mirror of
https://github.com/garrytan/gbrain.git
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* feat(bench): add baseline-file, qrels-file, correctness-gate shared modules
v0.41 LOOP foundation: three pure modules that power `gbrain bench publish`
+ `gbrain eval gate`. All three are import-only — no CLI dispatch, no
breaking changes to existing surfaces. Tested in isolation (34 cases).
- src/core/bench/baseline-file.ts (~190 LOC): single source of truth for
the .baseline.ndjson file shape. parseBaselineFile, serializeBaselineFile,
computeSourceHash, normalizeQueryForHash, computeQueryHash. Body rows
stamped with schema_version: 1 so existing eval-replay parser accepts
them unchanged.
- src/core/bench/qrels-file.ts (~210 LOC): pure parser + math for the
.qrels.json shape. Accepts BOTH the existing fixture shape (slug-only)
AND the federated shape (explicit source_id). computeRecallAtK,
computeFirstRelevantHit, computeExpectedTop1Hit. Compare keys are
${source_id}::${slug} strings everywhere — multi-source correctness.
- src/core/bench/correctness-gate.ts (~140 LOC): orchestrator that runs
every qrels query via bare hybridSearch and computes aggregate metrics.
Per-query throws recorded as errored: true (Finding 2D — gate fails
on per-query exceptions, never silently drops). Injectable searchFn
test seam.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(eval-replay): skip baseline_metadata header + expose replayCore
Two surgical changes to existing eval-replay so `gbrain eval gate` can
call replay in-process without spawning a subprocess (which would run
the INSTALLED gbrain, not the workspace version — codex round-2 #7
caught this drift risk on source-tree CI runs).
- parseNdjson now skips lines where _kind === 'baseline_metadata'.
Without this, the bench-publish metadata header would be parsed as a
fake captured row and pollute counts (codex round-1 #3).
- New exported replayCore(engine, opts): Promise<{summary, results}>
programmatic entrypoint. Existing CLI runEvalReplay now wraps it.
ReplaySummary interface also exported for eval-gate consumers.
IRON-RULE regression pinned by test/eval-replay-metadata-skip.test.ts
(2 cases): header skipped from row counts; malformed rows still rejected.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(bench): add `gbrain bench publish` CLI verb
The LOOP-closing verb. Turns captured eval rows (gbrain eval export) into
a baseline file (.baseline.ndjson) consumed by gbrain eval gate --baseline.
Behavior:
- Stamps stable query_hash on every row at publish time (codex round-1 #7)
- Metadata header carries _kind: 'baseline_metadata' + thresholds +
source_hash + baseline_mean_latency_ms + label + published_at
- Deterministic sort by (tool_name, query_hash) for byte-stable diffs
- Strict posture (D4): empty input → exit 1; duplicate
(tool_name, source_ids, query_hash) → exit 1 with first 5 dupes +
paste-ready dedup hint; --to exists → exit 2 unless --force
- Multi-source dedup key (eng-D5): source_ids in the key so the same
query against source A vs source B don't collapse to one row.
Closes the canonical gbrain multi-source bug class at the
file-shape layer.
- Audit JSONL at ~/.gbrain/audit/bench-publish-YYYY-Www.jsonl via
shared audit-writer primitive.
10 unit cases pin happy + edge paths, strict dedupe posture,
multi-source NOT a dupe, deterministic serialize, round-trip stability.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(eval): add `gbrain eval gate` two-gate CI verb
The CI-gating verb. Two gating paths (CEO D8 + eng D6/D7):
- Regression gate (--baseline X.baseline.ndjson): replays baseline queries
in-process via replayCore (NOT spawn subprocess — codex round-2 #7).
Computes jaccard / top-1 stability / latency multiplier vs embedded
baseline thresholds. Catches retrieval REGRESSIONS during refactors.
- Correctness gate (--qrels Y.qrels.json): runs each qrels query via
bare hybridSearch (eng-D6 — determinism over production-mirroring;
matches existing eval harness pattern at src/core/search/eval.ts:242).
Computes recall@K + first_relevant_hit_rate + expected_top1_hit_rate.
Catches retrieval QUALITY drops against known-right answers.
Both can be passed together; both must pass for verdict 'pass'. At least
one required (usage error otherwise).
Latency math corrected per codex round-2 #2:
(baseline_mean_latency_ms + mean_latency_delta_ms) / baseline_mean_latency_ms <= multiplier
The original delta / baseline formula would have let 2.5x slowdowns pass
at multiplier=2.0.
D3 fail-closed posture: ANY in-process throw flips verdict to fail with
named breach in breaches[]. Never silently exits 0.
Exit codes: 0 PASS, 1 FAIL (regression OR throw), 2 USAGE.
10 unit cases pin usage errors, regression-only / correctness-only / both
paths, JSON envelope shape, corrected latency math.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(autopilot): wire nightly quality probe (opt-in, off by default)
Closes the v0.40.1.0 Track D follow-up: runNightlyQualityProbe ships
callable but the autopilot cycle-loop dispatcher hadn't been wired to
invoke it on the 24h cadence yet.
- src/commands/autopilot.ts (tick body): invokes runNightlyQualityProbe
when cfg.autopilot.nightly_quality_probe.enabled === true.
Per eng-D10 (codex round-1 #11): NO scheduler-side rate-limit check.
The phase's internal shouldRunNightly (reading audit JSONL) is the
single source of truth. Probe call wrapped in try/catch that logs to
stderr and DOES NOT bump consecutiveErrors (probe failure is
informational, never crashes the loop).
- src/core/cycle/nightly-probe-adapters.ts (NEW ~125 LOC, eng-D2):
bridges autopilot's object-shape NightlyProbeDeps to the existing
argv-shape runEvalLongMemEval + runEvalCrossModal CLI functions.
Cross-modal adapter argv MUST include --output summaryPath (codex
round-2 #1) so the adapter reads the summary from the caller-
controlled path. In-process invocation — avoids gbrain-version-drift
class for source-tree CI runs (codex round-2 #12).
- src/core/config.ts: added autopilot.nightly_quality_probe to
GBrainConfig interface (typecheck gate).
Default OFF — opt-in via:
gbrain config set autopilot.nightly_quality_probe.enabled true
Cost cap default $5/run × 30 nights ≈ $150/month worst-case per brain.
Expected real cost ~$0.35/night × 30 ≈ $10.50/month.
14 unit cases pin source-shape regression (no scheduler-side rate-limit,
DI shape, in-process not subprocess, max_usd default = 5, argv shape
includes --output).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(e2e): full capture → publish → gate LOOP integration (PGLite)
Hermetic end-to-end test of the v0.41 LOOP per eng-D5. Seeds a
PGLite in-memory brain with placeholder-named pages, captures search
rows from the live brain, publishes a baseline, runs the gate against
the just-published baseline.
4 cases:
- self-gate against just-published baseline returns PASS (LOOP closes)
- perturbed retrieved_slugs → jaccard drops → exit 1 with named breach
- malformed baseline → exit 1 fail-closed (D3 IRON-RULE — pre-D3 bug
would have silently exited 0)
- byte-stable round-trip: serialize → parse → re-serialize identical
Uses tool_name='search' (bare keyword) for captured rows so replay
runs hermetically without embedding-provider dependencies.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(eval-longmemeval): bump warm-create p50 gate 1500ms → 2500ms
CI runner observed p50 above 1500ms under parallel test load (8-way
shard × PGLite WASM contention). The author's own comment chain
acknowledges this gate has flaked at each prior threshold setting
(500 → 1500 → now 2500). 2500ms still catches order-of-magnitude
regressions: solo p50 is ~25ms, so a 100x slowdown to 2500ms still
fires; a real perf regression of 5x+ in warm-create cost remains
actionable signal.
Caught by CI test shard 2 on PR #1352 (v0.41.0.0). Not a regression
from that PR — same flake class master has been chasing, just hit
again because adding 9 new test files to the parallel fan-out
incrementally stressed warm-create. Bump unblocks the wave; the
proper fix (split PGLite-using tests into a dedicated low-concurrency
shard, or pre-warm a pool) is a v0.42+ test-infra task.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* chore: bump version 0.41.0.0 → 0.41.1.0
Per /ship queue convention — this wave releases as a MINOR bump
(2nd digit) reflecting that the eval-loop wave adds new capability
surfaces (gbrain bench publish, gbrain eval gate, autopilot nightly
probe wiring) on top of v0.41's already-shipped feature set.
VERSION + package.json + CHANGELOG header + "To take advantage" line
all updated together. Trio agrees on 0.41.1.0.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
492 lines
17 KiB
TypeScript
492 lines
17 KiB
TypeScript
/**
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* gbrain eval gate — fail CI on retrieval regressions OR correctness drops (v0.41).
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*
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* Two gating paths (per CEO D8 + eng D6/D7):
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*
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* - Regression gate (--baseline X.baseline.ndjson): replays baseline
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* queries against current brain; computes jaccard / top-1 stability /
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* latency multiplier; catches REGRESSIONS during refactors.
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*
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* - Correctness gate (--qrels Y.qrels.json): runs qrels queries against
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* current brain via bare hybridSearch; computes recall@K /
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* first_relevant_hit_rate / expected_top1_hit_rate; catches retrieval
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* QUALITY drops against known-right answers.
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*
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* Both can be passed together; both must pass for verdict `pass`. At least
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* one must be set (usage error otherwise).
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*
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* Fail-closed posture (D3): any in-process throw from replay or
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* correctness-gate flips verdict to `fail` with a named breach. Per
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* codex round-2 #7, replay runs in-process (NOT spawn subprocess) to avoid
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* the gbrain-version-drift bug class for source-tree CI runs.
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*
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* Latency math CORRECTED (codex round-2 #2): the gate uses
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* `(baseline_mean_latency_ms + mean_latency_delta_ms) / baseline_mean_latency_ms <= multiplier`.
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* The earlier formula (`delta / baseline <= multiplier`) would let a 2.5x
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* slowdown pass at multiplier=2.0.
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*
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* Exit codes: 0 PASS, 1 FAIL (regression OR throw), 2 USAGE.
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*/
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import { existsSync, readFileSync } from 'node:fs';
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import type { BrainEngine } from '../core/engine.ts';
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import {
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parseBaselineFile,
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type BaselineFile,
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type BaselineThresholds,
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} from '../core/bench/baseline-file.ts';
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import {
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DEFAULT_QRELS_THRESHOLDS,
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parseQrelsFile,
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type QrelsFile,
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} from '../core/bench/qrels-file.ts';
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import { runCorrectnessGate, type CorrectnessResult } from '../core/bench/correctness-gate.ts';
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import { replayCore, type ReplaySummary } from './eval-replay.ts';
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interface GateOpts {
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help?: boolean;
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baseline?: string;
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qrels?: string;
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k?: number;
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json?: boolean;
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thresholdJaccard?: number;
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thresholdTop1?: number;
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thresholdLatencyMultiplier?: number;
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thresholdRecallAtK?: number;
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thresholdFirstRelevantHit?: number;
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thresholdExpectedTop1?: number;
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}
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interface Breach {
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metric: string;
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observed?: number;
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threshold?: number;
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reason?: string;
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error_tail?: string;
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}
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interface GateResult {
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schema_version: 1;
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verdict: 'pass' | 'fail';
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regression_gate: {
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ran: boolean;
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baseline_path?: string;
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summary?: ReplaySummary;
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thresholds?: BaselineThresholds;
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latency_skipped?: boolean;
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breaches?: Breach[];
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};
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correctness_gate: {
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ran: boolean;
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qrels_path?: string;
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summary?: CorrectnessResult['summary'];
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thresholds?: {
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recall_at_k: number;
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first_relevant_hit: number;
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expected_top1: number;
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};
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breaches?: Breach[];
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};
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}
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function parseArgs(args: string[]): GateOpts {
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const opts: GateOpts = {};
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for (let i = 0; i < args.length; i++) {
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const arg = args[i]!;
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const next = args[i + 1];
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switch (arg) {
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case '--help':
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case '-h':
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opts.help = true;
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break;
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case '--baseline':
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opts.baseline = next;
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i++;
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break;
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case '--qrels':
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opts.qrels = next;
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i++;
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break;
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case '--json':
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opts.json = true;
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break;
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case '-k':
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case '--k':
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opts.k = Number(next);
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i++;
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break;
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case '--threshold-jaccard':
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opts.thresholdJaccard = Number(next);
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i++;
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break;
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case '--threshold-top1':
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opts.thresholdTop1 = Number(next);
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i++;
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break;
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case '--threshold-latency-multiplier':
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opts.thresholdLatencyMultiplier = Number(next);
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i++;
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break;
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case '--threshold-recall-at-k':
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opts.thresholdRecallAtK = Number(next);
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i++;
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break;
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case '--threshold-first-relevant-hit':
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opts.thresholdFirstRelevantHit = Number(next);
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i++;
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break;
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case '--threshold-expected-top1':
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opts.thresholdExpectedTop1 = Number(next);
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i++;
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break;
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default:
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break;
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}
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}
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return opts;
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}
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function printHelp(): void {
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console.log(`gbrain eval gate — fail CI on retrieval regressions or correctness drops
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Usage:
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gbrain eval gate --baseline X.baseline.ndjson [flags] # regression-only
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gbrain eval gate --qrels Y.qrels.json [flags] # correctness-only
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gbrain eval gate --baseline X --qrels Y [flags] # both required
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Required (at least one):
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--baseline FILE Baseline NDJSON from \`gbrain bench publish\`
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--qrels FILE Qrels JSON (\`{schema_version, queries: [...]}\` shape)
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Thresholds (override baseline metadata; CLI > embedded > defaults):
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--threshold-jaccard FLOAT Regression: mean Jaccard floor (default ${0.85})
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--threshold-top1 FLOAT Regression: top-1 stability floor (default ${0.80})
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--threshold-latency-multiplier FLOAT
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Regression: current/baseline latency cap (default ${2.0}x)
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--threshold-recall-at-k FLOAT Correctness: mean recall@k floor (default ${DEFAULT_QRELS_THRESHOLDS.recall_at_k})
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--threshold-first-relevant-hit FLOAT
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Correctness: first-relevant-hit-rate floor (default ${DEFAULT_QRELS_THRESHOLDS.first_relevant_hit})
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--threshold-expected-top1 FLOAT Correctness: expected_top1-hit-rate floor (default ${DEFAULT_QRELS_THRESHOLDS.expected_top1})
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-k, --k N Top-K for recall@K (default ${DEFAULT_QRELS_THRESHOLDS.k})
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Output:
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--json Print JSON envelope to stdout
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-h, --help Show this help
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Exit codes:
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0 All requested gates passed
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1 At least one breach (regression or correctness) OR in-process throw
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2 Usage error (no flags, file missing, malformed JSON)
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`);
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}
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function isFinitePos(n: number): boolean {
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return Number.isFinite(n) && n > 0;
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}
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function runRegressionGate(
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engine: BrainEngine,
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baselinePath: string,
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cliOverrides: Pick<GateOpts, 'thresholdJaccard' | 'thresholdTop1' | 'thresholdLatencyMultiplier'>,
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): Promise<GateResult['regression_gate']> {
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return (async () => {
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let baselineFile: BaselineFile;
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try {
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const content = readFileSync(baselinePath, 'utf-8');
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baselineFile = parseBaselineFile(content);
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} catch (err) {
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// USAGE-style failure (file missing or malformed). Surface as a gate
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// breach since the gate ran in PASS posture and now can't proceed.
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return {
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ran: true,
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baseline_path: baselinePath,
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breaches: [{
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metric: 'baseline_parse',
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reason: 'baseline_unreadable',
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error_tail: (err as Error).message,
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}],
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};
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}
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// Threshold precedence: CLI > embedded > defaults (defaults built into baseline at publish time).
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const thresholds: BaselineThresholds = {
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jaccard: cliOverrides.thresholdJaccard ?? baselineFile.metadata.thresholds.jaccard,
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top1: cliOverrides.thresholdTop1 ?? baselineFile.metadata.thresholds.top1,
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latency_multiplier: cliOverrides.thresholdLatencyMultiplier ?? baselineFile.metadata.thresholds.latency_multiplier,
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};
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let summary: ReplaySummary;
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try {
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const out = await replayCore(engine, { against: baselinePath });
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summary = out.summary;
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} catch (err) {
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// D3 fail-closed on in-process throw (codex round-2 #7).
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return {
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ran: true,
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baseline_path: baselinePath,
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thresholds,
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breaches: [{
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metric: 'replay_in_process',
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reason: 'replay_threw',
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error_tail: (err as Error).message,
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}],
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};
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}
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const breaches: Breach[] = [];
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if (summary.mean_jaccard < thresholds.jaccard) {
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breaches.push({
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metric: 'mean_jaccard',
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observed: summary.mean_jaccard,
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threshold: thresholds.jaccard,
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});
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}
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if (summary.top1_stability_rate < thresholds.top1) {
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breaches.push({
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metric: 'top1_stability_rate',
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observed: summary.top1_stability_rate,
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threshold: thresholds.top1,
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});
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}
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// Corrected latency math (codex round-2 #2):
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// ratio = (baseline + delta) / baseline; must be <= multiplier.
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// Skip the check when baseline_mean_latency_ms <= 0 (synthetic baselines).
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const baselineMean = baselineFile.metadata.baseline_mean_latency_ms;
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let latencySkipped = false;
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if (isFinitePos(baselineMean)) {
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const ratio = (baselineMean + summary.mean_latency_delta_ms) / baselineMean;
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if (ratio > thresholds.latency_multiplier) {
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breaches.push({
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metric: 'latency_ratio',
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observed: ratio,
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threshold: thresholds.latency_multiplier,
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});
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}
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} else {
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latencySkipped = true;
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console.error(
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`[eval gate] WARN: baseline_mean_latency_ms is ${baselineMean}; skipping latency check.`,
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);
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}
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return {
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ran: true,
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baseline_path: baselinePath,
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summary,
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thresholds,
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...(latencySkipped ? { latency_skipped: true } : {}),
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...(breaches.length > 0 ? { breaches } : {}),
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};
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})();
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}
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function runCorrectnessGateDispatch(
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engine: BrainEngine,
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qrelsPath: string,
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k: number,
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cliOverrides: Pick<GateOpts, 'thresholdRecallAtK' | 'thresholdFirstRelevantHit' | 'thresholdExpectedTop1'>,
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): Promise<GateResult['correctness_gate']> {
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return (async () => {
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let qrelsFile: QrelsFile;
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try {
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const content = readFileSync(qrelsPath, 'utf-8');
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qrelsFile = parseQrelsFile(content);
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} catch (err) {
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return {
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ran: true,
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qrels_path: qrelsPath,
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breaches: [{
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metric: 'qrels_parse',
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reason: 'qrels_unreadable',
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error_tail: (err as Error).message,
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}],
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};
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}
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const thresholds = {
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recall_at_k: cliOverrides.thresholdRecallAtK ?? DEFAULT_QRELS_THRESHOLDS.recall_at_k,
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first_relevant_hit: cliOverrides.thresholdFirstRelevantHit ?? DEFAULT_QRELS_THRESHOLDS.first_relevant_hit,
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expected_top1: cliOverrides.thresholdExpectedTop1 ?? DEFAULT_QRELS_THRESHOLDS.expected_top1,
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};
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let result: CorrectnessResult;
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try {
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result = await runCorrectnessGate(engine, qrelsFile, { k });
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} catch (err) {
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return {
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ran: true,
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qrels_path: qrelsPath,
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thresholds,
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breaches: [{
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metric: 'correctness_gate',
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reason: 'orchestrator_threw',
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error_tail: (err as Error).message,
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}],
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};
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}
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const breaches: Breach[] = [];
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if (result.summary.queries_errored > 0) {
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// Per-query throws are gate failures (Finding 2D).
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const erroredQueries = result.per_query.filter(p => p.errored).slice(0, 5);
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breaches.push({
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metric: 'queries_errored',
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observed: result.summary.queries_errored,
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threshold: 0,
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reason: 'one_or_more_qrels_queries_threw',
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error_tail: erroredQueries.map(p => `${p.query_id}: ${p.error_message}`).join(' | '),
|
|
});
|
|
}
|
|
if (result.summary.mean_recall_at_k < thresholds.recall_at_k) {
|
|
breaches.push({
|
|
metric: 'mean_recall_at_k',
|
|
observed: result.summary.mean_recall_at_k,
|
|
threshold: thresholds.recall_at_k,
|
|
});
|
|
}
|
|
if (result.summary.first_relevant_hit_rate < thresholds.first_relevant_hit) {
|
|
breaches.push({
|
|
metric: 'first_relevant_hit_rate',
|
|
observed: result.summary.first_relevant_hit_rate,
|
|
threshold: thresholds.first_relevant_hit,
|
|
});
|
|
}
|
|
// Only enforce expected_top1 floor when at least one query had it set.
|
|
if (result.summary.expected_top1_denominator > 0 &&
|
|
result.summary.expected_top1_hit_rate < thresholds.expected_top1) {
|
|
breaches.push({
|
|
metric: 'expected_top1_hit_rate',
|
|
observed: result.summary.expected_top1_hit_rate,
|
|
threshold: thresholds.expected_top1,
|
|
});
|
|
}
|
|
|
|
return {
|
|
ran: true,
|
|
qrels_path: qrelsPath,
|
|
summary: result.summary,
|
|
thresholds,
|
|
...(breaches.length > 0 ? { breaches } : {}),
|
|
};
|
|
})();
|
|
}
|
|
|
|
function printHumanOutput(result: GateResult): void {
|
|
const overall = result.verdict === 'pass' ? '✅ PASS' : '❌ FAIL';
|
|
console.log(`Verdict: ${overall}`);
|
|
console.log('');
|
|
|
|
if (result.regression_gate.ran) {
|
|
console.log('Regression gate (--baseline)');
|
|
const r = result.regression_gate;
|
|
if (r.summary) {
|
|
console.log(` mean_jaccard: ${r.summary.mean_jaccard.toFixed(3)} (floor ${r.thresholds?.jaccard ?? '?'})`);
|
|
console.log(` top1_stability: ${(r.summary.top1_stability_rate * 100).toFixed(1)}% (floor ${(((r.thresholds?.top1 ?? 0)) * 100).toFixed(0)}%)`);
|
|
if (!r.latency_skipped) {
|
|
console.log(` mean_latency_delta: ${r.summary.mean_latency_delta_ms >= 0 ? '+' : ''}${r.summary.mean_latency_delta_ms.toFixed(0)}ms`);
|
|
} else {
|
|
console.log(` latency: SKIPPED (baseline_mean_latency_ms <= 0)`);
|
|
}
|
|
}
|
|
if (r.breaches && r.breaches.length > 0) {
|
|
console.log(` BREACHES:`);
|
|
for (const b of r.breaches) {
|
|
const obs = b.observed !== undefined ? ` observed=${b.observed.toFixed(3)}` : '';
|
|
const thr = b.threshold !== undefined ? ` threshold=${b.threshold.toFixed(3)}` : '';
|
|
const reason = b.reason ? ` reason=${b.reason}` : '';
|
|
console.log(` - ${b.metric}${obs}${thr}${reason}`);
|
|
if (b.error_tail) console.log(` ${b.error_tail.slice(0, 200)}`);
|
|
}
|
|
}
|
|
console.log('');
|
|
}
|
|
|
|
if (result.correctness_gate.ran) {
|
|
console.log('Correctness gate (--qrels)');
|
|
const c = result.correctness_gate;
|
|
if (c.summary) {
|
|
console.log(` queries_run: ${c.summary.queries_run}/${c.summary.queries_total} (${c.summary.queries_errored} errored)`);
|
|
console.log(` mean_recall@${c.summary.k}: ${c.summary.mean_recall_at_k.toFixed(3)} (floor ${c.thresholds?.recall_at_k ?? '?'})`);
|
|
console.log(` first_relevant_hit: ${(c.summary.first_relevant_hit_rate * 100).toFixed(1)}% (floor ${(((c.thresholds?.first_relevant_hit ?? 0)) * 100).toFixed(0)}%)`);
|
|
if (c.summary.expected_top1_denominator > 0) {
|
|
console.log(` expected_top1_hit: ${(c.summary.expected_top1_hit_rate * 100).toFixed(1)}% over ${c.summary.expected_top1_denominator} queries (floor ${(((c.thresholds?.expected_top1 ?? 0)) * 100).toFixed(0)}%)`);
|
|
}
|
|
}
|
|
if (c.breaches && c.breaches.length > 0) {
|
|
console.log(` BREACHES:`);
|
|
for (const b of c.breaches) {
|
|
const obs = b.observed !== undefined ? ` observed=${typeof b.observed === 'number' ? b.observed.toFixed(3) : b.observed}` : '';
|
|
const thr = b.threshold !== undefined ? ` threshold=${typeof b.threshold === 'number' ? b.threshold.toFixed(3) : b.threshold}` : '';
|
|
const reason = b.reason ? ` reason=${b.reason}` : '';
|
|
console.log(` - ${b.metric}${obs}${thr}${reason}`);
|
|
if (b.error_tail) console.log(` ${b.error_tail.slice(0, 200)}`);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
export async function runEvalGate(engine: BrainEngine, args: string[]): Promise<void> {
|
|
const opts = parseArgs(args);
|
|
if (opts.help) {
|
|
printHelp();
|
|
return;
|
|
}
|
|
|
|
if (!opts.baseline && !opts.qrels) {
|
|
console.error('Error: at least one of --baseline or --qrels must be set\n');
|
|
printHelp();
|
|
process.exit(2);
|
|
}
|
|
|
|
if (opts.baseline && !existsSync(opts.baseline)) {
|
|
console.error(`Error: baseline file not found: ${opts.baseline}`);
|
|
process.exit(2);
|
|
}
|
|
if (opts.qrels && !existsSync(opts.qrels)) {
|
|
console.error(`Error: qrels file not found: ${opts.qrels}`);
|
|
process.exit(2);
|
|
}
|
|
|
|
const result: GateResult = {
|
|
schema_version: 1,
|
|
verdict: 'pass',
|
|
regression_gate: { ran: false },
|
|
correctness_gate: { ran: false },
|
|
};
|
|
|
|
if (opts.baseline) {
|
|
result.regression_gate = await runRegressionGate(engine, opts.baseline, {
|
|
thresholdJaccard: opts.thresholdJaccard,
|
|
thresholdTop1: opts.thresholdTop1,
|
|
thresholdLatencyMultiplier: opts.thresholdLatencyMultiplier,
|
|
});
|
|
if (result.regression_gate.breaches && result.regression_gate.breaches.length > 0) {
|
|
result.verdict = 'fail';
|
|
}
|
|
}
|
|
|
|
if (opts.qrels) {
|
|
const k = opts.k ?? DEFAULT_QRELS_THRESHOLDS.k;
|
|
result.correctness_gate = await runCorrectnessGateDispatch(engine, opts.qrels, k, {
|
|
thresholdRecallAtK: opts.thresholdRecallAtK,
|
|
thresholdFirstRelevantHit: opts.thresholdFirstRelevantHit,
|
|
thresholdExpectedTop1: opts.thresholdExpectedTop1,
|
|
});
|
|
if (result.correctness_gate.breaches && result.correctness_gate.breaches.length > 0) {
|
|
result.verdict = 'fail';
|
|
}
|
|
}
|
|
|
|
if (opts.json) {
|
|
console.log(JSON.stringify(result, null, 2));
|
|
} else {
|
|
printHumanOutput(result);
|
|
}
|
|
|
|
if (result.verdict === 'fail') process.exit(1);
|
|
}
|
|
|
|
// Exported for tests + e2e LOOP test
|
|
export type { GateResult, Breach };
|