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import gradio as gr |
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from huggingface_hub import InferenceClient |
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client = InferenceClient("WhiteRabbitNeo/Llama-3.1-WhiteRabbitNeo-2-70B") |
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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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try: |
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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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except Exception as e: |
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yield f"An error occurred: {str(e)}" |
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system_message = ( |
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"You are a cybersecurity expert chatbot, providing assistance on penetration testing, ransomware analysis, and code classification. " |
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"Your responses should be concise, accurate, and tailored to cybersecurity professionals." |
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) |
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demo = gr.Interface( |
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fn=respond, |
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inputs=[ |
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gr.Textbox(value=system_message, 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(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (Nucleus Sampling)"), |
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gr.Checkbox(label="Dark Mode", value=False), |
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], |
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outputs=[gr.Textbox()], |
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theme="dark", |
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) |
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def toggle_theme(dark_mode): |
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"""Toggle between dark and light themes based on user input.""" |
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return "dark" if dark_mode else "light" |
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demo.change(fn=toggle_theme, inputs=[demo.inputs[4]], outputs=[demo]) |
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if __name__ == "__main__": |
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demo.launch() |
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