litellm-mirror/litellm/proxy/common_utils/openai_endpoint_utils.py
Ishaan Jaff 47e12802df
(feat) /batches Add support for using /batches endpoints in OAI format (#7402)
* run azure testing on ci/cd

* update docs on azure batches endpoints

* add input azure.jsonl

* refactor - use separate file for batches endpoints

* fixes for passing custom llm provider to /batch endpoints

* pass custom llm provider to files endpoints

* update azure batches doc

* add info for azure batches api

* update batches endpoints

* use simple helper for raising proxy exception

* update config.yml

* fix imports

* update tests

* use existing settings

* update env var used

* update configs

* update config.yml

* update ft testing
2024-12-24 16:58:05 -08:00

39 lines
1.2 KiB
Python

"""
Contains utils used by OpenAI compatible endpoints
"""
from typing import Optional
from fastapi import Request
from litellm.proxy.common_utils.http_parsing_utils import _read_request_body
def remove_sensitive_info_from_deployment(deployment_dict: dict) -> dict:
"""
Removes sensitive information from a deployment dictionary.
Args:
deployment_dict (dict): The deployment dictionary to remove sensitive information from.
Returns:
dict: The modified deployment dictionary with sensitive information removed.
"""
deployment_dict["litellm_params"].pop("api_key", None)
deployment_dict["litellm_params"].pop("vertex_credentials", None)
deployment_dict["litellm_params"].pop("aws_access_key_id", None)
deployment_dict["litellm_params"].pop("aws_secret_access_key", None)
return deployment_dict
async def get_custom_llm_provider_from_request_body(request: Request) -> Optional[str]:
"""
Get the `custom_llm_provider` from the request body
Safely reads the request body
"""
request_body: dict = await _read_request_body(request=request) or {}
if "custom_llm_provider" in request_body:
return request_body["custom_llm_provider"]
return None