Update app.py

app.py

@@ -1,4 +1,4 @@
-#Importing initial stuff
+#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
@@ -16,37 +16,44 @@ with gr.Blocks(theme=gr.themes.Monochrome(),css="footer{display:none !important}
 
     #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
+        global message_history #Made global variables so we can use them in the "predict_prompt" function.
         global instructions
-        message_history = []
-        instructions = 'You only speak in the form of periods and spaces. For example: "... .. .. ..... . ..."'
-        message_history.append({"role": "developer", "content": 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.
         
-        new_id = str(uuid.uuid4())
-        return gr.Markdown(f"<h1><center> Session Id: {new_id} </center></h1>",visible=True)
+        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.
         
-    # Message for User Interface
+    #Initial message for the User Interface (basically the message for the typing input area)
     initial_message = "Please write your prompt here and press 'enter'"
-    
+
+    #Creating a gradio-chatbot User Interface with the label "Anonymous User".
     Chatbot = gr.Chatbot(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})
+        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",
+            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,
         )
 
-        # Reply content for the chat bot
+        #Variable for the reply prompt.
         reply_prompt = create_prompt.choices[0].message.content
 
-        # Append answer as assistant reply to keep history of prompts
+        #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}) 
+
+        #Variable for the response
         response = [(message_history[i]["content"], message_history[i+1]["content"]) for i in range(1, len(message_history)-1, 2)]
 
-        # variable content store each message found in the message history and states the respective user. This is for the content to add in the file
+        #This chunk of code basically loops through the message history so we can write it to a save file repository.
         content = ''
         for i in range(1,len(message_history), 1):
             if (i % 2 == 1) and (message_history[i]["role"] == "user"):
@@ -56,15 +63,20 @@ with gr.Blocks(theme=gr.themes.Monochrome(),css="footer{display:none !important}
             else:
                 content += ''
 
-        #return response
+        #Returning the response
         return response
-    
+
+    #Creating the Row for the chatbot conversation using gradio.
     with gr.Row():
+
+        #Create Gradio Textbox for the user to type into
         txt = gr.Textbox(
             show_label = False,
             placeholder = initial_message,
         )
-            
+
+        #Adding the messages into the row with gradio.
         txt.submit(predict_prompt, txt, Chatbot)
         txt.submit(None, None, txt, js="() => {''}")
-chatblock.launch()
+        
+chatblock.launch() #launch!