import gradio as gr
import pandas as pd
import os
from huggingface_hub import snapshot_download

# clone / pull the lmeh eval data
TOKEN = os.environ.get("TOKEN", None)
RESULTS_REPO = f"lukecq/SeaExam-results"
CACHE_PATH=os.getenv("HF_HOME", ".")
EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results")
print(EVAL_RESULTS_PATH)
snapshot_download(
    repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", 
    token=TOKEN
)

# Load the CSV file
def load_csv(file_path):
    data = pd.read_csv(file_path)
    return data

# Example path to your CSV file
csv_path = f'{EVAL_RESULTS_PATH}/SeaExam_results_0419.csv'
data = load_csv(csv_path)

def show_data():
    return data

iface = gr.Interface(fn=show_data, inputs = None, outputs="dataframe", title="SeaExam Leaderboard", 
                     description="Leaderboard for the SeaExam competition.")
iface.launch()