Ai Deja

[Raptor30]

import random import time import psutil import nn import pandas as pd import matplotlib.pyplot as plt import lxml.html import pillow as pil import sklearn import scipy.stats import cv2 import tensorflow as tf import numpy as np

from tkinter import from pyttsx3 import from googlesearch import GoogleSearch from youtube import Youtube

class SelfImprovingAI:

def __init__(self):
    self.training_data = []
    self.algorithm = nn.Brain(900000000)
    self.learning_rate = 0.01
    self.cpu_limit = 50
    self.memory_limit = 1000

    self.interpreter = Interpreter()

    self.google = GoogleSearch()
    self.youtube = Youtube()

    self.sensors = [
        Sensor("temperature"),
        Sensor("humidity"),
        Sensor("light"),
        Sensor("camera"),
        Sensor("microphone"),
        Sensor("accelerometer"),
    ]
    self.goal = None
    self.user = None

    self.window = tk.Tk()
    self.window.title("Self-Improving AI")

    # Create a label to display the AI's current state
    self.state_label = tk.Label(self.window, text="AI is learning...")
    self.state_label.pack()

    # Create a progress bar to show the AI's progress
    self.progress_bar = ttk.Progressbar(self.window, orient=HORIZONTAL, length=200)
    self.progress_bar.pack()

    # Create a button to start learning
    self.learn_button = tk.Button(
        self.window, text="Start Learning", command=self.learn
    )
    self.learn_button.pack()

    # Create a button to stop learning
    self.stop_learning_button = tk.Button(
        self.window, text="Stop Learning", command=self.stop_learning
    )
    self.stop_learning_button.pack()

    # Create a button to test the AI
    self.test_button = tk.Button(
        self.window, text="Test AI", command=self.test
    )
    self.test_button.pack()

    # Create a canvas to display the AI's progress
    self.canvas = tk.Canvas(self.window, width=200, height=100)
    self.canvas.pack()

    # Create a text box to display the AI's thoughts
    self.text_box = tk.Text(self.window, height=10)
    self.text_box.pack()

    # Improve the AI's understanding of natural language
    self.algorithm.improve_understanding_of_natural_language()

    # Improve the AI's conversation capabilities
    self.algorithm.improve_conversation_capabilities()

    self.window.mainloop()

def learn(self):
    self.state_label.config(text="AI is learning...")
    self.progress_bar.config(value=0)

    # Learn from the data
    for data_item in self.training_data:
        # Update the progress bar
        self.progress_bar.config(value=self.progress_bar.value + 1)

        # Improve the AI's algorithm
        improved_algorithm = self.improve_algorithm(data_item)

        # Check if the improved algorithm is better
        if improved_algorithm.accuracy > self.algorithm.accuracy:
            self.algorithm = improved_algorithm

    # Update the state label
    self.state_label.config(text="AI has finished learning.")

def stop_learning(self):
    self.state_label.config(text="AI has stopped learning.")

def test(self):
    # Test the AI
    test_data = [
        "What is the capital of France?",
        "What is the meaning of life?",
        "What is the best way to solve world hunger?",
    ]
    for question in test_data:
        answer = self.algorithm.predict(question