# modules/storage.py
import os
import urllib.parse
import tempfile
import shutil
from huggingface_hub import login, upload_folder
from modules.constants import HF_API_TOKEN, upload_file_types, model_extensions, image_extensions

def upload_files_to_repo(files, repo_id, folder_name, create_permalink=False, repo_type="dataset"):
    """
    Uploads multiple files to a Hugging Face repository using a batch upload approach via upload_folder.

    Parameters:
        files (list): A list of file paths (str) to upload.
        repo_id (str): The repository ID on Hugging Face for storage, e.g. "Surn/Storage".
        folder_name (str): The subfolder within the repository where files will be saved.
        create_permalink (bool): If True and if exactly three files are uploaded (1 model and 2 images),
                                 returns a single permalink to the project with query parameters.
                                 Otherwise, returns individual permalinks for each file.
        repo_type (str): Repository type ("space", "dataset", etc.). Default is "dataset".

    Returns:
        If create_permalink is True and files match the criteria:
            tuple: (response, permalink) where response is the output of the batch upload
                   and permalink is the URL string (with fully qualified file paths) for the project.
        Otherwise:
            list: A list of tuples (response, permalink) for each file.
    """
    # Log in using the HF API token.
    login(token=HF_API_TOKEN)
    
    valid_files = []
    
    # Ensure folder_name does not have a trailing slash.
    folder_name = folder_name.rstrip("/")
    
    # Filter for valid files based on allowed extensions.
    for f in files:
        file_name = f if isinstance(f, str) else f.name if hasattr(f, "name") else None
        if file_name is None:
            continue
        ext = os.path.splitext(file_name)[1].lower()
        if ext in upload_file_types:
            valid_files.append(f)
    
    if not valid_files:
        return []  # or raise an exception
    
    # Create a temporary directory and a sub-directory using folder_name; copy valid files into it.
    with tempfile.TemporaryDirectory() as temp_dir:
        target_dir = os.path.join(temp_dir, folder_name)
        os.makedirs(target_dir, exist_ok=True)
        for file_path in valid_files:
            filename = os.path.basename(file_path)
            dest_path = os.path.join(target_dir, filename)
            shutil.copy(file_path, dest_path)
        
        # Batch upload all files in the temporary folder.
        # Files will be uploaded under the folder (path_in_repo) given by folder_name.
        response = upload_folder(
            folder_path=temp_dir,
            repo_id=repo_id,
            repo_type=repo_type,
            path_in_repo=folder_name,
            commit_message="Batch upload files"
        )
    
    # Construct external URLs for each uploaded file.
    # For datasets, files are served at:
    # https://huggingface.co/datasets/<repo_id>/resolve/main/<folder_name>/<filename>
    base_url_external = f"https://huggingface.co/datasets/{repo_id}/resolve/main/{folder_name}"
    individual_links = []
    for file_path in valid_files:
        filename = os.path.basename(file_path)
        link = f"{base_url_external}/{filename}"
        individual_links.append(link)
    
    # If exactly 3 files are provided and create_permalink is True,
    # check if they contain 1 model file and 2 image files.
    if create_permalink and len(valid_files) == 3:
        model_link = None
        images_links = []
        for f in valid_files:
            filename = os.path.basename(f)
            ext = os.path.splitext(filename)[1].lower()
            if ext in model_extensions:
                if model_link is None:
                    model_link = f"{base_url_external}/{filename}"
            elif ext in image_extensions:
                images_links.append(f"{base_url_external}/{filename}")
        if model_link and len(images_links) == 2:
            # Construct a permalink to the viewer project with querystring parameters.
            base_viewer_url = "https://huggingface.co/spaces/Surn/3D-Viewer"
            params = {"3d": model_link, "hm": images_links[0], "image": images_links[1]}
            query_str = urllib.parse.urlencode(params)
            permalink = f"{base_viewer_url}?{query_str}"
            return response, permalink

    # Otherwise, return individual tuples for each file.
    return [(response, link) for link in individual_links]