chat_bot.py

# Import the required libraries
import torch
from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load the pre-trained GPT-2 model and tokenizer
model_name = "gpt2"  # You can choose a different model size if needed
model = GPT2LMHeadModel.from_pretrained(model_name)
tokenizer = GPT2Tokenizer.from_pretrained(model_name)

# Set the device (CPU or GPU)
device = "cuda" if torch.cuda.is_available() else "cpu"
model.to(device)

# Define a function to generate responses
def generate_response(input_text, max_length=100):
    input_ids = tokenizer.encode(input_text, return_tensors="pt").to(device)
    output = model.generate(input_ids, max_length=max_length, num_return_sequences=1)
    response = tokenizer.decode(output[0], skip_special_tokens=True)
    return response

# Example conversation loop
while True:
    user_input = input("You: ")
    if user_input.lower() == "exit":
        break
    response = generate_response(user_input)
    print("Bot:", response)