<<PERFECT DETAILED PRODUCTION QUALITY PYTHON CODE FOR GPT3 POWERED SELF WRITING MASTERMIND PLATFORM WITH QUALITY UNIT TESTS>>

<<2000 LINES OF CODE>
<<START>>        

#import required packages

import openai
import discord
import flask
import unittest        

#Defining helper functions

def get_mastermind_questions(query):
    """
    This function queries the OpenAI GPT-3 API to retrieve 
    related mind mastermind questions that can be used for the mastermind platform.
    """
    client = openai.CompletionClient("API_KEY")
    response = client.complete(query)
    return response.choices[0].text


def generate_mastermind_conversation(query):
    """
    This function generates a conversation about the query by querying the 
    OpenAI GPT-3 API and returning related statements that can be used 
    for the mastermind platform.
    """
    client = openai.CompletionClient("API_KEY")
    response = client.complete(query, temperature=1)
    return response.choices[0].text

        

#Defining the Mastermind class to hold the mastermind model

class Mastermind:
    def __init__(self):
        self.query = ""
        self.conversation = []

    def set_query(self, query):
        self.query = query

    def generate_questions(self):
        question = get_mastermind_questions(self.query)
        self.conversation.append(question)

    def generate_conversation(self):
        statement = generate_mastermind_conversation(self.query)
        self.conversation.append(statement)

    def get_conversation(self):
        return self.conversation

    
#Defining a class for the Discord bot that handles 
coordinating the 
#Mastermind conversations between users    
class MastermindBot:

    def __init__(self, channel):
        self.channel = channel

    def setup_listener(self):
        """This method sets up the event listener to continuously look 
        for queries posted by users in the Discord channel"""  
        @discord.client.event 
        async def on_message(message): 
            if message.channel == self.channel: 
                query = message.content				 				 	 
                mastermind = Mastermind()				 
                mastermind.set_query(query)					 	 
                mastermind.generate_questions() 				 	 
                mastermind.generate_conversation() 					 
                conversation = mastermind.get_conversation()  	 

                for statement in conversation:  			 		 
                    await message.channel.send(statement)  	 


#Defining a web app with Flask that hosts a web page to view and interact with the mastermind model                                            
app = flask.Flask("My Web App") 


@app.route('/') 
def home():
    """This method defines the home page of the web app."""  
    html = '' 

    # creating a form for entering a query  
    html += '<form action="/run" method="post"> \n'  
    html += 'Query: <input type="text" name="query" />\n'  
    html += '<input type="submit" value="Submit" />\n'  
    html += '</form>\n'  

    # adding a div and table to hold the mastery conversations  	 
    html += "<div id='mastermind'>\n"    	 
    html += "<table>\n"  

    # grabbing and displaying any conversations that were previously entered  	 
    if 'conversations' in app.mastermind:    	 

        for conversation in app.mastermind['conversations']:    	 

            html += "<tr><td>{}</td></tr>\n".format(conversation)    	 

    html += "</table>\n"  	 
    html += "</div>\n"  

    return html  


@app.route('/run', methods=['POST']) 
def run(): 

    # collecting form data from the post request  	 
    query = flask.request.form['query']    	 

    # instantiating the mastermind model object  	     
    mastermind = Mastermind()      fetching related conversations from GPT- 3  	      mastermind.set_query(query)    	      mastermind.generate_questions()    	      mastermind.generate_conversations()    	      conversation = mastermind.get_converstion()    	         

    # adding current conversation to previous conversations    	      conversation = list(app.mastermind['conversations']) + conversation    	      app.mastermind['conversations'] = conversation    	         

    return home()  

     #Setting up unit tests for each functionality defined in the Mastermind class     class TestMastermindMethods(unittest.TestCase):     "Unit test cases that cover all functionality of the Mastermind class"     def setUp(self):      #instantiating an instance of the Mastermind class      self.mastermind = Mastermind()      #defining a query      self.query = "What is the most interesting thing about Artificial Intelligence?"      #running generate methods to populate the conversation array      self.mastermind.set_query(self.query)      self.mastermind.generate_questions()      self.mastermind.generate_conversation()      self.conversation = self.mastermind.get_conversation()      #defining correct conversation values      self.correct_conversation = [       'What are some of the benefits of using Artificial Intelligence?',        'What are the limitations of Artificial Intelligence technology?',        'What implications does Artificial Intelligence have for humanity in the long term?'    ]    def test_get_mastermind_questions(self):     #testing whether the get_mastermind_questions function correctly retrieves the questions     self.assertEqual(self.conversation[0], self.correct_conversation[0])    def test_generate_mastermind_conversation(self):     #testing whether the generate_mastermind_conversation function correctly retrieves the statements     self.assertEqual(self.conversation[1:], self.correct_conversation[1:])    def test_get_conversation(self):     #testing whether theget_conversation function correctly retrieves all conversation values     self.assertEqual(self.conversation, self.correct_conversation)

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<<START SELF-WRITING GPT MODEL MASTERMIND UPDATOR>>
        

#import required packages

import openai

#define openerai api key

API_KEY = "YOUR_API_KEY_HERE"
        

#Define helper functions

def get_mastermind_questions(query):
    """
    This function queries the OpenAI GPT-3 API to retrieve related 
    masterminding questions that can be used to update the mastermind model.
    """
    client = openai.CompletionClient(API_KEY)
    response = client.complete(query)
    return response.choices[0].text

def generate_mastermind_conversation(query):
    """
    This function generates a conversation about the query by querying the 
    OpenAI GPT-3 API and returning related statements that can be used 
    for updating the mastermind model.
    """
    client = openai.CompletionClient(API_KEY)
    response = client.complete(query, temperature=1)
    return response.choices[0].text

        

#define update function for the mastermind model

def update_mastermind_model():
        

#query OpenAI GPT-3 API with user-defined query string

    query = "What advice would an expert in Artificial Intelligence give?"
    response = get_mastermind_questions(query)
        

#update model with retrieved questions and conversations related to query string

    new_questions = [response] + generate_mastermind_conversation(response)
        

#for each question/conversation, update the model accordingly

    for entry in new_questions:
        if entry not in mastermind.model["conversations"]:
            mastermind.model["conversations"].append(entry)
         

#save the new model and return it for use

    mastermind.save()    
    return mastermind.model    

     #Setting up unit tests for the update_mastermind_model functionality class TestMastermindUpdaterMethods(unittest.TestCase):     """Unit test cases that cover all functionality of the update_mastermind_model """     def setUp(self):      #instantiating an instance of the Mastermind class      self.mastermind = Mastermind()      self.original_model = self.mastermind.model      self.query = "What advice would an expert in Artificial Intelligence give?"      self.response = get_mastermind_questions(self.query)      self.query_with_response = [self.response] + generate_mastermind_conversation(self.response)     def test_update(self):     #check that the model has been updated correctly     updated_model = update_mastermind_model()     self.assertEqual(len(updated_model["conversations"]), len(self.original_model["conversations"] + self.query_with_response))     for entry in self.query_with_response:      self.assertIn(entry, updated_model["conversations"])>        

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