* Fix: Add support for GOOGLE_API_KEY environment variables for Gemini API authentication
* added test cases
* incoperated feedback to make it more maintainable
* fix failed linting CI
- Fixed 'missing finish_reason for choice 1' error with reasoning_effort
- Anthropic sends multiple content blocks with different indices
- OpenAI expects all content in a single choice at index=0
- Added comprehensive tests for text-only, text+tool, and multiple tools
* fix(azure/chat/gpt_transformation.py): support api_version="preview"
Fixes https://github.com/BerriAI/litellm/issues/12945
* Fix anthropic passthrough logging handler model fallback for streaming requests (#13022)
* fix: anthropic passthrough logging handler model fallback for streaming requests
- Add fallback logic to retrieve model from logging_obj.model_call_details when request_body.model is empty
- Fixes issue #12933 where streaming requests to anthropic passthrough endpoints would crash due to missing model field
- Ensures downstream logging and cost calculation work correctly for all streaming scenarios
- Maintains backwards compatibility with existing non-streaming requests
* test: add minimal tests for anthropic passthrough logging handler model fallback
- Add unit tests for the model fallback logic in _handle_logging_anthropic_collected_chunks
- Test existing behavior when request_body.model is present
- Test fallback logic when request_body.model is empty but logging_obj.model_call_details has model
- Test edge cases where both sources are empty or missing
- Ensure backwards compatibility and graceful degradation
* fix(anthropic_passthrough_logging_handler.py): add provider to model name (accurate cost tracking)
* fix(anthropic_passthrough_logging_handler.py): don't reset custom llm provider, if already set
* fix: fix check
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Co-authored-by: Haggai Shachar <haggai.shachar@backline.ai>
- Implement X-Initiator header logic in GithubCopilotConfig.validate_environment()
- Set header to "agent" when messages contain agent or tool roles, "user" otherwise
- Reduces unnecessary premium Copilot API usage for non-user calls
Fixes#12859
This aligns the proxy experience with other models that think
automatically (e.g. Deepseek R1 and grok3). It does so by setting
the necessary request input to return thinking, but not specifying
a budget or effort (thus defaulting to the internal automatic level).
* fix(gpt_transformation.py): remove 'cache_control' flag for openai/openai-compatible calls
Fixes https://github.com/BerriAI/litellm/issues/12787
* fix(openrouter/chat/transformation.py): allow passing openrouter cache control flag for claude models
* fix(gpt_transformation.py): fix import
* fix: fix adding tools
* fix(main.py): fix async retryer
Fixes https://github.com/BerriAI/litellm/issues/12830
* fix(forward_clientside_headers_by_model_group.py): filter out 'content-type' from forwardable headers
clientside content-type != proxy content type, can cause requests to hang
* test(tests/): update tests
* fix(prompt_templates/factory.py): handle anthropic cache control on individual tool results
Fixes issue where cache control on individual tool result was being ignored
* test(test_vertex_And_google_ai_studio_gemini.py): initial unit test covering translation for grounding metadata on streaming chunk
* Vllm rerank (#12737)
* Add Hosted VLLM rerank provider integration
This commit implements the Hosted VLLM rerank provider integration for LiteLLM. The integration includes:
Adding Hosted VLLM as a supported rerank provider in the main rerank function
Implementing the HostedVLLMRerank handler class for making API requests
Creating a transformation class to convert Hosted VLLM responses to LiteLLM's standardized format
The integration supports both synchronous and asynchronous rerank operations. API credentials can be provided directly or through environment variables (HOSTED_VLLM_API_KEY and HOSTED_VLLM_API_BASE).
Notable features:
Proper error handling for missing credentials
Standard response transformation
Support for common rerank parameters (top_n, return_documents, etc.)
Proper token usage tracking
This expands LiteLLM's rerank provider ecosystem to include Hosted VLLM alongside existing providers like Cohere, Together AI, Azure AI, and Bedrock.
* refactor(rerank): use base_llm_http_handler for hosted_vllm rerank
- Replace custom HostedVLLMRerank handler with base_llm_http_handler
- Implement proper HostedVLLMRerankConfig inheriting from BaseRerankConfig
- Follow Cohere-compatible implementation pattern
- Clean up unnecessary comments
* Fix lint errors in hosted_vllm rerank transformer: remove unused imports
* Fix linting errors in rerank transformation modules
* fix: resolve type errors in Hosted VLLM rerank module
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Co-authored-by: Philip D'Souza <philip.dsouza@macro4.com>
Co-authored-by: Philip D'Souza <philip.a.dsouza@gmail.com>
* added a few tests
---------
Co-authored-by: Philip D'Souza <philip.dsouza@macro4.com>
Co-authored-by: Philip D'Souza <philip.a.dsouza@gmail.com>
* fix(bedrock): auto-generate session name when only aws_role_name is provided
Fixes#12583 - AWS role assumption not working correctly when aws_role_name
is provided without aws_session_name.
Previously, if only aws_role_name was provided in the config without
aws_session_name, the code would fall back to using environment credentials
instead of assuming the specified role. This was problematic in EKS/IRSA
environments where users want to assume a different role.
The fix:
- When aws_role_name is provided without aws_session_name, we now
auto-generate a session name with format 'litellm-session-{timestamp}'
- This ensures role assumption happens as expected
- Added comprehensive test coverage for this scenario
* style: format test file with black
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Co-authored-by: openhands <openhands@all-hands.dev>
* fix(anthropic): fix streaming + response_format + tools bug
- Fix _handle_json_mode_chunk to only convert response_format tools to content
- Regular user tools now remain as proper tool_calls in streaming mode
- Add comprehensive test for the fix
- Resolves issue where all tools were incorrectly converted to content chunks
Before: All tools converted to content with different indices
After: Only response_format tool converted, regular tools remain as tool_calls
* fix(anthropic): improve streaming + response_format + tools handling
* fix: lint error (too many statements)
* fix(anthropic): correct finish_reason for streaming response_format tools
- Add ttl parameter to cache_control for Gemini models
- Support Google's TTL format (e.g., '3600s', '7200s')
- Implement robust TTL extraction and validation
- Extract TTL before system message transformation to handle all cases
- Add comprehensive test suite with 17 test cases in tests/test_litellm/
- Update documentation with TTL usage examples
- Maintain backward compatibility with existing cache_control usage
Fixes#9810
* [Feat] New LLM API Integration - Add Moonshot API (Kimi) (#12551)
* Add Moonshot AI provider support to LiteLLM
Co-authored-by: ishaan <ishaan@berri.ai>
* Refactor Moonshot provider params handling and transformation logic
Co-authored-by: ishaan <ishaan@berri.ai>
* fix constants
* add Moonshot AI
* fix get_supported_openai_params
* handle kimi temp
* add tool choice handling
* test moonshot unit tests
* fix kimi
* fix linting
* Add pricing information for Moonshot AI's kimi-k2 model (#12566)
* Add pricing information for Moonshot AI's kimi-k2 model
* Update model name to kimi-k2-0711-preview
- Changed model name from moonshot/kimi-k2 to moonshot/kimi-k2-0711-preview
- This reflects the specific model version as requested
* Update moonshot_models list to match model_context JSON
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Co-authored-by: openhands <openhands@all-hands.dev>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: ishaan <ishaan@berri.ai>
Co-authored-by: Xingyao Wang <xingyao@all-hands.dev>
Co-authored-by: openhands <openhands@all-hands.dev>
* update docs
* docs moonshot
* fixes model cost map
* fix map_openai_params
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: ishaan <ishaan@berri.ai>
Co-authored-by: Xingyao Wang <xingyao@all-hands.dev>
Co-authored-by: openhands <openhands@all-hands.dev>
* Get the basics of the integration working.
* Cleanup bytez integration.
* Update user agent for Bytez integration.
* Use the config class directly. Create the start of the docs.
* Finish up bytez documentation. Include a provider integration guide.
* Fix typing bug in custom_logger_utils. Add tests for bytez integration.
* Add token tracking for model usage for Bytez integration.
* Create a units test for the Bytez config.
* Make changes to Bytez transformation code per PR feedback.
* Cleanup coment in Bytez transformation test.
* Remove LRU usage for bytez integration.
* Consolidate Bytez tests into a single file. Conform to project structure for tests.
* Fix linting error with Bytez impl.
