handled merge conflicts

litellm/main.py

@@ -59,7 +59,6 @@ def get_optional_params(
 ####### COMPLETION ENDPOINTS ################
 #############################################
 @client
-<<<<<<< HEAD
 @func_set_timeout(180, allowOverride=True) ## https://pypi.org/project/func-timeout/ - timeouts, in case calls hang (e.g. Azure)
 def completion(
     model, messages, # required params
@@ -77,12 +76,6 @@ def completion(
       temperature=temperature, top_p=top_p, n=n, stream=stream, stop=stop, max_tokens=max_tokens,
       presence_penalty=presence_penalty, frequency_penalty=frequency_penalty, logit_bias=logit_bias, user=user
     )
-=======
-@func_set_timeout(60, allowOverride=True) ## https://pypi.org/project/func-timeout/ - timeouts, in case calls hang (e.g. Azure)
-def completion(model, messages, max_tokens=None, *, forceTimeout=60, azure=False, logger_fn=None): # ,*,.. if optional params like forceTimeout, azure and logger_fn are passed then they're keyword arguments
-  try:
-    response = None
->>>>>>> bd42ec8 (clean up code files)
     if azure == True:
       # azure configs
       openai.api_type = "azure"
@@ -97,7 +90,7 @@ def completion(model, messages, max_tokens=None, *, forceTimeout=60, azure=False
         messages = messages,
         **optional_params
       )
-    elif model in open_ai_chat_completion_models:
+    elif model in litellm.open_ai_chat_completion_models:
       openai.api_type = "openai"
       openai.api_base = "https://api.openai.com/v1"
       openai.api_version = None
@@ -111,7 +104,7 @@ def completion(model, messages, max_tokens=None, *, forceTimeout=60, azure=False
         messages = messages,
         **optional_params
       )
-    elif model in open_ai_text_completion_models:
+    elif model in litellm.open_ai_text_completion_models:
       openai.api_type = "openai"
       openai.api_base = "https://api.openai.com/v1"
       openai.api_version = None
@@ -221,10 +214,6 @@ def completion(model, messages, max_tokens=None, *, forceTimeout=60, azure=False
           ],
       }
       response = new_response
-<<<<<<< HEAD
-    else:
-      raise Exception(f"Model '{model}' not found. Please check your model name and try again.")
-=======
 
     elif model in litellm.open_ai_chat_completion_models:
       openai.api_type = "openai"
@@ -255,7 +244,6 @@ def completion(model, messages, max_tokens=None, *, forceTimeout=60, azure=False
       logging(model=model, input=messages, azure=azure, logger_fn=logger_fn)
       args = locals()
       raise ValueError(f"No valid completion model args passed in - {args}")
->>>>>>> bd42ec8 (clean up code files)
     return response
   except Exception as e:
     logging(model=model, input=messages, azure=azure, additional_args={"max_tokens": max_tokens}, logger_fn=logger_fn)

litellm/tests/test_completion.py

@@ -1,10 +1,10 @@
 import sys, os
 import traceback
-sys.path.append('..')  # Adds the parent directory to the system path
-import main
-from main import completion
+sys.path.insert(0, os.path.abspath('../..'))  # Adds the parent directory to the system path
+import litellm
+from litellm import embedding, completion
 
-main.set_verbose = True
+litellm.set_verbose = True
 
 user_message = "Hello, whats the weather in San Francisco??"
 messages = [{ "content": user_message,"role": "user"}]

litellm/tests/test_model_fallback.py

@@ -17,20 +17,10 @@ model_fallback_list = ["replicate/llama-2-70b-chat:2c1608e18606fad2812020dc54193
 user_message = "Hello, how are you?"
 messages = [{ "content": user_message,"role": "user"}]
 
-# for _ in range(10):
 for model in model_fallback_list:
     try:
         response = embedding(model="text-embedding-ada-002", input=[user_message])
         response = completion(model=model, messages=messages)
         print(response)
-<<<<<<< HEAD
-        if response != None:
-            break
     except Exception as e:
-=======
-        # if response != None:
-        #     break
-    except:
->>>>>>> bd42ec8 (clean up code files)
         print(f"error occurred: {traceback.format_exc()}") 
-        raise e