import gradio as gr
from transformers import pipeline

# Créer le générateur de texte avec un modèle public
generator = pipeline("text-generation", model="gpt2")

def respond(message, history):
    history = history or []
    # Ajouter le message utilisateur
    history.append({"role": "user", "content": message})
    # Générer une réponse
    answer = generator(message, max_length=50, do_sample=True)[0]["generated_text"]
    history.append({"role": "assistant", "content": answer})
    # Vider la textbox
    return "", history

# Interface Gradio
with gr.Blocks() as demo:
    chatbot = gr.Chatbot()
    msg = gr.Textbox(label="Message")
    msg.submit(respond, [msg, chatbot], [msg, chatbot])

demo.launch()


# import gradio as gr