feat(advisor-comparison): add build_advisor_comparison diagnosis diffing
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
@@ -553,8 +553,10 @@ class TestBuildAdvisorComparison:
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.5}],
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)
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# Corrupt the previous run's scores.csv after it was written.
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(previous_dir / "scores.csv").write_text("not,a,valid\ncsv,,,", encoding="utf-8")
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# Corrupt the previous run's scores.csv with invalid-encoding bytes so
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# pd.read_csv raises UnicodeDecodeError (a ValueError subclass caught
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# by run_reader.read_scores_frame, which then returns an empty frame).
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(previous_dir / "scores.csv").write_bytes(b"\xff\xfe\x00\x01broken binary data \x00\x00")
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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@@ -6,7 +6,7 @@ from pathlib import Path
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import pandas as pd
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from webapp.services.advisor_comparison import find_previous_run
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from webapp.services.advisor_comparison import build_advisor_comparison, find_previous_run
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def _write_fake_run(
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@@ -86,3 +86,221 @@ class TestFindPreviousRun:
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assert previous is not None
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assert previous.run_id == "r1"
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class TestBuildAdvisorComparison:
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def test_resolved_status_when_previously_triggered_now_healthy(self, tmp_path: Path) -> None:
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_write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.5}, {"sample_id": "s2", "faithfulness": 0.5}],
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)
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.95}, {"sample_id": "s2", "faithfulness": 0.95}],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness"], extra_roots=[tmp_path]
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)
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assert comparison is not None
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assert len(comparison.entries) == 1
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entry = comparison.entries[0]
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assert entry.metric == "faithfulness"
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assert entry.status == "resolved"
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assert entry.previous_score == 0.5
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assert entry.current_score is None # not triggered now → no Diagnosis on current side
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def test_regressed_status_when_previously_healthy_now_triggered(self, tmp_path: Path) -> None:
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_write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.95}, {"sample_id": "s2", "faithfulness": 0.95}],
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)
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.5}, {"sample_id": "s2", "faithfulness": 0.5}],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness"], extra_roots=[tmp_path]
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)
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assert comparison is not None
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assert len(comparison.entries) == 1
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entry = comparison.entries[0]
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assert entry.status == "regressed"
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assert entry.previous_score is None
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assert entry.current_score == 0.5
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def test_still_triggered_status_shows_score_and_severity_change(self, tmp_path: Path) -> None:
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_write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.55}, {"sample_id": "s2", "faithfulness": 0.55}],
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)
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.45}, {"sample_id": "s2", "faithfulness": 0.45}],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness"], extra_roots=[tmp_path]
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)
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assert comparison is not None
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entry = comparison.entries[0]
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assert entry.status == "still_triggered"
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assert entry.previous_severity == "warning"
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assert entry.current_severity == "critical"
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assert entry.previous_score == 0.55
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assert entry.current_score == 0.45
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def test_new_metric_status_when_metric_not_measured_before(self, tmp_path: Path) -> None:
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# Previous run only measured context_recall (healthy); faithfulness wasn't tracked at all.
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_write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "context_recall": 0.95}, {"sample_id": "s2", "context_recall": 0.95}],
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)
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.5}, {"sample_id": "s2", "faithfulness": 0.5}],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness"], extra_roots=[tmp_path]
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)
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assert comparison is not None
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assert len(comparison.entries) == 1
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entry = comparison.entries[0]
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assert entry.metric == "faithfulness"
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assert entry.status == "new_metric"
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assert entry.previous_score is None
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assert entry.current_score == 0.5
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def test_metrics_healthy_in_both_are_omitted(self, tmp_path: Path) -> None:
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_write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.95}],
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)
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.96}],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness"], extra_roots=[tmp_path]
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)
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assert comparison is None # nothing to show → overall None
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def test_metric_dropped_from_current_scope_is_not_marked_resolved(self, tmp_path: Path) -> None:
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# Previous run triggered on context_precision, but current run doesn't
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# evaluate that metric at all — must NOT claim "resolved" without a
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# fair current-side measurement.
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_write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "context_precision": 0.3}],
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)
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.95}],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness"], extra_roots=[tmp_path]
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)
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assert comparison is None
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def test_returns_none_when_no_previous_run(self, tmp_path: Path) -> None:
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current_dir = _write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.5}],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness"], extra_roots=[tmp_path]
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)
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assert comparison is None
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def test_judge_model_changed_flag_set_when_models_differ(self, tmp_path: Path) -> None:
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_write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-4o",
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[{"sample_id": "s1", "faithfulness": 0.5}],
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)
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.5}],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness"], extra_roots=[tmp_path]
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)
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assert comparison is not None
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assert comparison.judge_model_changed is True
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assert comparison.previous_judge_model == "gpt-4o"
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assert comparison.current_judge_model == "gpt-5"
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def test_judge_model_changed_false_when_same(self, tmp_path: Path) -> None:
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_write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.5}],
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)
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.5}],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness"], extra_roots=[tmp_path]
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)
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assert comparison is not None
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assert comparison.judge_model_changed is False
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def test_gracefully_returns_none_on_corrupt_previous_scores_csv(self, tmp_path: Path) -> None:
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previous_dir = _write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.5}],
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)
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# Corrupt the previous run's scores.csv with invalid-encoding bytes so
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# pd.read_csv raises UnicodeDecodeError (a ValueError subclass caught
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# by run_reader.read_scores_frame, which then returns an empty frame).
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(previous_dir / "scores.csv").write_bytes(b"\xff\xfe\x00\x01broken binary data \x00\x00")
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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[{"sample_id": "s1", "faithfulness": 0.5}],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness"], extra_roots=[tmp_path]
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)
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assert comparison is None
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def test_worse_statuses_sorted_before_resolved(self, tmp_path: Path) -> None:
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"""regressed/still_triggered/new_metric surface above resolved for visibility."""
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_write_fake_run(
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tmp_path, "r1", "scn-a", "2026-01-01T00:00:00+00:00", "gpt-5",
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[
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{"sample_id": "s1", "faithfulness": 0.5, "context_recall": 0.95},
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],
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)
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current_dir = _write_fake_run(
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tmp_path, "r2", "scn-a", "2026-01-02T00:00:00+00:00", "gpt-5",
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[
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{"sample_id": "s1", "faithfulness": 0.95, "context_recall": 0.5},
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],
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)
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comparison = build_advisor_comparison(
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current_dir, "scn-a", ["faithfulness", "context_recall"], extra_roots=[tmp_path]
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)
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assert comparison is not None
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statuses = [entry.status for entry in comparison.entries]
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# context_recall regressed → must appear before faithfulness resolved.
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assert statuses.index("regressed") < statuses.index("resolved")
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