The Azure Responses API uses a different schema (flattened) for tools compared to the standard OpenAI/Azure Chat Completions API (nested). This caused a `BadRequestError` when users passed standard tool definitions.
Changes:
- Implemented tool flattening logic in `AzureOpenAIResponsesAPIConfig.transform_responses_api_request`.
- Added comprehensive unit tests in test_azure_transformation.py to verify nested-to-flat transformation, pass-through of flat tools, and immutability.
- Ensures cross-provider compatibility for tool definitions.
Fixes#19523
* Consolidated change
* fix(prompt_security): update message processing to persist sanitized files and filter for API calls
* fix per krrishdholakia suggestion
Forward static_headers from /mcp-rest/test/* routes into the MCP client so headers are present during session.initialize() and tool discovery.
Also add a shared merge_mcp_headers() helper to keep header precedence consistent and ensure OpenAPI-to-MCP generated tools include static_headers.
Tests:
- pytest tests/test_litellm/proxy/_experimental/mcp_server/test_rest_endpoints.py
- pytest tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py -k register_openapi_tools_includes_static_headers
Fixes#19341
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
Add support for 'file' and 'input_file' content types in
convert_to_gemini_tool_call_result(). File content in tool
results was previously silently dropped.
Supports base64 data URIs and HTTP URLs, matching the existing
image handling pattern. Enables PDF, audio, video, and other
file types as inline_data for Gemini.
The OpenAI Agents SDK (v0.6.9+) now passes reasoning_effort as a dict
when summary is specified: {"effort": "high", "summary": "auto"}
This change extracts the "effort" value from the dict for Vertex AI,
which only supports thinkingLevel (not summary).
Before: reasoning_effort={"effort": "high"} was silently ignored
After: reasoning_effort={"effort": "high"} correctly maps to thinkingLevel
Fixes#19411
* feat: add gemini video metadata and detail support
Implement support for video_metadata and enhanced detail parameter
for Gemini 3.0+ models:
- Add video_metadata field to ChatCompletionFileObjectFile type
- Supports fps, start_offset, and end_offset parameters
- Properly converts snake_case to camelCase for Gemini API
- Extend detail parameter to support medium and ultra_high levels
- Maps to MEDIA_RESOLUTION_MEDIUM and MEDIA_RESOLUTION_ULTRA_HIGH
- Update _process_gemini_image to handle video metadata transformation
- Add version gating to only apply features for Gemini 3+ models
- Add comprehensive test coverage (6 new test cases)
- Test detail parameter with file objects
- Test video_metadata fields (fps, start_offset, end_offset)
- Test combined detail + video_metadata usage
- Test new detail levels (medium, ultra_high)
- Test version gating (Gemini 1.5 vs 3.0)
Note: video_metadata is only supported for video files but error
handling is delegated to Vertex AI for other media types.
* refactor: rename _process_gemini_image to _process_gemini_media
The function handles multiple media types (images, audio, video, PDF),
not just images. Renamed to better reflect its actual purpose.
- Update function name in transformation.py
- Update all function calls and references
- Update test names and imports to match
- Improve docstring to clarify it handles all media types
* docs: add video metadata and media resolution control documentation
Add comprehensive documentation for Gemini 3+ video processing features:
- Document media resolution control (detail parameter) for images and videos
- Add video_metadata field documentation (fps, start_offset, end_offset)
- Include usage examples with tabs for basic, combined, and proxy scenarios
- Update both Gemini and Vertex AI provider documentation
- Clarify snake_case to camelCase field conversion for Gemini API
Signed-off-by: Kris Xia <xiajiayi0506@gmail.com>
* refactor(gemini): extract metadata application into helper function
Extract duplicated Gemini 3+ media_resolution and video_metadata
application logic from _process_gemini_media into a dedicated
_apply_gemini_3_metadata helper function to improve code maintainability.
---------
Signed-off-by: Kris Xia <xiajiayi0506@gmail.com>
* fix: preserve tool output ordering for gemini in responses bridge
- Keep function_call_output adjacent to its function_call when building chat messages
- Normalize function_call_output.output lists (input_* parts) into tool message content
* fix test
* small improvements
Emit Responses API streaming events for tool calls when the underlying chat stream contains tool_call deltas, and recover tool calls into the stream when they only appear in the final response.
