import gradio as gr
from transformers import pipeline

# Tiny, CPU-friendly model
chatbot_pipeline = pipeline("text-generation", model="sshleifer/tiny-gpt2")

def chat(message, history=[]):
    result = chatbot_pipeline(message, max_new_tokens=50)
    reply = result[0]['generated_text'].replace(message, "").strip()
    history.append((message, reply))
    return history, history

with gr.Blocks() as demo:
    gr.Markdown("## 🤖 Permanent Tiny AI Chatbot")
    chat_ui = gr.Chatbot()
    msg = gr.Textbox(label="Type your message here")
    clear = gr.Button("Clear Chat")

    msg.submit(chat, [msg, chat_ui], [chat_ui, chat_ui])
    clear.click(lambda: None, None, chat_ui, queue=False)

demo.launch()