mirror of
https://github.com/BerriAI/litellm.git
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d7b294dd0a
* build(pyproject.toml): add new dev dependencies - for type checking * build: reformat files to fit black * ci: reformat to fit black * ci(test-litellm.yml): make tests run clear * build(pyproject.toml): add ruff * fix: fix ruff checks * build(mypy/): fix mypy linting errors * fix(hashicorp_secret_manager.py): fix passing cert for tls auth * build(mypy/): resolve all mypy errors * test: update test * fix: fix black formatting * build(pre-commit-config.yaml): use poetry run black * fix(proxy_server.py): fix linting error * fix: fix ruff safe representation error
140 lines
3.5 KiB
Python
140 lines
3.5 KiB
Python
import types
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from abc import ABC, abstractmethod
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from typing import TYPE_CHECKING, Any, Dict, Optional, Union
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import httpx
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from litellm.types.llms.openai import (
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ResponseInputParam,
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ResponsesAPIOptionalRequestParams,
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ResponsesAPIResponse,
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ResponsesAPIStreamingResponse,
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)
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from litellm.types.router import GenericLiteLLMParams
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if TYPE_CHECKING:
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from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
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from ..chat.transformation import BaseLLMException as _BaseLLMException
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LiteLLMLoggingObj = _LiteLLMLoggingObj
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BaseLLMException = _BaseLLMException
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else:
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LiteLLMLoggingObj = Any
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BaseLLMException = Any
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class BaseResponsesAPIConfig(ABC):
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def __init__(self):
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pass
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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 k.startswith("_abc")
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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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@abstractmethod
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def get_supported_openai_params(self, model: str) -> list:
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pass
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@abstractmethod
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def map_openai_params(
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self,
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response_api_optional_params: ResponsesAPIOptionalRequestParams,
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model: str,
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drop_params: bool,
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) -> Dict:
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pass
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@abstractmethod
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def validate_environment(
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self,
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headers: dict,
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model: str,
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api_key: Optional[str] = None,
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) -> dict:
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return {}
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@abstractmethod
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def get_complete_url(
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self,
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api_base: Optional[str],
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model: str,
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stream: Optional[bool] = None,
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) -> str:
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"""
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OPTIONAL
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Get the complete url for the request
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Some providers need `model` in `api_base`
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"""
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if api_base is None:
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raise ValueError("api_base is required")
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return api_base
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@abstractmethod
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def transform_responses_api_request(
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self,
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model: str,
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input: Union[str, ResponseInputParam],
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response_api_optional_request_params: Dict,
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litellm_params: GenericLiteLLMParams,
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headers: dict,
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) -> Dict:
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pass
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@abstractmethod
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def transform_response_api_response(
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self,
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model: str,
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raw_response: httpx.Response,
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logging_obj: LiteLLMLoggingObj,
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) -> ResponsesAPIResponse:
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pass
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@abstractmethod
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def transform_streaming_response(
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self,
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model: str,
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parsed_chunk: dict,
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logging_obj: LiteLLMLoggingObj,
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) -> ResponsesAPIStreamingResponse:
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"""
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Transform a parsed streaming response chunk into a ResponsesAPIStreamingResponse
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"""
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pass
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def get_error_class(
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self, error_message: str, status_code: int, headers: Union[dict, httpx.Headers]
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) -> BaseLLMException:
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from ..chat.transformation import BaseLLMException
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raise BaseLLMException(
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status_code=status_code,
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message=error_message,
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headers=headers,
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)
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def should_fake_stream(
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self,
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model: Optional[str],
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stream: Optional[bool],
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custom_llm_provider: Optional[str] = None,
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) -> bool:
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"""Returns True if litellm should fake a stream for the given model and stream value"""
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return False
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