scripts/create_mcq_carbon.py

"""Create GenomeQA mcq_carbon by replacing species classification questions."""

import argparse
import json
import random
from collections import defaultdict
from pathlib import Path

from datasets import Dataset, concatenate_datasets, load_dataset
from huggingface_hub import CommitOperationAdd, HfApi, hf_hub_download


DATASET_ID = "HuggingFaceBio/genomeqa"
SEED = 42
PARQUET_PATH = "mcq_carbon/train-00000-of-00001.parquet"
QUOTAS = {"basic_class": 300, "reverse_search": 100, "odd_one_out": 100}
LABEL_KEYS = {"basic_class": "true", "reverse_search": "target", "odd_one_out": "minority"}


def main() -> None:
    parser = argparse.ArgumentParser()
    parser.add_argument("--source-revision", required=True)
    parser.add_argument("--output-dataset", default=DATASET_ID)
    parser.add_argument("--output-dir", type=Path, default=Path.cwd())
    parser.add_argument("--publish", action="store_true")
    args = parser.parse_args()

    mcq = load_dataset(DATASET_ID, "mcq", split="train", revision=args.source_revision)
    eukaryote = load_dataset(DATASET_ID, "eukaryote_cls", split="train", revision=args.source_revision)
    if mcq.features != eukaryote.features:
        raise ValueError("The source configurations must have matching features")

    strata = defaultdict(lambda: defaultdict(list))
    for index, metadata_text in enumerate(eukaryote["metadata"]):
        metadata = json.loads(metadata_text)
        dimension = metadata["dim"]
        strata[dimension][metadata[LABEL_KEYS[dimension]]].append(index)

    rng = random.Random(SEED)
    selected = []
    for dimension, quota in QUOTAS.items():
        groups = strata[dimension]
        if sum(len(indices) for indices in groups.values()) != 2 * quota:
            raise ValueError(f"Expected {2 * quota} {dimension} source rows")
        take = {label: len(indices) // 2 for label, indices in groups.items()}
        odd_labels = sorted(label for label, indices in groups.items() if len(indices) % 2)
        rng.shuffle(odd_labels)
        for label in odd_labels[: quota - sum(take.values())]:
            take[label] += 1
        for label in sorted(groups):
            selected.extend(rng.sample(groups[label], take[label]))
    rng.shuffle(selected)
    replacement = eukaryote.select(selected)

    species_positions = [index for index, subtask in enumerate(mcq["subtask"]) if subtask == "3_species_cls"]
    if len(species_positions) != 500 or species_positions != list(range(species_positions[0], species_positions[-1] + 1)):
        raise ValueError("Expected one contiguous 500-row 3_species_cls block")
    start = species_positions[0]
    combined = concatenate_datasets([mcq.select(range(start)), replacement, mcq.select(range(start + 500, len(mcq)))])

    parquet_path = args.output_dir / PARQUET_PATH
    parquet_path.parent.mkdir(parents=True, exist_ok=True)
    combined.to_parquet(parquet_path)
    materialized = Dataset.from_parquet(str(parquet_path))

    api = HfApi()
    head = api.repo_info(args.output_dataset, repo_type="dataset").sha
    card = Path(hf_hub_download(args.output_dataset, "README.md", repo_type="dataset", revision=head)).read_text()
    info = f"""- config_name: mcq_carbon
  features:
  - name: id
    dtype: int64
  - name: subtask
    dtype: string
  - name: question
    dtype: string
  - name: options
    list: string
  - name: answer_index
    dtype: int64
  - name: answer_text
    dtype: string
  - name: metadata
    dtype: string
  splits:
  - name: train
    num_bytes: {materialized.info.splits['train'].num_bytes}
    num_examples: {len(materialized)}
  download_size: {parquet_path.stat().st_size}
  dataset_size: {materialized.info.dataset_size}
"""
    marker = "- config_name: eukaryote_cls\n  features:"
    existing = "- config_name: mcq_carbon\n  features:"
    if existing in card:
        start = card.index(existing)
        end = card.index(marker, start)
        card = card[:start] + info + card[end:]
        commit_message = "Correct mcq_carbon size metadata"
    else:
        card = card.replace(marker, info + marker, 1)
        commit_message = "Add stratified mcq_carbon configuration"
        config = """- config_name: mcq_carbon
  data_files:
  - split: train
    path: mcq_carbon/train-*
"""
        card = card.replace("- config_name: eukaryote_cls\n  data_files:", config + "- config_name: eukaryote_cls\n  data_files:", 1)
        row = "| `mcq` | 2,600 | Full benchmark in four-option multiple-choice format. |\n"
        new_row = "| `mcq_carbon` | 2,600 | MCQ benchmark with the 500 `3_species_cls` rows replaced by 500 stratified `eukaryote_cls` rows. |\n"
        card = card.replace(row, row + new_row, 1)
        note = f"""The `mcq_carbon` configuration preserves the other `mcq` rows and inserts 500 `eukaryote_cls` questions at the
original species-classification position. From source revision `{args.source_revision}`, seed {SEED} selects 300
`basic_class`, 100 `reverse_search`, and 100 `odd_one_out` rows, sampling approximately half of each taxon label
within each question type. See [`scripts/create_mcq_carbon.py`](scripts/create_mcq_carbon.py).

"""
        card = card.replace("The `eukaryote_cls` configuration uses the `mcq` feature schema", note + "The `eukaryote_cls` configuration uses the `mcq` feature schema", 1)

    if "### mcq_carbon" not in card:
        card += f"""
### mcq_carbon

To rebuild and publish `mcq_carbon` from the pinned source revision, run:

```bash
python scripts/create_mcq_carbon.py --source-revision {args.source_revision} --output-dataset {args.output_dataset} --publish
```

The script publishes the Parquet file, this card, and the builder script together.
"""

    card_path = args.output_dir / "README.md"
    card_path.write_text(card)
    print(f"Prepared {len(combined)} rows ({len(replacement)} replacement rows) at {parquet_path}")
    if args.publish:
        commit = api.create_commit(
            repo_id=args.output_dataset,
            repo_type="dataset",
            parent_commit=head,
            commit_message=commit_message,
            operations=[
                CommitOperationAdd(path_in_repo=PARQUET_PATH, path_or_fileobj=parquet_path),
                CommitOperationAdd(path_in_repo="README.md", path_or_fileobj=card_path),
                CommitOperationAdd(path_in_repo="scripts/create_mcq_carbon.py", path_or_fileobj=__file__),
            ],
        )
        print(f"Published {commit.commit_url}")


if __name__ == "__main__":
    main()