* fix(openai): use optimized async http client for text completions
OpenAITextCompletion.acompletion was using litellm.aclient_session directly
instead of the optimized http client with aiohttp transport that
OpenAIChatCompletion uses. This fixes inconsistent behavior where custom
SSL configs and the faster aiohttp transport were not applied to async
text completion requests.
Fixes#17676
* test(openai): add test for text completion async http client
Verify that OpenAITextCompletion.acompletion uses the optimized
BaseOpenAILLM._get_async_http_client() instead of litellm.aclient_session.
Related to #17676
* test: move http client test to existing test file
Move test_acompletion_uses_optimized_http_client to
test_text_completion_unit_tests.py instead of separate file.
- Extract web_search_tool_result blocks in extract_response_content()
- Store web_search_results in provider_specific_fields for round-trip
- Detect srvtoolu_ prefix to reconstruct as server_tool_use (not tool_use)
- Add corresponding web_search_tool_result after server_tool_use blocks
This ensures multi-turn conversations with Anthropic web search + custom
tools work correctly without Anthropic expecting tool_result for server-
side tool executions.
Fixes issue where LiteLLM used the json_tool_call workaround for all Groq
models, even those that support native json_schema (e.g., gpt-oss-120b,
llama-4, kimi-k2). This caused errors when users passed their own tools
alongside structured outputs.
Changes:
- Check `supports_response_schema()` before using the workaround
- Only use json_tool_call workaround for models without native support
- Add clear error message when using workaround with user-provided tools
- Update model config to set `supports_response_schema: false` for models
that don't support native json_schema
- Add unit tests for structured output handling
- Add model identifier to FLASH_IMAGE_PREVIEW_MODEL_IDENTIFIERS
- Add imageSize parameter support (1K, 2K, 4K) with GeminiImageSize type
- Add tests for imageSize parameter transformation
- Update documentation with new model
* fix: fix getting mcp servers
* fix(litellm_logging.py): handle list objects for final response in standard logging payload
Fixes issue where mcp tool call response wouldn't show up
* fix(litellm_responses_transformation/): remove invalid item error for unmapped objects - breaks stream and there's no real value to this as outside of a few of them, not all can be mapped to chat completions
resolves error for web search calls via chat completions to responses api
* feat(anthropic/chat/transformations): for claude-4-5-sonnet and opus-4-1 support passing structured output to anthropic api
* docs: document new feature
* fix: fix output format
* fix: cleanup
* fix(transformation.py): conditionally pass in json tool call
* fix: support ARIZE_SPACE_ID instead of ARIZE_SPACE_KEY
* docs(arize_integration.md): cleanup arize docs
* feat(callback_info_helpers.tsx): allow setting arize space id via ui
* fix: fix linting error
* fix(opentelemetry.py): working arize phoenix root span tracing
* Add openai metadata filed in the request
* Add docs related to openai metadata
* Add utils
* test_completion_openai_metadata[True]
* Added support for though signature for gemini 3 in responses api (#16872)
* Added support for though signature for gemini 3
* Update docs with all supported endpoints and cost tracking
* Added config based routing support for batches and files
* fix lint errors
* Litellm anthropic image url support (#16868)
* Add image as url support to anthropic
* fix mypy errors
* fix tests
* Fix: Populate spend_logs_metadata in batch and files endpoints (#16921)
* Add spend-logs-metadata to the metadata
* Add tests for spend logs metadata in batches
* use better names
* Remove support for penalty param for gemini 3 (#16907)
* Remove support for penalty param
* remove halucinated model names
* fix mypy/test errors
* fix tests
* fix too many lines error
* fix too many lines error
* Add config for cicd test case
* Fix final tests
* fix batch tests
* fix batch tests
Implements support for reasoning_effort="none" parameter for Gemini models,
providing significant cost savings (up to 96% cheaper) by disabling thinking
budget while maintaining response quality.
Changes:
- Added "supports_reasoning": true to gemini-2.0-flash-thinking-exp-01-21 in model config
- Implemented mapping for reasoning_effort="none" to thinkingConfig {thinkingBudget: 0, includeThoughts: false}
- Added unit test to verify the mapping works correctly
Performance impact:
- Without reasoning_effort: ~313 tokens
- With reasoning_effort="none": ~12 tokens (96% cheaper)
Closes#16420
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
Fixes#16533
Before this fix, non-ASCII characters (Japanese, Spanish, Chinese, etc.)
in function call arguments were being escaped as Unicode sequences.
Example:
- Before: "やあ" → "\u3084\u3042"
- After: "やあ" → "やあ" (preserved)
Changes:
- Add ensure_ascii=False to json.dumps() in _transform_parts()
- Add test for Japanese and Spanish Unicode character preservation
This is not a breaking change as both formats are equivalent in JSON.
The fix improves readability and aligns with OpenAI's behavior.
