import gradio as gr
from gradio_leaderboard import Leaderboard
import config
from pathlib import Path
import pandas as pd

abs_path = Path(__file__).parent

df = pd.read_json(str(abs_path / "leaderboard_data.json"))

# Make a model size column
numeric_interval = pd.IntervalIndex(
    sorted([config.NUMERIC_INTERVALS[s] for s in config.NUMERIC_INTERVALS.keys()])
)
params_column = pd.to_numeric(df["#Params (B)"], errors="coerce")
df["Model Size"] = params_column.apply(lambda x: next(s for s in numeric_interval if x in s))


with gr.Blocks() as demo:
    gr.Markdown("""
    # 🥇 Leaderboard Component
    """)
    Leaderboard(value=df,
                allow_column_select=True,
                on_load_columns=config.ON_LOAD_COLUMNS,
                search_column="model_name_for_query",
                hide_columns=["model_name_for_query", "Model Size"],
                filter_columns=config.FILTER_COLUMNS,
                datatype=config.TYPES,
                column_widths=["2%", "33%"])

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