fix: fix linting error

litellm/proxy/db/db_spend_update_writer.py

@@ -159,7 +159,7 @@ class DBSpendUpdateWriter:
             )
 
             verbose_proxy_logger.debug("Runs spend update on all tables")
-        except Exception as e:
+        except Exception:
             verbose_proxy_logger.debug(
                 f"Error updating Prisma database: {traceback.format_exc()}"
             )

litellm/proxy/hooks/managed_files.py

@@ -5,7 +5,6 @@ import asyncio
 import base64
 import uuid
 from abc import ABC, abstractmethod
-from datetime import datetime
 from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Union, cast
 
 from litellm import Router, verbose_logger
@@ -301,7 +300,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger):
             purpose=cast(OpenAIFilesPurpose, purpose),
             created_at=file_objects[0].created_at,
             bytes=file_objects[0].bytes,
-            filename=str(datetime.now().timestamp()),
+            filename=file_objects[0].filename,
             status="uploaded",
         )
 

litellm/proxy/openai_files_endpoints/files_endpoints.py

@@ -159,6 +159,51 @@ async def create_file_for_each_model(
     return response
 
 
+async def route_create_file(
+    llm_router: Optional[Router],
+    _create_file_request: CreateFileRequest,
+    purpose: OpenAIFilesPurpose,
+    proxy_logging_obj: ProxyLogging,
+    user_api_key_dict: UserAPIKeyAuth,
+    target_model_names_list: List[str],
+    is_router_model: bool,
+    router_model: Optional[str],
+    custom_llm_provider: str,
+) -> OpenAIFileObject:
+    if (
+        litellm.enable_loadbalancing_on_batch_endpoints is True
+        and is_router_model
+        and router_model is not None
+    ):
+        response = await _deprecated_loadbalanced_create_file(
+            llm_router=llm_router,
+            router_model=router_model,
+            _create_file_request=_create_file_request,
+        )
+    elif target_model_names_list:
+        response = await create_file_for_each_model(
+            llm_router=llm_router,
+            _create_file_request=_create_file_request,
+            target_model_names_list=target_model_names_list,
+            purpose=purpose,
+            proxy_logging_obj=proxy_logging_obj,
+            user_api_key_dict=user_api_key_dict,
+        )
+    else:
+        # get configs for custom_llm_provider
+        llm_provider_config = get_files_provider_config(
+            custom_llm_provider=custom_llm_provider
+        )
+        if llm_provider_config is not None:
+            # add llm_provider_config to data
+            _create_file_request.update(llm_provider_config)
+        _create_file_request.pop("custom_llm_provider", None)  # type: ignore
+        # for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch
+        response = await litellm.acreate_file(**_create_file_request, custom_llm_provider=custom_llm_provider)  # type: ignore
+
+    return response
+
+
 @router.post(
     "/{provider}/v1/files",
     dependencies=[Depends(user_api_key_auth)],
@@ -267,37 +312,17 @@ async def create_file(
             file=file_data, purpose=cast(CREATE_FILE_REQUESTS_PURPOSE, purpose), **data
         )
 
-        response: Optional[OpenAIFileObject] = None
+        response = await route_create_file(
-        if (
-            litellm.enable_loadbalancing_on_batch_endpoints is True
-            and is_router_model
-            and router_model is not None
-        ):
-            response = await _deprecated_loadbalanced_create_file(
-                llm_router=llm_router,
-                router_model=router_model,
-                _create_file_request=_create_file_request,
-            )
-        elif target_model_names_list:
-            response = await create_file_for_each_model(
             llm_router=llm_router,
             _create_file_request=_create_file_request,
-                target_model_names_list=target_model_names_list,
             purpose=purpose,
             proxy_logging_obj=proxy_logging_obj,
             user_api_key_dict=user_api_key_dict,
+            target_model_names_list=target_model_names_list,
+            is_router_model=is_router_model,
+            router_model=router_model,
+            custom_llm_provider=custom_llm_provider,
         )
-        else:
-            # get configs for custom_llm_provider
-            llm_provider_config = get_files_provider_config(
-                custom_llm_provider=custom_llm_provider
-            )
-            if llm_provider_config is not None:
-                # add llm_provider_config to data
-                _create_file_request.update(llm_provider_config)
-            _create_file_request.pop("custom_llm_provider", None)  # type: ignore
-            # for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch
-            response = await litellm.acreate_file(**_create_file_request, custom_llm_provider=custom_llm_provider)  # type: ignore
 
         if response is None:
             raise HTTPException(

litellm/proxy/utils.py

@@ -278,6 +278,7 @@ class ProxyLogging:
         self.premium_user = premium_user
         self.service_logging_obj = ServiceLogging()
         self.db_spend_update_writer = DBSpendUpdateWriter()
+        self.proxy_hook_mapping: Dict[str, CustomLogger] = {}
 
     def startup_event(
         self,
@@ -353,8 +354,6 @@ class ProxyLogging:
             self.db_spend_update_writer.redis_update_buffer.redis_cache = redis_cache
             self.db_spend_update_writer.pod_lock_manager.redis_cache = redis_cache
 
-        self.proxy_hook_mapping: Dict[str, CustomLogger] = {}
-
     def _add_proxy_hooks(self, llm_router: Optional[Router] = None):
         """
         Add proxy hooks to litellm.callbacks