app.py

import os
import gradio as gr
from huggingface_hub import login, InferenceClient
import spaces

# Authenticate with Hugging Face API key
api_key = os.getenv("LLAMA")
login(api_key)

# Initialize InferenceClients for multiple models
client1 = InferenceClient("meta-llama/Llama-3.1-70B-Instruct")
client2 = InferenceClient("bigscience/bloom")

@spaces.GPU
def compare_models(
    message,
    history: list[dict],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    # Start with the system message
    messages = [{"role": "system", "content": system_message}]
    messages += history  # Add conversation history
    messages.append({"role": "user", "content": message})  # Add user message

    # Fetch responses from both models
    response1 = ""
    response2 = ""

    # Stream responses for Model 1
    for message in client1.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content
        response1 += token

    # Stream responses for Model 2
    for message in client2.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content
        response2 += token

    # Return responses side-by-side
    return response1, response2

def handle_vote(vote, current_votes):
    """Handle user votes."""
    current_votes[vote] += 1
    return f"Model 1: {current_votes['model1']} votes | Model 2: {current_votes['model2']} votes"

# Initialize voting state
votes = {"model1": 0, "model2": 0}

# Create Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# AI Model Comparison Tool")
    with gr.Row():
        system_message = gr.Textbox(
            value="You are a helpful assistant specializing in tech-related topics.",
            label="System message",
        )
        max_tokens = gr.Slider(
            minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"
        )
        temperature = gr.Slider(
            minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"
        )
        top_p = gr.Slider(
            minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p"
        )

    with gr.Row():
        message = gr.Textbox(label="Enter your message")

    compare_btn = gr.Button("Compare Models")

    with gr.Row():
        response1 = gr.Textbox(label="Response from Model 1")
        response2 = gr.Textbox(label="Response from Model 2")

    with gr.Row():
        vote_model1 = gr.Button("Vote for Model 1")
        vote_model2 = gr.Button("Vote for Model 2")

    vote_status = gr.Textbox(
        value=f"Model 1: {votes['model1']} votes | Model 2: {votes['model2']} votes",
        label="Voting Results",
    )

    # Link components
    compare_btn.click(
        compare_models,
        inputs=[message, [], system_message, max_tokens, temperature, top_p],
        outputs=[response1, response2],
    )

    vote_model1.click(
        handle_vote,
        inputs=["model1", votes],
        outputs=vote_status,
    )

    vote_model2.click(
        handle_vote,
        inputs=["model2", votes],
        outputs=vote_status,
    )

if __name__ == "__main__":
    demo.launch()