import gradio as gr
import pandas as pd
import numpy as np

# Create a sample dataframe with 10 language models and 57 attributes
np.random.seed(0)
data = pd.DataFrame(np.random.rand(10, 57), 
                    columns=[f'Attribute_{i+1}' for i in range(57)],
                    index=[f'Model_{i+1}' for i in range(10)])

# Let's consider the first attribute as the main one for sorting the leaderboard
data = data.sort_values('Attribute_1', ascending=False)

def show_leaderboard():
    # Convert dataframe to html so that it can be displayed properly in Gradio
    return data.to_html()

iface = gr.Interface(fn=show_leaderboard, inputs=[], outputs="html")

# Run the interface. 
# Note: you don't need to use .launch() in Hugging Face Spaces, this is for local testing.
iface.launch()