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import gradio as gr |
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from openai import OpenAI |
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import os |
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from dotenv import load_dotenv |
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load_dotenv() |
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client = OpenAI( |
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base_url="https://api-inference.huggingface.co/v1", |
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api_key=os.getenv('HF_TOKEN') |
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) |
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def generate_response(message, temperature=0.7): |
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try: |
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response = client.chat.completions.create( |
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model="Nac31/Sacha-Mistral-0", |
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messages=[{"role": "user", "content": message}], |
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temperature=temperature, |
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max_tokens=500, |
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stream=False |
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) |
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return response.choices[0].message.content |
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except Exception as e: |
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return f"Une erreur s'est produite : {str(e)}" |
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demo = gr.Interface( |
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fn=generate_response, |
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inputs=[ |
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gr.Textbox(label="Votre message", placeholder="Entrez votre message ici..."), |
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gr.Slider(minimum=0.1, maximum=1.0, value=0.7, label="Température") |
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], |
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outputs=gr.Textbox(label="Réponse"), |
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title="Chat avec Sacha-Mistral", |
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description="Un assistant conversationnel en français basé sur le modèle Sacha-Mistral" |
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) |
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if __name__ == "__main__": |
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demo.launch() |
