#!/usr/bin/env python3 """Upload the prepared viewer files to the Hugging Face Hub.""" from __future__ import annotations import argparse import json from pathlib import Path from typing import Dict from datasets import Dataset ROOT = Path(__file__).resolve().parents[1] DATA_DIR = ROOT / "data" CONFIGS = { "clue": DATA_DIR / "clue" / "train.jsonl", "mep": DATA_DIR / "mep" / "train.jsonl", } def read_stats() -> Dict[str, Dict[str, int]]: stats_path = DATA_DIR / "stats.json" if not stats_path.exists(): return {} with stats_path.open("r", encoding="utf-8") as handle: return json.load(handle) def push_config(config_name: str, file_path: Path, repo_id: str, args: argparse.Namespace) -> None: if not file_path.exists(): raise FileNotFoundError(f"Missing file for config '{config_name}': {file_path}") print(f"Loading {config_name} from {file_path.relative_to(ROOT)} ...") dataset = Dataset.from_json(str(file_path)) dataset.push_to_hub( repo_id=repo_id, config_name=config_name, split=args.split, private=args.private, token=args.token, branch=args.branch, max_shard_size=args.max_shard_size, ) print(f"✓ Uploaded {config_name}/{args.split} to {repo_id}") def main() -> None: parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("--repo", required=True, help="Target dataset repo id, e.g. user/cuebench") parser.add_argument("--split", default="train", help="Split name to register on the Hub (default: train)") parser.add_argument("--branch", default=None, help="Optional branch to push to (defaults to repo default)") parser.add_argument("--token", default=None, help="HuggingFace token; omit if already logged in via CLI") parser.add_argument("--private", action="store_true", help="Mark the uploaded dataset as private") parser.add_argument("--max-shard-size", default="500MB", help="Shard threshold passed to push_to_hub") args = parser.parse_args() stats = read_stats() for config_name, path in CONFIGS.items(): push_config(config_name, path, args.repo, args) if config_name in stats: summary = stats[config_name] print( f" ↳ stats: {summary.get('num_examples', '?')} examples, " f"{summary.get('num_bytes', '?')} bytes" ) if __name__ == "__main__": main()