mirror of
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80 lines
2.5 KiB
Python
80 lines
2.5 KiB
Python
"""
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*New config* for using aiohttp to make the request to the custom OpenAI-like provider
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This leads to 10x higher RPS than httpx
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https://github.com/BerriAI/litellm/issues/6592
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New config to ensure we introduce this without causing breaking changes for users
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"""
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from typing import TYPE_CHECKING, Any, List, Optional
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from aiohttp import ClientResponse
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from litellm.llms.openai_like.chat.transformation import OpenAILikeChatConfig
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from litellm.types.llms.openai import AllMessageValues
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from litellm.types.utils import Choices, ModelResponse
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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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LiteLLMLoggingObj = _LiteLLMLoggingObj
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else:
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LiteLLMLoggingObj = Any
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class AiohttpOpenAIChatConfig(OpenAILikeChatConfig):
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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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optional_params: dict,
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litellm_params: dict,
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stream: Optional[bool] = None,
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) -> str:
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"""
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Ensure - /v1/chat/completions is at the end of the url
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"""
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if api_base is None:
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api_base = "https://api.openai.com"
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if not api_base.endswith("/chat/completions"):
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api_base += "/chat/completions"
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return api_base
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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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messages: List[AllMessageValues],
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optional_params: dict,
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api_key: Optional[str] = None,
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api_base: Optional[str] = None,
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) -> dict:
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return {"Authorization": f"Bearer {api_key}"}
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async def transform_response( # type: ignore
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self,
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model: str,
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raw_response: ClientResponse,
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model_response: ModelResponse,
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logging_obj: LiteLLMLoggingObj,
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request_data: dict,
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messages: List[AllMessageValues],
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optional_params: dict,
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litellm_params: dict,
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encoding: Any,
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api_key: Optional[str] = None,
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json_mode: Optional[bool] = None,
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) -> ModelResponse:
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_json_response = await raw_response.json()
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model_response.id = _json_response.get("id")
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model_response.choices = [
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Choices(**choice) for choice in _json_response.get("choices")
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]
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model_response.created = _json_response.get("created")
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model_response.model = _json_response.get("model")
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model_response.object = _json_response.get("object")
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model_response.system_fingerprint = _json_response.get("system_fingerprint")
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return model_response
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