import os
import json
import pandas as pd
from huggingface_hub import list_repo_files, hf_hub_download

def load_data(file_path):
    """Load data based on file extension"""
    ext = os.path.splitext(file_path)[1].lower()
    if ext == '.json':
        with open(file_path, 'r', encoding='utf-8') as f:
            return json.load(f)
    elif ext == '.csv':
        return pd.read_csv(file_path)
    elif ext == '.jsonl':
        data = []
        with open(file_path, 'r', encoding='utf-8') as f:
            for line in f:
                data.append(json.loads(line))
        return data
    elif ext == '.parquet':
        return pd.read_parquet(file_path)
    else:
        raise ValueError(f"Unsupported file extension: {ext}")

def download_and_load_datasets():
    repo_id = "Antislab/LLM4PH"
    files = list_repo_files(repo_id=repo_id, repo_type="dataset")
    
    downloaded_files = []
    for file in files:
        if file.startswith("datasets/"):
            local_path = os.path.join(".", file)
            if not os.path.exists(local_path):
                print(f"Downloading {file}...")
                hf_hub_download(
                    repo_id=repo_id,
                    filename=file,
                    repo_type="dataset",
                    local_dir="."
                )
            else:
                print(f"File {file} already exists, skipping download.")
            downloaded_files.append(local_path)
    
    # Load all downloaded files
    loaded_data = {}
    for file_path in downloaded_files:
        try:
            loaded_data[file_path] = load_data(file_path)
            print(f"Successfully loaded {file_path}")
        except Exception as e:
            print(f"Error loading {file_path}: {str(e)}")
    
    return loaded_data

if __name__ == "__main__":
    data = download_and_load_datasets()