Merge pull request #1531 from BerriAI/litellm_max_parallel_request_invalid_provider_fix

fix(utils.py): add metadata to logging obj on setup, if exists (fixes max parallel request bug)

litellm/proxy/hooks/parallel_request_limiter.py

@@ -186,4 +186,4 @@ class MaxParallelRequestsHandler(CustomLogger):
                     request_count_api_key, new_val, ttl=60
                 )  # save in cache for up to 1 min.
         except Exception as e:
-            self.print_verbose(f"An exception occurred - {str(e)}")  # noqa
+            print(f"An exception occurred - {str(e)}")  # noqa

litellm/proxy/proxy_server.py

@@ -2227,7 +2227,11 @@ async def info_key_fn(
             )
         key_info = await prisma_client.get_data(token=key)
         ## REMOVE HASHED TOKEN INFO BEFORE RETURNING ##
-        key_info = key_info.model_dump()
+        try:
+            key_info = key_info.model_dump()  # noqa
+        except:
+            # if using pydantic v1
+            key_info = key_info.dict()
         key_info.pop("token")
         return {"key": key, "info": key_info}
     except Exception as e:
@@ -2366,7 +2370,11 @@ async def user_info(
         )
         ## REMOVE HASHED TOKEN INFO before returning ##
         for key in keys:
-            key = key.model_dump()
+            try:
+                key = key.model_dump()  # noqa
+            except:
+                # if using pydantic v1
+                key = key.dict()
             key.pop("token", None)
         return {"user_id": user_id, "user_info": user_info, "keys": keys}
     except Exception as e:

litellm/utils.py

@@ -773,7 +773,7 @@ class Logging:
         self.model = model
         self.user = user
         self.litellm_params = litellm_params
-        self.logger_fn = litellm_params["logger_fn"]
+        self.logger_fn = litellm_params.get("logger_fn", None)
         print_verbose(f"self.optional_params: {self.optional_params}")
         self.model_call_details = {
             "model": self.model,
@@ -1941,6 +1941,15 @@ def client(original_function):
                 call_type=call_type,
                 start_time=start_time,
             )
+            ## check if metadata is passed in
+            if "metadata" in kwargs:
+                litellm_params = {"metadata": kwargs["metadata"]}
+                logging_obj.update_environment_variables(
+                    model=model,
+                    user="",
+                    optional_params={},
+                    litellm_params=litellm_params,
+                )
             return logging_obj
         except Exception as e:
             import logging