from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

# Load pre-trained model and tokenizer
model_name = "microsoft/DialoGPT-medium"
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Function to generate a response
def generate_response(prompt):
    inputs = tokenizer.encode(prompt + tokenizer.eos_token, return_tensors="pt")
    reply_ids = model.generate(inputs, max_length=1000, pad_token_id=tokenizer.eos_token_id)
    reply = tokenizer.decode(reply_ids[:, inputs.shape[-1]:][0], skip_special_tokens=True)
    return reply

# Simple chat loop
if __name__ == "__main__":
    print("Chatbot: Hello! How can I help you today?")
    while True:
        user_input = input("You: ")
        if user_input.lower() in ["exit", "quit", "bye"]:
            print("Chatbot: Goodbye!")
            break
        response = generate_response(user_input)
        print(f"Chatbot: {response}")