forked from phoenix/litellm-mirror
LiteLLM Minor Fixes & Improvements (09/27/2024) (#5938)
* fix(langfuse.py): prevent double logging requester metadata Fixes https://github.com/BerriAI/litellm/issues/5935 * build(model_prices_and_context_window.json): add mistral pixtral cost tracking Closes https://github.com/BerriAI/litellm/issues/5837 * handle streaming for azure ai studio error * [Perf Proxy] parallel request limiter - use one cache update call (#5932) * fix parallel request limiter - use one cache update call * ci/cd run again * run ci/cd again * use docker username password * fix config.yml * fix config * fix config * fix config.yml * ci/cd run again * use correct typing for batch set cache * fix async_set_cache_pipeline * fix only check user id tpm / rpm limits when limits set * fix test_openai_azure_embedding_with_oidc_and_cf * fix(groq/chat/transformation.py): Fixes https://github.com/BerriAI/litellm/issues/5839 * feat(anthropic/chat.py): return 'retry-after' headers from anthropic Fixes https://github.com/BerriAI/litellm/issues/4387 * feat: raise validation error if message has tool calls without passing `tools` param for anthropic/bedrock Closes https://github.com/BerriAI/litellm/issues/5747 * [Feature]#5940, add max_workers parameter for the batch_completion (#5947) * handle streaming for azure ai studio error * bump: version 1.48.2 → 1.48.3 * docs(data_security.md): add legal/compliance faq's Make it easier for companies to use litellm * docs: resolve imports * [Feature]#5940, add max_workers parameter for the batch_completion method --------- Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com> Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com> Co-authored-by: josearangos <josearangos@Joses-MacBook-Pro.local> * fix(converse_transformation.py): fix default message value * fix(utils.py): fix get_model_info to handle finetuned models Fixes issue for standard logging payloads, where model_map_value was null for finetuned openai models * fix(litellm_pre_call_utils.py): add debug statement for data sent after updating with team/key callbacks * fix: fix linting errors * fix(anthropic/chat/handler.py): fix cache creation input tokens * fix(exception_mapping_utils.py): fix missing imports * fix(anthropic/chat/handler.py): fix usage block translation * test: fix test * test: fix tests * style(types/utils.py): trigger new build * test: fix test --------- Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com> Co-authored-by: Jose Alberto Arango Sanchez <jose.arangos@udea.edu.co> Co-authored-by: josearangos <josearangos@Joses-MacBook-Pro.local>
This commit is contained in:
Krish Dholakia
GitHub
parent
754981a78f
commit
0b30e212da
35 changed files with 3657 additions and 2820 deletions
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@ -220,104 +220,6 @@ class DeepInfraConfig:
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return optional_params
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class GroqConfig:
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"""
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Reference: https://deepinfra.com/docs/advanced/openai_api
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The class `DeepInfra` provides configuration for the DeepInfra's Chat Completions API interface. Below are the parameters:
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"""
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frequency_penalty: Optional[int] = None
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function_call: Optional[Union[str, dict]] = None
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functions: Optional[list] = None
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logit_bias: Optional[dict] = None
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max_tokens: Optional[int] = None
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n: Optional[int] = None
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presence_penalty: Optional[int] = None
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stop: Optional[Union[str, list]] = None
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temperature: Optional[int] = None
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top_p: Optional[int] = None
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response_format: Optional[dict] = None
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tools: Optional[list] = None
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tool_choice: Optional[Union[str, dict]] = None
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def __init__(
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self,
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frequency_penalty: Optional[int] = None,
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function_call: Optional[Union[str, dict]] = None,
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functions: Optional[list] = None,
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logit_bias: Optional[dict] = None,
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max_tokens: Optional[int] = None,
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n: Optional[int] = None,
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presence_penalty: Optional[int] = None,
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stop: Optional[Union[str, list]] = None,
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temperature: Optional[int] = None,
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top_p: Optional[int] = None,
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response_format: Optional[dict] = None,
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tools: Optional[list] = None,
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tool_choice: Optional[Union[str, dict]] = None,
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) -> None:
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locals_ = locals().copy()
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for key, value in locals_.items():
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if key != "self" and value is not None:
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setattr(self.__class__, key, value)
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@classmethod
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def get_config(cls):
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return {
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k: v
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for k, v in cls.__dict__.items()
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if not k.startswith("__")
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and not isinstance(
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v,
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(
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types.FunctionType,
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types.BuiltinFunctionType,
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classmethod,
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staticmethod,
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),
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)
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and v is not None
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}
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def get_supported_openai_params_stt(self):
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return [
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"prompt",
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"response_format",
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"temperature",
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"language",
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]
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def get_supported_openai_response_formats_stt(self) -> List[str]:
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return ["json", "verbose_json", "text"]
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def map_openai_params_stt(
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self,
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non_default_params: dict,
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optional_params: dict,
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model: str,
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drop_params: bool,
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) -> dict:
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response_formats = self.get_supported_openai_response_formats_stt()
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for param, value in non_default_params.items():
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if param == "response_format":
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if value in response_formats:
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optional_params[param] = value
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else:
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if litellm.drop_params is True or drop_params is True:
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pass
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else:
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raise litellm.utils.UnsupportedParamsError(
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message="Groq doesn't support response_format={}. To drop unsupported openai params from the call, set `litellm.drop_params = True`".format(
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value
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),
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status_code=400,
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)
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else:
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optional_params[param] = value
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return optional_params
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class OpenAIConfig:
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"""
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Reference: https://platform.openai.com/docs/api-reference/chat/create
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