| """在公开的中文 Text-to-SQL 基准 CSpider 的 dev 集上评测，好和别人的数字比。 |
| |
| python scripts/eval_cspider.py --cspider cspider --model Qwen/Qwen3-4B-Instruct-2507 --adapter out/lora \ |
| --out results/paper/cspider_main.json |
| |
| --cspider 指向 CSpider 官方包解压出来的目录（taolusi/chisp 给的 Google Drive），里面要有 dev.json 和 |
| database/<db_id>/<db_id>.sqlite。题目是中文，库是 Spider 的英文库，库里有真实数据。 |
| |
| 和 eval.py 的不同： |
| - 库是现成的真数据，不用 seed_suite 生成，只在这一份库上比结果（Spider 官方的执行准确率也是这么算的） |
| - 建表语句和「部分字段的取值」从库里现读，和 ask.py 一样 |
| - 主指标用严格口径（列数也要一样），和 Spider 的执行准确率一致；宽松口径照样记下来 |
| repair / vote 和 eval.py 一样，看的是同一个库上的执行结果，不看标准答案。 |
| """ |
|
|
| import argparse |
| import json |
| import sqlite3 |
| from pathlib import Path |
|
|
| import eval as ev |
| from prompt import build, values_from_db |
|
|
|
|
| def open_db(path: Path) -> sqlite3.Connection: |
| conn = sqlite3.connect(f"file:{path}?mode=ro", uri=True) |
| conn.execute("PRAGMA query_only = ON") |
| |
| conn.text_factory = lambda b: b.decode("utf-8", errors="replace") |
| return conn |
|
|
|
|
| def schema_of(conn: sqlite3.Connection) -> str: |
| return "\n\n".join(sql.strip() + ";" for (sql,) in conn.execute( |
| "select sql from sqlite_master where type='table' and name not like 'sqlite_%' and sql is not null")) |
|
|
|
|
| def main() -> None: |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--cspider", required=True, help="CSpider 解压目录，含 dev.json 和 database/") |
| ap.add_argument("--model", required=True) |
| ap.add_argument("--adapter", default="") |
| ap.add_argument("--out", required=True) |
| ap.add_argument("--limit", type=int, default=0) |
| ap.add_argument("--max-new-tokens", type=int, default=1024) |
| ap.add_argument("--batch-size", type=int, default=8) |
| ap.add_argument("--no-values", action="store_true") |
| ap.add_argument("--repair", type=int, default=0) |
| ap.add_argument("--vote", type=int, default=1) |
| ap.add_argument("--timeout", type=float, default=30.0, help="单条 SQL 最多跑几秒；Spider 有几个库比较大") |
| args = ap.parse_args() |
|
|
| from infer import Generator, answer, execute |
|
|
| ev.QUERY_TIMEOUT = args.timeout |
| root = Path(args.cspider) |
| items = json.loads((root / "dev.json").read_text(encoding="utf-8")) |
| if args.limit: |
| items = items[: args.limit] |
| conns, ddls, values = {}, {}, {} |
| for db in sorted({it["db_id"] for it in items}): |
| conns[db] = open_db(root / "database" / db / f"{db}.sqlite") |
| ddls[db] = schema_of(conns[db]) |
| values[db] = None if args.no_values else values_from_db(conns[db]) |
|
|
| gen = Generator(args.model, adapter=args.adapter, batch_size=args.batch_size, |
| max_new_tokens=args.max_new_tokens) |
| convs = [build(ddls[it["db_id"]], it["question"], values[it["db_id"]]) for it in items] |
| outs = answer(gen, convs, [conns[it["db_id"]] for it in items], repair=args.repair, vote=args.vote) |
|
|
| records, ok, loose, valid, bad_gold = [], 0, 0, 0, 0 |
| for it, o in zip(items, outs): |
| conn = conns[it["db_id"]] |
| try: |
| ev.rows_of(conn, it["query"]) |
| runs, hit, hit_loose = ev.judge(it["query"], o["sql"], [conn]) |
| except Exception: |
| |
| bad_gold += 1 |
| runs, hit, hit_loose = execute(conn, o["sql"])[1] is None, False, False |
| valid += runs |
| ok += hit |
| loose += hit_loose |
| records.append({"db": it["db_id"], "question": it["question"], "gold": it["query"], "pred": o["sql"], |
| "hit": hit, "hit_loose": hit_loose, "runs": runs, "raw": o["raw"], |
| "first_pred": o["first_sql"], "votes": o["votes"], "repairs": o["repairs"]}) |
|
|
| n = len(items) |
| print(f"\nCSpider dev 共 {n} 题｜可执行 {valid}（{valid/n:.1%}）｜执行准确率 {ok/n:.1%}" |
| f"｜宽松 {loose/n:.1%}｜标准答案跑不通 {bad_gold} 题") |
| tmp = Path(args.out + ".tmp") |
| tmp.parent.mkdir(parents=True, exist_ok=True) |
| tmp.write_text(json.dumps(records, ensure_ascii=False, indent=1), encoding="utf-8") |
| tmp.replace(args.out) |
| print("明细写到", args.out) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
