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import gradio as gr |
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from huggingface_hub import InferenceClient |
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") |
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def respond( |
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message, |
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history: list[tuple[str, str]], |
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system_message, |
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max_tokens, |
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temperature, |
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top_p, |
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): |
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messages = [{"role": "system", "content": system_message}] |
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for val in history: |
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if val[0]: |
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messages.append({"role": "user", "content": val[0]}) |
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if val[1]: |
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messages.append({"role": "assistant", "content": val[1]}) |
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messages.append({"role": "user", "content": message}) |
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response = "" |
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for message in client.chat_completion( |
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messages, |
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max_tokens=max_tokens, |
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stream=True, |
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temperature=temperature, |
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top_p=top_p, |
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): |
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token = message.choices[0].delta.content |
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response += token |
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yield response |
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custom_css = """ |
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#main-container { |
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background-color: #f0f0f0; |
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font-family: 'Arial', sans-serif; |
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} |
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.gradio-container { |
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max-width: 700px; |
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margin: 0 auto; |
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padding: 20px; |
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background: white; |
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box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1); |
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border-radius: 10px; |
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} |
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.gr-button { |
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background-color: #4CAF50; |
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color: white; |
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border: none; |
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border-radius: 5px; |
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padding: 10px 20px; |
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cursor: pointer; |
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transition: background-color 0.3s ease; |
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} |
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.gr-button:hover { |
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background-color: #45a049; |
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} |
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.gr-slider input { |
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color: #4CAF50; |
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} |
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.gr-chat { |
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font-size: 16px; |
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} |
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#title { |
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text-align: center; |
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font-size: 2em; |
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margin-bottom: 20px; |
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color: #333; |
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} |
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""" |
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demo = gr.ChatInterface( |
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respond, |
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additional_inputs=[ |
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gr.Textbox(value="You are a friendly Chatbot.", label="System message", interactive=True), |
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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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css=custom_css, |
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title="π Fancy AI Chatbot π", |
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description="Interact with the AI chatbot using customizable settings below." |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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