import gradio as gr
import pandas as pd

data = {
    "Model": [
        "MiniGPT-5", "EMU-2", "GILL", "Anole",
        "GPT-4o - Openjourney", "GPT-4o - SD-3", "GPT-4o - SD-XL", "GPT-4o - Flux",
        "Gemini-1.5 - Openjourney", "Gemini-1.5 - SD-3", "Gemini-1.5 - SD-XL", "Gemini-1.5 - Flux",
        "LLAVA-34b - Openjourney", "LLAVA-34b - SD-3", "LLAVA-34b - SD-XL", "LLAVA-34b - Flux",
        "Qwen-VL-70b - Openjourney", "Qwen-VL-70b - SD-3", "Qwen-VL-70b - SD-XL", "Qwen-VL-70b - Flux"
    ],
    "Situational analysis": [
        47.63, 39.65, 46.72, 48.95,
        53.05, 53.00, 56.12, 54.97,
        48.08, 47.48, 49.43, 47.07,
        54.12, 54.72, 55.97, 54.23,
        52.73, 54.98, 52.58, 54.23
    ],
    "Project-based learning": [
        55.12, 46.12, 57.57, 59.05,
        71.40, 71.20, 73.25, 68.80,
        67.93, 68.70, 71.85, 68.33,
        73.47, 72.55, 74.60, 71.32,
        71.63, 71.87, 73.57, 69.47
    ],
    "Multi-step reasoning": [
        42.17, 50.75, 39.33, 51.72,
        53.67, 53.67, 53.67, 53.67,
        60.05, 60.05, 60.05, 60.05,
        47.28, 47.28, 47.28, 47.28,
        55.63, 55.63, 55.63, 55.63
    ],
    "AVG": [
        50.92, 45.33, 51.58, 55.22,
        63.65, 63.52, 65.47, 62.63,
        61.57, 61.87, 64.15, 61.55,
        63.93, 63.57, 65.05, 62.73,
        64.05, 64.75, 65.12, 63.18
    ]
}


df = pd.DataFrame(data)

def leaderboard():
    return df

interface = gr.Interface(fn=leaderboard, inputs=[], outputs=gr.Dataframe())

interface.launch()