"""
Download LAION-Aesthetics dataset (aesthetic score >= 6.0).
High-quality images with captions, suitable for Flux fine-tuning.
Uses img2dataset for fast parallel downloading.
"""
import subprocess
import argparse
from pathlib import Path

OUTPUT_DIR = Path("/home/adminuser/chungcat/data/raw/laion")
PARQUET_DIR = Path("/home/adminuser/chungcat/data/raw/laion_meta")


def download_metadata():
    """Download LAION-Aesthetics v2 6+ metadata (parquet files with URLs + captions)."""
    PARQUET_DIR.mkdir(parents=True, exist_ok=True)

    print("Downloading LAION-Aesthetics v2 6+ metadata...")
    # This subset contains ~600K images with aesthetic score >= 6.0
    url = "https://huggingface.co/datasets/laion/laion2B-en-aesthetic/resolve/main"

    subprocess.run([
        "pip3", "install", "huggingface_hub[cli]"
    ], capture_output=True)

    subprocess.run([
        "python3", "-c", f"""
from huggingface_hub import snapshot_download
snapshot_download(
    repo_id="laion/laion2B-en-aesthetic",
    repo_type="dataset",
    local_dir="{PARQUET_DIR}",
    allow_patterns=["*.parquet"],
    max_workers=8,
)
print("Metadata download complete!")
"""
    ], check=True)


def download_images(num_images=1000000, resolution=1024, workers=64):
    """Download images using img2dataset from parquet metadata."""
    OUTPUT_DIR.mkdir(parents=True, exist_ok=True)

    parquet_files = list(PARQUET_DIR.glob("**/*.parquet"))
    if not parquet_files:
        print("No parquet files found. Run with --download-meta first.")
        return

    print(f"Found {len(parquet_files)} parquet files")
    print(f"Downloading up to {num_images} images at {resolution}px...")

    # img2dataset handles parallel download, resize, and WebDataset output
    cmd = [
        "img2dataset",
        "--url_list", str(parquet_files[0]),
        "--input_format", "parquet",
        "--url_col", "URL",
        "--caption_col", "TEXT",
        "--output_format", "webdataset",
        "--output_folder", str(OUTPUT_DIR),
        "--processes_count", str(workers),
        "--thread_count", "128",
        "--image_size", str(resolution),
        "--resize_mode", "center_crop",
        "--resize_only_if_bigger", "True",
        "--enable_wandb", "False",
        "--number_sample_per_shard", "1000",
        "--save_additional_columns", '["AESTHETIC_SCORE","WIDTH","HEIGHT"]',
        "--max_shard_retry", "3",
    ]

    if num_images:
        cmd.extend(["--max_shard_retry", "3"])

    print(f"Running: {' '.join(cmd)}")
    subprocess.run(cmd, check=True)
    print("Download complete!")


def download_images_multi(num_workers=64, resolution=1024):
    """Download from all parquet files."""
    OUTPUT_DIR.mkdir(parents=True, exist_ok=True)

    parquet_files = sorted(PARQUET_DIR.glob("**/*.parquet"))
    if not parquet_files:
        print("No parquet files found. Run with --download-meta first.")
        return

    print(f"Found {len(parquet_files)} parquet files")

    for i, pf in enumerate(parquet_files):
        shard_output = OUTPUT_DIR / f"shard_{i:04d}"
        shard_output.mkdir(parents=True, exist_ok=True)

        print(f"\n[{i+1}/{len(parquet_files)}] Processing {pf.name}...")

        cmd = [
            "img2dataset",
            "--url_list", str(pf),
            "--input_format", "parquet",
            "--url_col", "URL",
            "--caption_col", "TEXT",
            "--output_format", "webdataset",
            "--output_folder", str(shard_output),
            "--processes_count", str(num_workers),
            "--thread_count", "128",
            "--image_size", str(resolution),
            "--resize_mode", "center_crop",
            "--resize_only_if_bigger", "True",
            "--enable_wandb", "False",
            "--number_sample_per_shard", "1000",
            "--save_additional_columns", '["AESTHETIC_SCORE","WIDTH","HEIGHT"]',
        ]

        try:
            subprocess.run(cmd, check=True)
        except subprocess.CalledProcessError as e:
            print(f"Error on {pf.name}: {e}")
            continue

    print("\nAll shards downloaded!")


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Download LAION-Aesthetics dataset")
    parser.add_argument("--download-meta", action="store_true", help="Download metadata parquet files")
    parser.add_argument("--download-images", action="store_true", help="Download images from first parquet")
    parser.add_argument("--download-all", action="store_true", help="Download from all parquet files")
    parser.add_argument("--resolution", type=int, default=1024)
    parser.add_argument("--workers", type=int, default=64)
    parser.add_argument("--max-images", type=int, default=1000000)
    args = parser.parse_args()

    if args.download_meta:
        download_metadata()
    elif args.download_images:
        download_images(args.max_images, args.resolution, args.workers)
    elif args.download_all:
        download_images_multi(args.workers, args.resolution)
    else:
        print("Specify --download-meta, --download-images, or --download-all")
        print("\nWorkflow:")
        print("  1. python3 download_laion.py --download-meta")
        print("  2. python3 download_laion.py --download-images --max-images 1000000")
        print("  Or: python3 download_laion.py --download-all")