mirror of
https://github.com/BerriAI/litellm.git
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fix refactor - add batches endpoints proxy server.py
This commit is contained in:
Ishaan Jaff
parent
b09ac45d7b
commit
5dd5cc7d87
1 changed files with 224 additions and 0 deletions
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@ -4563,6 +4563,230 @@ async def run_thread(
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)
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######################################################################
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# /v1/batches Endpoints
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######################################################################
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@router.post(
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"/v1/batches",
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dependencies=[Depends(user_api_key_auth)],
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tags=["batch"],
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)
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@router.post(
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"/batches",
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dependencies=[Depends(user_api_key_auth)],
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tags=["batch"],
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)
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async def create_batch(
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request: Request,
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fastapi_response: Response,
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user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
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):
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"""
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Create large batches of API requests for asynchronous processing.
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This is the equivalent of POST https://api.openai.com/v1/batch
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Supports Identical Params as: https://platform.openai.com/docs/api-reference/batch
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Example Curl
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```
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curl http://localhost:4000/v1/batches \
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-H "Authorization: Bearer sk-1234" \
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-H "Content-Type: application/json" \
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-d '{
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"input_file_id": "file-abc123",
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"endpoint": "/v1/chat/completions",
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"completion_window": "24h"
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}'
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```
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"""
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global proxy_logging_obj
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data: Dict = {}
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try:
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# Use orjson to parse JSON data, orjson speeds up requests significantly
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form_data = await request.form()
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data = {key: value for key, value in form_data.items() if key != "file"}
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# Include original request and headers in the data
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data = await add_litellm_data_to_request(
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data=data,
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request=request,
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general_settings=general_settings,
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user_api_key_dict=user_api_key_dict,
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version=version,
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proxy_config=proxy_config,
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)
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_create_batch_data = CreateBatchRequest(**data)
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# for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch
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response = await litellm.acreate_batch(
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custom_llm_provider="openai", **_create_batch_data
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)
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### ALERTING ###
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data["litellm_status"] = "success" # used for alerting
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### RESPONSE HEADERS ###
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hidden_params = getattr(response, "_hidden_params", {}) or {}
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model_id = hidden_params.get("model_id", None) or ""
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cache_key = hidden_params.get("cache_key", None) or ""
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api_base = hidden_params.get("api_base", None) or ""
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fastapi_response.headers.update(
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get_custom_headers(
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user_api_key_dict=user_api_key_dict,
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model_id=model_id,
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cache_key=cache_key,
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api_base=api_base,
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version=version,
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model_region=getattr(user_api_key_dict, "allowed_model_region", ""),
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)
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)
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return response
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except Exception as e:
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data["litellm_status"] = "fail" # used for alerting
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await proxy_logging_obj.post_call_failure_hook(
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user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data
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)
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verbose_proxy_logger.error(
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"litellm.proxy.proxy_server.create_batch(): Exception occured - {}".format(
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str(e)
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)
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)
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verbose_proxy_logger.debug(traceback.format_exc())
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if isinstance(e, HTTPException):
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raise ProxyException(
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message=getattr(e, "message", str(e.detail)),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST),
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)
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else:
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error_msg = f"{str(e)}"
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raise ProxyException(
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message=getattr(e, "message", error_msg),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", 500),
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)
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@router.get(
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"/v1/batches{batch_id}",
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dependencies=[Depends(user_api_key_auth)],
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tags=["batch"],
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)
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@router.get(
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"/batches{batch_id}",
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dependencies=[Depends(user_api_key_auth)],
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tags=["batch"],
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)
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async def retrieve_batch(
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request: Request,
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fastapi_response: Response,
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user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
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batch_id: str = Path(
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title="Batch ID to retrieve", description="The ID of the batch to retrieve"
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),
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):
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"""
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Retrieves a batch.
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This is the equivalent of GET https://api.openai.com/v1/batches/{batch_id}
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Supports Identical Params as: https://platform.openai.com/docs/api-reference/batch/retrieve
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Example Curl
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```
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curl http://localhost:4000/v1/batches/batch_abc123 \
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-H "Authorization: Bearer sk-1234" \
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-H "Content-Type: application/json" \
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```
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"""
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global proxy_logging_obj
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data: Dict = {}
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try:
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# Use orjson to parse JSON data, orjson speeds up requests significantly
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form_data = await request.form()
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data = {key: value for key, value in form_data.items() if key != "file"}
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# Include original request and headers in the data
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data = await add_litellm_data_to_request(
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data=data,
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request=request,
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general_settings=general_settings,
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user_api_key_dict=user_api_key_dict,
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version=version,
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proxy_config=proxy_config,
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)
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_retrieve_batch_request = RetrieveBatchRequest(
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batch_id=batch_id,
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)
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# for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch
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response = await litellm.aretrieve_batch(
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custom_llm_provider="openai", **_retrieve_batch_request
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)
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### ALERTING ###
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data["litellm_status"] = "success" # used for alerting
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### RESPONSE HEADERS ###
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hidden_params = getattr(response, "_hidden_params", {}) or {}
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model_id = hidden_params.get("model_id", None) or ""
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cache_key = hidden_params.get("cache_key", None) or ""
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api_base = hidden_params.get("api_base", None) or ""
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fastapi_response.headers.update(
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get_custom_headers(
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user_api_key_dict=user_api_key_dict,
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model_id=model_id,
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cache_key=cache_key,
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api_base=api_base,
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version=version,
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model_region=getattr(user_api_key_dict, "allowed_model_region", ""),
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)
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)
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return response
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except Exception as e:
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data["litellm_status"] = "fail" # used for alerting
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await proxy_logging_obj.post_call_failure_hook(
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user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data
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)
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verbose_proxy_logger.error(
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"litellm.proxy.proxy_server.retrieve_batch(): Exception occured - {}".format(
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str(e)
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)
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)
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verbose_proxy_logger.debug(traceback.format_exc())
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if isinstance(e, HTTPException):
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raise ProxyException(
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message=getattr(e, "message", str(e.detail)),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST),
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)
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else:
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error_traceback = traceback.format_exc()
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error_msg = f"{str(e)}"
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raise ProxyException(
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message=getattr(e, "message", error_msg),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", 500),
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)
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######################################################################
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# END OF /v1/batches Endpoints Implementation
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######################################################################
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######################################################################
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# /v1/files Endpoints
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