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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 |