* fix(factory.py): handle qs:.. in mime type
Fixes https://github.com/BerriAI/litellm/issues/11839
* feat(litellm_proxy/): don't transform messages client-side
leave litellm proxy messages untouched - allow proxy to handle transformation
prevents double transformation
* feat(tag_management_endpoints.py): support adding models to tag by adding model_name
Closes https://github.com/BerriAI/litellm/issues/11884
* test(test_tag_management_endpoints.py): add unit tests for adding new model by public model name
* test: update test
* build(model_prices_and_context_window.json): mark all gemini-2.5 models as supporting pdf input
Closes https://github.com/BerriAI/litellm/issues/11881
* fix(anthropic_transformation.py): set custom llm provider custom property
Fixes https://github.com/BerriAI/litellm/issues/11861
* test: add unit test for checking supports_reasoning
* test: add test for vertex ai flow
* feat(bedrock/anthropic): ensure thinking param correctly passed for bedrock/invoke
* Enhance Mistral API: Add support for parallel tool calls and refine name handling in tool messages. Plus, introduce a new test for parallel tool calls in the Mistral model.
* tests
* make mypy happy
* Refine name handling in Mistral chat transformation: clarify conditions for removing the 'name' field based on message role and content.
* add pass through ui
* fix accordion for route path
* working route path renderer
* fix use sections
* clean up add pass through form
* docs fix add pass through routing
* clean up route preview
* add route preview
* feat - add websearch tools to responses to chat transform
* test_basic_google_ai_studio_responses_api_with_tools
* fix web search to responses api
* linting fixes
* fix(vertex_ai): Handle missing tokenCount in promptTokensDetails (#11581)
This PR is a Solution to the Error converting to a valid response block='tokenCount'. File an issue if litellm error - https://github.com/BerriAI/litellm/issues
It's happening because vertex_ai is not sometimes sending the token count for the audio modality.
* test_vertex_ai_usage_metadata_missing_token_count
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Co-authored-by: Nishith Jain <167524748+KingNish24@users.noreply.github.com>
* Enable Tool Calling for `meta_llama` (#11825)
* feat: enable tools and function_call features
* fix: ignore pydantic warnings for StreamingChoices from llama-api
* docs: add tool calling examples
* docs: change default models to Maverick
* docs: fix output of tool use
* test_map_openai_params
---------
Co-authored-by: Young Han <110819238+seyeong-han@users.noreply.github.com>
* feat(internal_user_endpoints.py): allow passing team-specific details when creating new user with team
allows assigning users to teams on creation
* feat(internal_user_endpoints.py): support for setting team values in default internal user params
Ensures admin can assign all new users to a default team
* test(test_internal_user_endpoints.py): add unit tests
* feat(ui/): allow setting default team on admin UI
easier onboarding for users
* fix(internal_user_endpoints.py): fix exception check
* fix(spend_tracking_utils.py): add user agent tags from standard logging payload, in spend logs payload
* feat(litellm_logging.py): identify user agent tags as `User-Agent: ..` and allow admin to disable storing user agent as tag
* fix(azure_ai/): pass content type header in azure ai request
Fixes https://github.com/BerriAI/litellm/issues/11227
* test: add unit test
* fix(router.py): fix passing dynamic credentials to retrieve batch
Fixes batch retrieval when using router
* test: add more unit tests
