"""Build the published Harvey prompt-metadata JSONL from the VAULT exports. Each Harvey VAULT_REVIEW export carries the as-configured per-column prompt in its question headers ("1. 1. Case ID ()"). This script extracts the value-column header of each of the 12 question blocks (same block layout as ``legex.harvey``) and writes one record per (run, field): {"model": "harvey", "inference_date": "2026-05-18", "field": ..., "prompt": ...} ``prompts_harvey.jsonl`` holds both dates of the paper run (2026-05-18 and 2026-06-30 — the 30 June re-created tables carry platform-rephrased prompts); ``prompts_harvey_2.jsonl`` holds the 2026-08-05 transparency run. python build_harvey_prompts_jsonl.py --raw-dir ../data/raw \\ --out-dir inference-results/prompts """ import argparse import json import re from pathlib import Path import openpyxl from legex.harvey import HARVEY_FIELDS_ORDER # run -> [(inference_date, export file)] RUNS: dict[str, tuple[tuple[str, str], ...]] = { "harvey": ( ("2026-05-18", "harvey_2026-05-18.xlsx"), ("2026-06-30", "harvey_2026-06-30.xlsx"), ), "harvey-2": (("2026-08-05", "harvey_2026-08-05.xlsx"),), } _FIRST_ANSWER_COL = 3 # after Name, Folder, Document Classification _TITLE_PREFIX_RE = re.compile(r"^\s*(?:\d+\.\s*)+") def _parse_header(header: str) -> str: """The prompt is the parenthetical after the column title; parens may nest.""" start = header.find("(") if start == -1 or not header.rstrip().endswith(")"): raise ValueError(f"header without a prompt parenthetical: {header[:80]!r}") prompt = header[start + 1 : header.rindex(")")] return " ".join(prompt.split()) def read_prompts(xlsx: Path) -> dict[str, str]: """Return ``{field: prompt}`` from the value-column headers of one export.""" wb = openpyxl.load_workbook(xlsx, read_only=True) ws = wb["Sheet1"]f header = next(ws.iter_rows(min_row=1, max_row=1, values_only=True)) wb.close() width = (len(header) - _FIRST_ANSWER_COL) // len(HARVEY_FIELDS_ORDER) if width < 1: raise ValueError(f"unexpected Harvey sheet width in {xlsx.name}: {len(header)} columns") out: dict[str, str] = {} for j, field in enumerate(HARVEY_FIELDS_ORDER): cell = header[_FIRST_ANSWER_COL + j * width] out[field] = _parse_header(str(cell)) return out def main(argv: list[str] | None = None) -> int: parser = argparse.ArgumentParser(description=__doc__.split("\n\n")[0]) parser.add_argument("--raw-dir", type=Path, default=Path("../data/raw"), help="Directory holding the harvey_.xlsx exports.") parser.add_argument("--out-dir", type=Path, default=Path("inference-results/prompts")) args = parser.parse_args(argv) args.out_dir.mkdir(parents=True, exist_ok=True) for run, exports in RUNS.items(): dst = args.out_dir / f"prompts_{run.replace('-', '_')}.jsonl" n = 0 with dst.open("w", encoding="utf-8") as f: for inference_date, filename in exports: for field, prompt in read_prompts(args.raw_dir / filename).items(): record = {"model": run, "inference_date": inference_date, "field": field, "prompt": prompt} f.write(json.dumps(record, ensure_ascii=False) + "\n") n += 1 print(f"wrote {n} prompt record(s) to {dst}") return 0 if __name__ == "__main__": raise SystemExit(main())