/** * Regression tests for the three advanced-API defects reported as BR-ADV-FEATURES-BUN: * * 1. Entity/concept extraction returned `[]` for entity-rich text. Root cause: the * SmartExtractor ensemble combined agreeing signals with a weighted *sum* compared against * an absolute gate, so a confident-but-low-weight signal was discarded whenever a * higher-weight signal voted a different (lower-confidence) type. Fixed by selecting and * gating on a normalized weighted *average*. * 2. `find({ aggregate })` rows did not expose the documented AggregateResult fields * (`groupKey`/`metrics`/`count`) at the top level, so callers saw "empty" rows. * 3. `find({ connected: { depth } })` ignored `depth`/`via` and returned only the 1-hop * neighbour. Fixed by delegating to the depth-aware `neighbors()` BFS. * * These run with REAL embeddings (no mocks) — the original failures were invisible under the * zero-vector mock embeddings used by the unit suite. */ import { describe, it, expect, beforeAll, afterAll } from 'vitest' import { Brainy } from '../../src/brainy.js' import { NounType, VerbType } from '../../src/types/graphTypes.js' describe('BR-ADV-FEATURES-BUN regression', () => { let brain: Brainy beforeAll(async () => { brain = new Brainy({ requireSubtype: false, storage: { type: 'memory' } }) await brain.init() // Warm the embedding model so the first real extraction isn't paying cold-start latency. await brain.embed('warmup') }) afterAll(async () => { await brain.close() }) describe('Bug 1 — entity extraction is not empty', () => { const text = 'Sarah Chen founded Acme Corp in New York' it('extractEntities returns the entity spans (was [])', async () => { const entities = await brain.extractEntities(text, { confidence: 0.1 }) expect(entities.length).toBeGreaterThan(0) const texts = entities.map(e => e.text) expect(texts).toContain('Sarah Chen') expect(texts).toContain('Acme Corp') }) it('does not bleed a neighbour\'s type indicator across candidates (R3)', async () => { // "Corp" belongs to "Acme Corp" — it must not flip "Sarah Chen" to Organization. const entities = await brain.extractEntities(text, { confidence: 0.1 }) const byText = (t: string) => entities.find(e => e.text === t) expect(byText('Sarah Chen')?.type).toBe(NounType.Person) expect(byText('Acme Corp')?.type).toBe(NounType.Organization) // (Type accuracy for "New York" → Location needs semantic/gazetteer support and is a // documented heuristic limitation, not the reported context-bleed bug.) }) it('a confident single-signal candidate classifies correctly in isolation', async () => { // "Acme Corp" carries a strong Organization indicator ("Corp") with no competing context. const entities = await brain.extractEntities('Acme Corp', { confidence: 0.6 }) expect(entities.length).toBeGreaterThan(0) expect(entities.some(e => e.type === NounType.Organization)).toBe(true) }) it('the confidence option actually controls the gate (no longer dead)', async () => { const loose = await brain.extractEntities(text, { confidence: 0.1 }) const strict = await brain.extractEntities(text, { confidence: 0.99 }) expect(loose.length).toBeGreaterThan(0) // Previously confidence had no effect because SmartExtractor applied a hardcoded 0.60 // floor; a near-1.0 threshold must now admit no fewer results than a loose one, and here // strictly fewer (nothing scores ≥ 0.99). expect(strict.length).toBeLessThanOrEqual(loose.length) }) }) describe('Bug 3 — multi-hop traversal honors depth', () => { let a: string let b: string let c: string beforeAll(async () => { a = await brain.add({ data: 'graph node A', type: NounType.Concept, metadata: { name: 'A' } }) b = await brain.add({ data: 'graph node B', type: NounType.Concept, metadata: { name: 'B' } }) c = await brain.add({ data: 'graph node C', type: NounType.Concept, metadata: { name: 'C' } }) await brain.relate({ from: a, to: b, type: VerbType.RelatedTo }) await brain.relate({ from: b, to: c, type: VerbType.RelatedTo }) }) const names = (rows: Array<{ metadata?: any }>) => rows.map(r => r.metadata?.name).filter(Boolean).sort() it('depth 1 returns only the immediate neighbour', async () => { const rows = await brain.find({ connected: { from: a, depth: 1, direction: 'out' } }) expect(names(rows)).toEqual(['B']) }) it('depth 2 reaches the second hop (was 1-hop only)', async () => { const rows = await brain.find({ connected: { from: a, depth: 2, direction: 'out' } }) expect(names(rows)).toEqual(['B', 'C']) }) it('depth 3 on a 2-edge chain still returns B and C', async () => { const rows = await brain.find({ connected: { from: a, depth: 3, direction: 'out' } }) expect(names(rows)).toEqual(['B', 'C']) }) }) describe('Bug 2 — find({ aggregate }) exposes AggregateResult fields', () => { beforeAll(async () => { brain.defineAggregate({ name: 'spend_by_cat', source: { type: NounType.Event }, groupBy: ['category'], metrics: { total: { op: 'sum', field: 'amount' }, count: { op: 'count' } } }) await brain.add({ data: 'coffee', type: NounType.Event, metadata: { category: 'food', amount: 5 } }) await brain.add({ data: 'lunch', type: NounType.Event, metadata: { category: 'food', amount: 12 } }) await brain.add({ data: 'bus', type: NounType.Event, metadata: { category: 'transit', amount: 3 } }) await brain.flush() await new Promise(r => setTimeout(r, 500)) // let materialization debounce settle }) it('rows carry top-level groupKey / metrics / count (was hidden under metadata)', async () => { const rows: any[] = await brain.find({ aggregate: 'spend_by_cat' }) expect(rows.length).toBe(2) const food = rows.find(r => r.groupKey?.category === 'food') const transit = rows.find(r => r.groupKey?.category === 'transit') expect(food).toBeDefined() expect(food.groupKey).toEqual({ category: 'food' }) expect(food.metrics.total).toBe(17) expect(food.count).toBe(2) expect(transit).toBeDefined() expect(transit.metrics.total).toBe(3) expect(transit.count).toBe(1) }) }) describe('R1 — aggregate backfills over a pre-populated store', () => { it('defineAggregate AFTER entities exist still returns correct rows', async () => { // The durable-storage case: a brain reopens pre-populated, then an aggregate is // defined. Write-time hooks never saw these entities, so without backfill this is []. const b: any = new Brainy({ requireSubtype: false, storage: { type: 'memory' } }) await b.init() await b.add({ data: 'a', type: NounType.Event, metadata: { category: 'food', amount: 5 } }) await b.add({ data: 'b', type: NounType.Event, metadata: { category: 'food', amount: 7 } }) await b.add({ data: 'c', type: NounType.Event, metadata: { category: 'transit', amount: 3 } }) await b.flush() b.defineAggregate({ name: 'after', source: { type: NounType.Event }, groupBy: ['category'], metrics: { total: { op: 'sum', field: 'amount' }, count: { op: 'count' } } }) const rows: any[] = await b.find({ aggregate: 'after' }) const food = rows.find(r => r.groupKey?.category === 'food') const transit = rows.find(r => r.groupKey?.category === 'transit') expect(food?.metrics.total).toBe(12) expect(food?.count).toBe(2) expect(transit?.count).toBe(1) await b.close() }) it('groupBy "noun" resolves to the entity type, not null', async () => { const b: any = new Brainy({ requireSubtype: false, storage: { type: 'memory' } }) await b.init() await b.add({ data: 'p', type: NounType.Person }) b.defineAggregate({ name: 'byNoun', source: { type: NounType.Person }, groupBy: ['noun'], metrics: { count: { op: 'count' } } }) const rows: any[] = await b.find({ aggregate: 'byNoun' }) expect(rows.length).toBe(1) expect(rows[0].groupKey.noun).toBe(NounType.Person) await b.close() }) }) describe('Traversal — via filter applies at every hop', () => { it('depth-2 via traversal follows the typed chain to the second hop', async () => { const b: any = new Brainy({ requireSubtype: false, storage: { type: 'memory' } }) await b.init() const a = await b.add({ data: 'a', type: NounType.Concept, metadata: { name: 'A' } }) const m = await b.add({ data: 'm', type: NounType.Concept, metadata: { name: 'M' } }) const z = await b.add({ data: 'z', type: NounType.Concept, metadata: { name: 'Z' } }) await b.relate({ from: a, to: m, type: VerbType.RelatedTo }) await b.relate({ from: m, to: z, type: VerbType.RelatedTo }) const viaMatch = await b.find({ connected: { from: a, depth: 2, direction: 'out', via: VerbType.RelatedTo } }) expect(viaMatch.map((x: any) => x.metadata?.name).sort()).toEqual(['M', 'Z']) // A non-matching verb type filters out hop 1 (and therefore everything) — proving the // filter is honored, not silently ignored as it was before. const viaMiss = await b.find({ connected: { from: a, depth: 2, direction: 'out', via: VerbType.Contains } }) expect(viaMiss.length).toBe(0) await b.close() }) }) describe('queryAggregate() + HAVING', () => { it('returns AggregateResult[] and filters groups by metric value', async () => { const b: any = new Brainy({ requireSubtype: false, storage: { type: 'memory' } }) await b.init() b.defineAggregate({ name: 'rev', source: { type: NounType.Event }, groupBy: ['cat'], metrics: { total: { op: 'sum', field: 'amt' }, count: { op: 'count' } } }) await b.add({ data: '1', type: NounType.Event, metadata: { cat: 'a', amt: 1500 } }) await b.add({ data: '2', type: NounType.Event, metadata: { cat: 'a', amt: 200 } }) await b.add({ data: '3', type: NounType.Event, metadata: { cat: 'b', amt: 50 } }) await b.flush() const all = await b.queryAggregate('rev', { orderBy: 'total', order: 'desc' }) expect(all.length).toBe(2) expect(all[0].groupKey.cat).toBe('a') // highest total first expect(all[0].metrics.total).toBe(1700) expect(all[0].count).toBe(2) // HAVING: only groups whose computed total exceeds 1000 const big = await b.queryAggregate('rev', { having: { total: { greaterThan: 1000 } } }) expect(big.length).toBe(1) expect(big[0].groupKey.cat).toBe('a') await b.close() }) }) describe('R2 — array-unnest groupBy (tag frequency)', () => { it('groups by each distinct array element; dedups per entity; skips empty', async () => { const b: any = new Brainy({ requireSubtype: false, storage: { type: 'memory' } }) await b.init() b.defineAggregate({ name: 'tags', source: { type: NounType.Concept }, groupBy: [{ field: 'tags', unnest: true }], metrics: { count: { op: 'count' } } }) await b.add({ data: 'a', type: NounType.Concept, metadata: { tags: ['ml', 'ai'] } }) await b.add({ data: 'b', type: NounType.Concept, metadata: { tags: ['ai', 'rust'] } }) await b.add({ data: 'c', type: NounType.Concept, metadata: { tags: ['ai'] } }) await b.add({ data: 'd', type: NounType.Concept, metadata: { tags: ['rust', 'rust'] } }) // dup → once await b.add({ data: 'e', type: NounType.Concept, metadata: {} }) // no tags → no group await b.flush() const rows = await b.queryAggregate('tags', { orderBy: 'count', order: 'desc' }) const freq = Object.fromEntries(rows.map((r: any) => [r.groupKey.tags, r.count])) expect(freq).toEqual({ ai: 3, rust: 2, ml: 1 }) await b.close() }) }) })