| """Model-scoped scan/apply: other models' files and changelog history stay untouched.""" |
| import json |
|
|
| import openpyxl |
| import pytest |
| from openpyxl import Workbook |
|
|
| import legex.evaluation.cleaning as cleaning |
| from legex.config import settings |
| from legex.evaluation.comparison import is_label_column |
|
|
|
|
| def test_inference_date_is_not_a_label(): |
| assert is_label_column("inference_date") is False |
|
|
|
|
| @pytest.fixture |
| def env(tmp_path, monkeypatch): |
| monkeypatch.setattr(settings, "data_dir", tmp_path) |
| monkeypatch.setattr(cleaning, "CHANGELOG", tmp_path / "changelog.jsonl") |
| (tmp_path / "zz").mkdir() |
| gs = Workbook() |
| ws = gs.active |
| ws.title = "GOLDENSET" |
| ws.append(["case_id", "link", "full_text", "legal_subject_judgement", "plaintiffs_all_count"]) |
| ws.append(["C-1", "", "text", "Contract_Law", "1"]) |
| gs.save(tmp_path / "zz" / "Goldenset_Testland.xlsx") |
|
|
| def record(model, subject): |
| return {"case_id": "C-1", "legal_subject_judgement": subject, |
| "plaintiffs_all_count": "1", "model": model, "error": None} |
|
|
| files = {} |
| for model, subject in (("modx", "Contract_Law"), ("mody", "Tort_Law")): |
| p = tmp_path / "zz" / f"Goldenset_Testland_v3_full_text_{model}.jsonl" |
| p.write_text(json.dumps(record(model, subject)) + "\n", encoding="utf-8") |
| files[model] = p |
| return tmp_path, files |
|
|
|
|
| def test_inference_files_model_filter(env): |
| tmp_path, files = env |
| assert cleaning._inference_files() == sorted(files.values()) |
| assert cleaning._inference_files({"modx"}) == [files["modx"]] |
|
|
|
|
| def test_scan_folds_in_conflicts_with_prefill(env): |
| tmp_path, files = env |
| conflicts = tmp_path / "conflicts.jsonl" |
| conflicts.write_text( |
| json.dumps({"model": "modx", "country": "zz", "case_id": "C-1", |
| "field": "legal_subject_judgement", "kept": "Contract_Law", |
| "alternative": "Property_Law"}) + "\n" |
| + json.dumps({"model": "mody", "country": "zz", "case_id": "C-1", |
| "field": "legal_subject_judgement", "kept": "Tort_Law", |
| "alternative": "IP_Law"}) + "\n", |
| encoding="utf-8", |
| ) |
| out = tmp_path / "review.xlsx" |
| n = cleaning.scan(out, models={"modx"}, conflicts=conflicts) |
| ws = openpyxl.load_workbook(out).active |
| rows = list(ws.iter_rows(values_only=True)) |
| header, data = rows[0], rows[1:] |
| assert n == len(data) == 1 |
| row = dict(zip(header, data[0])) |
| assert row["model"] == "modx" |
| assert row["current_value"] == "Contract_Law" |
| assert row["corrected_value"] == "Contract_Law" |
| assert "Property_Law" in row["reason"] |
|
|
|
|
| def test_apply_scoped_leaves_other_models_alone(env): |
| tmp_path, files = env |
| before_y = files["mody"].read_bytes() |
| cleaning.CHANGELOG.write_text( |
| json.dumps({"model": "mody", "country": "zz", "case_id": "C-1", |
| "field": "plaintiffs_all_count", "before": "one", "after": "1", |
| "kind": "reviewed"}) + "\n", |
| encoding="utf-8", |
| ) |
| xlsx = tmp_path / "review.xlsx" |
| wb = Workbook() |
| ws = wb.active |
| ws.append(cleaning._XLSX_HEADER) |
| ws.append(["modx", "zz", "C-1", "legal_subject_judgement", "Contract_Law", |
| "duplicate-run conflict; alternative: 'Property_Law'", "", "tp", "missed", |
| "Property_Law"]) |
| wb.save(xlsx) |
|
|
| cleaning.apply(xlsx, models={"modx"}) |
|
|
| assert files["mody"].read_bytes() == before_y |
| recs = [json.loads(l) for l in files["modx"].read_text(encoding="utf-8").splitlines()] |
| assert recs[0]["legal_subject_judgement"] == "Property_Law" |
| assert json.loads(recs[0]["original_input"]) == {"legal_subject_judgement": "Contract_Law"} |
| log_rows = [json.loads(l) for l in cleaning.CHANGELOG.read_text(encoding="utf-8").splitlines()] |
| assert {(r["model"], r["field"]) for r in log_rows} == { |
| ("modx", "legal_subject_judgement"), ("mody", "plaintiffs_all_count"), |
| } |
|
|
