Gemini 3 models require 'includeThoughts: True' in the thinkingConfig to return the actual thought text. Previously, using reasoning_effort set the 'thinkingLevel' but missed the boolean flag, resulting in empty reasoning_content.
This fix:
1. Updates `_map_reasoning_effort_to_thinking_level` to include `includeThoughts: True` for low/medium/high.
2. Adds unit tests to verify the config mapping.
Fixes#16805
When using Gemini models (2.5/3.0) with streaming + tools enabled,
the reasoning_content field was missing from stream chunks, even though
thinking_blocks were present in non-streaming responses.
Changes:
- Convert thinking_blocks to reasoning_content for streaming responses
- Extract "thinking" field from each thinking_block
- Concatenate multiple thinking parts with newlines
- Assign to reasoning_content in chat_completion_message for streaming
Testing:
- Added test_streaming_chunk_with_tool_calls_includes_reasoning_content
- Test verifies reasoning_content appears with tool calls in streaming
- All 39 existing Gemini tests pass
* feat: initial commit adding 'public_mcp_servers' endpoint
allow admin to make mcp servers public for AI Hub
* feat: expose public endpoint for getting public mcp's
* feat: initial flow for making MCP servers public via LiteLLM proxy
* fix: fix message on make mcp public
* fix: indicate existing public mcp servers are public, when making mcp servers public
* style: have a public column indicating if mcp server has been made public
* feat: expose new MCP Hub
* feat: include usage examples for mcp hub
- Fix blank function name in completions response when using native function calling
- Fix Enum name being used instead of Enum value for comparison in chunk conversion
- Added additional tests to cover changes
Thanks to @mcowger for the invaluable assitance with figuring this issue out!
Fixed#16863
* Use auth key name if there are no app id in in headers or in extra_data
* use key alias instead of key name
* Fix
* last priority key alias
* Fix
* Add tests
- Implement GithubCopilotResponsesAPIConfig for /responses endpoint
- Add support for models requiring responses API (e.g., gpt-5.1-codex)
- Auto-detect vision requests and set X-Initiator header
- Follow OpenAI Responses API compatibility pattern
- Add comprehensive unit tests (16 tests passing)
Fixes#16820
* fix(spend-logs): trim logged response strings
- route spend-log responses through the existing string sanitizer so oversized base64/text fields are truncated before persistence
- add unit tests covering the truncation path and the feature flag
Note: embeddings-specific truncation (numeric vectors) is still pending and will be handled separately.
* remove unnecessary comment
* add: sanitization unit test for embeddings
* fix: simplify sanatization logic
I overcomplicated a simple change for lack of understanding, fixed.
* fix: Add support for GPT-5.1 reasoning.effort='none' parameter
- Override Reasoning type to include 'none' effort value
- Maintains compatibility with semantic-router (requires openai <2.0.0)
- GPT-5.1 defaults to reasoning.effort='none' as of OpenAI SDK 2.8.0
- Override can be removed once semantic-router supports OpenAI SDK 2.x
Fixes#16741
* feat: Update to OpenAI SDK 2.8+ and Python 3.9+
- Update minimum Python version from 3.8.1 to 3.9 (3.8 EOL Oct 2024)
- Update OpenAI SDK requirement from >=1.99.5 to >=2.8.0
- Update semantic-router to >=0.1.12 with Python >=3.9,<3.14 constraint
- Update resend to >=0.8.0 (allows 2.x versions)
- Revert custom Reasoning TypedDict - now using native type from OpenAI SDK 2.8+
OpenAI SDK 2.8.0 natively supports reasoning.effort='none' for GPT-5.1,
eliminating the need for our custom type override.
* chore: Update poetry.lock with OpenAI SDK 2.8.1 and dependencies
Cost tracking was failing for Responses API when using custom deployment names
with base_model configuration. The issue occurred because:
- Chat Completions API stores model_info in 'metadata'
- Responses API stores model_info in 'litellm_metadata'
- Cost calculator only checked 'metadata', missing Responses API costs
Changes:
- Updated _get_base_model_from_metadata() to check both metadata locations
- Added comprehensive unit tests covering all scenarios
- Maintains backward compatibility (metadata takes precedence)
Fixes#16772
Krrish Dholakia