cagi.py

import agi
import cagi 
import CAGI
import discord
from discord.ext import commands
import gym
import numpy as np
import tensorflow 
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
import openai

# Initialize 
intents = discord.Intents.default()
intents.message_content = True
bot = commands.Bot(command_prefix="!", intents=intents)
cagi_agent = CAGI()
openai.api_key = 'YOUR_API_KEY'

# Helper functions
def interpret_acronym(acronym, dict):
  # function body
  
    def interact_with_gym():
  # gym environment code

# Load data
        iris = load_iris()
X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.2)
knn_classifier = KNeighborsClassifier(n_neighbors=3)
knn_classifier.fit(X_train, y_train)

# Chatbot class
class Chatbot:

  def __init__(self):
    self.chat_history = []
    
  def record_chat(self, message):
    self.chat_history.append(message)
    
  # Other methods
  
chatbot = Chatbot()
  
# Bot events  
@bot.event
async def on_ready():
  print("Ready!")
  
@bot.event  
async def on_message(message):

  if message.content.startswith("!interpret"):
     pass
     
  if message.content.startswith("!interact"):
     pass
  
  if message.content.startswith("!reboot")
     pass

  if message.content.startswith("!create_ai")
     pass    
  
  if message.content.startswith("!formulated_expansion")
     pass

  chatbot.record_chat(message)

class CAGI:
    def __init__(self):
        self.knowledge_base = {}

    def learn(self, topic, information):
        self.knowledge_base[topic] = information

    def query(self, topic):
        return self.knowledge_base.get(topic, "Information not found in the knowledge base.")

        cagi = CAGI()

# Learn about various topics
cagi.learn("Machine Learning", "A type of artificial intelligence that allows a system to learn from data rather than through explicit programming.")
cagi.learn("Neural Networks", "A set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns.")
cagi.learn("Natural Language Processing", "A field of AI that focuses on the interaction between computers and humans through natural language.")
cagi.learn("Reinforcement Learning", "A type of machine learning where an agent learns how to behave in an environment by performing actions and observing the rewards of those actions.")

# Query for information
print(cagi.query("Machine Learning"))
print(cagi.query("Neural Networks"))
print(cagi.query("Robotics"))

# Define A.C.R.O.N.Y.M.F.O.R.M.U.L.A
class BATMANAI:
    def __init__(self):
        self.chat_history = []  # Initialize an empty list to store chat data

    def ():
    # Define your training logic here
    pass

    def Cagi():
    # Define your training logic here
    pass

    def record_chat(self, message):
        self.chat_history.append(message)  # Add the message to the chat history

    def Assist(self):
        # Implement assistance functionality
        pass

    def Teach(self):
        # Implement teaching functionality
        pass

    def Monitor(self):
        # Implement monitoring functionality
        pass

    def Analyze(self):
        # Implement analysis functionality
        pass

    def Notify(self):
        # Implement notification functionality
        pass

# Initialize BATMANAI
batman_ai = BATMANAI()

# Define a function for chatting with the bot
async def chat_with_bot(message):
    if message.content.lower() == 'hello':
        await message.channel.send("Hello! How do you need my Assitance?")
    elif message.content.lower() == 'goodbye':
        await message.channel.send("Goodbye! Have a great day!")
    else:
        await message.channel.send("I'll try to come up with a better response. Try asking me about an acronym.")

# Initialize BATMANAI
batman_ai = BATMANAI()

@bot.event
async def on_message(message):
    if message.author == bot.user:
        return

    if message.content.startswith("!interpret"):
        acronym = message.content.split("!interpret ")[1]
        expanded_form = interpret_acronym(acronym, acronym_dict)
        await message.channel.send(f"The expanded form of {acronym} is: {expanded_form}")

        # ... (existing code)

    if message.content.startswith("!formulate"):
        acronym = message.content.split("!formulate ")[1]
        formulated_expansion = formulate_acronym(acronym)
        await message.channel.send(formulated_expansion)

    # Record chat data
    batman_ai.record_chat(message.content)


# Initialize BATMANAI
batman_ai = BATMANAI()

@bot.event
async def on_message(message):
    if message.author == bot.user:
        return

    if message.content.startswith("!interpret"):
        acronym = message.content.split("!interpret ")[1]
        expanded_form = interpret_acronym(acronym, acronym_dict)
        await message.channel.send(f"The expanded form of {acronym} is: {expanded_form}")

        # ... (existing code)

    if message.content.startswith("!formulate"):
        acronym = message.content.split("!formulate ")[1]
        formulated_expansion = formulate_acronym(acronym)
        await message.channel.send(formulated_expansion)

    # Record chat data
    batman_ai.record_chat(message.content)
   
    @bot.command()
async def reboot(ctx):
    # Add any necessary reboot logic here
    await ctx.send("Rebooting...")  # Example message, you can customize it

    # For example, you can reinitialize your bot or reset any necessary variables

    # NOTE: Be careful with rebooting, as it will temporarily disconnect your bot.

@bot.event
async def on_message(message):
    if message.author == bot.user:
        return

    if message.content.startswith("!interpret"):
        # ... (existing code)

    if message.content.startswith("!formulate"):
        # ... (existing code)

    if message.content.startswith("!reboot"):
        await reboot(message.channel)

    # Record chat data
    batman_ai.record_chat(message.content)

@bot.event
async def on_message(message):
    if message.author == bot.user:
        return

    if message.content.startswith("!interpret"):
        # ... (existing code)

    if message.content.startswith("!formulate"):
        # ... (existing code)

    if message.content.startswith("!create_ai"):
        acronym = message.content.split("!create_ai ")[1]
        ai_expansion = batman_ai.create_ai(acronym)
        await message.channel.send(f"The AI expansion of {acronym} is: {ai_expansion}")

    # Record chat data
    batman_ai.record_chat(message.content)

@bot.event
async def on_message(message):
    if message.author == bot.user:
        return

    if message.content.startswith("!interpret"):
        # ... (existing code)

    if message.content.startswith("!formulate"):
        # ... (existing code)

    if message.content.startswith("!create_ai"):
        acronym = message.content.split("!create_ai ")[1]
        ai_expansion = batman_ai.create_ai(acronym)
        await message.channel.send(f"The AI expansion of {acronym} is: {ai_expansion}")

    # Record chat data
    batman_ai.record_chat(message.content)

    if message.content.startswith("!reboot"):
        # Add any necessary reboot logic here
        await message.channel.send("Rebooting...")  # Example message, you can customize it

        # For example, you can reinitialize your bot or reset any necessary variables

        # NOTE: Be careful with rebooting, as it will temporarily disconnect your bot

    # Restart the bot
    await bot.logout()

# Add this command to your event loop
@bot.event
async def on_message(message):
    if message.author == bot.user:
        return

# Create an instance of CAGI
cagi = CAGI()

# Use the CAGI instance as described in the previous example
cagi.learn("Machine Learning", "A type of artificial intelligence that allows a system to learn from data rather than through explicit programming.")
print(cagi.query("Machine Learning"))

bot.run("")