#!/usr/bin/env python3 """Deterministic QA of publish/ (variants + generated): formats, keys, excerpts, variant/parent consistency, duplicates, leakage into val/test and the benchmark; writes stats.json and QA_REPORT.md. python qa.py # report only python qa.py --drop # also remove records with hard errors (format, leakage, duplicates) from publish/ """ import argparse import glob import json import re from collections import Counter, defaultdict from common import PUBLISH, RUNS, load_originals, norm_pl, read_jsonl, shingles, write_jsonl from tasks import SYNTH, parse, rubric_error, tf_truth from wiki import canon REPO_SRV = "/scratch/WarsawModelTrainersHackathon-main" HARD = {"format", "key", "excerpt", "leak_eval", "dup_exact", "parent_mismatch"} def body(r): """Task content without header, instructions and source texts (for duplicate detection).""" p = parse(r) if r["task_type"] == "true_false": return " ".join(t for _, t in p["statements"]) if r["task_type"] == "closed_choice": return " ".join(p["pre"][-1:] + [t for _, t in p["options"]]) if r["task_type"] == "essay": return (p["thesis"] or "") + " " + " ".join(p["elements"]) return " ".join(p["pre"]) def check(r, parents): f = [] q, t, p = r.get("question", ""), r.get("task_type"), r.get("max_points") if not all(r.get(k) not in (None, "") for k in ("id", "epoch", "requirement", "task_type", "max_points", "question", "rubric", "key_answer")): f.append(("format", "missing field")) if not re.match(rf"^Zadanie \d+\. \(0[–-]{p}\)$", q.split("\n")[0]): f.append(("format", "header")) if SYNTH in q: f.append(("format", "synthetic source label left")) if t == "closed_choice": if len(re.findall(r"(?m)^[A-D]\. ", q)) != 4 or r["key_answer"] not in list("ABCD"): f.append(("key", "mcq options/key")) elif t == "true_false": if len(re.findall(r"(?m)^[1-3]\. ", q)) != 3 or not re.fullmatch(r"1\. [PF], 2\. [PF], 3\. [PF]", r["key_answer"]): f.append(("key", "tf statements/key")) elif t == "essay": gk = r.get("grading_key") or {} if p != 15 or len(gk.get("elementy", [])) != 3 or "B. SPÓJNOŚĆ" not in r["rubric"]: f.append(("format", "essay key/rubric")) elif t and t.startswith("open"): if rubric_error(r["rubric"], p): f.append(("format", "open rubric")) for s in r.get("source_excerpt") or []: if canon(s["text"]) not in canon(q): f.append(("excerpt", "excerpt not in question")) if not (100 <= len(s["text"]) <= 700): f.append(("excerpt", f"excerpt length {len(s['text'])}")) if f"Fragment artykułu „{s['title']}”" not in q: f.append(("excerpt", "label")) if r.get("parent_id"): par = parents.get(r["parent_id"]) if not par: f.append(("parent_mismatch", "parent missing")) elif t == "closed_choice": pp, vp = parse(par), parse(r) po, vo = dict(pp["options"]), dict(vp["options"]) if sorted(canon(x) for x in po.values()) != sorted(canon(x) for x in vo.values()) or \ canon(po.get(par["key_answer"][:1], "")) != canon(vo.get(r["key_answer"], "?")): f.append(("parent_mismatch", "mcq options/correct option differ from parent")) elif t == "true_false": if sorted(tf_truth(par["key_answer"]).values()) != sorted(tf_truth(r["key_answer"]).values()): f.append(("parent_mismatch", "tf truth values differ from parent")) return f def grams(s, n=5): t = norm_pl(s).split() return {" ".join(t[i:i + n]) for i in range(max(0, len(t) - n + 1))} def main(a): parents = {r["id"]: r for r in load_originals()} recs = [] for fam in ("variants", "generated"): for fn in sorted(glob.glob(str(PUBLISH / fam / "*" / "*.jsonl"))): for r in read_jsonl(fn): recs.append((fam, fn, r)) flags = defaultdict(list) for fam, fn, r in recs: for k in check(r, parents): flags[r["id"]].append(k) # leakage into val/test/benchmark (80-char shingles, >= 2 shared) ev = set() for s in ("val", "test"): for x in read_jsonl(f"{REPO_SRV}/output/sft-v2.1/{s}.jsonl"): ev |= shingles(x["messages"][0]["content"]) for fn in glob.glob(f"{REPO_SRV}/benchmark/exams_claude_extracted/*.json"): try: d = json.load(open(fn, encoding="utf-8")) except Exception: continue for qq in (d.get("questions") or []) if isinstance(d, dict) else []: ev |= shingles(qq if isinstance(qq, str) else json.dumps(qq, ensure_ascii=False)) for fam, fn, r in recs: if len(shingles(r["question"]) & ev) >= 2: flags[r["id"]].append(("leak_eval", "shares >=2 shingles with val/test/benchmark")) # duplicates: exact (normalised body prefix) and near (word 5-gram Jaccard >= 0.8), variant-parent pairs excluded seen = {} for pid, par in parents.items(): seen.setdefault(norm_pl(body(par))[:200], pid) for fam, fn, r in recs: k = norm_pl(body(r))[:200] if k in seen and seen[k] != r.get("parent_id"): flags[r["id"]].append(("dup_exact", f"same text as {seen[k]}")) else: seen.setdefault(k, r["id"]) index, G = defaultdict(set), {} for fam, fn, r in recs: g = grams(body(r)) G[r["id"]] = g for x in list(g)[:40]: index[x].add(r["id"]) near = 0 for fam, fn, r in recs: cand = Counter(o for x in list(G[r["id"]])[:40] for o in index[x] if o != r["id"]) for o, c in cand.items(): if c >= 3 and o < r["id"]: a_, b_ = G[r["id"]], G[o] if a_ and len(a_ & b_) / len(a_ | b_) >= 0.8: flags[r["id"]].append(("dup_near", f"~{o}")) near += 1 break # stats st = {"families": {}, "kinds_total": Counter(), "by_epoch_type": Counter(), "verify": Counter(), "paraphrase": Counter(), "grounding": Counter(), "with_source": Counter()} kind_of = lambda t: "essay" if t == "essay" else "closed" if t in ("closed_choice", "true_false") else "open" for fam, fn, r in recs: st["families"][fam] = st["families"].get(fam, 0) + 1 st["kinds_total"][kind_of(r["task_type"])] += 1 st["by_epoch_type"][f"{fam}|{r['epoch']}|{r['task_type']}"] += 1 st["verify"][f"{fam}|{r['verify']['status']}|{r['verify']['method']}"] += 1 if fam == "variants": st["paraphrase"][r["paraphrase"]["kind"]] += 1 else: st["grounding"][r.get("grounding")] += 1 st["with_source"][f"{fam}|{bool(r.get('source_excerpt'))}"] += 1 fl = Counter(k for v in flags.values() for k, _ in v) hard_ids = {i for i, v in flags.items() if any(k in HARD for k, _ in v)} wc = [x for fn in glob.glob(str(PUBLISH / "wiki_check" / "*.jsonl")) for x in read_jsonl(fn)] st["wiki_check"] = Counter(f"{x['status']}|{'evidence' if x['evidence_verified'] else 'no_evidence'}" for x in wc) st["flags"] = fl st["hard_flagged"] = len(hard_ids) st = json.loads(json.dumps(st)) if a.drop and hard_ids: for fn in sorted({fn for fam, fn, r in recs}): rows = read_jsonl(fn) keep = [r for r in rows if r["id"] not in hard_ids] if len(keep) != len(rows): write_jsonl(fn, keep) st["dropped"] = len(hard_ids) kt = Counter(st["kinds_total"]) if a.drop: for fam, fn, r in recs: if r["id"] in hard_ids: kt[kind_of(r["task_type"])] -= 1 st["kinds_total_published"] = dict(kt) (PUBLISH / "stats.json").write_text(json.dumps(st, ensure_ascii=False, indent=1), encoding="utf-8") write_jsonl(RUNS / "qa_flags.jsonl", [{"id": i, "flags": [f"{k}: {m}" for k, m in v]} for i, v in flags.items()]) lines = ["# QA report (generated by scripts/qa.py)", "", f"Records checked: {len(recs)} ({st['families']}).", "", "## Totals per kind (variants + generated)", "", "| kind | records | published |", "|---|---|---|"] for k in ("closed", "open", "essay"): lines.append(f"| {k} | {st['kinds_total'].get(k, 0)} | {kt.get(k, 0)} |") lines += ["", "## Flags", "", "| flag | count | hard (dropped with --drop) |", "|---|---|---|"] for k, v in fl.most_common(): lines.append(f"| {k} | {v} | {'yes' if k in HARD else 'no'} |") lines += ["", f"Hard-flagged records: {len(hard_ids)}" + (" (dropped)" if a.drop else ""), "", "## Verification", "", "| family / status / method | count |", "|---|---|"] for k, v in sorted(st["verify"].items()): lines.append(f"| {k} | {v} |") lines += ["", "## Fact-check of the originals (wiki_check)", "", "| status | count |", "|---|---|"] for k, v in sorted(st["wiki_check"].items()): lines.append(f"| {k} | {v} |") (PUBLISH / "QA_REPORT.md").write_text("\n".join(lines) + "\n", encoding="utf-8") print(json.dumps({"records": len(recs), "flags": fl, "hard": len(hard_ids), "kinds": st["kinds_total"], "published": dict(kt)}, ensure_ascii=False)) if __name__ == "__main__": ap = argparse.ArgumentParser() ap.add_argument("--drop", action="store_true") main(ap.parse_args())