from huggingface_hub import hf_hub_download, snapshot_download
import pandas as pd
import importlib
import importlib.util
import streamlit as st
import sys
import os
from pathlib import Path

PRIVATE_SPACE_NAME = os.getenv("PRIVATE_SPACE_NAME")
 = os.getenv("USER_NAME")

REPO_ID = USER_NAME  + "/" + PRIVATE_SPACE_NAME
REPO_TYPE = "space"

# def setup_cache_directory():
#     """Set up and return cache directory for private space files"""
#     cache_dir = Path("private_space_cache")
#     cache_dir.mkdir(exist_ok=True)
#     return cache_dir

# def download_private_assets(cache_dir):
#     """Download necessary files from private space"""
#     try:
#         snapshot_download(
#             repo_id=REPO_ID,
#             repo_type=REPO_TYPE,
#             local_dir=cache_dir,
#         )
#         return True
#     except Exception as e:
#         print(f"Error downloading private assets: {str(e)}")
#         return False

# # Setup cache directory and download assets
# cache_dir = setup_cache_directory()
# download_private_assets(cache_dir)

# Download the entire space (optional, if needed)
repo_dir = snapshot_download(
    repo_id=REPO_ID,
    repo_type=REPO_TYPE,
    cache_dir="private_space_cache"
)

# Add repo directory to sys.path so Python can find modules inside it
sys.path.append(repo_dir)



# Download specific files (if snapshot_download wasn't used)
app_path = hf_hub_download(
    repo_id=REPO_ID,
    filename="app.py",
    repo_type=REPO_TYPE
)

# Load and execute `app.py`
spec_app = importlib.util.spec_from_file_location("app", app_path)
app_module = importlib.util.module_from_spec(spec_app)
spec_app.loader.exec_module(app_module)

# Now you can use functions from utils_module
result = app_module.main()