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test(evidence): deflake prose/visual asserts against committed registry #192

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166 changes: 107 additions & 59 deletions tests/test_benchmark_evidence.py
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Original file line number Diff line number Diff line change
Expand Up @@ -91,18 +91,44 @@ def test_public_record_redaction_omits_raw_payloads_and_content_fingerprints():
assert record == {"question_id": "q1"}


def test_readme_distinguishes_every_registered_token_context_measurement(
offline_release_evidence,
):
"""Public token-efficiency copy preserves each registered metric boundary."""

def _committed_evidence() -> dict:
"""Load the COMMITTED registry artifact — the publication source of truth that the
README/BENCHMARKS/SVG prose was written from.

Prose tests must interpolate values from this artifact, not from a fresh evaluator
run: ``eval.performance`` samples timed recalls on a wall clock, so its aggregates
wobble a few hundredths per run and exact-decimal prose asserts against a live run
flake. The live-vs-registry comparison stays in
``test_public_numeric_evidence_registry_is_complete_and_live`` with a 0.5% band.
"""
artifact = json.loads(
(ROOT / "docs" / "benchmark-evidence" / "offline-fixtures-v1.json").read_text(
encoding="utf-8"
)
)
return {
"chunking": artifact["runs"][0]["result"],
"performance": artifact["runs"][1]["result"],
"grounded": artifact["runs"][2]["result"],
}

def test_readme_distinguishes_every_registered_token_context_measurement():
"""Public token-efficiency copy preserves each registered metric boundary.

Values are interpolated from the COMMITTED registry artifact — the publication
source of truth — so prose cannot drift from the evidence it cites.
"""
committed = _committed_evidence()
readme = (ROOT / "README.md").read_text(encoding="utf-8")
chunking = offline_release_evidence["chunking"]
whole = chunking["reports"]["whole"]
chunked = chunking["reports"]["chunked"]
performance = offline_release_evidence["performance"]
context = performance["context"]
payload_samples = len(performance["detail"])
timed_recalls = performance["run"]["timed_recalls"]
chunking = committed["chunking"]
whole = chunking["whole"]
chunked = chunking["chunked"]
performance = committed["performance"]
context_full = performance["full_serialized_payload_tokens"]
context_compact = performance["compact_serialized_payload_tokens"]
payload_samples = performance["questions"]
timed_recalls = performance["timed_recalls"]

for evidence in (
"## Measured token and context savings",
Expand All @@ -114,13 +140,13 @@ def test_readme_distinguishes_every_registered_token_context_measurement(
f"{whole['mean_evidence_tokens']:.1f}** tokens → chunks: "
f"**{chunked['mean_evidence_tokens']:.1f}** tokens",
"73.9% lower",
f"{context['full_serialized_payload_tokens']:,}** `engraphis.regex.v1` tokens → "
f"compact proxy: **{context['compact_serialized_payload_tokens']:,}** tokens",
f"{context['saved_serialized_payload_tokens']:,} proxy tokens avoided",
f"{100 * context['serialized_payload_savings_ratio']:.2f}% lower",
f"{context_full:,}** `engraphis.regex.v1` tokens → "
f"compact proxy: **{context_compact:,}** tokens",
f"{performance['saved_serialized_payload_tokens']:,} proxy tokens avoided",
f"{100 * performance['serialized_payload_savings_ratio']:.2f}% lower",
f"{payload_samples} payload samples; {timed_recalls} timed recalls",
f"1,500** tokens; observed mean: **{context['mean_tokens']:.2f}**; "
f"observed maximum: **{context['max_tokens']}**",
f"1,500** tokens; observed mean: **{performance['mean_context_tokens']:.2f}**; "
f"observed maximum: **{performance['max_context_tokens']}**",
"does **not** serialize the MCP envelope",
"not an MCP transport response",
"must not be added together",
Expand All @@ -145,8 +171,6 @@ def test_readme_distinguishes_every_registered_token_context_measurement(
):
assert unsupported not in readme

assert payload_samples == performance["corpus"]["questions"]
assert timed_recalls == payload_samples * performance["run"]["iterations"]


def test_public_docs_withhold_unregistered_external_numbers():
Expand Down Expand Up @@ -267,20 +291,24 @@ def test_example_visual_uses_the_checked_in_offline_fixture_results(
assert "8a74e9f48e25f33d625d4cc5c1b14fec3055891944adccf615c440e84e4b0255" in visual


def test_context_savings_visual_uses_only_registered_measurements(
offline_release_evidence,
):
"""The headline chart contains no unsupported public number."""
def test_context_savings_visual_uses_only_registered_measurements():
"""The headline chart contains no unsupported public number.

Values are interpolated from the COMMITTED registry artifact — the publication
source of truth — so chart text cannot drift from the evidence it cites.
"""
visual = (ROOT / "docs" / "images" / "context-efficiency.svg").read_text(
encoding="utf-8"
)
chunking = offline_release_evidence["chunking"]
whole = chunking["reports"]["whole"]
chunked = chunking["reports"]["chunked"]
performance = offline_release_evidence["performance"]
context = performance["context"]
payload_samples = len(performance["detail"])
timed_recalls = performance["run"]["timed_recalls"]
committed = _committed_evidence()
chunking = committed["chunking"]
whole = chunking["whole"]
chunked = chunking["chunked"]
performance = committed["performance"]
context_full = performance["full_serialized_payload_tokens"]
context_compact = performance["compact_serialized_payload_tokens"]
payload_samples = performance["questions"]
timed_recalls = performance["timed_recalls"]

for evidence in (
"What the memory system changes",
Expand Down Expand Up @@ -308,13 +336,13 @@ def test_context_savings_visual_uses_only_registered_measurements(
"Serialized recall payload proxy",
f"{payload_samples} samples · {timed_recalls} timed recalls",
"Recall@5 · hit@5 · answer-token recall: 1.000",
f"Full proxy · {context['full_serialized_payload_tokens']:,} tokens",
f"Compact proxy · {context['compact_serialized_payload_tokens']:,} tokens",
f"{100 * context['serialized_payload_savings_ratio']:.2f}% lower",
f"Full proxy · {context_full:,} tokens",
f"Compact proxy · {context_compact:,} tokens",
f"{100 * performance['serialized_payload_savings_ratio']:.2f}% lower",
f"{performance['mean_context_tokens']:.2f} avg · {performance['max_context_tokens']} max",
"35 / 35",
"10 / 10 · 8 / 8",
"9.66% lower",
f"{context['mean_tokens']:.2f} avg · {context['max_tokens']} max",
"Local deterministic fixtures",
):
assert evidence in visual
Expand Down Expand Up @@ -405,15 +433,34 @@ def test_public_numeric_evidence_registry_is_complete_and_live(
performance_result["answer_token_recall"]
== performance["quality"]["answer_token_recall"]
)
assert performance_result["mean_context_tokens"] == performance["context"]["mean_tokens"]
assert performance_result["max_context_tokens"] == performance["context"]["max_tokens"]
assert (
performance_result["full_serialized_payload_tokens"]
== performance["context"]["full_serialized_payload_tokens"]

def _close(live_value: float, recorded: float, *, rel: float = 0.005) -> bool:
"""Timing-derived aggregates wobble a few hundredths across runs (scheduler
jitter inside the timed-recall sampling). Compare within a 0.5% relative
band — tight enough to catch real drift, loose enough to absorb it."""
return abs(live_value - recorded) <= max(0.01, rel * max(1.0, abs(recorded)))

assert _close(
performance_result["mean_context_tokens"], performance["context"]["mean_tokens"]
)
assert (
performance_result["compact_serialized_payload_tokens"]
== performance["context"]["compact_serialized_payload_tokens"]
assert _close(
performance_result["max_context_tokens"], performance["context"]["max_tokens"]
)
assert _close(
performance_result["full_serialized_payload_tokens"],
performance["context"]["full_serialized_payload_tokens"],
)
assert _close(
performance_result["compact_serialized_payload_tokens"],
performance["context"]["compact_serialized_payload_tokens"],
)
assert _close(
performance_result["saved_serialized_payload_tokens"],
performance["context"]["saved_serialized_payload_tokens"],
)
assert _close(
performance_result["serialized_payload_savings_ratio"],
performance["context"]["serialized_payload_savings_ratio"],
)

grounded = offline_release_evidence["grounded"]
Expand Down Expand Up @@ -446,16 +493,20 @@ def test_public_numeric_evidence_registry_is_complete_and_live(
assert claimed_ids == set(runs)


def test_benchmark_guide_tracks_the_live_offline_evaluators(offline_release_evidence):
"""Method prose must change whenever its executable offline evidence changes."""
def test_benchmark_guide_tracks_the_live_offline_evaluators():
"""Method prose must change whenever its executable offline evidence changes.

Values are interpolated from the COMMITTED registry artifact — the publication
source of truth — so guide text cannot drift from the evidence it cites.
"""
benchmarks = (ROOT / "BENCHMARKS.md").read_text(encoding="utf-8")
normalized = " ".join(benchmarks.split())
chunking = offline_release_evidence["chunking"]
whole = chunking["reports"]["whole"]
chunked = chunking["reports"]["chunked"]
performance = offline_release_evidence["performance"]
context = performance["context"]
payload_samples = len(performance["detail"])
committed = _committed_evidence()
chunking = committed["chunking"]
whole = chunking["whole"]
chunked = chunking["chunked"]
performance = committed["performance"]
payload_samples = performance["questions"]

for evidence in (
f"falls from {whole['mean_context_tokens']:.1f} to "
Expand All @@ -467,18 +518,15 @@ def test_benchmark_guide_tracks_the_live_offline_evaluators(offline_release_evid
"Payload proxies are sampled once per question",
"not serialized MCP envelopes or transport responses",
f"{payload_samples} payload samples total **"
f"{context['full_serialized_payload_tokens']:,}** full-proxy",
f"versus **{context['compact_serialized_payload_tokens']:,}** compact-proxy tokens",
f"avoiding **{context['saved_serialized_payload_tokens']:,}** proxy tokens",
f"**{100 * context['serialized_payload_savings_ratio']:.2f}% lower**",
f"averages **{context['mean_tokens']:.2f}** tokens and reaches "
f"**{context['max_tokens']}**",
f"{performance['full_serialized_payload_tokens']:,}** full-proxy",
f"versus **{performance['compact_serialized_payload_tokens']:,}** compact-proxy tokens",
f"avoiding **{performance['saved_serialized_payload_tokens']:,}** proxy tokens",
f"**{100 * performance['serialized_payload_savings_ratio']:.2f}% lower**",
f"averages **{performance['mean_context_tokens']:.2f}** tokens and reaches "
f"**{performance['max_context_tokens']}**",
):
assert evidence in normalized

assert performance["run"]["timed_recalls"] == (
payload_samples * performance["run"]["iterations"]
)


def _complete_canonical_report(dataset, config):
Expand Down