app.py

import os
import sys

# Check for required modules
required_modules = ['transformers', 'torch', 'numpy']

for module in required_modules:
    try:
        __import__(module)
    except ImportError:
        print(f"Module '{module}' not found. Installing...")
        os.system(f"{sys.executable} -m pip install {module}")

# Import necessary libraries
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
import numpy as np

# Setup model and tokenizer
model_name = "gpt-3.5-turbo"  # You might want to replace this with your specific model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Function to generate text
def generate_text(prompt, max_length=100):
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(inputs.input_ids, max_length=max_length, do_sample=True, top_k=50, top_p=0.95)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Main function
def main():
    print("Welcome to CATGPT! Type 'exit' to quit.")
    while True:
        prompt = input("\nEnter your prompt: ")
        if prompt.lower() == 'exit':
            break
        response = generate_text(prompt)
        print(f"\nCATGPT: {response}")

if __name__ == "__main__":
    main()