in utils.py
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* streaming support in langfuse otel
* Added testing for Langfuse Otel tracing in the response API
---------
Co-authored-by: eycjur <eycjur@example.com>
* Add v1 cut of container api
* fix lint errors
* Add proxy support to container apis & logging support (#16049)
* Add proxy support to container apis
* Add logging support
* Add cost tracking support for containers and documentation
* Add new constant documentation
* Add container cost in model map
* fix failing azure tests
* Update tests based on model map changes
* fix model map tests
* fix model map tests
* Container modeshould be container
* Container tests fix
* Merge branch 'main' into litellm_sameer_oct_staging_2
---------
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
- Access model_fields on class instead of instance to avoid deprecation warnings
- Add warning filter to suppress Pydantic instance attribute access warnings
- Fix affects streaming operations where warnings accumulate over time
- Updated cost_calculator.py, core_helpers.py, and model_response_utils.py
The previous implementation accessed model_fields on Pydantic model instances,
which triggers deprecation warnings in Pydantic 2.11+. These warnings accumulate
during streaming operations, causing memory leaks. Now accessing model_fields
via type(instance).model_fields to prevent warning generation.
* fix model error for apis which don't need model
* fix print statments:
* fix mypy lint errors
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* feat(vector_store_endpoints/endpoints.py): add new index_create endpoint
allows admin to create a virtual index, to do permission management for
* feat(key_management_endpoints.py): enable setting allowed_vector_store_indexes on keys
proxy admin can enable dev to create an index on a vector stor
* feat: initial commit adding vector store index passthrough logic to litellm
* feat: add vector store table
* fix(azure_ai/transformation.py): fix headers
* feat: track read/write endpoints by vector store integration
enables permissions by index to work
* fix: azure_ai/vector_stores/search
document the vector store endpoints correctly
ensures permission management works as expected
* fix(proxy/utils.py): improve error message
* docs(azure_ai_vector_stores_passthrough.md): document azure ai passthrough vector store support
* docs(create.md): document azure ai support via passthrough for vector store create
* fix: fix code qa errors
* fix: document new allowed_vector_store_indexes endpoint
* feat(milvus/): initial commit adding milvus vector store support to LiteLLM
allows querying milvus vector store through litellm
* feat(bedrock/vector_stores): support translating openai filters param to aws kb
adds filtering to aws kb
* feat(milvus/): add milvus vector store unified search support
allows calling milvus vector store in through chat completions
* docs(milvus_vector_stores.md): document new milvus vector search integration
* feat(pass_through_endpoints.py): support passing form data through to a passthrough endpoint
Closes LIT-1147
* fix: fix linting errors
