diff --git a/openai/bench.py b/openai/bench.py
index 18a92a7..2bfa7c3 100644
--- a/openai/bench.py
+++ b/openai/bench.py
@@ -1,17 +1,19 @@
-from client import chat,args
 import sys
-sys.path.append('../common/')
-from questions import questions
 import pandas as pd
 
-if __name__ == '__main__':
+from client import args, chat
+
+sys.path.append("../common/")
+from questions import questions
+
+if __name__ == "__main__":
     counter = 1
     responses = []
     for q in questions:
         response = chat(q)
-        if counter >= 2: # allow for a warmup
+        if counter >= 2:  # allow for a warmup
             responses.append(response)
-        counter +=1
+        counter += 1
 
     df = pd.DataFrame(responses)
     df.to_csv(args.filename, index=False)
diff --git a/openai/client.py b/openai/client.py
index f1b243e..9934b70 100644
--- a/openai/client.py
+++ b/openai/client.py
@@ -1,44 +1,69 @@
-from openai import OpenAI
 import argparse
 import time
 
-#TODO: should use a parent parser without --filename here.
-parser = argparse.ArgumentParser(description='Run LLM inference requests and save to a CSV.')
-parser.add_argument('--filename', type=str, default='/dev/stdout',
-                    help='Path to the output CSV file (stdout by default).')
-parser.add_argument('--note', type=str,
-                    help='Note to add to the rows of the file (--model by default).')
-parser.add_argument('--model', type=str, default='gpt-3.5-turbo',
-                    help='Model to use (gpt-3.5-turbo by default).')
-parser.add_argument('--baseurl', type=str, default='https://api.openai.com:443/v1',
-                    help='Endpoint base URL (https://api.openai.com:443/v1 by default).')
+from openai import OpenAI
+
+# TODO: should use a parent parser without --filename here.
+parser = argparse.ArgumentParser(
+    description="Run LLM inference requests and save to a CSV."
+)
+parser.add_argument(
+    "--filename",
+    type=str,
+    default="/dev/stdout",
+    help="Path to the output CSV file (stdout by default).",
+)
+parser.add_argument(
+    "--note", type=str, help="Note to add to the rows of the file (--model by default)."
+)
+parser.add_argument(
+    "--model",
+    type=str,
+    default="gpt-3.5-turbo",
+    help="Model to use (gpt-3.5-turbo by default).",
+)
+parser.add_argument(
+    "--baseurl",
+    type=str,
+    default="https://api.openai.com:443/v1",
+    help="Endpoint base URL (https://api.openai.com:443/v1 by default).",
+)
 args = parser.parse_args()
-if ('note' not in args):
+if "note" not in args:
     args.note = args.model
 
 client = OpenAI(base_url=args.baseurl)
 
-def chat(prompt:str):
+
+def chat(prompt: str):
     start = time.perf_counter()
     result = client.chat.completions.create(
         model=args.model,
         max_tokens=200,
         messages=[
-            {"role": "system", "content": "You are a very verbose and helpful assistant"},
-            {"role": "user", "content": prompt}
-        ]
+            {
+                "role": "system",
+                "content": "You are a very verbose and helpful assistant",
+            },
+            {"role": "user", "content": prompt},
+        ],
     )
     request_time = time.perf_counter() - start
-    return {'tok_count': result.usage.completion_tokens,
-        'time': request_time,
-        'question': prompt,
-        'answer': result.choices[0].message.content,
-        'note': args.note}
+    return {
+        "tok_count": result.usage.completion_tokens,
+        "time": request_time,
+        "question": prompt,
+        "answer": result.choices[0].message.content,
+        "note": args.note,
+    }
+
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     prompt = "San Francisco is a city in"
     result = chat(prompt)
-    tokPerSec = result['tok_count']/result['time']
-    print(f"User: {prompt}\n"
-          f"Chatbot in {result['time']}s with {result['tok_count']} tokens ({tokPerSec} t/s):\n"
-          f"{result['answer']}")
+    tokPerSec = result["tok_count"] / result["time"]
+    print(
+        f"User: {prompt}\n"
+        f"Chatbot in {result['time']}s with {result['tok_count']} tokens ({tokPerSec} t/s):\n"
+        f"{result['answer']}"
+    )