#!/usr/bin/env python3
"""Load every unified action22/state23 episode using unmodified official LeRobot."""
import argparse
import json
import os
from pathlib import Path


def collection_root(root, name="all"):
    # Historical CLI alias selects the same full set; it never creates a subset.
    if name == "main":
        name = "all"
    root = Path(root).resolve()
    registry = json.loads((root / "meta/collections.json").read_text())
    if registry.get("default_collection") != "all" or [r["name"] for r in registry["collections"]] != ["all"]:
        raise ValueError("This loader requires the single unified all collection")
    row = next((r for r in registry["collections"] if r["name"] == name), None)
    if row is None:
        raise ValueError(f"Unknown collection {name}; available: {[r['name'] for r in registry['collections']]}")
    rel = Path(row["root"])
    if rel.is_absolute() or ".." in rel.parts:
        raise ValueError("Collection root must stay inside the extracted dataset")
    target = (root / rel).resolve()
    if not target.is_relative_to(root):
        raise ValueError("Collection root escapes dataset")
    return target


def load_collection(root, name="all", episodes=None, cache_dir=None):
    os.environ["HF_HUB_OFFLINE"] = "1"
    os.environ["HF_DATASETS_OFFLINE"] = "1"
    os.environ["TOKENIZERS_PARALLELISM"] = "false"
    if cache_dir is not None:
        os.environ["HF_DATASETS_CACHE"] = str(Path(cache_dir).resolve())
    from lerobot.datasets.lerobot_dataset import LeRobotDataset
    return LeRobotDataset(
        repo_id=f"local/robotagentbench-{name}", root=collection_root(root, name), episodes=episodes,
        download_videos=False, video_backend="pyav", tolerance_s=0.0003,
    )


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("--root", type=Path, required=True, help="Extracted dataset directory containing meta/collections.json")
    parser.add_argument("--collection", default="all")
    parser.add_argument("--episode", type=int, default=0)
    parser.add_argument("--frame", type=int, default=0)
    parser.add_argument("--cache-dir", type=Path)
    args = parser.parse_args()
    dataset = load_collection(args.root, args.collection, [args.episode], args.cache_dir)
    sample = dataset[args.frame]
    print(json.dumps({"root": str(collection_root(args.root, args.collection)), "collection": args.collection,
                      "selected_episode": args.episode, "selected_episode_frames": len(dataset),
                      "task": sample.get("task"),
                      "sample_shapes": {k: list(v.shape) for k, v in sample.items() if hasattr(v, "shape")}}, indent=2))