app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

def chatbot_response(user_message):
    model_name = "gpt2"  # You can change this to any other model from the list above
    tokenizer = AutoTokenizer.from_pretrained(model_name)
    model = AutoModelForCausalLM.from_pretrained(model_name)

    inputs = tokenizer.encode("User: " + user_message, return_tensors="pt")
    outputs = model.generate(inputs, max_length=100, num_return_sequences=1)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)

    return response

# Define the chatbot interface using Gradio
iface = gr.Interface(
    fn=chatbot_response,
    inputs=gr.Textbox(prompt="You:"),
    outputs=gr.Textbox(),
    live=True,
    capture_session=True,
    title="Chatbot",
    description="Type your message in the box above, and the chatbot will respond.",
)

# Launch the Gradio interface
if __name__ == "__main__":
    iface.launch()