| | import gradio as gr |
| | from huggingface_hub import InferenceClient |
| |
|
| | |
| | client = InferenceClient("WhiteRabbitNeo/Llama-3.1-WhiteRabbitNeo-2-70B") |
| |
|
| | def respond( |
| | message, |
| | history: list[tuple[str, str]], |
| | system_message, |
| | max_tokens, |
| | temperature, |
| | top_p, |
| | ): |
| | messages = [{"role": "system", "content": system_message}] |
| |
|
| | for val in history: |
| | if val[0]: |
| | messages.append({"role": "user", "content": val[0]}) |
| | if val[1]: |
| | messages.append({"role": "assistant", "content": val[1]}) |
| |
|
| | messages.append({"role": "user", "content": message}) |
| |
|
| | response = "" |
| |
|
| | try: |
| | for message in client.chat_completion( |
| | messages, |
| | max_tokens=max_tokens, |
| | stream=True, |
| | temperature=temperature, |
| | top_p=top_p, |
| | ): |
| | token = message['choices'][0]['delta']['content'] |
| | response += token |
| | yield response |
| | except Exception as e: |
| | yield f"An error occurred: {str(e)}" |
| |
|
| | |
| | system_message = ( |
| | "You are a cybersecurity expert chatbot, providing assistance on penetration testing, ransomware analysis, and code classification. " |
| | "Your responses should be concise, accurate, and tailored to cybersecurity professionals." |
| | ) |
| |
|
| | |
| | demo = gr.Interface( |
| | fn=respond, |
| | inputs=[ |
| | gr.Textbox(value=system_message, label="System Message"), |
| | gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max New Tokens"), |
| | gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), |
| | gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (Nucleus Sampling)"), |
| | gr.Checkbox(label="Dark Mode", value=False), |
| | ], |
| | outputs=[gr.Textbox()], |
| | theme="dark", |
| | ) |
| |
|
| | def toggle_theme(dark_mode): |
| | """Toggle between dark and light themes based on user input.""" |
| | return "dark" if dark_mode else "light" |
| |
|
| | |
| | demo.change(fn=toggle_theme, inputs=[demo.inputs[4]], outputs=[demo]) |
| |
|
| | if __name__ == "__main__": |
| | demo.launch() |
| |
|