app.py

import gradio as gr
from transformers import pipeline

# Load a very small model so it runs quickly on CPU (free tier)
generator = pipeline("text-generation", model="sshleifer/tiny-gpt2")

def chat(user_input):
    try:
        response = generator(
            user_input,
            max_new_tokens=50,
            do_sample=True,
            top_p=0.9,
            temperature=0.8
        )
        # Remove the original prompt from the generated text
        reply = response[0]["generated_text"][len(user_input):].strip()
        return reply
    except Exception as e:
        return f"⚠️ Error: {str(e)}"

iface = gr.Interface(
    fn=chat,
    inputs=gr.Textbox(
        placeholder="Type something...",
        lines=2,
        label="Your Question"
    ),
    outputs=gr.Textbox(label="AI Response"),
    title="🧠 Tiny AI Chatbot",
    description="A lightweight chatbot running on Hugging Face Spaces (Free CPU tier)"
)

if __name__ == "__main__":
    # Hugging Face Spaces handles the server automatically
    iface.launch()