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5 changed files with 116 additions and 267 deletions

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@ -57,14 +57,7 @@ export default defineConfig({
// otherwise-correctness integration suite (self-skipped everywhere // otherwise-correctness integration suite (self-skipped everywhere
// else via BRAINY_PERF_LANE). Stays in the integration gate's // else via BRAINY_PERF_LANE). Stays in the integration gate's
// include too, so every OTHER test in the file keeps running there. // include too, so every OTHER test in the file keeps running there.
'tests/integration/storage-batch-operations.test.ts', 'tests/integration/storage-batch-operations.test.ts'
// Same pattern: one wall-clock budget case (100-file write + readdir,
// 5.5s budget) inside an otherwise-correctness VFS unit suite
// (self-skipped everywhere else via BRAINY_PERF_LANE — see
// tests/vfs/vfs.unit.test.ts's 'Performance > should handle many
// files efficiently'). Stays in the unit gate's *.unit.test.ts match
// too, so every OTHER test in the file keeps running there.
'tests/vfs/vfs.unit.test.ts'
], ],
reporters: process.env.CI ? ['dot'] : ['basic'], reporters: process.env.CI ? ['dot'] : ['basic'],

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@ -9,34 +9,9 @@
* 8.0 BigInt boundary: entity ints in (resolved via the metadata index's * 8.0 BigInt boundary: entity ints in (resolved via the metadata index's
* idMapper), entity/verb ints out (`bigint[]`). Entity ints map back to UUIDs * idMapper), entity/verb ints out (`bigint[]`). Entity ints map back to UUIDs
* via `idMapper.getUuid(Number(int))`; verb ints via `verbIntsToIds()`. * via `idMapper.getUuid(Number(int))`; verb ints via `verbIntsToIds()`.
*
* COST NOTE (2026-09): this file's `beforeEach` used to recreate a fresh
* FileSystemStorage-backed Brainy plus 51 real-embedded entities before
* EVERY one of the 18 tests below (~950 add()/relate() calls total, each
* paying the real ONNX embedder the whole file walled ~328s). Fixed
* without touching a single assertion:
*
* (1) `vector: []` on every add() below these tests exercise graph
* pagination, never similarity, so a pre-supplied vector is honest, not
* a shortcut: `add()`'s `params.vector || (await this.embed(...))` never
* calls the embedder once `vector` is present, even the sanctioned
* unvectored `[]` shape (see brainy.ts's add(), the zero-norm-law
* comment) and the `vector.length > 0` gate on dimension-pinning means
* `[]` never poisons `this.dimensions` for later real embeds.
* (2) `storage: { type: 'memory' }` instead of the 'auto' default
* (FileSystemStorage at ./brainy-data) real disk I/O the pagination
* assertions never needed, and it sidesteps tests/setup.ts's global
* per-test `rm -rf brainy-data`, which would otherwise corrupt a brain
* shared across a describe's beforeAll out from under it.
* (3) the base fixture (one central hub + 50 outgoing-edge neighbors) now
* builds ONCE per describe (`beforeAll`) instead of once per test safe
* because no test in a given describe block mutates the shared fixture
* in a way an earlier sibling test's assertion depends on (the one
* mutating case, the incoming-direction test, is the LAST test in its
* describe).
*/ */
import { describe, it, expect, beforeAll, afterAll } from 'vitest' import { describe, it, expect, beforeEach } from 'vitest'
import { Brainy } from '../../src/brainy.js' import { Brainy } from '../../src/brainy.js'
import { NounType, VerbType } from '../../src/types/graphTypes.js' import { NounType, VerbType } from '../../src/types/graphTypes.js'
@ -64,21 +39,14 @@ describe('GraphAdjacencyIndex Pagination', () => {
.map((i) => idMapper().getUuid(Number(i))) .map((i) => idMapper().getUuid(Number(i)))
.filter((u: string | undefined): u is string => u !== undefined) .filter((u: string | undefined): u is string => u !== undefined)
/** beforeEach(async () => {
* Builds one central hub + 50 neighbor entities (all outgoing edges from
* the hub), unvectored and on in-memory storage (see the file header).
* Assigns the describe-scoped `brain`/`centralId`/`neighborIds` above;
* called once per describe via `beforeAll`, not once per test.
*/
async function buildFixture(): Promise<void> {
brain = new Brainy({ requireSubtype: false }) brain = new Brainy({ requireSubtype: false })
await brain.init({ storage: { type: 'memory' } }) await brain.init()
// Create central entity // Create central entity
centralId = await brain.add({ centralId = await brain.add({
data: { name: 'Central Hub' }, data: { name: 'Central Hub' },
type: NounType.Thing, type: NounType.Thing
vector: []
}) })
// Create 50 neighbor entities with relationships // Create 50 neighbor entities with relationships
@ -86,8 +54,7 @@ describe('GraphAdjacencyIndex Pagination', () => {
for (let i = 0; i < 50; i++) { for (let i = 0; i < 50; i++) {
const neighborId = await brain.add({ const neighborId = await brain.add({
data: { name: `Neighbor ${i}`, index: i }, data: { name: `Neighbor ${i}`, index: i },
type: NounType.Thing, type: NounType.Thing
vector: []
}) })
neighborIds.push(neighborId) neighborIds.push(neighborId)
@ -98,14 +65,9 @@ describe('GraphAdjacencyIndex Pagination', () => {
type: VerbType.RelatesTo type: VerbType.RelatesTo
}) })
} }
} })
describe('getNeighbors() Pagination', () => { describe('getNeighbors() Pagination', () => {
beforeAll(buildFixture)
afterAll(async () => {
await brain?.close()
})
it('should return all neighbors without pagination', async () => { it('should return all neighbors without pagination', async () => {
const neighborInts = await graphIndex().getNeighbors(entityInt(centralId)) const neighborInts = await graphIndex().getNeighbors(entityInt(centralId))
const neighbors = intsToUuids(neighborInts) const neighbors = intsToUuids(neighborInts)
@ -187,8 +149,7 @@ describe('GraphAdjacencyIndex Pagination', () => {
// Create some incoming relationships // Create some incoming relationships
const sourceId = await brain.add({ const sourceId = await brain.add({
data: { name: 'Source' }, data: { name: 'Source' },
type: NounType.Thing, type: NounType.Thing
vector: []
}) })
await brain.relate({ await brain.relate({
@ -208,11 +169,6 @@ describe('GraphAdjacencyIndex Pagination', () => {
}) })
describe('getVerbIdsBySource() Pagination', () => { describe('getVerbIdsBySource() Pagination', () => {
beforeAll(buildFixture)
afterAll(async () => {
await brain?.close()
})
it('should return all verb ints without pagination and resolve them back to ids', async () => { it('should return all verb ints without pagination and resolve them back to ids', async () => {
const verbInts: bigint[] = await graphIndex().getVerbIdsBySource(entityInt(centralId)) const verbInts: bigint[] = await graphIndex().getVerbIdsBySource(entityInt(centralId))
@ -267,11 +223,6 @@ describe('GraphAdjacencyIndex Pagination', () => {
}) })
describe('getVerbIdsByTarget() Pagination', () => { describe('getVerbIdsByTarget() Pagination', () => {
beforeAll(buildFixture)
afterAll(async () => {
await brain?.close()
})
it('should return all verb ints targeting an entity', async () => { it('should return all verb ints targeting an entity', async () => {
// Pick a neighbor that's a target of relationships // Pick a neighbor that's a target of relationships
const targetId = neighborIds[0] const targetId = neighborIds[0]
@ -285,16 +236,14 @@ describe('GraphAdjacencyIndex Pagination', () => {
// Create entity with many incoming relationships // Create entity with many incoming relationships
const popularTarget = await brain.add({ const popularTarget = await brain.add({
data: { name: 'Popular Target' }, data: { name: 'Popular Target' },
type: NounType.Thing, type: NounType.Thing
vector: []
}) })
// Create 30 relationships pointing to it // Create 30 relationships pointing to it
for (let i = 0; i < 30; i++) { for (let i = 0; i < 30; i++) {
const sourceId = await brain.add({ const sourceId = await brain.add({
data: { name: `Source ${i}` }, data: { name: `Source ${i}` },
type: NounType.Thing, type: NounType.Thing
vector: []
}) })
await brain.relate({ await brain.relate({
from: sourceId, from: sourceId,
@ -318,11 +267,6 @@ describe('GraphAdjacencyIndex Pagination', () => {
}) })
describe('Performance with Pagination', () => { describe('Performance with Pagination', () => {
beforeAll(buildFixture)
afterAll(async () => {
await brain?.close()
})
it('should maintain sub-5ms performance with pagination', async () => { it('should maintain sub-5ms performance with pagination', async () => {
const central = entityInt(centralId) const central = entityInt(centralId)
@ -341,17 +285,11 @@ describe('GraphAdjacencyIndex Pagination', () => {
}) })
describe('Real-World Use Cases', () => { describe('Real-World Use Cases', () => {
beforeAll(buildFixture)
afterAll(async () => {
await brain?.close()
})
it('should efficiently paginate through high-degree node', async () => { it('should efficiently paginate through high-degree node', async () => {
// Simulate popular entity with 100+ relationships // Simulate popular entity with 100+ relationships
const hub = await brain.add({ const hub = await brain.add({
data: { name: 'Popular Hub' }, data: { name: 'Popular Hub' },
type: NounType.Thing, type: NounType.Thing
vector: []
}) })
// Create 100 relationships // Create 100 relationships
@ -359,8 +297,7 @@ describe('GraphAdjacencyIndex Pagination', () => {
for (let i = 0; i < 100; i++) { for (let i = 0; i < 100; i++) {
const targetId = await brain.add({ const targetId = await brain.add({
data: { name: `Target ${i}` }, data: { name: `Target ${i}` },
type: NounType.Thing, type: NounType.Thing
vector: []
}) })
targetIds.push(targetId) targetIds.push(targetId)
await brain.relate({ await brain.relate({

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@ -1,172 +0,0 @@
/**
* Triple Intelligence Correctness Tests
*
* Moved out of tests/performance/triple-intelligence-scale.test.ts (the
* perf-lane split excludes the whole `tests/performance/**` directory from
* the correctness gate see vitest.config.ts's exclude list which left
* this describe's 4 tests running nowhere by default). Every `expect(...)`
* below is byte-for-byte what the original file asserted nothing here
* changes an assertion.
*
* Fixture-only fixes were required to make this run at all against the
* current engine exactly the kind of drift that running nowhere hides
* (tsconfig.json excludes `**\/*.test.ts`, so tsc never typechecked this file
* either, and nothing else exercised it since the perf-lane split):
* `addMany()` now takes `{ items }`, not a bare array; `relate()`'s `type` is
* a `VerbType` enum value, not the string `'related'`; `add()`'s `type` is
* required at runtime (`type: NounType.Document` added no test asserts on
* it); the `where` filter spells its operators bare (`gte`, not `$gte`);
* `storage: { type: 'memory' }` avoids tests/setup.ts's global per-test
* `rm -rf brainy-data` tearing the writer lock out from under this describe's
* shared (beforeAll) brain between tests.
*
* Two of the four tests are `it.skip` with a defect filed in a comment above
* each, not patched: `graphTraversal()` bypasses the 8.0 id-normalization law
* (a natural-key `connected.from` never resolves), and `vectorSearch()`
* throws a hardcoded O(log n) wall-time guard that a 6-row fixture's cold
* WASM/JIT cost blows through by 6-15x both genuine TripleIntelligenceSystem
* defects the original file never surfaced because it ran (when it ran at
* all, in-process) after a 1M-item warm-up suite. See each skip's comment.
*/
import { describe, it, expect, beforeAll, afterAll } from 'vitest'
import { Brainy } from '../../src/brainy.js'
import { TripleIntelligenceSystem } from '../../src/triple/TripleIntelligenceSystem.js'
import { NounType, VerbType } from '../../src/types/graphTypes.js'
describe('Triple Intelligence Correctness', () => {
let brain: Brainy
let triple: TripleIntelligenceSystem
beforeAll(async () => {
brain = new Brainy({ requireSubtype: false })
await brain.init({
enableMetadataIndex: true,
enableGraphIndex: true,
// Memory, not the 'auto' default's FileSystemStorage at ./brainy-data:
// tests/setup.ts's global per-test `rm -rf brainy-data` was ripping the
// writer lock out from under this describe's shared (beforeAll) brain
// between tests ("Writer fence lost" on close) — a store this test
// never needed to touch disk for.
storage: { type: 'memory' }
})
// Add test data with known patterns
const testData = [
{ id: 'doc1', data: 'Machine learning algorithms', type: NounType.Document, metadata: { topic: 'AI', year: 2023 } },
{ id: 'doc2', data: 'Deep learning neural networks', type: NounType.Document, metadata: { topic: 'AI', year: 2024 } },
{ id: 'doc3', data: 'Natural language processing', type: NounType.Document, metadata: { topic: 'AI', year: 2023 } },
{ id: 'doc4', data: 'Computer vision applications', type: NounType.Document, metadata: { topic: 'AI', year: 2024 } },
{ id: 'doc5', data: 'Quantum computing basics', type: NounType.Document, metadata: { topic: 'Physics', year: 2023 } },
{ id: 'doc6', data: 'Blockchain technology', type: NounType.Document, metadata: { topic: 'Crypto', year: 2024 } }
]
await brain.addMany({ items: testData })
// Add relationships
await brain.relate({ from: 'doc1', to: 'doc2', type: VerbType.RelatedTo })
await brain.relate({ from: 'doc2', to: 'doc3', type: VerbType.RelatedTo })
await brain.relate({ from: 'doc3', to: 'doc4', type: VerbType.RelatedTo })
triple = brain.getTripleIntelligence()
})
afterAll(async () => {
await brain?.close()
})
it('should return exact matches for field queries', async () => {
const results = await triple.find({
where: { topic: 'AI' },
limit: 10
})
expect(results).toHaveLength(4)
for (const result of results) {
expect(result.metadata.topic).toBe('AI')
}
})
it('should handle range queries correctly', async () => {
const results = await triple.find({
where: { year: { gte: 2024 } },
limit: 10
})
expect(results).toHaveLength(3)
for (const result of results) {
expect(result.metadata.year).toBeGreaterThanOrEqual(2024)
}
})
// SKIPPED — genuine TripleIntelligenceSystem defect, out of test-hygiene
// scope, filed rather than patched: graphTraversal() (TripleIntelligenceSystem.ts)
// calls storage.getNoun(id) / graphIndex.getNeighbors(id) directly with the
// caller's raw `connected.from` string, bypassing the 8.0 id-normalization
// law (Brainy.add() coerces a natural-key id like 'doc1' to a stable v5
// UUID and stores the original only for translation at the public API
// surface — see coerceNewEntityId in brainy.ts). A caller passing a
// natural-key id here gets storage.getNoun('doc1') → undefined; every
// result's `id` is whatever raw string seeded the BFS queue, so results
// can never match by natural key either. Reproduces identically against
// the pre-move fixture and code — not introduced by this file's move, just
// never exercised (this describe ran nowhere since the perf-lane split).
it.skip('should traverse graph relationships', async () => {
const results = await triple.find({
connected: { from: 'doc1', depth: 2 },
limit: 10
})
// Should find doc1, doc2 (depth 1), and doc3 (depth 2)
const ids = results.map(r => r.id)
expect(ids).toContain('doc1')
expect(ids).toContain('doc2')
expect(ids).toContain('doc3')
// Check depth values
const doc1Result = results.find(r => r.id === 'doc1')
const doc2Result = results.find(r => r.id === 'doc2')
const doc3Result = results.find(r => r.id === 'doc3')
expect(doc1Result?.depth).toBe(0)
expect(doc2Result?.depth).toBe(1)
expect(doc3Result?.depth).toBe(2)
})
// SKIPPED — genuine TripleIntelligenceSystem defect, out of test-hygiene
// scope, filed rather than patched: vectorSearch() (TripleIntelligenceSystem.ts)
// throws `Vector search O(log n) violation` when elapsed wall time exceeds
// `log2(hnswIndex.size()) * 5 * 2` — on a 6-row fixture that bound is
// ~25.8ms, which the real cost of a WASM/Candle embed call plus first-call
// JIT/cache warmup blows through by 6-15x (measured 166-375ms across
// repeated runs) — a hardcoded constant that assumes an already-warm,
// presumably-native runtime, not this environment. The ORIGINAL file never
// hit this: it ran after 'Triple Intelligence Performance at Scale', whose
// 1M-item setup + many queries left the embedder/HNSW thoroughly warm by
// the time this describe's tests ran in the same process — an accidental
// dependency on a sibling suite, not a property of this test. Standalone,
// cold, it is inherently flaky by the SUT's own design, not fixable by
// fixture changes (enlarging the fixture only pushes elapsed time up
// alongside the threshold's log-scaled — not linear — growth).
it.skip('should combine signals with proper fusion', async () => {
const results = await triple.find({
similar: 'deep learning',
where: { topic: 'AI' },
limit: 3
}, {
fusion: {
strategy: 'rrf',
weights: { vector: 0.7, field: 0.3 }
}
})
// doc2 should rank highest (matches both signals)
expect(results[0].id).toBe('doc2')
expect(results[0].fusionScore).toBeGreaterThan(0)
// All results should have AI topic
for (const result of results) {
expect(result.metadata.topic).toBe('AI')
}
})
})

View file

@ -352,8 +352,106 @@ describe('Triple Intelligence Performance at Scale', () => {
}) })
}) })
// The former 'Triple Intelligence Correctness' describe (4 tests, no timing describe('Triple Intelligence Correctness', () => {
// assertions) moved to tests/integration/triple-intelligence-correctness.test.ts let brain: Brainy
// so it runs in the default correctness gate — this whole directory let triple: TripleIntelligenceSystem
// (tests/performance/**) is excluded from that gate (see vitest.config.ts),
// which had silently stopped running those 4 tests after the perf-lane split. beforeAll(async () => {
brain = new Brainy({ requireSubtype: false })
await brain.init({
enableMetadataIndex: true,
enableGraphIndex: true
})
// Add test data with known patterns
const testData = [
{ id: 'doc1', data: 'Machine learning algorithms', metadata: { topic: 'AI', year: 2023 } },
{ id: 'doc2', data: 'Deep learning neural networks', metadata: { topic: 'AI', year: 2024 } },
{ id: 'doc3', data: 'Natural language processing', metadata: { topic: 'AI', year: 2023 } },
{ id: 'doc4', data: 'Computer vision applications', metadata: { topic: 'AI', year: 2024 } },
{ id: 'doc5', data: 'Quantum computing basics', metadata: { topic: 'Physics', year: 2023 } },
{ id: 'doc6', data: 'Blockchain technology', metadata: { topic: 'Crypto', year: 2024 } }
]
await brain.addMany(testData)
// Add relationships
await brain.relate({ from: 'doc1', to: 'doc2', type: 'related' })
await brain.relate({ from: 'doc2', to: 'doc3', type: 'related' })
await brain.relate({ from: 'doc3', to: 'doc4', type: 'related' })
triple = brain.getTripleIntelligence()
})
afterAll(async () => {
await brain?.close()
})
it('should return exact matches for field queries', async () => {
const results = await triple.find({
where: { topic: 'AI' },
limit: 10
})
expect(results).toHaveLength(4)
for (const result of results) {
expect(result.metadata.topic).toBe('AI')
}
})
it('should handle range queries correctly', async () => {
const results = await triple.find({
where: { year: { $gte: 2024 } },
limit: 10
})
expect(results).toHaveLength(3)
for (const result of results) {
expect(result.metadata.year).toBeGreaterThanOrEqual(2024)
}
})
it('should traverse graph relationships', async () => {
const results = await triple.find({
connected: { from: 'doc1', depth: 2 },
limit: 10
})
// Should find doc1, doc2 (depth 1), and doc3 (depth 2)
const ids = results.map(r => r.id)
expect(ids).toContain('doc1')
expect(ids).toContain('doc2')
expect(ids).toContain('doc3')
// Check depth values
const doc1Result = results.find(r => r.id === 'doc1')
const doc2Result = results.find(r => r.id === 'doc2')
const doc3Result = results.find(r => r.id === 'doc3')
expect(doc1Result?.depth).toBe(0)
expect(doc2Result?.depth).toBe(1)
expect(doc3Result?.depth).toBe(2)
})
it('should combine signals with proper fusion', async () => {
const results = await triple.find({
similar: 'deep learning',
where: { topic: 'AI' },
limit: 3
}, {
fusion: {
strategy: 'rrf',
weights: { vector: 0.7, field: 0.3 }
}
})
// doc2 should rank highest (matches both signals)
expect(results[0].id).toBe('doc2')
expect(results[0].fusionScore).toBeGreaterThan(0)
// All results should have AI topic
for (const result of results) {
expect(result.metadata.topic).toBe('AI')
}
})
})

View file

@ -389,14 +389,7 @@ describe('VirtualFileSystem - Production Tests', () => {
}) })
describe('Performance', () => { describe('Performance', () => {
it('should handle many files efficiently', async (ctx) => { it('should handle many files efficiently', async () => {
// Wall-clock budget assertion — belongs to the perf lane (npm run
// test:perf), not the correctness gate: 121ms alone but 16.5s under
// the gate's sibling-file contention, a flake the code never caused
// (same pattern as storage-batch-operations.test.ts's batch-vs-
// individual timing case).
ctx.skip(!process.env.BRAINY_PERF_LANE, 'wall-clock budget assertion — runs only under the perf lane (npm run test:perf)')
const dir = '/performance-test' const dir = '/performance-test'
await vfs.mkdir(dir) await vfs.mkdir(dir)