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()