* 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(main.py): fix async retryer
Fixes https://github.com/BerriAI/litellm/issues/12830
* fix(forward_clientside_headers_by_model_group.py): filter out 'content-type' from forwardable headers
clientside content-type != proxy content type, can cause requests to hang
* test(tests/): update tests
* Fix missing signature_delta in thinking blocks when streaming from Claude 3.7 (#8797)
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* test: update test to enforce signature found
* feat(refactor-signature-param-to-be-'signature'-instead-of-'signature_delta'): keeps it in sync with anthropic
* fix: fix linting error
---------
Co-authored-by: Martin Krasser <krasserm@googlemail.com>
* feat(bedrock/converse/transformation.py): support claude-3-7-sonnet reasoning_Content transformation
Closes https://github.com/BerriAI/litellm/issues/8777
* fix(bedrock/): support returning `reasoning_content` on streaming for claude-3-7
Resolves https://github.com/BerriAI/litellm/issues/8777
* feat(bedrock/): unify converse reasoning content blocks for consistency across anthropic and bedrock
* fix(anthropic/chat/transformation.py): handle deepseek-style 'reasoning_content' extraction within transformation.py
simpler logic
* feat(bedrock/): fix streaming to return blocks in consistent format
* fix: fix linting error
* test: fix test
* feat(factory.py): fix bedrock thinking block translation on tool calling
allows passing the thinking blocks back to bedrock for tool calling
* fix(types/utils.py): don't exclude provider_specific_fields on model dump
ensures consistent responses
* fix: fix linting errors
* fix(convert_dict_to_response.py): pass reasoning_content on root
* fix: test
* fix(streaming_handler.py): add helper util for setting model id
* fix(streaming_handler.py): fix setting model id on model response stream chunk
* fix(streaming_handler.py): fix linting error
* fix(streaming_handler.py): fix linting error
* fix(types/utils.py): add provider_specific_fields to model stream response
* fix(streaming_handler.py): copy provider specific fields and add them to the root of the streaming response
* fix(streaming_handler.py): fix check
* fix: fix test
* fix(types/utils.py): ensure messages content is always openai compatible
* fix(types/utils.py): fix delta object to always be openai compatible
only introduce new params if variable exists
* test: fix bedrock nova tests
* test: skip flaky test
* test: skip flaky test in ci/cd
* fix(o_series_transformation.py): fix optional param check for o-series models
o3-mini and o-1 do not support parallel tool calling
* fix(utils.py): support 'drop_params' for 'thinking' param across models
allows switching to older claude versions (or non-anthropic models) and param to be safely dropped
* fix: fix passing thinking param in optional params
allows dropping thinking_param where not applicable
* test: update old model
* fix(utils.py): fix linting errors
* fix(main.py): add param to acompletion
* feat(main.py): use asyncio.sleep for mock_Timeout=true on async request
adds unit testing to ensure proxy does not fail if specific Openai requests hang (e.g. recent o1 outage)
* fix(streaming_handler.py): fix deepseek r1 return reasoning content on streaming
Fixes https://github.com/BerriAI/litellm/issues/7942
* Revert "fix(streaming_handler.py): fix deepseek r1 return reasoning content on streaming"
This reverts commit 7a052a64e3642616405e71350627e2e4f66615b4.
* fix(deepseek-r-1): return reasoning_content as a top-level param
ensures compatibility with existing tools that use it
* fix: fix linting error
* fix(types/utils.py): support returning 'reasoning_content' for deepseek models
Fixes https://github.com/BerriAI/litellm/issues/7877#issuecomment-2603813218
* fix(convert_dict_to_response.py): return deepseek response in provider_specific_field
allows for separating openai vs. non-openai params in model response
* fix(utils.py): support 'provider_specific_field' in delta chunk as well
allows deepseek reasoning content chunk to be returned to user from stream as well
Fixes https://github.com/BerriAI/litellm/issues/7877#issuecomment-2603813218
* fix(watsonx/chat/handler.py): fix passing space id to watsonx on chat route
* fix(watsonx/): fix watsonx_text/ route with space id
* fix(watsonx/): qa item - also adds better unit testing for watsonx embedding calls
* fix(utils.py): rename to '..fields'
* fix: fix linting errors
* fix(utils.py): fix typing - don't show provider-specific field if none or empty - prevents default respons
e from being non-oai compatible
* fix: cleanup unused imports
* docs(deepseek.md): add docs for deepseek reasoning model
* refactor: initial commit for using separate sync vs. async transformation routes for bedrock
ensures no blocking calls e.g. when converting image url to b64
* perf(converse_transformation.py): make bedrock converse transformation async
asyncify's the bedrock message transformation - useful for handling image urls for bedrock
* fix(converse_handler.py): fix logging for async streaming
* style: cleanup unused imports
* test(azure_openai_o1.py): initial commit with testing for azure openai o1 preview model
* fix(base_llm_unit_tests.py): handle azure o1 preview response format tests
skip as o1 on azure doesn't support tool calling yet
* fix: initial commit of azure o1 handler using openai caller
simplifies calling + allows fake streaming logic alr. implemented for openai to just work
* feat(azure/o1_handler.py): fake o1 streaming for azure o1 models
azure does not currently support streaming for o1
* feat(o1_transformation.py): support overriding 'should_fake_stream' on azure/o1 via 'supports_native_streaming' param on model info
enables user to toggle on when azure allows o1 streaming without needing to bump versions
* style(router.py): remove 'give feedback/get help' messaging when router is used
Prevents noisy messaging
Closes https://github.com/BerriAI/litellm/issues/5942
* fix(types/utils.py): handle none logprobs
Fixes https://github.com/BerriAI/litellm/issues/328
* fix(exception_mapping_utils.py): fix error str unbound error
* refactor(azure_ai/): move to openai_like chat completion handler
allows for easy swapping of api base url's (e.g. ai.services.com)
Fixes https://github.com/BerriAI/litellm/issues/7275
* refactor(azure_ai/): move to base llm http handler
* fix(azure_ai/): handle differing api endpoints
* fix(azure_ai/): make sure all unit tests are passing
* fix: fix linting errors
* fix: fix linting errors
* fix: fix linting error
* fix: fix linting errors
* fix(azure_ai/transformation.py): handle extra body param
* fix(azure_ai/transformation.py): fix max retries param handling
* fix: fix test
* test(test_azure_o1.py): fix test
* fix(llm_http_handler.py): support handling azure ai unprocessable entity error
* fix(llm_http_handler.py): handle sync invalid param error for azure ai
* fix(azure_ai/): streaming support with base_llm_http_handler
* fix(llm_http_handler.py): working sync stream calls with unprocessable entity handling for azure ai
* fix: fix linting errors
* fix(llm_http_handler.py): fix linting error
* fix(azure_ai/): handle cohere tool call invalid index param error
* refactor(utils.py): migrate amazon titan config to base config
* refactor(utils.py): refactor bedrock meta invoke model translation to use base config
* refactor(utils.py): move bedrock ai21 to base config
* refactor(utils.py): move bedrock cohere to base config
* refactor(utils.py): move bedrock mistral to use base config
* refactor(utils.py): move all provider optional param translations to using a config
* docs(clientside_auth.md): clarify how to pass vertex region to litellm proxy
* fix(utils.py): handle scenario where custom llm provider is none / empty
* fix: fix get config
* test(test_otel_load_tests.py): widen perf margin
* fix(utils.py): fix get provider config check to handle custom llm's
* fix(utils.py): fix check
* fix(invoke_handler.py): fix mock response iterator to handle tool calling
returns tool call if returned by model response
* fix(prometheus.py): add new 'tokens_by_tag' metric on prometheus
allows tracking 'token usage' by task
* feat(prometheus.py): add input + output token tracking by tag
* feat(prometheus.py): add tag based deployment failure tracking
allows admin to track failure by use-case
* feat(router.py): support passing model-specific messages in fallbacks
* docs(routing.md): separate router timeouts into separate doc
allow for 1 fallbacks doc (across proxy/router)
* docs(routing.md): cleanup router docs
* docs(reliability.md): cleanup docs
* docs(reliability.md): cleaned up fallback doc
just have 1 doc across sdk/proxy
simplifies docs
* docs(reliability.md): add setting model-specific fallback prompts
* fix: fix linting errors
* test: skip test causing openai rate limit errros
* test: fix test
* test: run vertex test first to catch error
Ishaan Jaffer