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Create app.py
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app.py
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import gradio as gr
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from transformers import pipeline
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import random
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import time
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# Création du pipeline pour le modèle de Hugging Face
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pipe = pipeline(task='text-generation', model='meta-llama/Llama-2-7b-chat-hf')
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# Création de l'interface Gradio
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with gr.Blocks() as demo:
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chatbot = gr.Chatbot()
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msg = gr.Textbox()
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clear = gr.ClearButton([msg, chatbot])
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def respond(message, chat_history):
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# Utilisation du modèle de Hugging Face pour générer une réponse
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bot_message = pipe(message, max_length=50)[0]['generated_text']
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chat_history.append((message, bot_message))
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time.sleep(2)
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return "", chat_history
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msg.submit(respond, [msg, chatbot], [msg, chatbot])
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if __name__ == "__main__":
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demo.launch()
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