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)