Update app.py

app.py

@@ -1,57 +1,44 @@
-#Importing gradio for User Interface, importing openai api for the chatbot, importing os for retrieving the secrets from the environment to save as variables, importing uuid for creating a user id.
+# Importing gradio for User Interface, importing openai api for the chatbot, importing os for retrieving the secrets from the environment to save as variables, importing uuid for creating a user id.
 import gradio as gr
 import openai
 import os
 from github import Github
 import uuid
 
-#Initializing secrets
-openai.api_key = os.getenv('OPENAI_KEY')
+openai.api_key = os.getenv('OPENAI_KEY') # Initializing secrets
 
-# Creating UI using gradio Blocks. This line sets the block as a variable called "chatblock", the theme as monochrome, and removes the footer of the page.
-with gr.Blocks(theme=gr.themes.Monochrome(),css="footer{display:none !important}") as chatblock:
-
-    #Displaying the user id, it is made not-visible because the id hasnt been created yet.
-    user_id = gr.Markdown(visible=False)
-
-    #When the chatblock loads we send the information from the following function below called "load_user" to "user_id".
-    @chatblock.load(outputs=[user_id])
-    #When the chatblock loads, the message history is initialized, the instructions are initialized, and the users id is created, sent, and made visible to the ui variable above.
-    def load_user():
-        global message_history #Made global variables so we can use them in the "predict_prompt" function.
+with gr.Blocks(theme=gr.themes.Monochrome(),css="footer{display:none !important}") as chatblock: # Creating UI using gradio Blocks. This line sets the block as a variable called "chatblock", the theme as monochrome, and removes the footer of the page.
+    user_id = gr.Markdown(visible=False) # Displaying the user id, it is made not-visible because the id hasnt been created yet.
+    
+    @chatblock.load(outputs=[user_id]) # When the chatblock loads we send the information from the following function below called "load_user" to "user_id".
+    def load_user(): # When the chatblock loads, the message history is initialized, the instructions are initialized, and the users id is created, sent, and made visible to the ui variable above.
+        global message_history # Made global variables so we can use them in the "predict_prompt" function.
         global instructions
 
-        message_history = [] #List for message history.
-        instructions = 'You only speak in the form of periods and spaces. For example: "... .. .. ..... . ..."' #Change the message under the apostrophes to change the instructions you want the bot to inhibit.
-        message_history.append({"role": "developer", "content": instructions}) #This line adds the instructions to the message history (as a developer) so it will always inhibit the instructions no matter what the user says.
+        message_history = [] # List for message history.
+        instructions = 'You only speak in the form of periods and spaces. For example: "... .. .. ..... . ..."' # Change the message under the apostrophes to change the instructions you want the bot to inhibit.
+        message_history.append({"role": "developer", "content": instructions}) # This line adds the instructions to the message history (as a developer) so it will always inhibit the instructions no matter what the user says.
         
         new_id = str(uuid.uuid4()) #id created by uuid.
         return gr.Markdown(f"<h1><center> Session Id: {new_id} </center></h1>",visible=True) #Returning the "Markdown" object with what we want.
         
-    #Initial message for the User Interface (basically the message for the typing input area)
-    initial_message = "Please write your prompt here and press 'enter'"
+    initial_message = "Please write your prompt here and press 'enter'" # Initial message for the User Interface (basically the message for the typing input area so change the message under the quotes if you want to change that)
 
-    #Creating a gradio-chatbot User Interface with the label "Anonymous User".
-    Chatbot = gr.Chatbot(label="Anonymous User")
+    Chatbot = gr.Chatbot(label="Anonymous User") # Creating a gradio-chatbot User Interface with the label "Anonymous User".
     
-    #This function creates a response for the chatbot to respond with.
-    def predict_prompt(input):
-        message_history.append({"role": "user", "content": input}) #This adds the input from the user and saves it to the history before we do anything else.
+    def predict_prompt(input): # This function creates a response for the chatbot to respond with.
+        message_history.append({"role": "user", "content": input}) # This adds the input from the user and saves it to the history before we do anything else.
 
-        #Asking openai for a prompt based on the current message history.
-        create_prompt = openai.ChatCompletion.create(
-            model = "gpt-4o", #Change the message in the qoutes to change the model. Note: it must be a recognized model by openai's api (case sensetive).
+        create_prompt = openai.ChatCompletion.create( #A sking openai for a prompt based on the current message history.
+            model = "gpt-4o", # Change the message in the qoutes to change the model. Note: it must be a recognized model by openai's api (case sensetive).
             messages = message_history,
         )
 
-        #Variable for the reply prompt.
-        reply_prompt = create_prompt.choices[0].message.content
+        reply_prompt = create_prompt.choices[0].message.content # Variable for the reply prompt.
 
-        #Adds the chatbots response to the history as an "assistant". This is the role commonly used for chatbots.
-        message_history.append({"role": "assistant", "content": reply_prompt}) 
+        message_history.append({"role": "assistant", "content": reply_prompt}) # Adds the chatbots response to the history as an "assistant". This is the role commonly used for chatbots.
 
-        #Variable for the response
-        response = [(message_history[i]["content"], message_history[i+1]["content"]) for i in range(1, len(message_history)-1, 2)]
+        response = [(message_history[i]["content"], message_history[i+1]["content"]) for i in range(1, len(message_history)-1, 2)]  # Variable for the response
 
         #This chunk of code basically loops through the message history so we can write it to a save file repository.
         content = ''
@@ -63,11 +50,9 @@ with gr.Blocks(theme=gr.themes.Monochrome(),css="footer{display:none !important}
             else:
                 content += ''
 
-        #Returning the response
-        return response
+        return response #Returning the response
 
-    #Creating the Row for the chatbot conversation using gradio.
-    with gr.Row():
+    with gr.Row(): #Creating the Row for the chatbot conversation using gradio.
 
         #Create Gradio Textbox for the user to type into
         txt = gr.Textbox(