diff --git a/autogen/oai/chat_completion_proxy.py b/autogen/oai/chat_completion_proxy.py
index 5a1d105715f..a8f6c443400 100644
--- a/autogen/oai/chat_completion_proxy.py
+++ b/autogen/oai/chat_completion_proxy.py
@@ -3,29 +3,30 @@
 
 from openai.openai_object import OpenAIObject
 
-class ChatCompletionProxy():
+
+class ChatCompletionProxy:
     @classmethod
     def _prompt_tokens(cls, messages):
         # Get the encoding for OpenAI's "cl100k_base" model
         encoding = tiktoken.get_encoding("cl100k_base")
-        
+
         # Calculate the total number of tokens in the prompt
         # by iterating over each message in the 'messages' list,
         # encoding its content, and summing up the token counts.
-        return sum([len(encoding.encode(msg['content'])) for msg in messages])
+        return sum([len(encoding.encode(msg["content"])) for msg in messages])
 
     @classmethod
     def create(cls, *args, **kwargs):
         # Check if streaming is enabled in the function arguments
-        if kwargs.get('stream', False) and 'functions' not in kwargs:
+        if kwargs.get("stream", False) and "functions" not in kwargs:
             # Prepare response array based on parameter 'n'
-            response_contents = [""] * kwargs.get('n', 1)
-            finish_reasons = [""] * kwargs.get('n', 1)
+            response_contents = [""] * kwargs.get("n", 1)
+            finish_reasons = [""] * kwargs.get("n", 1)
             completion_tokens = 0
-            
+
             # Set the terminal text color to green for better visibility
-            print("\033[32m", end='')
-            
+            print("\033[32m", end="")
+
             # Send the chat completion request to OpenAI's API and process the response in chunks
             for chunk in openai.ChatCompletion.create(*args, **kwargs):
                 if chunk["choices"]:
@@ -33,43 +34,42 @@ def create(cls, *args, **kwargs):
                         content = choice.get("delta", {}).get("content")
                         # If content is present, print it to the terminal and update response variables
                         if content is not None:
-                            print(content, end='', flush=True)
+                            print(content, end="", flush=True)
                             response_contents[choice.index] += content
                             finish_reasons[choice.index] = choice.get("finish_reasons", None)
                             completion_tokens += 1
                         else:
                             print()
-            
+
             # Reset the terminal text color
             print("\033[0m\n")
-            
+
             # Prepare the final response object based on the accumulated data
             prompt_tokens = cls._prompt_tokens(kwargs["messages"])
             response = OpenAIObject()
-            response.id = chunk['id']
-            response.object = 'chat.completion'
-            response.created = chunk['created']
-            response.model = chunk['model']
+            response.id = chunk["id"]
+            response.object = "chat.completion"
+            response.created = chunk["created"]
+            response.model = chunk["model"]
             response.choices = []
             response.usage = {
                 "prompt_tokens": prompt_tokens,
                 "completion_tokens": completion_tokens,
-                "total_tokens": prompt_tokens + completion_tokens
+                "total_tokens": prompt_tokens + completion_tokens,
             }
             for i in range(len(response_contents)):
-                response["choices"].append({
-                    "index": i,
-                    "finish_reason": finish_reasons[i],
-                    "message": {
-                        'role': 'assistant',
-                        'content': response_contents[i]
+                response["choices"].append(
+                    {
+                        "index": i,
+                        "finish_reason": finish_reasons[i],
+                        "message": {"role": "assistant", "content": response_contents[i]},
                     }
-                })
+                )
         else:
             # If streaming is not enabled, send a regular chat completion request
             # Ensure streaming is disabled
-            kwargs['stream'] = False
+            kwargs["stream"] = False
             response = openai.ChatCompletion.create(*args, **kwargs)
-        
+
         # Return the final response object
         return response
diff --git a/autogen/oai/completion.py b/autogen/oai/completion.py
index 38d8cde4dee..18239842a32 100644
--- a/autogen/oai/completion.py
+++ b/autogen/oai/completion.py
@@ -208,7 +208,7 @@ def _get_response(cls, config: Dict, raise_on_ratelimit_or_timeout=False, use_ca
                 cls._book_keeping(config, response)
                 return response
         openai_completion = (
-            ChatCompletionProxy # Support streaming for chat models
+            ChatCompletionProxy  # Support streaming for chat models
             if config["model"].replace("gpt-35-turbo", "gpt-3.5-turbo") in cls.chat_models
             or issubclass(cls, ChatCompletion)
             else openai.Completion