import pickle
import datasets
from renumics import spotlight
import os
import pandas as pd

if __name__ == "__main__":
    cache_file = "dataset_cache.parquet"
    cache_file_enrichment="cifar100-enrichment-cv.parquet"
    cache_file_issues="sliceguard-issues.pkl"
    
    if os.path.exists(cache_file):
        # Load dataset from cache
        df = pd.read_parquet(cache_file) 
        print("Dataset loaded from cache.")
    else:
        # Load dataset using datasets.load_dataset()
        dataset = datasets.load_dataset("renumics/cifar100-enriched", split="test")
        print("Dataset loaded using datasets.load_dataset().")
        
        df = dataset.to_pandas()  

        # Save dataset to cache
        df.to_parquet(cache_file)

        print("Dataset saved to cache.")
    
    df_cv=pd.read_parquet(cache_file_enrichment) 
    
    df = pd.concat([df, df_cv], axis=1)
     
    with open(cache_file_issues, "rb") as issue_file:
        issues = pickle.load(issue_file)

    #df = dataset.to_pandas()
    df_show = df.drop(columns=['embedding', 'probabilities'])
    while True:
        view = spotlight.show(df_show, issues=issues, port=7860, host="0.0.0.0", layout="sliceguard-layout.json",
                    dtype={"image": spotlight.Image, "embedding_reduced": spotlight.Embedding}, allow_filebrowsing=False)
        view.close()