- Introduced a comprehensive contributing guide outlining the checklist for PR submissions, including signing the Contributor License Agreement, adding tests, and ensuring code quality.
- Updated README.md to link to the new CONTRIBUTING.md and provide a quick start for contributors.
- Enhanced Makefile with additional commands for installation and testing to streamline the development workflow.
* Handle file content type transformation in responses api (#11310)
* Handle file content type transformation in responses api
* change to use input_file
* -
* TestLiteLLMCompletionResponsesConfig
* test: TestLiteLLMCompletionResponsesConfig
* fix: fix linting
---------
Co-authored-by: Jayme Gordon <jayme_gordon@icloud.com>
* fix(vertex_and_google_ai_studio_gemini.py): add web search request tracking
Enables cost calculation for google web search
* fix(vertex_and_gemini): use common processing logic across stream / non-stream calls
* fix(vertex_And_google_ai_studio_Gemini.py): fix initial choice
* fix: fix linting error
* fix: add initial support for google search cost tracking
* fix(tool_call_cost_tracking.py): working tool cost tracking for gemini
* fix(vertex_ai/gemini/cost_calculator.py): add google web search tool cost tracking for vertex ai
Closes LIT-210
* fix: fix check
* build(model_prices_and_context_window.json): fix amazon nova max output tokens
Closes https://github.com/BerriAI/litellm/issues/11441
* fix: fix ruff check
* Add tests for function calling support in LiteLLM proxy models
- Introduced a new test script `test_proxy_function_calling.py` to validate function calling capabilities for both direct and proxied models.
- Created a comprehensive test suite in `tests/litellm_utils_tests/test_proxy_function_calling.py` using pytest, covering various model configurations and edge cases.
- Implemented parameterized tests to ensure consistency between direct and proxied model function calling support.
- Added tests for specific proxy models, edge cases, and import verification for the `supports_function_calling` function.
- Included a demonstration test to highlight the current issue with proxy model resolution.
* feat: add fallback handling for litellm_proxy models in model info retrieval
* feat: enhance proxy function calling tests with custom model name handling and documentation
* fix: add type ignore comments for custom logger callback initialization
* fix: remove styling diff
* fix: style
* fix(utils.py): remove outdated comment regarding litellm_proxy models
* feat(utils.py): add proxy model handling for underlying model extraction
* feat(utils.py): enhance model name handling for litellm_proxy integration
* refactor(utils.py): remove unused _handle_proxy_model_names function
* fix: using litellm with claude code bedrock
* fix: usage for bedrock with /messages
* fix: bedrock_sse_wrapper
* tests: test for test_chunk_parser_usage_transformation
* test fix
Introduce the ExceptionCheckers class to encapsulate methods for checking error conditions in exception strings, specifically for identifying rate limit errors. Update the Fireworks AI exception mapping tests to cover various scenarios, including standard 429 errors and text-based detection, ensuring accurate mapping to RateLimitError. Enhance test coverage for both positive and negative cases of rate limit detection.
* fix(huggingface): use get() instead of pop() for input_type parameter
Fixes embedding generation for HuggingFace models where input_type override
is required (e.g. BAAI/bge-m3). The pop() method was mutating optional_params
and removing input_type before downstream functions could access it.
* Add unit tests to catch regression
* Move tests around
* fix(convert_dict_to_response.py): handle None values in usage field for gpt-image-1
* test: add tests for handling None and partial values in usage fields for gpt-image-1 responses
