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| from huggingface_hub import InferenceClient | |
| import gradio as gr | |
| import base64 | |
| import datetime | |
| client = InferenceClient("meta-llama/Meta-Llama-3-8B-Instruct") | |
| # Debate response function | |
| def debate_respond(message, history: list[tuple[str, str]], | |
| max_tokens=1024, temperature=0.4, top_p=0.95): | |
| # System message defining assistant behavior in a debate | |
| system_message = { | |
| "role": "system", | |
| "content": f"Act as a debate participant taking the position '{position}' on the topic '{topic}'. Respond professionally, thoughtfully, and convincingly, staying within the specified role." | |
| f"If the user's point challenges your position, provide a counterargument. Maintain a respectful tone throughout the discussion." | |
| } | |
| messages = [system_message] | |
| # Adding conversation history | |
| for val in history: | |
| if val[0]: | |
| messages.append({"role": "user", "content": val[0]}) | |
| if val[1]: | |
| messages.append({"role": "assistant", "content": val[1]}) | |
| # Adding the current user input | |
| messages.append({"role": "user", "content": message}) | |
| # Generating the response | |
| response = "" | |
| for message in client.chat_completion( | |
| messages, | |
| max_tokens=max_tokens, | |
| stream=True, | |
| temperature=temperature, | |
| top_p=top_p, | |
| ): | |
| response += message.choices[0].delta.content | |
| yield response | |
| print(f"{datetime.datetime.now()}::{messages[-1]['content']}->{response}\n") | |
| # Encode image function for logos (optional, kept for design) | |
| def encode_image(image_path): | |
| with open(image_path, "rb") as image_file: | |
| return base64.b64encode(image_file.read()).decode('utf-8') | |
| # Gradio interface | |
| global topic, position | |
| with gr.Blocks(theme=gr.themes.Ocean(font=[gr.themes.GoogleFont("Roboto Mono")]), | |
| css='footer {visibility: hidden}') as demo: | |
| gr.Markdown("# LLM Debate Participant") | |
| with gr.Tabs(): | |
| with gr.TabItem("Debate Interface"): | |
| with gr.Row(): | |
| topic = gr.Textbox(label="Debate Topic", placeholder="Enter the topic of the debate") | |
| position = gr.Radio(["For", "Against"], label="Position", info="LLM's debate stance") | |
| chatbot = gr.Chatbot(height=500) | |
| debate_interface = gr.ChatInterface(debate_respond, | |
| chatbot=chatbot, | |
| examples=[ | |
| "Why do you support this stance?", | |
| "Can you refute the opposing view on this topic?", | |
| "What evidence supports your position?" | |
| ] | |
| ) | |
| gr.HTML("<footer><p>LLM Debate Participant © 2024</p></footer>") | |
| if __name__ == "__main__": | |
| demo.launch(share=True) | |