#!/usr/bin/env python3
"""
Upload the prepared `data/` folder to a Hugging Face repo under the `data/` path.

Usage:
  # interactive login (recommended)
  huggingface-cli login
  python3 scripts/upload_to_hf.py --repo Aybee5/ha-tts-mixed

  # or provide token via env var HUGGINGFACE_HUB_TOKEN
  HUGGINGFACE_HUB_TOKEN=... python3 scripts/upload_to_hf.py --repo Aybee5/ha-tts-mixed

This will use `huggingface_hub.upload_folder` to upload `data/` content to the repo under the `data/` folder.
"""
import os
import argparse
from huggingface_hub import upload_folder, HfApi


def main():
    parser = argparse.ArgumentParser()
    parser.add_argument("--repo", required=True, help="Repo id, e.g. username/repo")
    parser.add_argument("--path-in-repo", default="data", help="Destination path inside the repo")
    parser.add_argument("--local-folder", default="data", help="Local folder to upload")
    parser.add_argument("--token", default=None, help="HF token (optional; can be provided via HUGGINGFACE_HUB_TOKEN env var or huggingface-cli login)")
    args = parser.parse_args()

    token = args.token or os.environ.get("HUGGINGFACE_HUB_TOKEN")

    print(f"Uploading local folder '{args.local_folder}' to repo '{args.repo}' at path '{args.path_in_repo}'")

    api = HfApi()
    # Ensure repo exists or will error
    try:
        upload_folder(
            folder_path=args.local_folder,
            repo_id=args.repo,
            path_in_repo=args.path_in_repo,
            token=token,
            repo_type="dataset",
            # allow large uploads; may still be subject to HF limits
            max_workers=8,
        )
    except Exception as e:
        print(f"Upload failed: {e}")


if __name__ == "__main__":
    main()