fix: flush all native providers on shutdown to prevent data loss

Shutdown/close/flush now properly flushes all 4 components in parallel:
metadataIndex, graphIndex, HNSW dirty nodes, and storage counts. Previously
only counts were flushed, causing native provider data loss on restart.

Also:
- Wire roaring, msgpack, entityIdMapper provider consumption from plugins
- Fix allOf filter O(n²) intersection → O(n) Set-based
- Fix ne/exists negation filter to use Set-based exclusion
- Add setMsgpackImplementation() swap in SSTable for native msgpack
- Add setRoaringImplementation() swap for native CRoaring bitmaps
- Add getAllIntIds() to EntityIdMapper for bitmap operations
- Remove TypeAwareHNSWIndex from default index creation path
- Export memory detection utilities from internals
- Clean up 26 permanently-skipped dead tests
This commit is contained in:
David Snelling 2026-02-01 16:23:49 -08:00
parent b87426409d
commit 773c5171c3
24 changed files with 297 additions and 1268 deletions

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@ -104,40 +104,6 @@ describe('brain.get() Metadata-Only Optimization (v5.11.1)', () => {
})
describe('Performance Comparison', () => {
// Performance test is flaky depending on system load - skip for CI
it.skip('metadata-only should be 75%+ faster than full entity', async () => {
// Warm up (populate caches)
await brain.get(entityId)
await brain.get(entityId, { includeVectors: true })
// Measure metadata-only performance
const metadataIterations = 100
const metadataStart = performance.now()
for (let i = 0; i < metadataIterations; i++) {
await brain.get(entityId)
}
const metadataTime = (performance.now() - metadataStart) / metadataIterations
// Measure full entity performance
const fullIterations = 100
const fullStart = performance.now()
for (let i = 0; i < fullIterations; i++) {
await brain.get(entityId, { includeVectors: true })
}
const fullTime = (performance.now() - fullStart) / fullIterations
// Calculate speedup
const speedup = ((fullTime - metadataTime) / fullTime) * 100
// MemoryStorage is already very fast, so speedup is less dramatic than FileSystemStorage
// FileSystemStorage: 76-81% speedup
// MemoryStorage: 15-30% speedup (less overhead to save)
expect(speedup).toBeGreaterThan(10)
// Log performance for manual verification
console.log(`[Performance] Metadata-only: ${metadataTime.toFixed(2)}ms, Full: ${fullTime.toFixed(2)}ms, Speedup: ${speedup.toFixed(1)}%`)
})
it('metadata-only should complete in <15ms (MemoryStorage)', async () => {
// Warm up
await brain.get(entityId)

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@ -459,29 +459,8 @@ describe('Brainy.add()', () => {
)
})
it.skip('should handle batch adds efficiently', async () => {
// NOTE: Flaky performance test - depends on system load
// Arrange
const count = 100
const params = Array.from({ length: count }, (_, i) =>
createAddParams({
data: `Batch entity ${i}`,
type: 'thing'
})
)
// Act
const start = performance.now()
const ids = await Promise.all(params.map(p => brain.add(p)))
const duration = performance.now() - start
// Assert
expect(ids).toHaveLength(count)
const opsPerSecond = (count / duration) * 1000
expect(opsPerSecond).toBeGreaterThan(100) // At least 100 ops/second
})
})
describe('caching behavior', () => {
it('should retrieve consistent entities', async () => {
// Arrange (v5.1.0: use valid UUID format)

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@ -36,83 +36,6 @@ describe('Brainy Batch Operations', () => {
}
})
// TODO: Investigate missing entities in batch operations - may be concurrency/timing issue
it.skip('should handle large batches efficiently', async () => {
const batchSize = 100
const entities = Array.from({ length: batchSize }, (_, i) => ({
data: `Entity ${i}`,
type: NounType.Thing,
metadata: { index: i, batch: true }
}))
const startTime = Date.now()
const result = await brain.addMany({ items: entities })
const duration = Date.now() - startTime
expect(result.successful).toHaveLength(batchSize)
expect(duration).toBeLessThan(10000) // 10 seconds for 100 embeddings is reasonable
// Verify a sample
const sampleEntity = await brain.get(result.successful[50])
expect(sampleEntity?.metadata?.index).toBe(50)
})
it.skip('should handle mixed entity types', async () => {
// NOTE: Test skipped - addMany order preservation is flaky (see d582069)
const entities = [
{ data: 'John Doe', type: NounType.Person, metadata: { role: 'developer' } },
{ data: 'TechCorp', type: NounType.Organization, metadata: { industry: 'tech' } },
{ data: 'San Francisco', type: NounType.Location, metadata: { country: 'USA' } },
{ data: 'Project Alpha', type: NounType.Project, metadata: { status: 'active' } }
]
const result = await brain.addMany({ items: entities })
expect(result.successful).toHaveLength(4)
// Verify different types were added correctly
const person = await brain.get(result.successful[0])
expect(person?.type).toBe(NounType.Person)
const org = await brain.get(result.successful[1])
expect(org?.type).toBe(NounType.Organization)
})
it.skip('should handle partial failures gracefully', async () => {
// NOTE: Test is flaky - fails intermittently with empty data validation
const entities = [
{ data: 'Valid Entity 1', type: NounType.Thing },
{ data: '', type: NounType.Thing }, // Invalid - empty data
{ data: 'Valid Entity 2', type: NounType.Thing }
]
try {
const result = await brain.addMany({ items: entities })
// Some implementations might skip invalid entries
expect(result.successful.length).toBeLessThanOrEqual(3)
} catch (error) {
// Or might throw an error
expect(error).toBeDefined()
}
})
it.skip('should maintain order of additions', async () => {
// NOTE: Test skipped - addMany order preservation is flaky (see d582069)
const entities = Array.from({ length: 10 }, (_, i) => ({
data: `Ordered Entity ${i}`,
type: NounType.Thing,
metadata: { order: i }
}))
const result = await brain.addMany({ items: entities })
// Verify order is maintained
for (let i = 0; i < result.successful.length; i++) {
const entity = await brain.get(result.successful[i])
expect(entity?.metadata?.order).toBe(i)
}
})
it('should generate embeddings for all entities', async () => {
const entities = [
{ data: 'Machine learning is fascinating', type: NounType.Concept },
@ -325,25 +248,6 @@ describe('Brainy Batch Operations', () => {
expect(sample).toBeNull()
})
// TODO: Investigate deleteMany not actually deleting entities - may be cache/consistency issue
it.skip('should ignore non-existent IDs', async () => {
const mixedIds = [
testIds[0],
'non-existent-1',
testIds[1],
'non-existent-2'
]
// Should not throw
await brain.deleteMany({ ids: mixedIds })
// Valid ones should be deleted
expect(await brain.get(testIds[0])).toBeNull()
expect(await brain.get(testIds[1])).toBeNull()
// Others should still exist
expect(await brain.get(testIds[2])).toBeDefined()
})
})
describe('relateMany - Batch Relationship Creation', () => {

View file

@ -1,359 +0,0 @@
import { describe, it, expect, beforeAll } from 'vitest'
import { Brainy } from '../../../src/brainy'
import { createAddParams } from '../../helpers/test-factory'
// v4.11.2: SKIPPED - brain.init() takes >60s causing timeout
// This is a pre-existing performance issue (also failed in v4.11.0)
// TODO: Investigate why Brainy initialization is so slow in this test context
describe.skip('Brainy.delete()', () => {
let brain: Brainy<any>
// v4.11.2: Use shared brain instance to prevent memory errors
// Creating new instance per test consumes too much memory (OOM errors)
beforeAll(async () => {
brain = new Brainy()
await brain.init()
}, 60000) // Increase timeout for initial setup
describe('success paths', () => {
it('should delete an existing entity', async () => {
// Arrange
const id = await brain.add(createAddParams({
data: 'Test entity',
type: 'thing',
metadata: { test: true }
}))
// Verify it exists
const before = await brain.get(id)
expect(before).not.toBeNull()
// Act
await brain.delete(id)
// Assert
const after = await brain.get(id)
expect(after).toBeNull()
})
it('should delete entity with relationships', async () => {
// TODO: Fix relationship cleanup - verbs are being found after deletion
// Possible causes: storage cache, metadata index, or graph index not updating
// Arrange - Create entities and relationships
const entity1 = await brain.add(createAddParams({ data: 'Entity 1' }))
const entity2 = await brain.add(createAddParams({ data: 'Entity 2' }))
const entity3 = await brain.add(createAddParams({ data: 'Entity 3' }))
await brain.relate({
from: entity1,
to: entity2,
type: 'relatedTo'
})
await brain.relate({
from: entity1,
to: entity3,
type: 'creates'
})
await brain.relate({
from: entity2,
to: entity1,
type: 'references'
})
// Act - Delete entity1
await brain.delete(entity1)
// Assert - Entity should be gone
const deleted = await brain.get(entity1)
expect(deleted).toBeNull()
// Entity2 and entity3 should still exist
const e2 = await brain.get(entity2)
const e3 = await brain.get(entity3)
expect(e2).not.toBeNull()
expect(e3).not.toBeNull()
// Relationships involving entity1 should be removed
const fromEntity1 = await brain.getRelations({ from: entity1 })
const toEntity1 = await brain.getRelations({ to: entity1 })
expect(fromEntity1).toHaveLength(0)
expect(toEntity1).toHaveLength(0)
// Other relationships should remain
const fromEntity2 = await brain.getRelations({ from: entity2 })
expect(fromEntity2.some(r => r.to === entity1)).toBe(false)
})
it.skip('should delete entity and clean up index', async () => {
// Arrange
const id = await brain.add(createAddParams({
data: 'Searchable entity',
metadata: { searchable: true }
}))
// Verify it's searchable
const beforeResults = await brain.find({
query: 'Searchable entity',
limit: 10
})
expect(beforeResults.some(r => r.entity.id === id)).toBe(true)
// Act
await brain.delete(id)
// Assert - Should not be in search results
const afterResults = await brain.find({
query: 'Searchable entity',
limit: 10
})
expect(afterResults.some(r => r.entity.id === id)).toBe(false)
})
it('should handle deleting multiple entities', async () => {
// Arrange
const ids = await Promise.all([
brain.add(createAddParams({ data: 'Entity 1' })),
brain.add(createAddParams({ data: 'Entity 2' })),
brain.add(createAddParams({ data: 'Entity 3' }))
])
// Act - Delete all
await Promise.all(ids.map(id => brain.delete(id)))
// Assert - All should be gone
const results = await Promise.all(ids.map(id => brain.get(id)))
expect(results.every(r => r === null)).toBe(true)
})
it('should handle deleting entity with bidirectional relationships', async () => {
// Arrange
const entity1 = await brain.add(createAddParams({ data: 'Entity 1' }))
const entity2 = await brain.add(createAddParams({ data: 'Entity 2' }))
await brain.relate({
from: entity1,
to: entity2,
type: 'friendOf',
bidirectional: true
})
// Verify both directions exist
const before1 = await brain.getRelations({ from: entity1 })
const before2 = await brain.getRelations({ from: entity2 })
expect(before1.some(r => r.to === entity2)).toBe(true)
expect(before2.some(r => r.to === entity1)).toBe(true)
// Act
await brain.delete(entity1)
// Assert - All relationships should be cleaned up
const after1 = await brain.getRelations({ from: entity1 })
const after2 = await brain.getRelations({ from: entity2 })
expect(after1).toHaveLength(0)
expect(after2.some(r => r.to === entity1)).toBe(false)
})
})
describe('error paths', () => {
it('should handle deleting non-existent entity', async () => {
// Act - Delete non-existent entity (should not throw)
const nonExistentId = 'fake-id-123'
// Should complete without error
await expect(brain.delete(nonExistentId)).resolves.not.toThrow()
})
it('should handle invalid ID format', async () => {
// Act & Assert
await expect(brain.delete('')).resolves.not.toThrow()
await expect(brain.delete(null as any)).resolves.not.toThrow()
await expect(brain.delete(undefined as any)).resolves.not.toThrow()
})
it('should handle double deletion', async () => {
// Arrange
const id = await brain.add(createAddParams({ data: 'Test' }))
// Act - Delete twice
await brain.delete(id)
await brain.delete(id) // Should not throw
// Assert
const result = await brain.get(id)
expect(result).toBeNull()
})
})
describe('edge cases', () => {
it('should handle deletion with circular relationships', async () => {
// TODO: Fix relationship cleanup - related to same issue as above
// Arrange - Create circular relationship
const entity1 = await brain.add(createAddParams({ data: 'Entity 1' }))
const entity2 = await brain.add(createAddParams({ data: 'Entity 2' }))
const entity3 = await brain.add(createAddParams({ data: 'Entity 3' }))
await brain.relate({ from: entity1, to: entity2, type: 'relatedTo' })
await brain.relate({ from: entity2, to: entity3, type: 'relatedTo' })
await brain.relate({ from: entity3, to: entity1, type: 'relatedTo' })
// Act
await brain.delete(entity2)
// Assert - Entity2 gone, others remain
expect(await brain.get(entity2)).toBeNull()
expect(await brain.get(entity1)).not.toBeNull()
expect(await brain.get(entity3)).not.toBeNull()
// Relationships involving entity2 should be gone
const relations1 = await brain.getRelations({ from: entity1 })
const relations3 = await brain.getRelations({ from: entity3 })
expect(relations1.some(r => r.to === entity2)).toBe(false)
expect(relations3.some(r => r.to === entity2)).toBe(false)
})
it('should handle concurrent deletions', async () => {
// Arrange
const ids = await Promise.all(
Array.from({ length: 10 }, (_, i) =>
brain.add(createAddParams({ data: `Entity ${i}` }))
)
)
// Act - Delete concurrently
await Promise.all(ids.map(id => brain.delete(id)))
// Assert - All should be deleted
const results = await Promise.all(ids.map(id => brain.get(id)))
expect(results.every(r => r === null)).toBe(true)
})
it('should maintain data integrity after deletion', async () => {
// Arrange
const keepId = await brain.add(createAddParams({
data: 'Keep this',
metadata: { important: true }
}))
const deleteIds = await Promise.all([
brain.add(createAddParams({ data: 'Delete 1' })),
brain.add(createAddParams({ data: 'Delete 2' })),
brain.add(createAddParams({ data: 'Delete 3' }))
])
// Create relationships
for (const deleteId of deleteIds) {
await brain.relate({
from: keepId,
to: deleteId,
type: 'relatedTo'
})
}
// Act - Delete some entities
await Promise.all(deleteIds.map(id => brain.delete(id)))
// Assert - Kept entity should be intact
const kept = await brain.get(keepId)
expect(kept).not.toBeNull()
expect(kept!.metadata.important).toBe(true)
// Relations to deleted entities should be gone
const relations = await brain.getRelations({ from: keepId })
expect(relations).toHaveLength(0)
})
})
describe('performance', () => {
it('should delete entities quickly', async () => {
// Arrange
const id = await brain.add(createAddParams({ data: 'Fast delete' }))
// Act & Assert
const start = Date.now()
await brain.delete(id)
const duration = Date.now() - start
expect(duration).toBeLessThan(50) // Should be very fast
})
it('should handle batch deletion efficiently', async () => {
// Arrange - Create many entities
const ids = await Promise.all(
Array.from({ length: 100 }, (_, i) =>
brain.add(createAddParams({ data: `Entity ${i}` }))
)
)
// Act
const start = Date.now()
await Promise.all(ids.map(id => brain.delete(id)))
const duration = Date.now() - start
// Assert
// Note: After fixing the relationship cleanup bug, deletes are slightly slower
// because we now properly fetch ALL relationships (not just first 100)
expect(duration).toBeLessThan(2000) // Should handle 100 deletes in under 2s
// Verify all deleted
const results = await Promise.all(ids.map(id => brain.get(id)))
expect(results.every(r => r === null)).toBe(true)
})
})
describe('consistency', () => {
it.skip('should properly invalidate cache after deletion', async () => {
// NOTE: Test skipped - flaky search timing issue (see commits 8476047, c64967d)
// Arrange
const id = await brain.add(createAddParams({
data: 'Cached entity',
metadata: { cached: true }
}))
// Do a search to potentially cache results
const before = await brain.find({ query: 'Cached entity' })
expect(before.some(r => r.entity.id === id)).toBe(true)
// Act
await brain.delete(id)
// Assert - Cache should be invalidated
const after = await brain.find({ query: 'Cached entity' })
expect(after.some(r => r.entity.id === id)).toBe(false)
})
it('should maintain consistency across operations', async () => {
// Arrange
const entity1 = await brain.add(createAddParams({ data: 'Entity 1' }))
const entity2 = await brain.add(createAddParams({ data: 'Entity 2' }))
await brain.relate({
from: entity1,
to: entity2,
type: 'relatedTo'
})
// Act - Update entity1, delete entity2
await brain.update({
id: entity1,
metadata: { updated: true },
merge: true
})
await brain.delete(entity2)
// Assert
const e1 = await brain.get(entity1)
expect(e1).not.toBeNull()
expect(e1!.metadata.updated).toBe(true)
const e2 = await brain.get(entity2)
expect(e2).toBeNull()
// Relations should be cleaned up
const relations = await brain.getRelations({ from: entity1 })
expect(relations.some(r => r.to === entity2)).toBe(false)
})
})
})

View file

@ -296,27 +296,8 @@ describe('Brainy.relate()', () => {
expect(relation!.metadata || {}).toMatchObject(specialMetadata)
})
it.skip('should handle concurrent relationship creation', async () => {
// NOTE: Test skipped - flaky due to race condition in duplicate detection (expected 10, got 9)
// Act - Create 10 relationships concurrently
const promises = Array.from({ length: 10 }, (_, i) =>
brain.relate({
from: entity1Id,
to: entity2Id,
type: 'relatedTo',
metadata: { index: i }
})
)
await Promise.all(promises)
// Assert
const relations = await brain.getRelations({ from: entity1Id })
const toEntity2 = relations.filter(r => r.to === entity2Id)
expect(toEntity2.length).toBe(10)
})
})
describe('performance', () => {
it('should create relationships quickly', async () => {
// Act & Assert

View file

@ -78,75 +78,4 @@ New York,location`
console.log('\n✅ Graph entities created by default!')
})
// TODO: Investigate "Source entity not found" error in VFS mkdir - likely cache/timing issue
it.skip('should NOT create graph entities when createEntities is explicitly false', async () => {
// Create a minimal CSV to import
const csvContent = `Name,Type
Alice,person
Bob,person`
const csvPath = path.join(testDir, 'test2.csv')
fs.mkdirSync(testDir, { recursive: true })
fs.writeFileSync(csvPath, csvContent)
// Import WITH createEntities: false
const result = await brain.import(csvPath, {
vfsPath: '/imports/test2',
groupBy: 'flat',
createEntities: false // Explicitly disable
})
console.log('\n📊 Import Result (createEntities: false):')
console.log(` Entities created: ${result.stats.graphNodesCreated}`)
console.log(` VFS files created: ${result.stats.vfsFilesCreated}`)
// Verify NO graph entities were created
expect(result.stats.graphNodesCreated).toBe(0)
// Verify VFS files were still created
expect(result.stats.vfsFilesCreated).toBeGreaterThan(0)
// Verify type filtering returns 0 (no graph entities)
const people = await brain.find({ type: NounType.Person, limit: 10 })
console.log(`\n🔍 Type Filtering:`)
console.log(` Person filter: ${people.length}`)
expect(people.length).toBe(0)
console.log('\n✅ Graph entities NOT created when explicitly disabled!')
})
// TODO: Investigate "Source entity not found" error in VFS mkdir - likely cache/timing issue
it.skip('should create graph entities when createEntities is explicitly true', async () => {
// Create a minimal CSV to import
const csvContent = `Name,Type
Charlie,person`
const csvPath = path.join(testDir, 'test3.csv')
fs.mkdirSync(testDir, { recursive: true })
fs.writeFileSync(csvPath, csvContent)
// Import WITH createEntities: true
const result = await brain.import(csvPath, {
vfsPath: '/imports/test3',
groupBy: 'flat',
createEntities: true // Explicitly enable
})
console.log('\n📊 Import Result (createEntities: true):')
console.log(` Entities created: ${result.stats.graphNodesCreated}`)
console.log(` VFS files created: ${result.stats.vfsFilesCreated}`)
// Verify graph entities were created
expect(result.stats.graphNodesCreated).toBeGreaterThan(0)
// Verify type filtering works
const people = await brain.find({ type: NounType.Person, limit: 10 })
console.log(`\n🔍 Type Filtering:`)
console.log(` Person filter: ${people.length}`)
expect(people.length).toBeGreaterThan(0)
console.log('\n✅ Graph entities created when explicitly enabled!')
})
})

View file

@ -88,7 +88,7 @@ describe('Lazy Vector Loading (B2)', () => {
})
it('should return correct top-k results in lazy mode', async () => {
for (let i = 0; i < 30; i++) {
for (let i = 0; i < 50; i++) {
const id = uuidv4()
const v = randomVector(dim)
await saveVector(storage, id, v)

View file

@ -111,31 +111,4 @@ describe('Import preserveSource Fix (v5.1.2)', () => {
fs.unlinkSync(jsonFilePath)
})
it.skip('should work with large text files', async () => {
// Create a large CSV (above inline threshold of 100KB)
const rows = []
for (let i = 0; i < 5000; i++) {
rows.push(`row${i},value${i},data${i}`)
}
const largeCsvContent = 'col1,col2,col3\n' + rows.join('\n')
const largeFilePath = path.join(tempDir, 'large.csv')
fs.writeFileSync(largeFilePath, largeCsvContent)
// Import large file
await brain.import(largeFilePath, {
format: 'csv',
vfsPath: '/large-file',
preserveSource: true,
enableNeuralExtraction: false,
createEntities: true
})
// Verify file was preserved
const content = await brain.vfs.readFile('/large-file/_source.csv')
expect(content.toString('utf-8')).toBe(largeCsvContent)
// Cleanup
fs.unlinkSync(largeFilePath)
})
})

View file

@ -21,165 +21,7 @@ describe('Domain and Time Clustering', () => {
await brain.init()
})
describe('clusterByDomain() - Field-based clustering', () => {
it.skip('should cluster entities by type field', async () => {
// Add entities of different types
await brain.add(createAddParams({
data: 'John Smith is a person',
type: NounType.Person
}))
await brain.add(createAddParams({
data: 'Jane Doe is also a person',
type: NounType.Person
}))
await brain.add(createAddParams({
data: 'Technical document about AI',
type: NounType.Document
}))
await brain.add(createAddParams({
data: 'Research paper on machine learning',
type: NounType.Document
}))
await brain.add(createAddParams({
data: 'Microsoft Corporation',
type: NounType.Organization
}))
// Cluster by type field
const clusters = await brain.neural().clusterByDomain('type', {
minClusterSize: 1,
maxClusters: 10
})
// Should have clusters for each type
expect(Array.isArray(clusters)).toBe(true)
expect(clusters.length).toBeGreaterThan(0)
// Verify domain values exist
const domains = new Set(clusters.map(c => c.domain))
expect(domains.has(NounType.Person) || domains.has('person')).toBe(true)
expect(domains.has(NounType.Document) || domains.has('document')).toBe(true)
})
it.skip('should cluster entities by metadata field', async () => {
// Add entities with category metadata
await brain.add(createAddParams({
data: 'JavaScript programming guide',
type: NounType.Document,
metadata: { category: 'programming' }
}))
await brain.add(createAddParams({
data: 'Python tutorial',
type: NounType.Document,
metadata: { category: 'programming' }
}))
await brain.add(createAddParams({
data: 'Chocolate cake recipe',
type: NounType.Document,
metadata: { category: 'cooking' }
}))
await brain.add(createAddParams({
data: 'Pasta preparation',
type: NounType.Document,
metadata: { category: 'cooking' }
}))
// Cluster by category field
const clusters = await brain.neural().clusterByDomain('category', {
minClusterSize: 1,
maxClusters: 5
})
expect(Array.isArray(clusters)).toBe(true)
expect(clusters.length).toBeGreaterThan(0)
// Verify categories are in domains
const domains = new Set(clusters.map(c => c.domain))
expect(domains.has('programming')).toBe(true)
expect(domains.has('cooking')).toBe(true)
})
it.skip('should handle entities without the specified field', async () => {
// Add entities with and without category
await brain.add(createAddParams({
data: 'Has category',
metadata: { category: 'tech' }
}))
await brain.add(createAddParams({
data: 'No category'
}))
const clusters = await brain.neural().clusterByDomain('category', {
minClusterSize: 1
})
expect(Array.isArray(clusters)).toBe(true)
// Should have 'tech' and 'unknown' domains
const domains = new Set(clusters.map(c => c.domain))
expect(domains.has('tech')).toBe(true)
expect(domains.has('unknown')).toBe(true)
})
})
describe('clusterByTime() - Temporal clustering', () => {
it.skip('should cluster entities by time windows', async () => {
const now = new Date()
const oneDayAgo = new Date(now.getTime() - 24 * 60 * 60 * 1000)
const oneWeekAgo = new Date(now.getTime() - 7 * 24 * 60 * 60 * 1000)
const oneMonthAgo = new Date(now.getTime() - 30 * 24 * 60 * 60 * 1000)
// Add entities with different timestamps
await brain.add(createAddParams({
data: 'Recent item 1',
metadata: { publishedAt: now.toISOString() }
}))
await brain.add(createAddParams({
data: 'Recent item 2',
metadata: { publishedAt: oneDayAgo.toISOString() }
}))
await brain.add(createAddParams({
data: 'Old item 1',
metadata: { publishedAt: oneWeekAgo.toISOString() }
}))
await brain.add(createAddParams({
data: 'Very old item',
metadata: { publishedAt: oneMonthAgo.toISOString() }
}))
// Define time windows
const timeWindows = [
{
start: new Date(now.getTime() - 2 * 24 * 60 * 60 * 1000), // Last 2 days
end: now,
label: 'Recent'
},
{
start: new Date(now.getTime() - 14 * 24 * 60 * 60 * 1000), // 2-14 days ago
end: new Date(now.getTime() - 2 * 24 * 60 * 60 * 1000),
label: 'This Week'
},
{
start: new Date(now.getTime() - 60 * 24 * 60 * 60 * 1000), // 14-60 days ago
end: new Date(now.getTime() - 14 * 24 * 60 * 60 * 1000),
label: 'Older'
}
]
// Cluster by time
const clusters = await brain.neural().clusterByTime('publishedAt', timeWindows, {
timeField: 'publishedAt',
windows: timeWindows
})
expect(Array.isArray(clusters)).toBe(true)
expect(clusters.length).toBeGreaterThan(0)
// Verify time windows are represented
const windowLabels = new Set(clusters.map(c => c.timeWindow?.label))
expect(windowLabels.size).toBeGreaterThan(0)
})
it('should cluster entities by createdAt timestamps', async () => {
// These will use the auto-generated createdAt timestamps
const id1 = await brain.add(createAddParams({

View file

@ -347,23 +347,6 @@ describe('Neural API - Production Testing', () => {
expect(Array.isArray(clusters)).toBe(true)
})
// TODO: Investigate "Cannot read properties of undefined (reading 'vector')" - clustering needs vector data
it.skip('should handle different clustering algorithms', async () => {
await brain.add(createAddParams({ data: 'Algorithm test 1' }))
await brain.add(createAddParams({ data: 'Algorithm test 2' }))
const algorithms = ['auto', 'semantic', 'hierarchical', 'kmeans', 'dbscan']
for (const algorithm of algorithms) {
const clusters = await brain.neural().clusters({
algorithm: algorithm as any,
minClusterSize: 1,
maxClusters: 5
})
expect(Array.isArray(clusters)).toBe(true)
}
})
})
describe('11. Streaming Clustering', () => {
@ -435,24 +418,6 @@ describe('Neural API - Production Testing', () => {
expect(duration).toBeLessThan(5000) // Should complete in under 5 seconds
})
// TODO: Investigate "Cannot read properties of undefined (reading 'vector')" - clustering needs vector data
it.skip('should handle concurrent neural operations', async () => {
await brain.add(createAddParams({ data: 'Concurrent test 1' }))
await brain.add(createAddParams({ data: 'Concurrent test 2' }))
const operations = [
brain.neural().similar('test1', 'test2'),
brain.neural().clusters({ maxClusters: 3 }),
brain.neural().outliers({ threshold: 0.8 })
]
const results = await Promise.all(operations)
expect(results.length).toBe(3)
expect(typeof results[0]).toBe('number') // similarity
expect(Array.isArray(results[1])).toBe(true) // clusters
expect(Array.isArray(results[2])).toBe(true) // outliers
})
})
describe('14. Configuration and Options', () => {