app.py

import gradio as gr
from apscheduler.schedulers.background import BackgroundScheduler
from huggingface_hub import snapshot_download

from src.about import (
    CITATION_BUTTON_LABEL,
    CITATION_BUTTON_TEXT,
    INTRODUCTION_TEXT,
    LLM_BENCHMARKS_TEXT,
    TITLE,
    SUBMIT_TEXT
)
from src.display.css_html_js import custom_css
from src.display.utils import (
    BENCHMARK_COLS,
    COLS,
    AutoEvalColumn,
    fields,
)
from src.envs import API, EVAL_RESULTS_PATH, REPO_ID, RESULTS_REPO, TOKEN
from src.populate import get_leaderboard_df


def restart_space():
    API.restart_space(repo_id=REPO_ID)

### Space initialisation
try:
    snapshot_download(
        repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN
    )
except Exception:
    restart_space()


LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, COLS, BENCHMARK_COLS)

def init_leaderboard(dataframe, css):
    if dataframe is None or dataframe.empty:
        raise ValueError("Leaderboard DataFrame is empty or None.")
    
    with gr.Blocks(css=css) as app:
        # Title
        gr.Markdown("# Leaderboard")

        # Select Columns - Full width, as CheckboxGroup
        select_columns = gr.CheckboxGroup(
            label="Select Columns to Display:",
            choices=[c.name for c in fields(AutoEvalColumn)],
            value=[c.name for c in fields(AutoEvalColumn) if c.displayed_by_default],
            elem_id="select-columns"
        )

        # Search Columns - Full width
        search_columns = gr.Textbox(
            label="Search",
            placeholder=f"Search in {', '.join([AutoEvalColumn.model_name.name])}...",
            lines=1,
            elem_id="search-columns"
        )

        # Initialize DataFrame with only default-selected columns
        default_columns = [c.name for c in fields(AutoEvalColumn) if c.displayed_by_default]
        initial_dataframe = dataframe[default_columns].copy()

        # Leaderboard Component
        leaderboard = gr.Dataframe(
            value=initial_dataframe,
            datatype=[c.type for c in fields(AutoEvalColumn) if c.name in default_columns],
            headers=default_columns,
            wrap=True,
            interactive=False,
            max_height=800
        )

        # Update function
        def update_leaderboard(search, selected_cols):
            df = dataframe.copy()
            # Apply search
            if search:
                df = df[df[AutoEvalColumn.model_name.name].str.contains(search, case=False, na=False)]
            # Filter columns to display
            visible_cols = [col for col in selected_cols if col in df.columns]
            df = df[visible_cols]
            return df

        # Connect inputs to update leaderboard
        search_columns.change(
            fn=update_leaderboard,
            inputs=[search_columns, select_columns],
            outputs=leaderboard
        )
        select_columns.change(
            fn=update_leaderboard,
            inputs=[search_columns, select_columns],
            outputs=leaderboard
        )

    return app


demo = gr.Blocks(fill_height=False, css=custom_css)
with demo:
    gr.HTML(TITLE)
    gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")

    with gr.Tabs(elem_classes="tab-buttons") as tabs:
        with gr.TabItem("🏅 LLM Benchmark", elem_id="llm-benchmark-tab-table", id=0):
            leaderboard = init_leaderboard(LEADERBOARD_DF, css=custom_css)

        with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=2):
            gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")

        with gr.TabItem("🚀 Submit here! ", elem_id="llm-benchmark-tab-table", id=3):
            with gr.Row():
                gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")

            with gr.Row():
                gr.Markdown(SUBMIT_TEXT, elem_classes="markdown-text")

    with gr.Row():
        with gr.Accordion("📙 Citation", open=True):
            citation_button = gr.Textbox(
                value=CITATION_BUTTON_TEXT,
                label=CITATION_BUTTON_LABEL,
                lines=10,
                elem_id="citation-button",
                show_copy_button=True,
            )

scheduler = BackgroundScheduler()
scheduler.add_job(restart_space, "interval", seconds=1800)
scheduler.start()
demo.queue(default_concurrency_limit=40).launch()