fixing exception mapping

litellm/main.py

@@ -6,7 +6,7 @@ from functools import partial
 import dotenv
 import traceback
 import litellm
-from litellm import client, logging, exception_type, timeout
+from litellm import client, logging, exception_type, timeout, get_optional_params
 import random
 import asyncio
 from tenacity import (
@@ -20,51 +20,6 @@ dotenv.load_dotenv() # Loading env variables using dotenv
 # TODO move this to utils.py
 # TODO add translations
 # TODO see if this worked - model_name == krrish
-def get_optional_params(
-    # 12 optional params
-    functions = [],
-    function_call = "",
-    temperature = 1,
-    top_p = 1,
-    n = 1,
-    stream = False,
-    stop = None,
-    max_tokens = float('inf'),
-    presence_penalty = 0,
-    frequency_penalty = 0,
-    logit_bias = {},
-    user = "",
-    deployment_id = None
-):
-  optional_params = {}
-  if functions != []:
-      optional_params["functions"] = functions
-  if function_call != "":
-      optional_params["function_call"] = function_call
-  if temperature != 1:
-      optional_params["temperature"] = temperature
-  if top_p != 1:
-      optional_params["top_p"] = top_p
-  if n != 1:
-      optional_params["n"] = n
-  if stream:
-      optional_params["stream"] = stream
-  if stop != None:
-      optional_params["stop"] = stop
-  if max_tokens != float('inf'):
-      optional_params["max_tokens"] = max_tokens
-  if presence_penalty != 0:
-      optional_params["presence_penalty"] = presence_penalty
-  if frequency_penalty != 0:
-      optional_params["frequency_penalty"] = frequency_penalty
-  if logit_bias != {}:
-      optional_params["logit_bias"] = logit_bias
-  if user != "":
-      optional_params["user"] = user
-  if deployment_id != None:
-      optional_params["deployment_id"] = user
-  return optional_params
-
 ####### COMPLETION ENDPOINTS ################
 #############################################
 async def acompletion(*args, **kwargs):
@@ -285,12 +240,13 @@ def completion(
       }
       response = new_response
     else: 
+      ## LOGGING
       logging(model=model, input=messages, azure=azure, logger_fn=logger_fn)
       args = locals()
       raise ValueError(f"No valid completion model args passed in - {args}")
     return response
   except Exception as e:
-    # log the original exception
+    ## LOGGING
     logging(model=model, input=messages, azure=azure, additional_args={"max_tokens": max_tokens}, logger_fn=logger_fn, exception=e)
     ## Map to OpenAI Exception
     raise exception_type(model=model, original_exception=e)