import os
from pathlib import Path

from huggingface_hub import snapshot_download


def make_env(n_envs: int = 1, use_async_envs: bool = False):
    """
    Create vectorized environments for leisaac task.

    Bi-arm direct: pick torus and cuboid into the box (2 objects).

    Args:
        n_envs: Number of parallel environments
        use_async_envs: Whether to use AsyncVectorEnv or SyncVectorEnv
            (not use now)

    Returns:
        ManagerBasedRLEnv or DirectRLEnv inherit from gym.Env implemented in IsaacLab
    """

    # Scene/robot assets live on the upstream Hub repo; materialize them next to this script so
    # thin forks (e.g. kd-forge/leisaac_env with only envs/*.py) still resolve LEISAAC_ASSETS_ROOT.
    repo_root = Path(__file__).resolve().parent.parent
    assets_root = repo_root / "assets"
    snapshot_download(
        repo_id="kd-forge/leisaac_env",
        local_dir=str(repo_root),
        allow_patterns=["assets/**"],
    )
    os.environ["LEISAAC_ASSETS_ROOT"] = str(assets_root)

    from isaaclab.app import AppLauncher

    _ = AppLauncher({"enable_cameras": True})

    from leisaac.utils.envhub_utils import export_env

    return export_env(
        "LeIsaac-SO101-CleanToyTable-2Objects-v0",
        device="cuda:0",
        num_envs=n_envs,
    )