runpod-ready/scripts/sync_hf.py

#!/usr/bin/env python3
"""Sync datasets and model artifacts with Hugging Face Hub."""

from __future__ import annotations

import argparse
import os
from pathlib import Path

ROOT = Path(__file__).resolve().parents[1]


def require_hf() -> None:
    try:
        import huggingface_hub  # noqa: F401
    except ImportError as exc:
        raise SystemExit("Install huggingface_hub: pip install huggingface_hub") from exc


def hf_token() -> str | None:
    return os.environ.get("HF_TOKEN") or os.environ.get("HUGGING_FACE_HUB_TOKEN")


def upload_dataset(repo_id: str, folder: Path, private: bool) -> None:
    from huggingface_hub import HfApi

    api = HfApi(token=hf_token())
    api.create_repo(repo_id=repo_id, repo_type="dataset", exist_ok=True, private=private)
    api.upload_folder(
        folder_path=str(folder),
        repo_id=repo_id,
        repo_type="dataset",
        commit_message="Scriptwriter dataset sync",
    )
    visibility = "private" if private else "public"
    print(f"Dataset uploaded ({visibility}): https://huggingface.co/datasets/{repo_id}")


def download_dataset(repo_id: str, folder: Path) -> None:
    from huggingface_hub import snapshot_download

    folder.mkdir(parents=True, exist_ok=True)
    snapshot_download(
        repo_id=repo_id,
        repo_type="dataset",
        local_dir=str(folder),
        token=hf_token(),
    )
    print(f"Dataset downloaded to {folder}")


def upload_model(repo_id: str, folder: Path, private: bool) -> None:
    from huggingface_hub import HfApi

    api = HfApi(token=hf_token())
    api.create_repo(repo_id=repo_id, repo_type="model", exist_ok=True, private=private)
    api.upload_folder(
        folder_path=str(folder),
        repo_id=repo_id,
        repo_type="model",
        commit_message="Scriptwriter LoRA adapter sync",
    )
    visibility = "private" if private else "public"
    print(f"Model uploaded ({visibility}): https://huggingface.co/models/{repo_id}")


def download_model(repo_id: str, folder: Path) -> None:
    from huggingface_hub import snapshot_download

    folder.mkdir(parents=True, exist_ok=True)
    snapshot_download(
        repo_id=repo_id,
        repo_type="model",
        local_dir=str(folder),
        token=hf_token(),
    )
    print(f"Model downloaded to {folder}")


def main() -> None:
    parser = argparse.ArgumentParser(description="Sync scriptwriter artifacts with HF Hub")
    sub = parser.add_subparsers(dest="cmd", required=True)

    up_ds = sub.add_parser("upload-dataset")
    up_ds.add_argument("--repo", default=os.environ.get("HF_DATASET_REPO", ""))
    up_ds.add_argument("--folder", type=Path, default=ROOT / "data" / "processed")
    up_ds.add_argument("--public", action="store_true", help="Upload as public (default: private)")

    down_ds = sub.add_parser("download-dataset")
    down_ds.add_argument("--repo", default=os.environ.get("HF_DATASET_REPO", ""))
    down_ds.add_argument("--folder", type=Path, default=ROOT / "data" / "processed")

    up_m = sub.add_parser("upload-model")
    up_m.add_argument("--repo", default=os.environ.get("HF_MODEL_REPO", ""))
    up_m.add_argument("--folder", type=Path, default=ROOT / "models" / "lora")
    up_m.add_argument("--public", action="store_true", help="Upload as public (default: private)")

    down_m = sub.add_parser("download-model")
    down_m.add_argument("--repo", default=os.environ.get("HF_MODEL_REPO", ""))
    down_m.add_argument("--folder", type=Path, default=ROOT / "models" / "lora")

    args = parser.parse_args()
    require_hf()

    if args.cmd == "upload-dataset":
        if not args.repo:
            raise SystemExit("Set --repo or HF_DATASET_REPO")
        upload_dataset(args.repo, args.folder, private=not args.public)
    elif args.cmd == "download-dataset":
        if not args.repo:
            raise SystemExit("Set --repo or HF_DATASET_REPO")
        download_dataset(args.repo, args.folder)
    elif args.cmd == "upload-model":
        if not args.repo:
            raise SystemExit("Set --repo or HF_MODEL_REPO")
        upload_model(args.repo, args.folder, private=not args.public)
    elif args.cmd == "download-model":
        if not args.repo:
            raise SystemExit("Set --repo or HF_MODEL_REPO")
        download_model(args.repo, args.folder)


if __name__ == "__main__":
    main()