* fix: use fastuuid helper across the codebase
First batch of changes, simple drop in replacement.
* second batch of changes
* fixed: script mistake on helper file
* fix(streaming_handler.py): maintain same 'created' across all chunks
Fixes https://github.com/BerriAI/litellm/issues/11437
* test: add unit test to ensure created is always the same across all chunks
* fix(types/utils.py): set a tool call id, if missing in delta tool call
Ensures stream chunk builder can reconstruct tool calls correctly
Fixes https://github.com/BerriAI/litellm/issues/11262
* fix(responses/transformation.py): support passing mcp server tool call to anthropic
allows switching between openai and anthropic for mcp tool calling
* fix(ollama/chat/transformation.py): set tool call id's when missing
* fix(anthropic/): fix regression when passing file url's to the 'file_id' parameter
add test and ensure anthropic file url's are correctly sent as 'document' blocks
* fix(vertex_and_google_ai_studio.py): Use same usage calculation function as non-streaming
Closes https://github.com/BerriAI/litellm/issues/10667
* test(test_vertex_and_google_ai_studio_gemini.py): update test
* feat(parallel_request_limiter_v2.py): add sliding window logic
allows rate limiting to work across minutes
* fix(parallel_request_limiter_v2.py): decrement usage on rate limit error
* fix(base_routing_strategy.py): fix merge from redis - preserve values in in-memory cache during gap b/w push to redis and read from redis
* fix(base_routing_strategy.py): catch the delta change during redis sync
ensures values are kept in sync
* fix(parallel_request_limiter_v2.py): update tpm tracking to use slot key logic
* fix: fix linting error
* test: update testing
* test: update tests
* test: skip on rate limit or internal server errors
* test: use pytest fixture instead
* test: bump mistral model
* fix(openai/gpt_transformation.py): handle missing filename for openai file data call
* fix(openai/gpt_transformation.py): clean handling for sync + async pdf url transformation flows
Fixes https://github.com/BerriAI/litellm/issues/10820
* build(model_prices_and_context_window.json): add 'supports_pdf_input' for all openai models which have 'vision' support
Follows openai guidelines
* feat(bedrock/chat): support cache pointing tool calls on Bedrock
Closes https://github.com/BerriAI/litellm/pull/10613
* fix: fix linting error
* add test_function_calling_with_tool_response to base llm tests
* run test suite for nova
* update test_function_calling_with_tool_response
* allowed ToolJsonSchemaBlock keys
* fix ToolJsonSchemaBlock
* add back pytest fixture
* test: test_prompt_caching
* test(base_llm_unit_tests.py): return '<thinking>' tag in response content
* fix(converse_transformation.py): extract `<thinking>` block from nova tool use response
Fixes https://github.com/BerriAI/litellm/issues/9063
* fix(factory.py): handle non-signature reasoning blocks to bedrock
pass as text input - bedrock raises ""User messages cannot contain reasoning content. Please remove the r
easoning content and try again." otherwise
* fix(main.py): Add drop params support for gpt
Fixes https://github.com/BerriAI/litellm/issues/10501
* fix(converse_transformation.py): fix linting error
* fix(utils.py): fix linting error
* test: cleanup test
* test: skip test until we have bedrock prompt caching permission
* fix(vertex_and_google_ai_studio.py): fix finish reason to be 'tool_calls' when tool call returned
Vertex returns 'Stop', openai format is 'tool calls'
* test(base_llm_unit_tests.py): bump test to assert tool calls in finish reason
* feat(fireworks_ai/chat): handle tool calling with fireworks ai correctly
Fixes https://github.com/BerriAI/litellm/issues/7209
* fix(utils.py): handle none type in message
* fix: fix model name in test
* fix(utils.py): fix validate check for openai messages
* fix: fix model returned
* fix(main.py): fix text completion routing
* test: update testing
* test: skip test - cohere having RBAC issues
* build(model_prices_and_context_window.json): add vertex ai gemini-2.5-flash pricing
* build(model_prices_and_context_window.json): add gemini reasoning token pricing
* fix(vertex_and_google_ai_studio_gemini.py): support counting thinking tokens for gemini
allows accurate cost calc
* fix(utils.py): add reasoning token cost calc to generic cost calc
ensures gemini-2.5-flash cost calculation is accurate
* build(model_prices_and_context_window.json): mark gemini-2.5-flash as 'supports_reasoning'
* feat(gemini/): support 'thinking' + 'reasoning_effort' params + new unit tests
allow controlling thinking effort for gemini-2.5-flash models
* test: update unit testing
* feat(vertex_and_google_ai_studio_gemini.py): return reasoning content if given in gemini response
* test: update model name
* fix: fix ruff check
* test(test_spend_management_endpoints.py): update tests to be less sensitive to new keys / updates to usage object
* fix(vertex_and_google_ai_studio_gemini.py): fix translation
* fix(litellm_proxy/chat/transformation.py): support 'thinking' param
Fixes https://github.com/BerriAI/litellm/issues/9380
* feat(azure/gpt_transformation.py): add azure audio model support
Closes https://github.com/BerriAI/litellm/issues/6305
* fix(utils.py): use provider_config in common functions
* fix(utils.py): add missing provider configs to get_chat_provider_config
* test: fix test
* fix: fix path
* feat(utils.py): make bedrock invoke nova config baseconfig compatible
* fix: fix linting errors
* fix(azure_ai/transformation.py): remove buggy optional param filtering for azure ai
Removes incorrect check for support tool choice when calling azure ai - prevented calling models with response_format unless on litell model cost map
* fix(amazon_cohere_transformation.py): fix bedrock invoke cohere transformation to inherit from coherechatconfig
* test: fix azure ai tool choice mapping
* fix: fix model cost map to add 'supports_tool_choice' to cohere models
* fix(get_supported_openai_params.py): check if custom llm provider in llm providers
* fix(get_supported_openai_params.py): fix llm provider in list check
* fix: fix ruff check errors
* fix: support defs when calling bedrock nova
* fix(factory.py): fix test
* test: move test to just checking async
* fix(transformation.py): handle function call with no schema
* fix(utils.py): handle pydantic base model in message tool calls
Fix https://github.com/BerriAI/litellm/issues/9321
* fix(vertex_and_google_ai_studio.py): handle tools=[]
Fixes https://github.com/BerriAI/litellm/issues/9080
* test: remove max token restriction
* test: fix basic test
* fix(get_supported_openai_params.py): fix check
* fix(converse_transformation.py): support fake streaming for meta.llama3-3-70b-instruct-v1:0
* fix: fix test
* fix: parse out empty dictionary on dbrx streaming + tool calls
* fix(handle-'strict'-param-when-calling-fireworks-ai): fireworks ai does not support 'strict' param
* fix: fix ruff check
'
* fix: handle no strict in function
* fix: revert bedrock change - handle in separate PR
* fix(internal_user_endpoints.py): cleanup unused variables on beta endpoint
no team/org split on daily user endpoint
* build(model_prices_and_context_window.json): gemini-2.0-flash supports audio input
* feat(gemini/transformation.py): support passing audio input to gemini
* test: fix test
* fix(gemini/transformation.py): support audio input as a url
enables passing google cloud bucket urls
* fix(gemini/transformation.py): support explicitly passing format of file
* fix(gemini/transformation.py): expand support for inferred file types from url
* fix(sagemaker/completion/transformation.py): fix special token error when counting sagemaker tokens
* test: fix import
* fix(anthropic/chat/transformation.py): Don't set tool choice on response_format conversion when thinking is enabled
Not allowed by Anthropic
Fixes https://github.com/BerriAI/litellm/issues/8901
* refactor: move test to base anthropic chat tests
ensures consistent behaviour across vertex/anthropic/bedrock
* fix(anthropic/chat/transformation.py): if thinking token is specified and max tokens is not - ensure max token to anthropic is higher than thinking tokens
* feat(converse_transformation.py): correctly handle thinking + response format on Bedrock Converse
Fixes https://github.com/BerriAI/litellm/issues/8901
* fix(converse_transformation.py): correctly handle adding max tokens
* test: handle service unavailable error
* fix(anthropic_claude3_transformation.py): fix amazon anthropic claude 3 tool calling transformation on invoke route
move to using anthropic config as base
* fix(utils.py): expose anthropic config via providerconfigmanager
* fix(llm_http_handler.py): support json mode on async completion calls
* fix(invoke_handler/make_call): support json mode for anthropic called via bedrock invoke
* fix(anthropic/): handle 'response_format: {"type": "text"}` + migrate amazon claude 3 invoke config to inherit from anthropic config
Prevents error when passing in 'response_format: {"type": "text"}
* test: fix test
* fix(utils.py): fix base invoke provider check
* fix(anthropic_claude3_transformation.py): don't pass 'stream' param
* fix: fix linting errors
* fix(converse_transformation.py): handle response_format type=text for converse
* feat(proxy/_types.py): add new jwt field params
allows users + services to auth into proxy
* feat(handle_jwt.py): allow team role proxy access
allows proxy admin to set allowed team roles
* fix(proxy/_types.py): add 'routes' to role based permissions
allow proxy admin to restrict what routes a team can access easily
* feat(handle_jwt.py): support more flexible role based route access
v2 on role based 'allowed_routes'
* test(test_jwt.py): add unit test for rbac for proxy routes
* feat(handle_jwt.py): ensure cost tracking always works for any jwt request with `enforce_rbac=True`
* docs(token_auth.md): add documentation on controlling model access via OIDC Roles
* test: increase time delay before retrying
* test: handle model overloaded for test
