blacken code format

ai_single_response.py

@@ -140,8 +140,6 @@ def query_gpt_model(
         to_gpu=use_gpu,
     )
 
-
-
     p_list = []  # track conversation
     p_list.append(speaker.lower() + ":" + "\n")
     p_list.append(prompt_msg.lower() + "\n")

app.py

@@ -3,7 +3,16 @@ deploy-as-bot\gradio_chatbot.py
 A system, method for deploying to Gradio. Gradio is a basic "deploy" interface which allows for other users to test your model from a web URL. It also enables some basic functionality like user flagging for weird responses.
 Note that the URL is displayed once the script is run. 
 """
-from flask import Flask, request, session, jsonify, abort, send_file, render_template, redirect
+from flask import (
+    Flask,
+    request,
+    session,
+    jsonify,
+    abort,
+    send_file,
+    render_template,
+    redirect,
+)
 from ai_single_response import query_gpt_model
 from datetime import datetime
 from transformers import pipeline
@@ -19,10 +28,10 @@ import sys
 from os.path import dirname
 import nltk
 
-nltk.download('stopwords') # still unsure where this error originates from
+nltk.download("stopwords")  # still unsure where this error originates from
 
 sys.path.append(dirname(dirname(os.path.abspath(__file__))))
-#from gradio.networking import get_state, set_state
+# from gradio.networking import get_state, set_state
 warnings.filterwarnings(action="ignore", message=".*gradient_checkpointing*")
 logging.basicConfig()
 cwd = Path.cwd()
@@ -101,7 +110,6 @@ def chat(message):
     return html
 
 
-
 def get_parser():
     """
     get_parser - a helper function for the argparse module
@@ -161,4 +169,7 @@ if __name__ == "__main__":
     )
 
     # launch the gradio interface and start the server
-    iface.launch(share=True, enable_queue=True,)
+    iface.launch(
+        share=True,
+        enable_queue=True,
+    )