push_to_hf.py

import os
from pathlib import Path

from huggingface_hub import HfApi, create_repo, update_repo_settings


ROOT = Path("/root/knowledgegrapheval/type_prediction_dataset")
ENV_PATHS = [
    Path("/root/knowledgegrapheval/.env"),
    Path("/root/knowledge-graph-rag/.env"),
]
REPO_ID = "U4RASD/TypePrediction"


def load_env():
    for env_path in ENV_PATHS:
        if not env_path.exists():
            continue
        for line in env_path.read_text(encoding="utf-8").splitlines():
            line = line.strip()
            if not line or line.startswith("#") or "=" not in line:
                continue
            key, value = line.split("=", 1)
            os.environ.setdefault(key.strip(), value.strip().strip('"').strip("'"))


def main():
    load_env()
    token = os.environ.get("HF_TOKEN_UNIT") or os.environ.get("HF_TOKEN")
    if not token:
        raise RuntimeError("Missing HF token.")

    create_repo(
        repo_id=REPO_ID,
        repo_type="dataset",
        token=token,
        exist_ok=True,
        private=False,
    )
    update_repo_settings(
        repo_id=REPO_ID,
        repo_type="dataset",
        token=token,
        private=False,
    )
    api = HfApi(token=token)
    api.upload_folder(
        repo_id=REPO_ID,
        repo_type="dataset",
        folder_path=str(ROOT),
        path_in_repo=".",
        commit_message="Upload TypePrediction dataset",
    )
    print(REPO_ID)


if __name__ == "__main__":
    main()