leaderboard_tab.py

import gradio as gr
from fuzzywuzzy import fuzz

from utils import submit_gradio_module


def search_leaderboard(df, model_name, columns_to_show, threshold=95):
    """
    Search the leaderboard for models matching the search term using fuzzy matching.

    Args:
        df: The dataframe containing all leaderboard data
        model_name: The search term to find models
        columns_to_show: List of columns to include in the result
        threshold: Minimum similarity threshold (default: 95)

    Returns:
        Filtered dataframe with only matching models and selected columns
    """
    if not model_name.strip():
        return df.loc[:, columns_to_show]
    search_name = model_name.lower()  # compute once for efficiency

    def calculate_similarity(row):
        return fuzz.partial_ratio(search_name, row["Model"].lower())

    filtered_df = df.copy()
    filtered_df["similarity"] = filtered_df.apply(calculate_similarity, axis=1)
    filtered_df = filtered_df[filtered_df["similarity"] >= threshold].sort_values(
        "similarity", ascending=False
    )
    filtered_df = filtered_df.drop("similarity", axis=1).loc[:, columns_to_show]
    return filtered_df


def update_columns_to_show(df, columns_to_show):
    """
    Update the displayed columns in the dataframe.

    Args:
        df: The dataframe to update
        columns_to_show: List of columns to include

    Returns:
        gradio.update object with the updated dataframe
    """
    dummy_df = df.loc[:, [col for col in df.columns if col in columns_to_show]]
    columns_widths = []
    for col in dummy_df.columns:
        if col == "Rank":
            columns_widths.append(80)
        elif col == "Model":
            columns_widths.append(400)
        else:
            columns_widths.append(150)
    return gr.update(value=dummy_df, column_widths=columns_widths)


def create_leaderboard_tab(
    df,
    initial_columns_to_show,
    search_function,
    update_function,
    about_section,
    task_type,
    model_param_limit=2000,
):
    """
    Create a complete leaderboard tab with search, column selection, and data display.

    Args:
        df: The dataframe containing the leaderboard data
        initial_columns_to_show: Initial list of columns to display
        search_function: Function to handle searching
        update_function: Function to handle column updates
        about_section: Markdown text for the About tab
        task_type: Type of the task ("Retriever" or "Reranker")

    Returns:
        A gradio Tabs component with the complete leaderboard interface
    """
    columns_widths = [
        80 if col == "Rank" else 400 if col == "Model" else 150
        for col in initial_columns_to_show
    ]

    with gr.Tabs() as tabs:
        with gr.Tab("👑 Leaderboard"):
            with gr.Column():
                with gr.Row(equal_height=True):
                    search_box = gr.Textbox(
                        placeholder="Search for models...",
                        label="Search (You can also press Enter to search)",
                        scale=5,
                    )
                    search_button = gr.Button(
                        value="Search", variant="primary", scale=1
                    )
                columns_to_show_input = gr.CheckboxGroup(
                    label="Columns to Show",
                    choices=df.columns.tolist(),
                    value=initial_columns_to_show,
                    scale=4,
                )

            leaderboard = gr.Dataframe(
                value=df.loc[:, initial_columns_to_show],
                datatype="markdown",
                wrap=True,
                show_fullscreen_button=True,
                interactive=False,
                column_widths=columns_widths,
            )

            # Connect events
            search_box.submit(
                search_function,
                inputs=[search_box, columns_to_show_input],
                outputs=leaderboard,
            )
            columns_to_show_input.select(
                update_function, inputs=columns_to_show_input, outputs=leaderboard
            )
            search_button.click(
                search_function,
                inputs=[search_box, columns_to_show_input],
                outputs=leaderboard,
            )

        with gr.Tab("🏵️ Submit"):
            submit_gradio_module(task_type, model_param_limit=model_param_limit)

        with gr.Tab("ℹ️ About"):
            gr.Markdown(about_section)

    return tabs