core/tests/test_gsm8k_experience_flywheel.py
Shay 9e7432748d fix(gsm8k): patch experience flywheel merge, provenance, and layering
- merge_compacted_runs merges key-by-key without re-expanding prior counts
- load default train_sample cases for live operation_class resolution
- hash full scout row evidence in source_report_hash and source_run_id
- replace scripts.gsm8k_frontier_report import with local _extract_category
2026-06-17 21:25:36 -07:00

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21 KiB
Python

"""Tests for GSM8K bounded experience flywheel (PR-1)."""
from __future__ import annotations
import json
from pathlib import Path
import pytest
from evals.gsm8k_math.runner import CaseOutcome
from evals.gsm8k_math.train_sample.v1.experience import (
CompactedExperienceRecord,
ExperienceRecord,
_extract_category,
build_experience_report,
compact_records,
compute_dedupe_key,
compute_record_id,
compute_report_hash,
compute_run_id,
load_compacted_from_report,
merge_compacted_runs,
records_from_scout_rows,
scout_row_to_experience_record,
should_retain_row,
write_experience_json,
)
from evals.gsm8k_math.train_sample.v1.scout import (
SealedAttemptScoutRow,
build_scout_row,
build_scout_summary,
classify_delta_kind,
)
from formation.hashing import canonical_json
_REPO_ROOT = Path(__file__).resolve().parents[1]
_REPORT = _REPO_ROOT / "evals/gsm8k_math/train_sample/v1/report.json"
_FIXTURE_CASES = _REPO_ROOT / "tests/fixtures/gsm8k_experience_flywheel_cases.jsonl"
def _outcome(
*,
case_id: str,
outcome: str,
reason: str = "",
actual: float | None = None,
expected: float = 0.0,
) -> CaseOutcome:
return CaseOutcome(
case_id=case_id,
outcome=outcome, # type: ignore[arg-type]
reason=reason,
expected_answer=expected,
expected_unit="",
actual_answer=actual,
actual_unit=None,
trace_hash=None,
realized_prose=None,
)
def _lift_row(case_id: str = "gsm8k-train-sample-v1-0003") -> SealedAttemptScoutRow:
raw = {
"case_id": case_id,
"question": "Revenue question",
"answer_numeric": 864,
"answer_expression": "#### 864",
}
served = _outcome(
case_id=case_id,
outcome="refused",
reason=(
"candidate_graph: recognizer matched but produced no injection "
"(category=discrete_count_statement)"
),
expected=864.0,
)
sealed = _outcome(
case_id=case_id,
outcome="correct",
reason="resolve_pooled",
actual=864.0,
expected=864.0,
)
return build_scout_row(raw, served, sealed)
def _sealed_wrong_row(case_id: str = "gsm8k-train-sample-v1-0011") -> SealedAttemptScoutRow:
raw = {
"case_id": case_id,
"question": "Elimination hazard",
"answer_numeric": 50,
"answer_expression": "#### 50",
}
served = _outcome(
case_id=case_id,
outcome="refused",
reason="candidate_graph: no admissible candidate for statement",
expected=50.0,
)
sealed = _outcome(
case_id=case_id,
outcome="wrong",
reason="resolve_pooled",
actual=3200.0,
expected=50.0,
)
return build_scout_row(raw, served, sealed)
def _joint_refusal_row(
case_id: str,
failure_family: str = "joint_skill_gap_no_admissible_statement",
) -> SealedAttemptScoutRow:
raw = {
"case_id": case_id,
"question": "Joint refusal",
"answer_numeric": 10,
"answer_expression": "#### 10",
}
served = _outcome(
case_id=case_id,
outcome="refused",
reason="candidate_graph: no admissible candidate for statement",
expected=10.0,
)
sealed = _outcome(
case_id=case_id,
outcome="refused",
reason="resolve_pooled: no resolution",
expected=10.0,
)
row = build_scout_row(raw, served, sealed)
return SealedAttemptScoutRow(
case_id=row.case_id,
served_status=row.served_status,
aggressive_status=row.aggressive_status,
aggressive_answer=row.aggressive_answer,
gold_answer=row.gold_answer,
refusal_reason=row.refusal_reason,
failure_family=failure_family,
candidate_lift_family=row.candidate_lift_family,
first_failed_step=row.first_failed_step,
trace_key=row.trace_key,
)
def _scout_summary_from_rows(rows: tuple[SealedAttemptScoutRow, ...]) -> dict:
return {
"schema_version": 1,
"adr": "0175",
"regime": "sealed_attempt_scout",
"cases_source": "fixture",
"sample_count": len(rows),
"serving_counts": {"correct": 0, "wrong": 0, "refused": len(rows)},
"sealed_counts": {"correct": 0, "wrong": 0, "refused": len(rows)},
"delta_counts": {"joint_refusal": len(rows)},
"lift_recommendations": [],
"rows": [r.as_dict() for r in rows],
}
def test_record_id_is_deterministic():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
recs = records_from_scout_rows((row,), scout_summary=scout, cases_by_id={})
assert len(recs) == 1
a = compute_record_id(recs[0])
b = compute_record_id(recs[0])
assert a == b
assert recs[0].record_id == a
def test_run_id_and_report_hash_deterministic():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
assert compute_run_id(scout) == compute_run_id(scout)
assert compute_report_hash(scout) == compute_report_hash(scout)
def test_refused_to_correct_retained_as_candidate():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
recs = records_from_scout_rows((row,), scout_summary=scout)
assert len(recs) == 1
assert recs[0].promotion_status == "candidate"
assert recs[0].candidate_family is not None
assert recs[0].first_missing_primitive == "relation_hypothesis"
def test_sealed_wrong_retained_as_blocked():
row = _sealed_wrong_row()
scout = _scout_summary_from_rows((row,))
recs = records_from_scout_rows((row,), scout_summary=scout)
assert len(recs) == 1
assert recs[0].promotion_status == "blocked_by_wrong_risk"
assert "sealed_wrong" in recs[0].hazard_tags
assert recs[0].negative_evidence_refs
def test_low_signal_joint_refusal_dropped():
row = _joint_refusal_row("gsm8k-train-sample-v1-9001")
delta = classify_delta_kind(row.served_status, row.aggressive_status)
assert delta == "joint_refusal"
assert not should_retain_row(row, delta_kind=delta, high_freq_joint_families=set())
def test_high_frequency_joint_refusal_retained():
fam = "joint_skill_gap_no_admissible_statement"
rows = tuple(_joint_refusal_row(f"gsm8k-train-sample-v1-90{i:02d}", fam) for i in range(3))
scout = _scout_summary_from_rows(rows)
recs = records_from_scout_rows(rows, scout_summary=scout)
assert len(recs) == 3
def test_duplicate_compaction_collapses_count():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
recs = records_from_scout_rows((row, row), scout_summary=scout)
compacted = compact_records(recs)
assert len(compacted) == 1
assert compacted[0].count == 2
assert compacted[0].first_seen_run_id == compacted[0].last_seen_run_id
def test_merge_compacted_runs_increments_count():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
first = compact_records(records_from_scout_rows((row,), scout_summary=scout))
second_recs = records_from_scout_rows((row,), scout_summary=scout)
merged = merge_compacted_runs(first, second_recs)
assert len(merged) == 1
assert merged[0].count == 2
def _experience_record(
*,
case_id: str = "gsm8k-train-sample-v1-0003",
serving_status: str = "refused",
sealed_status: str = "correct",
promotion_status: str = "candidate",
signature: str = "lift_refused_to_correct|additive|recognizer_injection|abc123",
source_run_id: str = "run-a",
source_report_hash: str = "hash-a",
positive_refs: tuple[str, ...] = (),
negative_refs: tuple[str, ...] = (),
) -> ExperienceRecord:
record = ExperienceRecord(
record_id="",
case_id=case_id,
serving_status=serving_status, # type: ignore[arg-type]
sealed_status=sealed_status, # type: ignore[arg-type]
gold_answer="864",
sealed_answer="864",
serving_refusal_family="lift_family",
sealed_failure_family="lift_family",
candidate_family="relation_hypothesis:discrete_count_statement",
first_missing_primitive="relation_hypothesis",
arithmetic_chain_signature=signature,
positive_evidence_refs=positive_refs,
negative_evidence_refs=negative_refs,
hazard_tags=(),
recommended_action="action",
promotion_status=promotion_status, # type: ignore[arg-type]
source_run_id=source_run_id,
source_report_hash=source_report_hash,
)
return ExperienceRecord(
record_id=compute_record_id(record),
case_id=record.case_id,
serving_status=record.serving_status,
sealed_status=record.sealed_status,
gold_answer=record.gold_answer,
sealed_answer=record.sealed_answer,
serving_refusal_family=record.serving_refusal_family,
sealed_failure_family=record.sealed_failure_family,
candidate_family=record.candidate_family,
first_missing_primitive=record.first_missing_primitive,
arithmetic_chain_signature=record.arithmetic_chain_signature,
positive_evidence_refs=record.positive_evidence_refs,
negative_evidence_refs=record.negative_evidence_refs,
hazard_tags=record.hazard_tags,
recommended_action=record.recommended_action,
promotion_status=record.promotion_status,
source_run_id=record.source_run_id,
source_report_hash=record.source_report_hash,
)
def test_merge_preserves_prior_transition_history():
prior_rec = _experience_record(
promotion_status="candidate",
serving_status="refused",
source_run_id="run-prior",
source_report_hash="hash-prior",
positive_refs=("scout:prior=1",),
)
prior = compact_records((prior_rec,))
promoted = _experience_record(
promotion_status="promoted_in_pr",
serving_status="correct",
source_run_id="run-new",
source_report_hash="hash-new",
positive_refs=("scout:new=2",),
)
merged = merge_compacted_runs(prior, (promoted,))
assert merged[0].status_transitions == (
"refused/correct:candidate",
"correct/correct:promoted_in_pr",
)
assert merged[0].first_seen_run_id == "run-prior"
assert merged[0].last_seen_run_id == "run-new"
def test_merge_accumulates_evidence_refs():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
recs = records_from_scout_rows((row,), scout_summary=scout)
prior = compact_records(recs)
prior_record = CompactedExperienceRecord(
dedupe_key=prior[0].dedupe_key,
record_id=prior[0].record_id,
case_id=prior[0].case_id,
serving_status=prior[0].serving_status,
sealed_status=prior[0].sealed_status,
gold_answer=prior[0].gold_answer,
sealed_answer=prior[0].sealed_answer,
serving_refusal_family=prior[0].serving_refusal_family,
sealed_failure_family=prior[0].sealed_failure_family,
candidate_family=prior[0].candidate_family,
first_missing_primitive=prior[0].first_missing_primitive,
arithmetic_chain_signature=prior[0].arithmetic_chain_signature,
positive_evidence_refs=("scout:alpha=1", "scout:beta=2"),
negative_evidence_refs=("scout:neg=1",),
hazard_tags=prior[0].hazard_tags,
recommended_action=prior[0].recommended_action,
promotion_status=prior[0].promotion_status,
count=1,
first_seen_run_id="run-prior",
last_seen_run_id="run-prior",
status_transitions=prior[0].status_transitions,
source_report_hash="hash-prior",
)
new_rec = ExperienceRecord(
record_id=prior[0].record_id,
case_id=prior[0].case_id,
serving_status=prior[0].serving_status,
sealed_status=prior[0].sealed_status,
gold_answer=prior[0].gold_answer,
sealed_answer=prior[0].sealed_answer,
serving_refusal_family=prior[0].serving_refusal_family,
sealed_failure_family=prior[0].sealed_failure_family,
candidate_family=prior[0].candidate_family,
first_missing_primitive=prior[0].first_missing_primitive,
arithmetic_chain_signature=prior[0].arithmetic_chain_signature,
positive_evidence_refs=("scout:beta=2", "scout:gamma=3"),
negative_evidence_refs=("scout:neg=2",),
hazard_tags=prior[0].hazard_tags,
recommended_action=prior[0].recommended_action,
promotion_status=prior[0].promotion_status,
source_run_id="run-new",
source_report_hash="hash-new",
)
merged = merge_compacted_runs((prior_record,), (new_rec,))
assert merged[0].positive_evidence_refs == (
"scout:alpha=1",
"scout:beta=2",
"scout:gamma=3",
)
assert merged[0].negative_evidence_refs == ("scout:neg=1", "scout:neg=2")
def test_merge_scales_with_compacted_records_not_prior_count():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
recs = records_from_scout_rows((row,), scout_summary=scout)
prior = compact_records(recs)
heavy = CompactedExperienceRecord(
dedupe_key=prior[0].dedupe_key,
record_id=prior[0].record_id,
case_id=prior[0].case_id,
serving_status=prior[0].serving_status,
sealed_status=prior[0].sealed_status,
gold_answer=prior[0].gold_answer,
sealed_answer=prior[0].sealed_answer,
serving_refusal_family=prior[0].serving_refusal_family,
sealed_failure_family=prior[0].sealed_failure_family,
candidate_family=prior[0].candidate_family,
first_missing_primitive=prior[0].first_missing_primitive,
arithmetic_chain_signature=prior[0].arithmetic_chain_signature,
positive_evidence_refs=prior[0].positive_evidence_refs,
negative_evidence_refs=prior[0].negative_evidence_refs,
hazard_tags=prior[0].hazard_tags,
recommended_action=prior[0].recommended_action,
promotion_status=prior[0].promotion_status,
count=10_000,
first_seen_run_id="run-heavy",
last_seen_run_id="run-heavy",
status_transitions=prior[0].status_transitions,
source_report_hash="hash-heavy",
)
merged = merge_compacted_runs((heavy,), recs)
assert merged[0].count == 10_001
def test_blocked_family_cannot_be_candidate_in_summary():
rows = (_lift_row("gsm8k-train-sample-v1-0003"), _sealed_wrong_row())
scout = _scout_summary_from_rows(rows)
report = build_experience_report(scout, include_raw_records=False)
families = {f["family"]: f for f in report["family_summaries"]}
blocked_fams = [
f for f in report["family_summaries"] if f["promotion_status"] == "candidate"
]
for fam in blocked_fams:
assert fam["blocked_count"] == 0
assert any(f["promotion_status"] == "blocked_by_wrong_risk" for f in families.values())
def test_experience_report_hash_stable():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
a = build_experience_report(scout)
b = build_experience_report(scout)
assert a["experience_report_hash"] == b["experience_report_hash"]
def test_canonical_json_roundtrip(tmp_path: Path):
row = _lift_row()
scout = _scout_summary_from_rows((row,))
report = build_experience_report(scout)
out = tmp_path / "experience.json"
write_experience_json(report, out)
loaded = json.loads(out.read_text(encoding="utf-8"))
assert loaded["experience_report_hash"] == report["experience_report_hash"]
compacted = load_compacted_from_report(loaded)
assert len(compacted) == 1
def test_report_json_mtime_unchanged_by_experience_import():
before = _REPORT.stat().st_mtime_ns
_ = compute_record_id
after = _REPORT.stat().st_mtime_ns
assert before == after
def test_live_experience_report_determinism():
a = build_experience_report()
b = build_experience_report()
assert json.dumps(a, sort_keys=True) == json.dumps(b, sort_keys=True)
def test_live_serving_wrong_remains_zero_in_experience():
report = build_experience_report()
assert report["scout_serving_counts"]["wrong"] == 0
def test_no_floats_in_hashed_payloads():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
recs = records_from_scout_rows((row,), scout_summary=scout)
for rec in recs:
canonical_json(rec.as_dict())
def test_promoted_in_pr_for_served_correct():
raw = {
"case_id": "gsm8k-train-sample-v1-0002",
"question": "Already served",
"answer_numeric": 18,
"answer_expression": "#### 18",
}
served = _outcome(case_id=raw["case_id"], outcome="correct", actual=18.0, expected=18.0)
sealed = _outcome(case_id=raw["case_id"], outcome="correct", actual=18.0, expected=18.0)
row = build_scout_row(raw, served, sealed)
scout = _scout_summary_from_rows((row,))
recs = records_from_scout_rows((row,), scout_summary=scout)
assert len(recs) == 1
assert recs[0].promotion_status == "promoted_in_pr"
def test_dedupe_key_ignores_run_id():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
cases_by_id = {
row.case_id: {
"case_id": row.case_id,
"answer_expression": "#### 864",
}
}
recs = records_from_scout_rows(
(row,), scout_summary=scout, cases_by_id=cases_by_id
)
key_a = compute_dedupe_key(recs[0])
op_class = recs[0].arithmetic_chain_signature.split("|")[1]
rec_b = scout_row_to_experience_record(
row,
source_run_id="different-run",
source_report_hash="different-hash",
operation_class=op_class,
category="discrete_count_statement",
high_freq_joint_families=set(),
)
assert rec_b is not None
assert compute_dedupe_key(rec_b) == key_a
@pytest.fixture
def injected_scout_summary():
cases = [
{
"case_id": "gsm8k-train-sample-v1-0003",
"question": "Q",
"answer_numeric": 864,
"answer_expression": "#### 864",
},
{
"case_id": "gsm8k-train-sample-v1-0011",
"question": "Q2",
"answer_numeric": 50,
"answer_expression": "#### 50",
},
]
def serving(adapted: dict) -> CaseOutcome:
if "0003" in adapted["id"]:
return _outcome(
case_id=adapted["id"],
outcome="refused",
reason=(
"candidate_graph: recognizer matched but produced no injection "
"(category=discrete_count_statement)"
),
expected=864.0,
)
return _outcome(
case_id=adapted["id"],
outcome="refused",
reason="candidate_graph: no admissible candidate for statement",
expected=50.0,
)
def sealed(adapted: dict) -> CaseOutcome:
if "0003" in adapted["id"]:
return _outcome(
case_id=adapted["id"],
outcome="correct",
actual=864.0,
expected=864.0,
)
return _outcome(
case_id=adapted["id"],
outcome="wrong",
actual=3200.0,
expected=50.0,
)
return build_scout_summary(
cases, cases_source="fixture", serving_scorer=serving, sealed_scorer=sealed
)
def test_injected_scout_adapter_produces_retained_records(injected_scout_summary):
report = build_experience_report(injected_scout_summary)
assert report["retained_record_count"] >= 2
statuses = {r["promotion_status"] for r in report["case_records"]}
assert "candidate" in statuses
assert "blocked_by_wrong_risk" in statuses
def test_extract_category_canonical_no_injection_reason():
reason = (
"candidate_graph: recognizer matched but produced no injection "
"(category=discrete_count_statement)"
)
assert _extract_category(reason) == "discrete_count_statement"
def test_extract_category_returns_none_for_unrelated_reason():
assert _extract_category("candidate_graph: no admissible candidate for statement") is None
def test_report_hash_differs_when_row_evidence_differs():
base = _scout_summary_from_rows((_lift_row(),))
other = dict(base)
other["rows"] = [
{
**_lift_row().as_dict(),
"case_id": "gsm8k-train-sample-v1-9999",
}
]
assert compute_report_hash(base) != compute_report_hash(other)
def test_report_hash_stable_for_identical_input():
scout = _scout_summary_from_rows((_lift_row(), _sealed_wrong_row()))
assert compute_report_hash(scout) == compute_report_hash(scout)
def test_live_default_report_uses_real_operation_classes():
report = build_experience_report()
op_classes = {
rec["arithmetic_chain_signature"].split("|")[1]
for rec in report["case_records"]
}
assert op_classes - {"unknown", "additive"}
assert any(
cls in {"multiplicative", "divisive"}
for cls in op_classes
)
def test_scout_summary_without_cases_uses_unknown_operation_class():
row = _lift_row()
scout = _scout_summary_from_rows((row,))
recs = records_from_scout_rows((row,), scout_summary=scout, cases_by_id={})
assert len(recs) == 1
assert recs[0].arithmetic_chain_signature.split("|")[1] == "unknown"