feat: expand secure assistant workflows
Harden runtime execution and add local knowledge, Smart Heartbeat, usage visibility, responsive product surfaces, and cross-platform packaging support. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
This commit is contained in:
lofyer
co-authored by
factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
parent
6ef1795b81
commit
b3fdf96962
@@ -31,6 +31,8 @@ import type {
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GraphStrategy,
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GraphEntity,
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GraphRelation,
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EmbeddingProvider,
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HybridSearchResult,
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KnowledgeBase,
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KnowledgeSource,
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SearchResult
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@@ -76,12 +78,15 @@ export type KnowledgeServiceOptions = {
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managedRoot: string
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extractStructured?: ExtractStructured
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urlImporter?: UrlImporter
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embeddingProvider?: EmbeddingProvider
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embeddingBatchSize?: number
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}
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const supportedExtensions = new Set<string>(supportedDocumentExtensions)
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const maximumFileBytes = 20 * 1024 * 1024
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const maximumSourceBytes = 500 * 1024 * 1024
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const maximumFilesPerSource = 2_000
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const maximumEmbeddingChunksPerBatch = 32
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function isInside(root: string, candidate: string): boolean {
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const path = relative(resolve(root), resolve(candidate))
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@@ -114,15 +119,30 @@ export class KnowledgeService {
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private readonly managedRoot: string
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private readonly extractStructured?: ExtractStructured
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private readonly urlImporter: UrlImporter
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private embeddingProvider?: EmbeddingProvider
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private readonly embeddingBatchSize: number
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private readonly watchers = new Map<string, FSWatcher>()
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private readonly syncTimers = new Map<string, ReturnType<typeof setTimeout>>()
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private readonly activeSyncs = new Map<string, Promise<void>>()
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private readonly lifecycleController = new AbortController()
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constructor(options: KnowledgeServiceOptions) {
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this.database = new KnowledgeDatabase(options.databasePath)
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this.managedRoot = resolve(options.managedRoot)
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this.extractStructured = options.extractStructured
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this.urlImporter = options.urlImporter ?? new UrlImporter()
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this.embeddingProvider = options.embeddingProvider
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const embeddingBatchSize = options.embeddingBatchSize ?? 16
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if (
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!Number.isSafeInteger(embeddingBatchSize) ||
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embeddingBatchSize < 1 ||
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embeddingBatchSize > maximumEmbeddingChunksPerBatch
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) {
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throw new RangeError(
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`embeddingBatchSize must be between 1 and ${maximumEmbeddingChunksPerBatch}`
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)
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}
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this.embeddingBatchSize = embeddingBatchSize
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}
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async initialize(): Promise<void> {
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@@ -142,6 +162,9 @@ export class KnowledgeService {
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}
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async dispose(): Promise<void> {
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this.lifecycleController.abort(
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new Error('Knowledge service is shutting down')
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)
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for (const timer of this.syncTimers.values()) {
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clearTimeout(timer)
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}
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@@ -154,6 +177,57 @@ export class KnowledgeService {
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this.database.close()
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}
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setEmbeddingProvider(provider?: EmbeddingProvider): Promise<void> {
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if (
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this.embeddingProvider === provider ||
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(this.embeddingProvider?.fingerprint !== undefined &&
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this.embeddingProvider.fingerprint === provider?.fingerprint)
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) {
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this.embeddingProvider = provider
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return Promise.resolve()
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}
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this.embeddingProvider = provider
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if (!provider) {
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return Promise.resolve()
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}
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const reindex = this.reindexEmbeddings(provider)
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this.activeSyncs.set('embedding-reindex', reindex)
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void reindex.then(
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() => {
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if (this.activeSyncs.get('embedding-reindex') === reindex) {
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this.activeSyncs.delete('embedding-reindex')
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}
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},
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() => {
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if (this.activeSyncs.get('embedding-reindex') === reindex) {
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this.activeSyncs.delete('embedding-reindex')
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}
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}
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)
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return reindex
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}
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private async reindexEmbeddings(
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provider: EmbeddingProvider
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): Promise<void> {
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for (const library of this.database.listKnowledgeBases(100)) {
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if (this.embeddingProvider !== provider) {
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return
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}
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for (const document of this.database.listDocuments(
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library.id,
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500
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)) {
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if (this.embeddingProvider !== provider) {
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return
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}
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if (document.metadata.status === 'ready') {
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await this.indexDocumentEmbeddings(document, provider)
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}
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}
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}
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}
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createLibrary(input: CreateKnowledgeBaseInput): KnowledgeBase {
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return this.database.createKnowledgeBase(input)
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}
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@@ -256,6 +330,76 @@ export class KnowledgeService {
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})
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}
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async searchHybrid(
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knowledgeBaseId: string,
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query: string,
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limit = 6,
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signal?: AbortSignal
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): Promise<HybridSearchResult[]> {
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const library = this.requireLibrary(knowledgeBaseId)
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const vector = await this.embedQuery(query, signal)
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return this.database.hybridSearch({
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knowledgeBaseId,
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query,
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limit,
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provider: vector ? this.embeddingProvider?.provider : undefined,
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model: vector ? this.embeddingProvider?.model : undefined,
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vector,
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graphEnabled: library.graphEnabled
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})
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}
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async searchHybridMany(
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knowledgeBaseIds: readonly string[],
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query: string,
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limitPerLibrary = 6,
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signal?: AbortSignal
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): Promise<
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Array<{ knowledgeBaseId: string; result: HybridSearchResult }>
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> {
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const vector = await this.embedQuery(query, signal)
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return knowledgeBaseIds.flatMap((knowledgeBaseId) => {
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const library = this.requireLibrary(knowledgeBaseId)
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return this.database
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.hybridSearch({
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knowledgeBaseId,
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query,
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limit: limitPerLibrary,
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provider: vector
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? this.embeddingProvider?.provider
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: undefined,
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model: vector ? this.embeddingProvider?.model : undefined,
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vector,
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graphEnabled: library.graphEnabled
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})
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.map((result) => ({ knowledgeBaseId, result }))
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})
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}
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private async embedQuery(
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query: string,
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signal?: AbortSignal
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): Promise<readonly number[] | undefined> {
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if (!this.embeddingProvider) {
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return undefined
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}
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const effectiveSignal = signal
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? AbortSignal.any([signal, this.lifecycleController.signal])
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: this.lifecycleController.signal
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try {
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const result = await this.embeddingProvider.embed(
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[query],
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effectiveSignal
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)
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return result.length === 1 ? result[0] : undefined
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} catch {
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if (effectiveSignal.aborted) {
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throw effectiveSignal.reason
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}
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return undefined
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}
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}
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async importPaths(
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knowledgeBaseId: string,
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selectedPaths: string[],
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@@ -343,7 +487,12 @@ export class KnowledgeService {
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const effectiveLibrary = graphStrategy
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? { ...library, graphStrategy }
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: library
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const result = await this.urlImporter.import(input, signal)
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const effectiveSignal = AbortSignal.any([
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signal,
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this.lifecycleController.signal,
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AbortSignal.timeout(60_000)
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])
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const result = await this.urlImporter.import(input, effectiveSignal)
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let source = this.database.upsertSource({
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id: sourceId,
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knowledgeBaseId,
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@@ -381,6 +530,7 @@ export class KnowledgeService {
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location: chunk.locator
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}))
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)
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await this.indexDocumentEmbeddings(document)
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await this.extractGraph(effectiveLibrary, document)
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source = this.database.upsertSource({
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...source,
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@@ -452,7 +602,7 @@ export class KnowledgeService {
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await this.importUrl(
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library.id,
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source.location,
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new AbortController().signal,
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this.lifecycleController.signal,
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source.id
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)
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return
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@@ -543,6 +693,7 @@ export class KnowledgeService {
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}))
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)
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this.database.removeEvidenceForDocument(document.id)
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await this.indexDocumentEmbeddings(document)
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await this.extractGraph(library, document)
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} catch (error) {
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failures.push(
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@@ -567,6 +718,83 @@ export class KnowledgeService {
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}
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}
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private async indexDocumentEmbeddings(
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document: Document,
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requestedProvider?: EmbeddingProvider
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): Promise<void> {
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const provider = requestedProvider ?? this.embeddingProvider
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if (!provider) {
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return
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}
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try {
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const chunks = this.database.listChunks(document.id, 10_000)
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const embeddings: Array<{
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chunkId: string
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contentChecksum: string
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vector: readonly number[]
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}> = []
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let expectedDimensions: number | undefined
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for (
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let offset = 0;
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offset < chunks.length;
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offset += this.embeddingBatchSize
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) {
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const batch = chunks.slice(offset, offset + this.embeddingBatchSize)
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const vectors = await provider.embed(
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batch.map((chunk) => chunk.content),
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this.lifecycleController.signal
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)
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if (vectors.length !== batch.length) {
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throw new Error('Embedding provider returned an invalid result count')
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}
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for (let index = 0; index < batch.length; index += 1) {
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const chunk = batch[index]
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const vector = vectors[index]
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if (!chunk || !vector) {
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throw new Error('Embedding provider returned an incomplete batch')
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}
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if (expectedDimensions === undefined) {
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expectedDimensions = vector.length
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} else if (vector.length !== expectedDimensions) {
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throw new Error('Embedding provider returned inconsistent dimensions')
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}
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embeddings.push({
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chunkId: chunk.id,
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contentChecksum: createHash('sha256')
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.update(chunk.content)
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.digest('hex'),
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vector
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})
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}
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}
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if (this.embeddingProvider !== provider) {
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return
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}
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this.database.replaceDocumentEmbeddings(
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document.id,
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provider.provider,
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provider.model,
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embeddings
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)
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} catch (error) {
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if (this.lifecycleController.signal.aborted) {
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return
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}
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const message =
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error instanceof Error ? error.message : 'Embedding indexing failed'
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try {
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this.database.recordEmbeddingIndexError(
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document.id,
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provider.provider,
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provider.model,
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message.slice(0, 2_000)
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)
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} catch {
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// FTS indexing is authoritative; embedding diagnostics are best effort.
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}
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}
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}
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private async extractGraph(
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library: KnowledgeBase,
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document: Document
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