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Update app.py
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app.py
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import gradio as gr
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from huggingface_hub import InferenceClient
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def respond(
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message,
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history: list[dict[str, str]],
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top_p,
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hf_token: gr.OAuthToken,
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):
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client = InferenceClient(token=hf_token.token, model="deepseek-ai/DeepSeek-V3.2")
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messages = [{"role": "system", "content": system_message}]
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messages.extend(history)
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messages.append({"role": "user", "content": message})
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response = ""
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response += token
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yield response
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theme = gr.themes.Soft(
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primary_hue="indigo",
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secondary_hue="violet",
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)
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css = """
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h1 { text-align: center; color: #4f46e5; }
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"""
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type="messages",
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avatar_images=(None, "https://huggingface.co/datasets/huggingface/brand-assets/resolve/main/hf-logo.svg"),
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show_copy_button=True
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)
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chat = gr.ChatInterface(
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respond,
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chatbot=my_chatbot,
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type="messages",
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title="Le chatbot qu'il vous faut",
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additional_inputs=[
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gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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gr.Slider(
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],
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)
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with gr.Blocks(
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with gr.
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with gr.Column(scale=4):
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chat.render()
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if __name__ == "__main__":
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demo.launch(
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import gradio as gr
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from huggingface_hub import InferenceClient
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def respond(
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message,
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history: list[dict[str, str]],
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top_p,
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hf_token: gr.OAuthToken,
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):
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"""
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For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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"""
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client = InferenceClient(token=hf_token.token, model="deepseek-ai/DeepSeek-V3.2")
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messages = [{"role": "system", "content": system_message}]
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messages.extend(history)
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messages.append({"role": "user", "content": message})
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response = ""
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response += token
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yield response
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"""
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For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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"""
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chatbot = gr.ChatInterface(
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respond,
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type="messages",
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additional_inputs=[
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gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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gr.Slider(
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minimum=0.1,
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maximum=1.0,
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value=0.95,
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step=0.05,
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label="Top-p (nucleus sampling)",
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),
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],
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)
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with gr.Blocks() as demo:
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with gr.Sidebar():
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gr.LoginButton()
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chatbot.render()
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if __name__ == "__main__":
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demo.launch(share=True)
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