* feat(cohere/embed): v2 embed api support
adds output_dimensions param support
* fix(cohere/embed): migrate to v2 embedding
Adds output dimension support
* fix: maintain /v1/embedding compatibility for bedrock cohere
Bedrock cohere is still using /v1 endpoints
* fix: fix linting error
* fix: fix passing extra headers
* test: update tests
* 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
* fix(main.py): use base model instead of user model if given
Fixes https://github.com/BerriAI/litellm/issues/10760
* feat(azure/image_generation/__init__.py): make azure image gen check more robust
Fixes https://github.com/BerriAI/litellm/issues/10760
* fix(user_api_key_auth.py): support bearer token auth for `x-litellm-api-key` header
Fixes earlier regression on vertex ai passthrough auth
* fix(user_api_key_auth.py): refactor get api key into separate function
enables easier testing
* fix: cleanup
* fix: fix linting error
* fix: cleanup
* test: update tests
* Support pdf url's to openai (#10640)
* fix(gpt_transformation.py): support pdf url input to openai
pass as base64 as openai doesn't support image url's
* fix(openai.py): support async message transformation
allows async get request to convert url to base64
* fix(gpt_transformation.py): fix linting errrors and use common components across sync + async flows
* fix: fix linting errors
* fix(openai.py): pop correct var
* Fix sagemaker chat calls - content length error (#10607)
* fix(sagemaker_chat/): support passing dynamic aws params
previously being ignored
* refactor(sagemaker/chat): more refactoring
* fix(sagemaker_chat/): make sure streaming is correctly handled post-refactor
* refactor: more refactoring to support using signed json str
* fix(sagemaker/chat): working sync streaming post refactor
* fix(sagemaker/chat): support async streaming post refactor
* fix(llm_http_handler.py): await async function
* fix: remove print statements
* test: update test
* test: update test
* fix(llm_http_handler.py): retain passing in data as json str
* test: update test
* fix(base_model_iterator.py): fix linting error
* test: test auth
* fix: fix linting error
* test: update test
* test: update translation test
* fix(gpt_transformation.py): handle awaitable/non-awaitable object
* fix: handle async flow for message transformation on openai compatible api's
* test: cleanup testing
* test: update test
* test(test_router.py): use model with higher quota
* test: simplify test
* test: update test
* 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
* build(model_prices_and_context_window.json): add bedrock llama4 models to model cost map
* fix template conversion for Llama 4 models in Bedrock (#10557)
* test: add testing to repro https://github.com/BerriAI/litellm/pull/10557
* test: add unit testing
* test(test_main.py): refactor where test is kept
---------
Co-authored-by: aswny <87371411+aswny@users.noreply.github.com>
* 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
* test(test_auth_checks.py): add unit tests for ExperimentalUIJWTToken
* test: add appropriate flag
* fix: fix ruff check
* test: add autouse fixture to test salt key
* fix(user_api_key_auth.py): fix auth flow logic
* test: skip flaky test - anthropic does not reliably return 'redacted_thinking'
* fix(triton/completion/transformation.py): remove bad_words / stop words from triton call
parameter 'bad_words' has invalid type. It should be either 'int', 'bool', or 'string'.
* fix(proxy_track_cost_callback.py): add debug logging for track cost callback error
* 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(azure/common_utils.py): check for azure tenant id, client id, client secret in env var
Fixes https://github.com/BerriAI/litellm/issues/9598#issuecomment-2801966027
* fix(azure/gpt_transformation.py): fix passing response_format to azure when api year = 2025
Fixes https://github.com/BerriAI/litellm/issues/9703
* test: monkeypatch azure api version in test
* test: update testing
* test: fix test
* test: update test
* docs(config_settings.md): document env vars
* 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(vertex_ai.py): common_utils.py
move to only passing in accepted keys by vertex ai
prevent json schema compatible keys like $id, and $comment from causing vertex ai openapi calls to fail
* fix(test_vertex.py): add testing to ensure only accepted schema params passed in
* fix(common_utils.py): fix linting error
* test: update test
* test: accept function
