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