- Implemented VolcEngineEmbeddingHandler for synchronous and asynchronous embedding requests.
- Created VolcEngineEmbeddingConfig for transforming requests and responses to/from Volcengine format.
- Added integration tests for embedding functionality, covering various scenarios including error handling and parameter validation.
- Established test structure for Volcengine embedding, ensuring compliance with LiteLLM testing patterns.
- Included comprehensive tests for parameter mapping, request transformation, and response handling.
* add support for vertex AI QWEN API
* streaming QWEN API support
* test_partner_models_httpx
* test_partner_models_httpx_streaming
* add cost tracking for vertex_ai/qwen/qwen3-235b-a22b-instruct-2507-maa
* docs qwen models vertexAI
Responses API - add default api version for openai responses api calls + Openrouter - fix claude-sonnet-4 on openrouter + Azure - Handle `openai/v1/responses`
- Added `forward_client_headers_to_llm_api` setting in the Bedrock documentation to facilitate client-side header forwarding.
- Updated `completion` function to use merged headers instead of original `extra_headers`.
- Improved request handling in `BedrockConverseLLM` and `AmazonInvokeConfig` to ensure proper header management for `anthropic-beta` parameters.
- Refactored request transformation logic to return the transformed request for better clarity and functionality.
- Renamed `AmazonAnthropicClaude3Config` and `AmazonAnthropicClaude3MessagesConfig` to `AmazonAnthropicClaudeConfig` and `AmazonAnthropicClaudeMessagesConfig` respectively for consistency.
- Implemented `get_anthropic_beta_from_headers` function to extract and handle `anthropic-beta` headers across various transformations.
- Updated request transformations in `AmazonConverseConfig` and `AmazonInvokeConfig` to include `anthropic_beta` parameters based on user headers.
- Added tests to ensure proper handling of `anthropic_beta` headers in different scenarios.
* fix(litellm_proxy/chat/transformation.py): support 'user' and all other openai chat completion params
Fixes issue where 'user' was not being sent in request to litellm proxy via sdk
* fix(prisma_migration.py): remove 'use_prisma_migrate' flag, is now default
* docs: cleanup docs
* fix(proxy_cli.py): remove --use_prisma_migrate flag
* refactor: remove references to use_prisma_migrate env var
This is now the default flow for db migrations
* fix(router.py): support base model for model group usage
allows model group info to show accurate cost information for azure models
* fix(router.py): fix changes
* test: add unit tests
* build(pyproject.toml): bump openai version requirements
support custom tool from responses api
Closes https://github.com/BerriAI/litellm/issues/13391
* docs(responses_api.md): add verbosity + free-form function calling parameters
* docs(responses_api.md): add cfg + minimal reasoning to docs
Closes https://github.com/BerriAI/litellm/issues/13391
* docs(responses_api.md): add proxy examples to docs
* refactor: fix ruff error