compare_gradio.py

import json
import logging
import os
import threading
import time
import uuid
import datetime
import gradio as gr
import huggingface_hub
import requests
import random
from functools import partial

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)


# API configuration
API_URL = os.getenv("API_URL")
API_KEY = os.getenv("API_KEY")

auth_token = os.environ.get("TOKEN") or True
hf_repo = "Iker/Feedback_FactCheking"
huggingface_hub.create_repo(
    repo_id=hf_repo,
    repo_type="dataset",
    token=auth_token,
    exist_ok=True,
    private=True,
)


headers = {"X-API-Key": API_KEY, "Content-Type": "application/json"}


def update_models():
    models = random.sample(["pro", "pro2", "turbo", "turbo2"], 2)
    print(f"Models updated: {models}")
    return models


# Function to submit a fact-checking request
def submit_fact_check(article_topic, config, language, location):
    endpoint = f"{API_URL}/fact-check"
    payload = {
        "article_topic": article_topic,
        "config": config,
        "language": language,
        "location": location,
    }

    response = requests.post(endpoint, json=payload, headers=headers)
    response.raise_for_status()  # Raise an exception for HTTP errors
    return response.json()["job_id"]


# Function to get the result of a fact-checking job
def get_fact_check_result(job_id):
    endpoint = f"{API_URL}/result/{job_id}"

    response = requests.get(endpoint, headers=headers)
    response.raise_for_status()  # Raise an exception for HTTP errors
    return response.json()


def fact_checking(article_topic, config):
    language = "es"
    location = "es"
    logger.info(f"Submitting fact-checking request for article: {article_topic}")
    try:
        job_id = submit_fact_check(article_topic, config, language, location)
        logger.info(f"Fact-checking job submitted. Job ID: {job_id}")

        # Poll for results
        start_time = time.time()
        while True:
            try:
                result = get_fact_check_result(job_id)
                if result["status"] == "completed":
                    logger.info("Fact-checking completed:")
                    logger.info(f"Response object: {result}")
                    logger.info(
                        f"Result: {json.dumps(result['result'], indent=4, ensure_ascii=False)}"
                    )
                    return result["result"]
                elif result["status"] == "failed":
                    logger.error("Fact-checking failed:")
                    logger.error(f"Response object: {result}")
                    logger.error(f"Error message: {result['error']}")
                    return None
                else:
                    elapsed_time = time.time() - start_time
                    logger.info(
                        f"Fact-checking in progress. Elapsed time: {elapsed_time:.2f} seconds"
                    )
                    time.sleep(2)  # Wait for 2 seconds before checking again
            except requests.exceptions.RequestException as e:
                logger.error(f"Error while polling for results: {e}")
                time.sleep(2)  # Wait before retrying

    except requests.exceptions.RequestException as e:
        logger.error(f"An error occurred while submitting the request: {e}")


def format_response(response):
    title = response["metadata"]["title"]
    main_claim = response["metadata"]["main_claim"]

    fc = response["answer"]

    rq = response["related_questions"]

    rq_block = []
    for q, a in rq.items():
        rq_block.append(f"**{q}**\n{a}")

    return f"## {title}\n\n### {main_claim}\n\n{fc}\n\n{'\n'.join(rq_block)}"


def do_both_fact_checking(msg):
    models = update_models()

    results = [None, None]
    threads = []

    def fact_checking_1_thread():
        results[0] = fact_checking(msg, config=models[0])

    def fact_checking_2_thread():
        results[1] = fact_checking(msg, config=models[1])

    # Start the threads
    thread1 = threading.Thread(target=fact_checking_1_thread)
    thread2 = threading.Thread(target=fact_checking_2_thread)
    threads.append(thread1)
    threads.append(thread2)
    thread1.start()
    thread2.start()

    # Wait for the threads to complete
    for thread in threads:
        thread.join()

    # Format the responses
    response_1 = format_response(results[0]) if results[0] else None
    response_2 = format_response(results[1]) if results[1] else None
    history_a = [(msg, response_1)]
    history_b = [(msg, response_2)]
    return ("", history_a, history_b, models)


def save_history(
    models,
    history_0,
    history_1,
    max_new_tokens=None,
    temperature=None,
    top_p=None,
    repetition_penalty=None,
    winner=None,
):
    path = f"history_{uuid.uuid4()}.json"
    path = os.path.join("data", path)
    os.makedirs("data", exist_ok=True)
    data = {
        "timestamp": datetime.datetime.now().isoformat(),
        # "models": models,
        "model_a": models[0],
        "model_b": models[1],
        "hyperparameters": {
            "max_new_tokens": max_new_tokens,
            "temperature": temperature,
            "top_p": top_p,
            "repetition_penalty": repetition_penalty,
        },
        "message": history_0[0][0],
        "fc_a": history_0[0][1],
        "fc_b": history_1[0][1],
        "winner": winner,
    }

    with open(path, "w") as f:
        json.dump(data, ensure_ascii=False, indent=4, fp=f)

    huggingface_hub.upload_file(
        repo_id=hf_repo,
        repo_type="dataset",
        token=os.environ.get("TOKEN") or True,
        path_in_repo=path,
        path_or_fileobj=path,
    )

    gr.Info("Feedback sent successfully! Thank you for your help.")


with gr.Blocks(
    theme="gradio/soft",
    fill_height=True,
    fill_width=True,
    analytics_enabled=False,
    title="Fact Cheking Demo",
    css=".center-text { text-align: center; } footer {visibility: hidden;} .avatar-container {width: 50px; height: 50px; border: none;}",
) as demo:
    gr.Markdown("# Fact Checking Arena", elem_classes="center-text")
    models = gr.State([])
    with gr.Row():
        with gr.Column():
            chatbot_a = gr.Chatbot(
                height=800,
                show_copy_all_button=True,
                avatar_images=[
                    None,
                    "https://upload.wikimedia.org/wikipedia/commons/a/ac/Green_tick.svg",
                ],
            )

        with gr.Column():
            chatbot_b = gr.Chatbot(
                show_copy_all_button=True,
                height=800,
                avatar_images=[
                    None,
                    "https://upload.wikimedia.org/wikipedia/commons/a/ac/Green_tick.svg",
                ],
            )

    msg = gr.Textbox(
        label="Introduce que quieres verificar",
        placeholder="Los coches electricos contaminan más que los coches de gasolina",
        autofocus=True,
    )

    with gr.Row():
        with gr.Column():
            left = gr.Button("👈 Derecha mejor")
        with gr.Column():
            tie = gr.Button("🤝 Iguald de buenos")
        with gr.Column():
            fail = gr.Button("👎 Igual de malos")
        with gr.Column():
            right = gr.Button("👉 Iquierda mejor")

    msg.submit(
        do_both_fact_checking,
        inputs=[
            msg,
        ],
        outputs=[msg, chatbot_a, chatbot_b, models],
    )

    left.click(
        partial(
            save_history,
            winner="model_a",
        ),
        inputs=[
            models,
            chatbot_a,
            chatbot_b,
        ],
    )

    tie.click(
        partial(
            save_history,
            winner="tie",
        ),
        inputs=[
            models,
            chatbot_a,
            chatbot_b,
        ],
    )

    fail.click(
        partial(
            save_history,
            winner="tie (both bad)",
        ),
        inputs=[
            models,
            chatbot_a,
            chatbot_b,
        ],
    )

    right.click(
        partial(
            save_history,
            winner="model_b",
        ),
        inputs=[
            models,
            chatbot_a,
            chatbot_b,
        ],
    )

    demo.load(update_models, inputs=[], outputs=[models])

demo.launch(
    server_name="0.0.0.0",
    server_port=7860,
    auth=(os.getenv("GRADIO_USERNAME"), os.getenv("GRADIO_PASSWORD")),
)