a801c7e721
Implements ruvLLM integration with multi-temporal learning: P0 - Foundation: - Extended config schema for ruvllm options - TrajectoryRecorder for search pattern recording - ContextInjector for agent prompt enrichment - SONA engine integration with trajectory support P1 - Learning Core: - PatternStore with K-means++ clustering - Search re-ranking using learned patterns - GraphExpander for automatic edge discovery - ruvector_recall tool (pattern-aware recall) P2 - Adaptive Loops: - BackgroundLoop (30s interval pattern clustering) - InstantLoop (real-time feedback processing) - RelationshipInferrer (entity extraction) - ruvector_learn tool (manual knowledge injection) P3 - Advanced Features: - EWCConsolidator (catastrophic forgetting prevention) - ConsolidationLoop (deep pattern analysis) - GraphAttention (multi-head context aggregation) - Pattern export/import CLI commands Tests: 275 passing (229 + 46 new) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
4823 lines
147 KiB
TypeScript
4823 lines
147 KiB
TypeScript
/**
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* Memory Ruvector Plugin Tests
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*
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* Tests the ruvector memory plugin functionality including:
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* - RuvectorClient operations (connect, insert, search, delete)
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* - RuvectorService lifecycle
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* - RuvectorDatabase (with in-memory fallback)
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* - EmbeddingProvider
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* - MessageBatcher and hooks
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* - Configuration parsing
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* - Search tool
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*/
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import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
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// =============================================================================
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// Mock ruvector package
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// =============================================================================
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const mockVectorDb = {
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insert: vi.fn().mockResolvedValue(undefined),
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insertBatch: vi.fn().mockResolvedValue(["id-1", "id-2"]),
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search: vi.fn().mockResolvedValue([]),
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get: vi.fn().mockResolvedValue(null),
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delete: vi.fn().mockResolvedValue(true),
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len: vi.fn().mockResolvedValue(0),
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isEmpty: vi.fn().mockResolvedValue(true),
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close: vi.fn().mockResolvedValue(undefined),
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};
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// Mock SONA engine for self-learning tests
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const mockSonaEngine = {
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setEnabled: vi.fn(),
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isEnabled: vi.fn().mockReturnValue(true),
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beginTrajectory: vi.fn().mockReturnValue("traj-1"),
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addStep: vi.fn(),
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endTrajectory: vi.fn(),
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applyMicroLora: vi.fn(),
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findPatterns: vi.fn().mockReturnValue([]),
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getStats: vi.fn().mockReturnValue({ patternsLearned: 0 }),
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forceLearn: vi.fn(),
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};
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// Mock CodeGraph for graph tests
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const mockCodeGraph = {
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createNode: vi.fn().mockResolvedValue(undefined),
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createEdge: vi.fn().mockResolvedValue(undefined),
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cypher: vi.fn().mockResolvedValue({ columns: [], rows: [] }),
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neighbors: vi.fn().mockResolvedValue([]),
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};
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// Mock RuvectorLayer for GNN tests
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const mockRuvectorLayer = {};
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// Create mock class constructors
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class MockVectorDb {
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insert = mockVectorDb.insert;
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insertBatch = mockVectorDb.insertBatch;
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search = mockVectorDb.search;
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get = mockVectorDb.get;
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delete = mockVectorDb.delete;
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len = mockVectorDb.len;
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isEmpty = mockVectorDb.isEmpty;
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close = mockVectorDb.close;
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}
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class MockSonaEngine {
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static withConfig = vi.fn().mockImplementation(() => new MockSonaEngine());
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setEnabled = mockSonaEngine.setEnabled;
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isEnabled = mockSonaEngine.isEnabled;
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beginTrajectory = mockSonaEngine.beginTrajectory;
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addStep = mockSonaEngine.addStep;
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endTrajectory = mockSonaEngine.endTrajectory;
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applyMicroLora = mockSonaEngine.applyMicroLora;
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findPatterns = mockSonaEngine.findPatterns;
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getStats = mockSonaEngine.getStats;
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forceLearn = mockSonaEngine.forceLearn;
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}
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class MockCodeGraph {
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createNode = mockCodeGraph.createNode;
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createEdge = mockCodeGraph.createEdge;
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cypher = mockCodeGraph.cypher;
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neighbors = mockCodeGraph.neighbors;
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}
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class MockRuvectorLayer {}
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vi.mock("ruvector", () => ({
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VectorDb: MockVectorDb,
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VectorDB: MockVectorDb,
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SonaEngine: MockSonaEngine,
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CodeGraph: MockCodeGraph,
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RuvectorLayer: MockRuvectorLayer,
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default: {
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VectorDb: MockVectorDb,
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VectorDB: MockVectorDb,
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},
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}));
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// =============================================================================
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// Test Helpers
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// =============================================================================
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function createMockLogger() {
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return {
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debug: vi.fn(),
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info: vi.fn(),
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warn: vi.fn(),
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error: vi.fn(),
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};
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}
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function createFakeApi(overrides: Record<string, unknown> = {}) {
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const registeredTools: Array<{ tool: unknown; opts?: Record<string, unknown> }> = [];
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const registeredServices: Array<Record<string, unknown>> = [];
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const registeredClis: Array<{ registrar: unknown; opts?: Record<string, unknown> }> = [];
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const registeredHooks: Record<string, Array<{ handler: unknown; opts?: unknown }>> = {};
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return {
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id: "memory-ruvector",
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name: "Memory (ruvector)",
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source: "test",
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config: {},
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pluginConfig: {
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dbPath: "/tmp/test-ruvector-db",
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dimension: 1536,
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metric: "cosine",
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embedding: {
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provider: "openai",
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apiKey: "test-api-key",
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model: "text-embedding-3-small",
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},
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hooks: {
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enabled: true,
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indexInbound: true,
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indexOutbound: true,
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indexAgentResponses: true,
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batchSize: 10,
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debounceMs: 500,
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},
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},
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runtime: { version: "test" },
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logger: createMockLogger(),
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registerTool: vi.fn((tool, opts) => {
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registeredTools.push({ tool, opts });
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}),
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registerCli: vi.fn((registrar, opts) => {
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registeredClis.push({ registrar, opts });
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}),
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registerService: vi.fn((service) => {
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registeredServices.push(service);
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}),
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on: vi.fn((hookName: string, handler: unknown, opts?: unknown) => {
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if (!registeredHooks[hookName]) registeredHooks[hookName] = [];
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registeredHooks[hookName].push({ handler, opts });
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}),
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resolvePath: vi.fn((p: string) => p),
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_registeredTools: registeredTools,
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_registeredServices: registeredServices,
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_registeredClis: registeredClis,
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_registeredHooks: registeredHooks,
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...overrides,
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};
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}
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// =============================================================================
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// RuvectorClient Tests
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// =============================================================================
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describe("RuvectorClient", () => {
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let RuvectorClient: typeof import("./client.js").RuvectorClient;
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beforeEach(async () => {
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vi.clearAllMocks();
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const module = await import("./client.js");
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RuvectorClient = module.RuvectorClient;
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});
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afterEach(() => {
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vi.restoreAllMocks();
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});
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it("connects to the database", async () => {
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const logger = createMockLogger();
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const client = new RuvectorClient(
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{ dimension: 1536, storagePath: "/tmp/test", metric: "cosine" },
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logger,
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);
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await client.connect();
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expect(client.isConnected()).toBe(true);
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expect(logger.info).toHaveBeenCalledWith(expect.stringContaining("connecting"));
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});
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it("throws ALREADY_CONNECTED when connecting twice", async () => {
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const logger = createMockLogger();
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const client = new RuvectorClient({ dimension: 1536 }, logger);
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await client.connect();
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await expect(client.connect()).rejects.toThrow(/already connected/i);
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});
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it("disconnects cleanly", async () => {
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const logger = createMockLogger();
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const client = new RuvectorClient({ dimension: 1536 }, logger);
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await client.connect();
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await client.disconnect();
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expect(client.isConnected()).toBe(false);
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expect(logger.info).toHaveBeenCalledWith(expect.stringContaining("disconnected"));
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});
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it("inserts vectors with generated UUID", async () => {
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const logger = createMockLogger();
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const client = new RuvectorClient({ dimension: 1536 }, logger);
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await client.connect();
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const id = await client.insert({
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vector: new Array(1536).fill(0.1),
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metadata: { text: "test memory" },
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});
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expect(id).toMatch(/^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$/i);
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expect(mockVectorDb.insert).toHaveBeenCalled();
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});
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it("throws INVALID_DIMENSION for mismatched vector size", async () => {
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const logger = createMockLogger();
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const client = new RuvectorClient({ dimension: 1536 }, logger);
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await client.connect();
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await expect(
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client.insert({
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vector: new Array(768).fill(0.1), // Wrong dimension
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metadata: { text: "test" },
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}),
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).rejects.toThrow(/dimension mismatch/i);
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});
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it("validates ID is non-empty before delete", async () => {
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const logger = createMockLogger();
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const client = new RuvectorClient({ dimension: 1536 }, logger);
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await client.connect();
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await expect(client.delete("")).rejects.toThrow(/invalid id/i);
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// Note: Non-UUID strings are accepted since custom IDs are allowed on insert
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});
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it("accepts valid UUID for delete", async () => {
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const logger = createMockLogger();
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const client = new RuvectorClient({ dimension: 1536 }, logger);
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await client.connect();
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const validUuid = "550e8400-e29b-41d4-a716-446655440000";
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const result = await client.delete(validUuid);
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expect(result).toBe(true);
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expect(mockVectorDb.delete).toHaveBeenCalledWith(validUuid);
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});
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it("throws NOT_CONNECTED when operating without connection", async () => {
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const logger = createMockLogger();
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const client = new RuvectorClient({ dimension: 1536 }, logger);
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await expect(
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client.insert({ vector: [], metadata: { text: "" } }),
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).rejects.toThrow(/not connected/i);
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});
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it("returns stats including connection status", async () => {
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const logger = createMockLogger();
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const client = new RuvectorClient({ dimension: 1536, metric: "euclidean" }, logger);
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const statsDisconnected = await client.stats();
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expect(statsDisconnected.connected).toBe(false);
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expect(statsDisconnected.dimension).toBe(1536);
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expect(statsDisconnected.metric).toBe("euclidean");
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await client.connect();
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const statsConnected = await client.stats();
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expect(statsConnected.connected).toBe(true);
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});
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});
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// =============================================================================
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// RuvectorService Tests
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// =============================================================================
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describe("RuvectorService", () => {
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let RuvectorService: typeof import("./service.js").RuvectorService;
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beforeEach(async () => {
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vi.clearAllMocks();
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const module = await import("./service.js");
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RuvectorService = module.RuvectorService;
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});
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it("starts and connects the client", async () => {
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const logger = createMockLogger();
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const service = new RuvectorService({ dimension: 1536 }, logger);
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await service.start();
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expect(service.isRunning()).toBe(true);
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expect(logger.warn).not.toHaveBeenCalled();
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});
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it("warns when started twice", async () => {
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const logger = createMockLogger();
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const service = new RuvectorService({ dimension: 1536 }, logger);
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await service.start();
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await service.start(); // Second start
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expect(logger.warn).toHaveBeenCalledWith(expect.stringContaining("already started"));
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});
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it("stops and disconnects", async () => {
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const logger = createMockLogger();
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const service = new RuvectorService({ dimension: 1536 }, logger);
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await service.start();
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await service.stop();
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expect(service.isRunning()).toBe(false);
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});
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it("throws when getting client before start", async () => {
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const logger = createMockLogger();
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const service = new RuvectorService({ dimension: 1536 }, logger);
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expect(() => service.getClient()).toThrow(/not started/i);
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});
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it("returns client after start", async () => {
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const logger = createMockLogger();
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const service = new RuvectorService({ dimension: 1536 }, logger);
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await service.start();
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const client = service.getClient();
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expect(client).toBeDefined();
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expect(client.isConnected()).toBe(true);
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});
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});
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// =============================================================================
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// Configuration Schema Tests
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// =============================================================================
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describe("ruvectorConfigSchema", () => {
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let ruvectorConfigSchema: typeof import("./config.js").ruvectorConfigSchema;
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let dimensionForModel: typeof import("./config.js").dimensionForModel;
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beforeEach(async () => {
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vi.clearAllMocks();
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const module = await import("./config.js");
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ruvectorConfigSchema = module.ruvectorConfigSchema;
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dimensionForModel = module.dimensionForModel;
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});
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it("parses valid config", () => {
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const config = ruvectorConfigSchema.parse({
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embedding: {
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provider: "openai",
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apiKey: "sk-test",
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model: "text-embedding-3-small",
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},
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});
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expect(config.embedding.provider).toBe("openai");
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expect(config.embedding.apiKey).toBe("sk-test");
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expect(config.dimension).toBe(1536);
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expect(config.metric).toBe("cosine");
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});
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it("throws when embedding config is missing", () => {
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expect(() => ruvectorConfigSchema.parse({})).toThrow(/embedding config is required/i);
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});
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it("throws when apiKey is missing for non-local provider", () => {
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expect(() =>
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ruvectorConfigSchema.parse({
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embedding: { provider: "openai" },
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}),
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).toThrow(/apiKey is required/i);
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});
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it("allows missing apiKey for local provider", () => {
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const config = ruvectorConfigSchema.parse({
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embedding: { provider: "local", baseUrl: "http://localhost:8080" },
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});
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expect(config.embedding.provider).toBe("local");
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expect(config.embedding.apiKey).toBeUndefined();
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});
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it("resolves environment variables in apiKey", () => {
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process.env.TEST_RUVECTOR_KEY = "resolved-key";
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const config = ruvectorConfigSchema.parse({
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embedding: {
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provider: "openai",
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apiKey: "${TEST_RUVECTOR_KEY}",
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},
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});
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expect(config.embedding.apiKey).toBe("resolved-key");
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delete process.env.TEST_RUVECTOR_KEY;
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});
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it("throws on missing environment variable", () => {
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expect(() =>
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ruvectorConfigSchema.parse({
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embedding: {
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provider: "openai",
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apiKey: "${NONEXISTENT_VAR}",
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},
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}),
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).toThrow(/not set/i);
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});
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it("validates metric values", () => {
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expect(() =>
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ruvectorConfigSchema.parse({
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embedding: { provider: "openai", apiKey: "key" },
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metric: "invalid",
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}),
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).toThrow(/invalid metric/i);
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});
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it("returns correct dimensions for known models", () => {
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expect(dimensionForModel("text-embedding-3-small")).toBe(1536);
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expect(dimensionForModel("text-embedding-3-large")).toBe(3072);
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expect(dimensionForModel("voyage-3")).toBe(1024);
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expect(dimensionForModel("nomic-embed-text")).toBe(768);
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expect(dimensionForModel("unknown-model")).toBe(1536); // Default
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});
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it("parses hooks config with defaults", () => {
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const config = ruvectorConfigSchema.parse({
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embedding: { provider: "openai", apiKey: "key" },
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});
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expect(config.hooks.enabled).toBe(true);
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expect(config.hooks.indexInbound).toBe(true);
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expect(config.hooks.indexOutbound).toBe(true);
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expect(config.hooks.batchSize).toBe(10);
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expect(config.hooks.debounceMs).toBe(500);
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});
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});
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|
|
// =============================================================================
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|
// EmbeddingProvider Tests
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|
// =============================================================================
|
|
|
|
describe("EmbeddingProvider", () => {
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let OpenAICompatibleEmbeddings: typeof import("./embeddings.js").OpenAICompatibleEmbeddings;
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|
let createEmbeddingProvider: typeof import("./embeddings.js").createEmbeddingProvider;
|
|
|
|
beforeEach(async () => {
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|
vi.clearAllMocks();
|
|
global.fetch = vi.fn();
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|
const module = await import("./embeddings.js");
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|
OpenAICompatibleEmbeddings = module.OpenAICompatibleEmbeddings;
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createEmbeddingProvider = module.createEmbeddingProvider;
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});
|
|
|
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afterEach(() => {
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vi.restoreAllMocks();
|
|
});
|
|
|
|
it("creates OpenAI provider with correct base URL", () => {
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|
const provider = createEmbeddingProvider(
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|
{ provider: "openai", apiKey: "sk-test", model: "text-embedding-3-small" },
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1536,
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);
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|
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expect(provider.dimension).toBe(1536);
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|
});
|
|
|
|
it("creates Voyage provider with correct base URL", () => {
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|
const provider = createEmbeddingProvider(
|
|
{ provider: "voyage", apiKey: "voyage-test", model: "voyage-3" },
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1024,
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|
);
|
|
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expect(provider.dimension).toBe(1024);
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|
});
|
|
|
|
it("throws for local provider without baseUrl", () => {
|
|
expect(() =>
|
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createEmbeddingProvider({ provider: "local", model: "local-model" }, 768),
|
|
).toThrow(/base URL/i);
|
|
});
|
|
|
|
it("embeds text via API call", async () => {
|
|
(global.fetch as ReturnType<typeof vi.fn>).mockResolvedValueOnce({
|
|
ok: true,
|
|
json: async () => ({
|
|
data: [{ index: 0, embedding: new Array(1536).fill(0.1) }],
|
|
}),
|
|
});
|
|
|
|
const provider = new OpenAICompatibleEmbeddings({
|
|
baseUrl: "https://api.openai.com/v1",
|
|
apiKey: "sk-test",
|
|
model: "text-embedding-3-small",
|
|
dimension: 1536,
|
|
});
|
|
|
|
const embedding = await provider.embed("test text");
|
|
|
|
expect(embedding).toHaveLength(1536);
|
|
expect(global.fetch).toHaveBeenCalledWith(
|
|
"https://api.openai.com/v1/embeddings",
|
|
expect.objectContaining({
|
|
method: "POST",
|
|
headers: expect.objectContaining({
|
|
Authorization: "Bearer sk-test",
|
|
}),
|
|
}),
|
|
);
|
|
});
|
|
|
|
it("handles API errors gracefully", async () => {
|
|
(global.fetch as ReturnType<typeof vi.fn>).mockResolvedValueOnce({
|
|
ok: false,
|
|
status: 401,
|
|
text: async () => "Unauthorized",
|
|
});
|
|
|
|
const provider = new OpenAICompatibleEmbeddings({
|
|
baseUrl: "https://api.openai.com/v1",
|
|
apiKey: "invalid",
|
|
model: "text-embedding-3-small",
|
|
dimension: 1536,
|
|
});
|
|
|
|
await expect(provider.embed("test")).rejects.toThrow(/401/);
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// RuvectorDatabase Tests
|
|
// =============================================================================
|
|
|
|
describe("RuvectorDatabase", () => {
|
|
let RuvectorDatabase: typeof import("./db.js").RuvectorDatabase;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./db.js");
|
|
RuvectorDatabase = module.RuvectorDatabase;
|
|
});
|
|
|
|
it("inserts and retrieves document count", async () => {
|
|
const db = new RuvectorDatabase("/tmp/test-db", {
|
|
dimension: 1536,
|
|
metric: "cosine",
|
|
});
|
|
|
|
const id = await db.insert({
|
|
content: "test message",
|
|
vector: new Array(1536).fill(0.1),
|
|
direction: "inbound",
|
|
channel: "telegram",
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
expect(id).toMatch(/^[0-9a-f-]{36}$/i);
|
|
});
|
|
|
|
it("performs batch insert", async () => {
|
|
const db = new RuvectorDatabase("/tmp/test-db", {
|
|
dimension: 1536,
|
|
metric: "cosine",
|
|
});
|
|
|
|
const ids = await db.insertBatch([
|
|
{
|
|
content: "message 1",
|
|
vector: new Array(1536).fill(0.1),
|
|
direction: "inbound",
|
|
channel: "discord",
|
|
timestamp: Date.now(),
|
|
},
|
|
{
|
|
content: "message 2",
|
|
vector: new Array(1536).fill(0.2),
|
|
direction: "outbound",
|
|
channel: "discord",
|
|
timestamp: Date.now(),
|
|
},
|
|
]);
|
|
|
|
expect(ids).toHaveLength(2);
|
|
});
|
|
|
|
it("calculates cosine similarity correctly", async () => {
|
|
// Test with in-memory fallback to verify similarity calculation
|
|
const db = new RuvectorDatabase("/tmp/nonexistent", {
|
|
dimension: 3,
|
|
metric: "cosine",
|
|
});
|
|
|
|
// Insert a document with a known vector
|
|
await db.insert({
|
|
content: "test",
|
|
vector: [1, 0, 0],
|
|
direction: "inbound",
|
|
channel: "test",
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
// Search with identical vector should have high score
|
|
const results = await db.search([1, 0, 0], { limit: 1 });
|
|
|
|
// With mocked ruvector, this will use in-memory if ruvector fails to init
|
|
expect(results).toBeDefined();
|
|
});
|
|
|
|
it("closes cleanly", async () => {
|
|
const db = new RuvectorDatabase("/tmp/test-db", {
|
|
dimension: 1536,
|
|
metric: "cosine",
|
|
});
|
|
|
|
await db.close();
|
|
// Should not throw
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// Hooks Tests
|
|
// =============================================================================
|
|
|
|
describe("MessageBatcher", () => {
|
|
let MessageBatcher: typeof import("./hooks.js").MessageBatcher;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
vi.useFakeTimers();
|
|
const module = await import("./hooks.js");
|
|
MessageBatcher = module.MessageBatcher;
|
|
});
|
|
|
|
afterEach(() => {
|
|
vi.useRealTimers();
|
|
});
|
|
|
|
it("batches messages and flushes on batch size", async () => {
|
|
const mockDb = {
|
|
insertBatch: vi.fn().mockResolvedValue(["id-1", "id-2"]),
|
|
};
|
|
const mockEmbeddings = {
|
|
embed: vi.fn().mockResolvedValue(new Array(1536).fill(0.1)),
|
|
embedBatch: vi.fn().mockResolvedValue([new Array(1536).fill(0.1)]),
|
|
dimension: 1536,
|
|
};
|
|
const logger = createMockLogger();
|
|
|
|
const batcher = new MessageBatcher(mockDb as any, mockEmbeddings, {
|
|
batchSize: 2,
|
|
debounceMs: 1000,
|
|
logger,
|
|
});
|
|
|
|
// Queue 2 messages (triggers flush at batch size)
|
|
const p1 = batcher.queue({
|
|
content: "msg 1",
|
|
direction: "inbound",
|
|
channel: "test",
|
|
timestamp: Date.now(),
|
|
});
|
|
const p2 = batcher.queue({
|
|
content: "msg 2",
|
|
direction: "inbound",
|
|
channel: "test",
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
// Allow flush to complete
|
|
await vi.runAllTimersAsync();
|
|
await Promise.all([p1, p2]);
|
|
|
|
// Uses embedBatch for efficiency (one call for all messages)
|
|
expect(mockEmbeddings.embedBatch).toHaveBeenCalledTimes(1);
|
|
expect(mockDb.insertBatch).toHaveBeenCalledTimes(1);
|
|
});
|
|
|
|
it("flushes on debounce timeout", async () => {
|
|
const mockDb = {
|
|
insertBatch: vi.fn().mockResolvedValue(["id-1"]),
|
|
};
|
|
const mockEmbeddings = {
|
|
embed: vi.fn().mockResolvedValue(new Array(1536).fill(0.1)),
|
|
embedBatch: vi.fn().mockResolvedValue([new Array(1536).fill(0.1)]),
|
|
dimension: 1536,
|
|
};
|
|
const logger = createMockLogger();
|
|
|
|
const batcher = new MessageBatcher(mockDb as any, mockEmbeddings, {
|
|
batchSize: 10, // Large batch size
|
|
debounceMs: 500,
|
|
logger,
|
|
});
|
|
|
|
// Queue 1 message (below batch size)
|
|
const p = batcher.queue({
|
|
content: "msg 1",
|
|
direction: "inbound",
|
|
channel: "test",
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
// Advance timer past debounce
|
|
await vi.advanceTimersByTimeAsync(600);
|
|
await p;
|
|
|
|
expect(mockDb.insertBatch).toHaveBeenCalledTimes(1);
|
|
});
|
|
});
|
|
|
|
describe("Content filtering", () => {
|
|
// Note: shouldIndex is not exported, but we test its behavior indirectly
|
|
// through the MessageBatcher. These tests document the expected filtering rules.
|
|
|
|
it("documents short message filtering rule (< 5 chars)", () => {
|
|
// Messages under MIN_CONTENT_LENGTH (5) should be filtered
|
|
const shortMessages = ["hi", "ok", "yes", "no"];
|
|
for (const msg of shortMessages) {
|
|
expect(msg.length).toBeLessThan(5);
|
|
}
|
|
});
|
|
|
|
it("documents system marker filtering rule", () => {
|
|
// Messages containing system markers should be filtered
|
|
const systemMessages = [
|
|
"<relevant-memories>injected</relevant-memories>",
|
|
"<system>instructions</system>",
|
|
];
|
|
for (const msg of systemMessages) {
|
|
expect(msg.includes("<relevant-memories>") || msg.includes("<system>")).toBe(true);
|
|
}
|
|
});
|
|
|
|
it("documents command filtering rule (starts with /)", () => {
|
|
// Messages starting with / should be filtered as control commands
|
|
const commands = ["/help", "/status", "/config"];
|
|
for (const cmd of commands) {
|
|
expect(cmd.startsWith("/")).toBe(true);
|
|
}
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// Tool Tests
|
|
// =============================================================================
|
|
|
|
describe("createRuvectorSearchTool", () => {
|
|
let createRuvectorSearchTool: typeof import("./tool.js").createRuvectorSearchTool;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./tool.js");
|
|
createRuvectorSearchTool = module.createRuvectorSearchTool;
|
|
});
|
|
|
|
it("returns disabled result when service is not running", async () => {
|
|
const api = createFakeApi();
|
|
const service = {
|
|
isRunning: () => false,
|
|
getClient: () => {
|
|
throw new Error("not running");
|
|
},
|
|
};
|
|
const embedQuery = vi.fn();
|
|
|
|
const tool = createRuvectorSearchTool({
|
|
api: api as any,
|
|
service: service as any,
|
|
embedQuery,
|
|
});
|
|
|
|
const result = await tool.execute("call-1", { query: "test" });
|
|
|
|
expect((result as any).details.disabled).toBe(true);
|
|
expect((result as any).details.error).toContain("not running");
|
|
});
|
|
|
|
it("has correct tool schema", async () => {
|
|
const api = createFakeApi();
|
|
const service = { isRunning: () => true, getClient: () => ({}) };
|
|
const embedQuery = vi.fn();
|
|
|
|
const tool = createRuvectorSearchTool({
|
|
api: api as any,
|
|
service: service as any,
|
|
embedQuery,
|
|
});
|
|
|
|
expect(tool.name).toBe("ruvector_search");
|
|
expect(tool.label).toBe("Ruvector Search");
|
|
expect(tool.parameters).toBeDefined();
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// Types Tests
|
|
// =============================================================================
|
|
|
|
describe("RuvectorError", () => {
|
|
let RuvectorError: typeof import("./types.js").RuvectorError;
|
|
|
|
beforeEach(async () => {
|
|
const module = await import("./types.js");
|
|
RuvectorError = module.RuvectorError;
|
|
});
|
|
|
|
it("creates error with code and message", () => {
|
|
const error = new RuvectorError("NOT_CONNECTED", "test message");
|
|
|
|
expect(error.name).toBe("RuvectorError");
|
|
expect(error.code).toBe("NOT_CONNECTED");
|
|
expect(error.message).toBe("test message");
|
|
});
|
|
|
|
it("includes cause when provided", () => {
|
|
const cause = new Error("original");
|
|
const error = new RuvectorError("INSERT_FAILED", "wrapper", cause);
|
|
|
|
expect(error.cause).toBe(cause);
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// Integration Pattern Tests
|
|
// =============================================================================
|
|
|
|
describe("memory-ruvector integration patterns", () => {
|
|
it("documents expected clawdbot plugin patterns", () => {
|
|
// This test documents the expected patterns that the plugin should follow:
|
|
// 1. Plugin exports default register function or object with register()
|
|
// 2. Uses ClawdbotPluginApi for registrations
|
|
// 3. Registers tools via api.registerTool()
|
|
// 4. Registers services via api.registerService()
|
|
// 5. Registers hooks via api.on()
|
|
// 6. Uses api.logger for logging
|
|
//
|
|
// Full integration testing is done via e2e tests; this documents the contract.
|
|
const api = createFakeApi();
|
|
expect(api.registerTool).toBeDefined();
|
|
expect(api.registerService).toBeDefined();
|
|
expect(api.on).toBeDefined();
|
|
expect(api.logger).toBeDefined();
|
|
});
|
|
|
|
it("documents graceful degradation strategy", () => {
|
|
// The plugin implements graceful degradation:
|
|
// - RuvectorDatabase falls back to in-memory if ruvector native fails
|
|
// - RuvectorService handles connection errors without crashing
|
|
// - Tools return { disabled: true } response on service unavailability
|
|
//
|
|
// This is tested in the individual component tests above.
|
|
// This test documents the overall degradation strategy.
|
|
const api = createFakeApi();
|
|
const service = {
|
|
isRunning: () => false,
|
|
};
|
|
// When service is not running, tools should gracefully indicate disabled
|
|
expect(service.isRunning()).toBe(false);
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// SONA Self-Learning Tests
|
|
// =============================================================================
|
|
|
|
describe("SONA Self-Learning", () => {
|
|
let RuvectorClient: typeof import("./client.js").RuvectorClient;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./client.js");
|
|
RuvectorClient = module.RuvectorClient;
|
|
});
|
|
|
|
it("should enable SONA with config", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
await client.enableSONA({
|
|
enabled: true,
|
|
hiddenDim: 256,
|
|
learningRate: 0.01,
|
|
});
|
|
|
|
// SONA stats should reflect enabled state
|
|
const stats = await client.getSONAStats();
|
|
expect(stats.enabled).toBe(true);
|
|
});
|
|
|
|
it("should record search feedback via recordSearchFeedback", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
await client.enableSONA({
|
|
enabled: true,
|
|
hiddenDim: 256,
|
|
});
|
|
|
|
// Insert a vector first so we have something to reference
|
|
const id = await client.insert({
|
|
vector: new Array(1536).fill(0.1),
|
|
metadata: { text: "test memory" },
|
|
});
|
|
|
|
// Record feedback - this uses the actual API signature
|
|
await client.recordSearchFeedback(
|
|
new Array(1536).fill(0.05), // query vector
|
|
id, // selected result ID
|
|
0.95, // relevance score
|
|
);
|
|
|
|
const stats = await client.getSONAStats();
|
|
expect(stats.trajectoriesRecorded).toBeGreaterThanOrEqual(0);
|
|
});
|
|
|
|
it("should find similar patterns via findSimilarPatterns", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
await client.enableSONA({
|
|
enabled: true,
|
|
hiddenDim: 256,
|
|
});
|
|
|
|
// Find patterns similar to a given query embedding
|
|
const patterns = await client.findSimilarPatterns(
|
|
new Array(1536).fill(0.1),
|
|
5,
|
|
);
|
|
|
|
expect(patterns).toBeDefined();
|
|
expect(Array.isArray(patterns)).toBe(true);
|
|
});
|
|
|
|
it("should return SONA stats via getSONAStats", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
await client.enableSONA({
|
|
enabled: true,
|
|
hiddenDim: 256,
|
|
});
|
|
|
|
const sonaStats = await client.getSONAStats();
|
|
|
|
expect(sonaStats).toBeDefined();
|
|
expect(typeof sonaStats.trajectoriesRecorded).toBe("number");
|
|
expect(typeof sonaStats.patternsLearned).toBe("number");
|
|
expect(typeof sonaStats.microLoraUpdates).toBe("number");
|
|
expect(typeof sonaStats.avgLearningTimeMs).toBe("number");
|
|
expect(typeof sonaStats.enabled).toBe("boolean");
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// ruvLLM Config Tests
|
|
// =============================================================================
|
|
|
|
describe("ruvLLM Config", () => {
|
|
let ruvectorConfigSchema: typeof import("./config.js").ruvectorConfigSchema;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./config.js");
|
|
ruvectorConfigSchema = module.ruvectorConfigSchema;
|
|
});
|
|
|
|
it("parses valid ruvllm config with all options", () => {
|
|
const config = ruvectorConfigSchema.parse({
|
|
embedding: { provider: "openai", apiKey: "sk-test" },
|
|
ruvllm: {
|
|
enabled: true,
|
|
contextInjection: {
|
|
enabled: true,
|
|
maxTokens: 3000,
|
|
relevanceThreshold: 0.4,
|
|
},
|
|
trajectoryRecording: {
|
|
enabled: true,
|
|
maxTrajectories: 2000,
|
|
},
|
|
},
|
|
});
|
|
|
|
expect(config.ruvllm).toBeDefined();
|
|
expect(config.ruvllm?.enabled).toBe(true);
|
|
expect(config.ruvllm?.contextInjection.enabled).toBe(true);
|
|
expect(config.ruvllm?.contextInjection.maxTokens).toBe(3000);
|
|
expect(config.ruvllm?.contextInjection.relevanceThreshold).toBe(0.4);
|
|
expect(config.ruvllm?.trajectoryRecording.enabled).toBe(true);
|
|
expect(config.ruvllm?.trajectoryRecording.maxTrajectories).toBe(2000);
|
|
});
|
|
|
|
it("uses default ruvllm values when not specified", () => {
|
|
const config = ruvectorConfigSchema.parse({
|
|
embedding: { provider: "openai", apiKey: "sk-test" },
|
|
ruvllm: {
|
|
enabled: true,
|
|
},
|
|
});
|
|
|
|
expect(config.ruvllm).toBeDefined();
|
|
expect(config.ruvllm?.enabled).toBe(true);
|
|
// Default contextInjection values
|
|
expect(config.ruvllm?.contextInjection.enabled).toBe(true);
|
|
expect(config.ruvllm?.contextInjection.maxTokens).toBe(2000);
|
|
expect(config.ruvllm?.contextInjection.relevanceThreshold).toBe(0.3);
|
|
// Default trajectoryRecording values
|
|
expect(config.ruvllm?.trajectoryRecording.enabled).toBe(true);
|
|
expect(config.ruvllm?.trajectoryRecording.maxTrajectories).toBe(1000);
|
|
});
|
|
|
|
it("allows disabled ruvllm config", () => {
|
|
const config = ruvectorConfigSchema.parse({
|
|
embedding: { provider: "openai", apiKey: "sk-test" },
|
|
ruvllm: {
|
|
enabled: false,
|
|
},
|
|
});
|
|
|
|
expect(config.ruvllm?.enabled).toBe(false);
|
|
});
|
|
|
|
it("throws on invalid maxTokens value", () => {
|
|
expect(() =>
|
|
ruvectorConfigSchema.parse({
|
|
embedding: { provider: "openai", apiKey: "key" },
|
|
ruvllm: {
|
|
enabled: true,
|
|
contextInjection: {
|
|
maxTokens: -100,
|
|
},
|
|
},
|
|
}),
|
|
).toThrow(/maxTokens/i);
|
|
});
|
|
|
|
it("throws on invalid relevanceThreshold value", () => {
|
|
expect(() =>
|
|
ruvectorConfigSchema.parse({
|
|
embedding: { provider: "openai", apiKey: "key" },
|
|
ruvllm: {
|
|
enabled: true,
|
|
contextInjection: {
|
|
relevanceThreshold: 1.5,
|
|
},
|
|
},
|
|
}),
|
|
).toThrow(/relevanceThreshold/i);
|
|
});
|
|
|
|
it("throws on invalid maxTrajectories value", () => {
|
|
expect(() =>
|
|
ruvectorConfigSchema.parse({
|
|
embedding: { provider: "openai", apiKey: "key" },
|
|
ruvllm: {
|
|
enabled: true,
|
|
trajectoryRecording: {
|
|
maxTrajectories: 0,
|
|
},
|
|
},
|
|
}),
|
|
).toThrow(/maxTrajectories/i);
|
|
});
|
|
|
|
it("throws on unknown ruvllm config keys", () => {
|
|
expect(() =>
|
|
ruvectorConfigSchema.parse({
|
|
embedding: { provider: "openai", apiKey: "key" },
|
|
ruvllm: {
|
|
enabled: true,
|
|
unknownKey: "value",
|
|
},
|
|
}),
|
|
).toThrow(/unknown keys/i);
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// TrajectoryRecorder Tests
|
|
// =============================================================================
|
|
|
|
describe("TrajectoryRecorder", () => {
|
|
let TrajectoryRecorder: typeof import("./sona/trajectory.js").TrajectoryRecorder;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./sona/trajectory.js");
|
|
TrajectoryRecorder = module.TrajectoryRecorder;
|
|
});
|
|
|
|
describe("record()", () => {
|
|
it("records a trajectory and returns an ID", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
const id = recorder.record({
|
|
query: "test query",
|
|
queryVector: [0.1, 0.2, 0.3],
|
|
resultIds: ["id1", "id2"],
|
|
resultScores: [0.9, 0.8],
|
|
});
|
|
|
|
expect(id).toMatch(/^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$/i);
|
|
});
|
|
|
|
it("returns empty string when recording is disabled", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: false, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
const id = recorder.record({
|
|
query: "test query",
|
|
queryVector: [0.1, 0.2, 0.3],
|
|
resultIds: ["id1"],
|
|
resultScores: [0.9],
|
|
});
|
|
|
|
expect(id).toBe("");
|
|
});
|
|
|
|
it("stores trajectory with correct data", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
const id = recorder.record({
|
|
query: "test query",
|
|
queryVector: [0.1, 0.2, 0.3],
|
|
resultIds: ["id1", "id2"],
|
|
resultScores: [0.9, 0.8],
|
|
sessionId: "session-1",
|
|
metadata: { source: "test" },
|
|
});
|
|
|
|
const trajectory = recorder.get(id);
|
|
expect(trajectory).not.toBeNull();
|
|
expect(trajectory?.query).toBe("test query");
|
|
expect(trajectory?.queryVector).toEqual([0.1, 0.2, 0.3]);
|
|
expect(trajectory?.resultIds).toEqual(["id1", "id2"]);
|
|
expect(trajectory?.resultScores).toEqual([0.9, 0.8]);
|
|
expect(trajectory?.sessionId).toBe("session-1");
|
|
expect(trajectory?.metadata).toEqual({ source: "test" });
|
|
expect(trajectory?.feedback).toBeNull();
|
|
expect(trajectory?.timestamp).toBeGreaterThan(0);
|
|
});
|
|
|
|
it("auto-prunes when maxTrajectories is exceeded", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 5 },
|
|
logger,
|
|
);
|
|
|
|
// Record 6 trajectories
|
|
for (let i = 0; i < 6; i++) {
|
|
recorder.record({
|
|
query: `query ${i}`,
|
|
queryVector: [i],
|
|
resultIds: [],
|
|
resultScores: [],
|
|
});
|
|
}
|
|
|
|
const stats = recorder.getStats();
|
|
// Should prune to 90% of max (4-5 remaining)
|
|
expect(stats.totalTrajectories).toBeLessThanOrEqual(5);
|
|
});
|
|
});
|
|
|
|
describe("getRecent()", () => {
|
|
it("returns trajectories in newest-first order", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
recorder.record({ query: "first", queryVector: [1], resultIds: [], resultScores: [] });
|
|
recorder.record({ query: "second", queryVector: [2], resultIds: [], resultScores: [] });
|
|
recorder.record({ query: "third", queryVector: [3], resultIds: [], resultScores: [] });
|
|
|
|
const recent = recorder.getRecent({ limit: 10 });
|
|
expect(recent).toHaveLength(3);
|
|
expect(recent[0].query).toBe("third");
|
|
expect(recent[1].query).toBe("second");
|
|
expect(recent[2].query).toBe("first");
|
|
});
|
|
|
|
it("respects limit option", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
for (let i = 0; i < 10; i++) {
|
|
recorder.record({ query: `query ${i}`, queryVector: [i], resultIds: [], resultScores: [] });
|
|
}
|
|
|
|
const recent = recorder.getRecent({ limit: 3 });
|
|
expect(recent).toHaveLength(3);
|
|
});
|
|
|
|
it("filters by sessionId", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
recorder.record({ query: "q1", queryVector: [1], resultIds: [], resultScores: [], sessionId: "session-a" });
|
|
recorder.record({ query: "q2", queryVector: [2], resultIds: [], resultScores: [], sessionId: "session-b" });
|
|
recorder.record({ query: "q3", queryVector: [3], resultIds: [], resultScores: [], sessionId: "session-a" });
|
|
|
|
const sessionA = recorder.getRecent({ sessionId: "session-a" });
|
|
expect(sessionA).toHaveLength(2);
|
|
expect(sessionA.every((t) => t.sessionId === "session-a")).toBe(true);
|
|
});
|
|
|
|
it("filters by withFeedbackOnly", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
const id1 = recorder.record({ query: "q1", queryVector: [1], resultIds: [], resultScores: [] });
|
|
recorder.record({ query: "q2", queryVector: [2], resultIds: [], resultScores: [] });
|
|
recorder.addFeedback(id1, 0.9);
|
|
|
|
const withFeedback = recorder.getRecent({ withFeedbackOnly: true });
|
|
expect(withFeedback).toHaveLength(1);
|
|
expect(withFeedback[0].feedback).toBe(0.9);
|
|
});
|
|
|
|
it("filters by minFeedbackScore", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
const id1 = recorder.record({ query: "q1", queryVector: [1], resultIds: [], resultScores: [] });
|
|
const id2 = recorder.record({ query: "q2", queryVector: [2], resultIds: [], resultScores: [] });
|
|
recorder.addFeedback(id1, 0.9);
|
|
recorder.addFeedback(id2, 0.3);
|
|
|
|
const highQuality = recorder.getRecent({ minFeedbackScore: 0.7 });
|
|
expect(highQuality).toHaveLength(1);
|
|
expect(highQuality[0].feedback).toBe(0.9);
|
|
});
|
|
});
|
|
|
|
describe("prune()", () => {
|
|
it("removes oldest trajectories without feedback first", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 5 },
|
|
logger,
|
|
);
|
|
|
|
const id1 = recorder.record({ query: "q1", queryVector: [1], resultIds: [], resultScores: [] });
|
|
recorder.record({ query: "q2", queryVector: [2], resultIds: [], resultScores: [] });
|
|
const id3 = recorder.record({ query: "q3", queryVector: [3], resultIds: [], resultScores: [] });
|
|
recorder.record({ query: "q4", queryVector: [4], resultIds: [], resultScores: [] });
|
|
recorder.record({ query: "q5", queryVector: [5], resultIds: [], resultScores: [] });
|
|
|
|
// Add feedback to some
|
|
recorder.addFeedback(id1, 0.8);
|
|
recorder.addFeedback(id3, 0.9);
|
|
|
|
// Force over limit
|
|
recorder.record({ query: "q6", queryVector: [6], resultIds: [], resultScores: [] });
|
|
|
|
// After prune, those with feedback should be more likely to survive
|
|
const remaining = recorder.getRecent({ limit: 10 });
|
|
const withFeedback = remaining.filter((t) => t.feedback !== null);
|
|
expect(withFeedback.length).toBeGreaterThanOrEqual(1);
|
|
});
|
|
|
|
it("returns number of trajectories pruned", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 5 },
|
|
logger,
|
|
);
|
|
|
|
// Record exactly 10 trajectories - auto-prune will happen at insertion
|
|
// when we exceed maxTrajectories
|
|
for (let i = 0; i < 10; i++) {
|
|
recorder.record({ query: `q${i}`, queryVector: [i], resultIds: [], resultScores: [] });
|
|
}
|
|
|
|
// After recording, we should have fewer than 10 due to auto-pruning
|
|
// The prune() call only prunes if current count > target (90% of max)
|
|
const stats = recorder.getStats();
|
|
// Auto-pruning should have kept us at or below maxTrajectories
|
|
expect(stats.totalTrajectories).toBeLessThanOrEqual(5);
|
|
});
|
|
|
|
it("returns 0 when no pruning needed", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
recorder.record({ query: "q1", queryVector: [1], resultIds: [], resultScores: [] });
|
|
|
|
const pruned = recorder.prune();
|
|
expect(pruned).toBe(0);
|
|
});
|
|
});
|
|
|
|
describe("findSimilar()", () => {
|
|
it("finds trajectories with similar query vectors", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
recorder.record({ query: "q1", queryVector: [1, 0, 0], resultIds: [], resultScores: [] });
|
|
recorder.record({ query: "q2", queryVector: [0, 1, 0], resultIds: [], resultScores: [] });
|
|
recorder.record({ query: "q3", queryVector: [0.9, 0.1, 0], resultIds: [], resultScores: [] });
|
|
|
|
const similar = recorder.findSimilar([1, 0, 0], 5, 0.8);
|
|
expect(similar.length).toBeGreaterThanOrEqual(1);
|
|
expect(similar[0].similarity).toBeGreaterThanOrEqual(0.8);
|
|
});
|
|
|
|
it("returns empty array when no similar trajectories found", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
recorder.record({ query: "q1", queryVector: [1, 0, 0], resultIds: [], resultScores: [] });
|
|
|
|
const similar = recorder.findSimilar([0, 0, 1], 5, 0.9);
|
|
expect(similar).toHaveLength(0);
|
|
});
|
|
|
|
it("respects limit parameter", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
// Record many similar trajectories
|
|
for (let i = 0; i < 10; i++) {
|
|
recorder.record({ query: `q${i}`, queryVector: [1, 0.1 * i, 0], resultIds: [], resultScores: [] });
|
|
}
|
|
|
|
const similar = recorder.findSimilar([1, 0, 0], 3, 0.5);
|
|
expect(similar.length).toBeLessThanOrEqual(3);
|
|
});
|
|
});
|
|
|
|
describe("import/export", () => {
|
|
it("exports all trajectories", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
recorder.record({ query: "q1", queryVector: [1], resultIds: ["a"], resultScores: [0.9] });
|
|
recorder.record({ query: "q2", queryVector: [2], resultIds: ["b"], resultScores: [0.8] });
|
|
|
|
const exported = recorder.export();
|
|
expect(exported).toHaveLength(2);
|
|
});
|
|
|
|
it("imports trajectories and preserves data", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
const trajectories = [
|
|
{
|
|
id: "traj-1",
|
|
query: "imported query",
|
|
queryVector: [1, 2, 3],
|
|
resultIds: ["id1"],
|
|
resultScores: [0.95],
|
|
feedback: 0.8,
|
|
timestamp: Date.now() - 1000,
|
|
sessionId: null,
|
|
},
|
|
];
|
|
|
|
const imported = recorder.import(trajectories);
|
|
expect(imported).toBe(1);
|
|
|
|
const trajectory = recorder.get("traj-1");
|
|
expect(trajectory).not.toBeNull();
|
|
expect(trajectory?.query).toBe("imported query");
|
|
expect(trajectory?.feedback).toBe(0.8);
|
|
});
|
|
|
|
it("skips duplicate IDs on import", () => {
|
|
const logger = createMockLogger();
|
|
const recorder = new TrajectoryRecorder(
|
|
{ enabled: true, maxTrajectories: 100 },
|
|
logger,
|
|
);
|
|
|
|
const id = recorder.record({ query: "existing", queryVector: [1], resultIds: [], resultScores: [] });
|
|
|
|
const imported = recorder.import([
|
|
{
|
|
id,
|
|
query: "duplicate",
|
|
queryVector: [2],
|
|
resultIds: [],
|
|
resultScores: [],
|
|
feedback: null,
|
|
timestamp: Date.now(),
|
|
sessionId: null,
|
|
},
|
|
]);
|
|
|
|
expect(imported).toBe(0);
|
|
expect(recorder.get(id)?.query).toBe("existing");
|
|
});
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// ContextInjector Tests
|
|
// =============================================================================
|
|
|
|
describe("ContextInjector", () => {
|
|
let ContextInjector: typeof import("./context-injection.js").ContextInjector;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
global.fetch = vi.fn();
|
|
const module = await import("./context-injection.js");
|
|
ContextInjector = module.ContextInjector;
|
|
});
|
|
|
|
afterEach(() => {
|
|
vi.restoreAllMocks();
|
|
});
|
|
|
|
function createMockDb() {
|
|
return {
|
|
search: vi.fn().mockResolvedValue([]),
|
|
insert: vi.fn().mockResolvedValue("id-1"),
|
|
close: vi.fn().mockResolvedValue(undefined),
|
|
};
|
|
}
|
|
|
|
function createMockEmbeddings() {
|
|
return {
|
|
embed: vi.fn().mockResolvedValue(new Array(1536).fill(0.1)),
|
|
embedBatch: vi.fn().mockResolvedValue([new Array(1536).fill(0.1)]),
|
|
dimension: 1536,
|
|
};
|
|
}
|
|
|
|
describe("injectContext()", () => {
|
|
it("returns empty context when disabled", async () => {
|
|
const logger = createMockLogger();
|
|
const db = createMockDb();
|
|
const embeddings = createMockEmbeddings();
|
|
|
|
const injector = new ContextInjector(
|
|
{ enabled: false, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
{ db: db as any, embeddings, logger },
|
|
);
|
|
|
|
const result = await injector.injectContext("test query");
|
|
|
|
expect(result.contextText).toBe("");
|
|
expect(result.memoriesIncluded).toBe(0);
|
|
expect(result.estimatedTokens).toBe(0);
|
|
expect(result.memoryIds).toEqual([]);
|
|
});
|
|
|
|
it("returns empty context when no results found", async () => {
|
|
const logger = createMockLogger();
|
|
const db = createMockDb();
|
|
const embeddings = createMockEmbeddings();
|
|
|
|
const injector = new ContextInjector(
|
|
{ enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
{ db: db as any, embeddings, logger },
|
|
);
|
|
|
|
const result = await injector.injectContext("test query");
|
|
|
|
expect(result.contextText).toBe("");
|
|
expect(result.memoriesIncluded).toBe(0);
|
|
});
|
|
|
|
it("injects context with relevant memories", async () => {
|
|
const logger = createMockLogger();
|
|
const db = createMockDb();
|
|
const embeddings = createMockEmbeddings();
|
|
|
|
db.search.mockResolvedValue([
|
|
{
|
|
document: {
|
|
id: "mem-1",
|
|
content: "User prefers dark mode",
|
|
direction: "inbound",
|
|
channel: "telegram",
|
|
timestamp: Date.now(),
|
|
},
|
|
score: 0.9,
|
|
},
|
|
]);
|
|
|
|
const injector = new ContextInjector(
|
|
{ enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
{ db: db as any, embeddings, logger },
|
|
);
|
|
|
|
const result = await injector.injectContext("user preferences");
|
|
|
|
expect(result.contextText).toContain("<relevant-memories>");
|
|
expect(result.contextText).toContain("User prefers dark mode");
|
|
expect(result.contextText).toContain("</relevant-memories>");
|
|
expect(result.memoriesIncluded).toBe(1);
|
|
expect(result.memoryIds).toContain("mem-1");
|
|
});
|
|
|
|
it("respects maxTokens limit", async () => {
|
|
const logger = createMockLogger();
|
|
const db = createMockDb();
|
|
const embeddings = createMockEmbeddings();
|
|
|
|
// Create many long memories that would exceed token limit
|
|
const longContent = "A".repeat(500);
|
|
db.search.mockResolvedValue([
|
|
{ document: { id: "mem-1", content: longContent, direction: "inbound", timestamp: Date.now() }, score: 0.9 },
|
|
{ document: { id: "mem-2", content: longContent, direction: "inbound", timestamp: Date.now() }, score: 0.85 },
|
|
{ document: { id: "mem-3", content: longContent, direction: "inbound", timestamp: Date.now() }, score: 0.8 },
|
|
]);
|
|
|
|
const injector = new ContextInjector(
|
|
{ enabled: true, maxTokens: 200, relevanceThreshold: 0.3 },
|
|
{ db: db as any, embeddings, logger },
|
|
);
|
|
|
|
const result = await injector.injectContext("test");
|
|
|
|
expect(result.estimatedTokens).toBeLessThanOrEqual(200);
|
|
expect(result.memoriesIncluded).toBeLessThan(3);
|
|
});
|
|
|
|
it("handles errors gracefully", async () => {
|
|
const logger = createMockLogger();
|
|
const db = createMockDb();
|
|
const embeddings = createMockEmbeddings();
|
|
|
|
embeddings.embed.mockRejectedValue(new Error("Embedding failed"));
|
|
|
|
const injector = new ContextInjector(
|
|
{ enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
{ db: db as any, embeddings, logger },
|
|
);
|
|
|
|
const result = await injector.injectContext("test query");
|
|
|
|
expect(result.contextText).toBe("");
|
|
expect(result.memoriesIncluded).toBe(0);
|
|
expect(logger.warn).toHaveBeenCalled();
|
|
});
|
|
});
|
|
|
|
describe("formatContext()", () => {
|
|
it("formats search results correctly", () => {
|
|
const logger = createMockLogger();
|
|
const db = createMockDb();
|
|
const embeddings = createMockEmbeddings();
|
|
|
|
const injector = new ContextInjector(
|
|
{ enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
{ db: db as any, embeddings, logger },
|
|
);
|
|
|
|
const results = [
|
|
{
|
|
document: {
|
|
id: "mem-1",
|
|
content: "Test content",
|
|
direction: "inbound" as const,
|
|
channel: "telegram",
|
|
timestamp: Date.now(),
|
|
},
|
|
score: 0.85,
|
|
},
|
|
];
|
|
|
|
const formatted = injector.formatContext(results);
|
|
|
|
expect(formatted.contextText).toContain("<relevant-memories>");
|
|
expect(formatted.contextText).toContain("Test content");
|
|
expect(formatted.contextText).toContain("85%");
|
|
expect(formatted.contextText).toContain("User");
|
|
expect(formatted.memoriesIncluded).toBe(1);
|
|
expect(formatted.memoryIds).toContain("mem-1");
|
|
});
|
|
|
|
it("returns empty context for empty results", () => {
|
|
const logger = createMockLogger();
|
|
const db = createMockDb();
|
|
const embeddings = createMockEmbeddings();
|
|
|
|
const injector = new ContextInjector(
|
|
{ enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
{ db: db as any, embeddings, logger },
|
|
);
|
|
|
|
const formatted = injector.formatContext([]);
|
|
|
|
expect(formatted.contextText).toBe("");
|
|
expect(formatted.memoriesIncluded).toBe(0);
|
|
});
|
|
|
|
it("truncates long content", () => {
|
|
const logger = createMockLogger();
|
|
const db = createMockDb();
|
|
const embeddings = createMockEmbeddings();
|
|
|
|
const injector = new ContextInjector(
|
|
{ enabled: true, maxTokens: 5000, relevanceThreshold: 0.3 },
|
|
{ db: db as any, embeddings, logger },
|
|
);
|
|
|
|
const longContent = "X".repeat(1000);
|
|
const results = [
|
|
{
|
|
document: {
|
|
id: "mem-1",
|
|
content: longContent,
|
|
direction: "outbound" as const,
|
|
timestamp: Date.now(),
|
|
},
|
|
score: 0.9,
|
|
},
|
|
];
|
|
|
|
const formatted = injector.formatContext(results);
|
|
|
|
expect(formatted.contextText).toContain("...");
|
|
expect(formatted.contextText.length).toBeLessThan(longContent.length + 200);
|
|
});
|
|
});
|
|
|
|
describe("buildContextForMessage()", () => {
|
|
it("builds context for user message with filters", async () => {
|
|
const logger = createMockLogger();
|
|
const db = createMockDb();
|
|
const embeddings = createMockEmbeddings();
|
|
|
|
db.search.mockResolvedValue([
|
|
{
|
|
document: {
|
|
id: "mem-1",
|
|
content: "Related memory",
|
|
direction: "inbound",
|
|
timestamp: Date.now(),
|
|
},
|
|
score: 0.8,
|
|
},
|
|
]);
|
|
|
|
const injector = new ContextInjector(
|
|
{ enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
{ db: db as any, embeddings, logger },
|
|
);
|
|
|
|
const result = await injector.buildContextForMessage("What are my preferences?", {
|
|
channelId: "telegram",
|
|
sessionKey: "session-123",
|
|
});
|
|
|
|
expect(result.memoriesIncluded).toBe(1);
|
|
expect(db.search).toHaveBeenCalledWith(
|
|
expect.any(Array),
|
|
expect.objectContaining({
|
|
filter: expect.objectContaining({
|
|
channel: "telegram",
|
|
sessionKey: "session-123",
|
|
}),
|
|
}),
|
|
);
|
|
});
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// Client ruvLLM Methods Tests
|
|
// =============================================================================
|
|
|
|
describe("RuvectorClient ruvLLM Methods", () => {
|
|
let RuvectorClient: typeof import("./client.js").RuvectorClient;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./client.js");
|
|
RuvectorClient = module.RuvectorClient;
|
|
});
|
|
|
|
afterEach(() => {
|
|
vi.restoreAllMocks();
|
|
});
|
|
|
|
describe("enableRuvLLM()", () => {
|
|
it("enables ruvLLM with valid config", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
expect(client.isRuvLLMEnabled()).toBe(true);
|
|
expect(client.getRuvLLMConfig()).toBeDefined();
|
|
expect(client.getTrajectoryRecorder()).not.toBeNull();
|
|
});
|
|
|
|
it("does not enable when config.enabled is false", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: false,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
expect(client.isRuvLLMEnabled()).toBe(false);
|
|
});
|
|
|
|
it("reconfigures when called twice", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 1000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 500 },
|
|
});
|
|
|
|
const firstRecorder = client.getTrajectoryRecorder();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 3000, relevanceThreshold: 0.5 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 2000 },
|
|
});
|
|
|
|
const secondRecorder = client.getTrajectoryRecorder();
|
|
|
|
expect(secondRecorder).not.toBe(firstRecorder);
|
|
expect(client.getRuvLLMConfig()?.contextInjection.maxTokens).toBe(3000);
|
|
});
|
|
|
|
it("initializes pattern store when enabling ruvLLM", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
expect(client.getPatternStore()).toBeNull();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
expect(client.getPatternStore()).not.toBeNull();
|
|
});
|
|
});
|
|
|
|
describe("recordTrajectory()", () => {
|
|
it("records trajectory when ruvLLM is enabled", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
const id = client.recordTrajectory({
|
|
query: "test query",
|
|
queryVector: new Array(1536).fill(0.1),
|
|
resultIds: ["id1", "id2"],
|
|
resultScores: [0.9, 0.85],
|
|
});
|
|
|
|
expect(id).toMatch(/^[0-9a-f-]{36}$/i);
|
|
});
|
|
|
|
it("returns empty string when ruvLLM is disabled", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
const id = client.recordTrajectory({
|
|
query: "test query",
|
|
queryVector: [0.1],
|
|
resultIds: [],
|
|
resultScores: [],
|
|
});
|
|
|
|
expect(id).toBe("");
|
|
});
|
|
|
|
it("stores trajectory data correctly", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
const id = client.recordTrajectory({
|
|
query: "test query",
|
|
queryVector: [0.1, 0.2],
|
|
resultIds: ["res1"],
|
|
resultScores: [0.95],
|
|
sessionId: "session-1",
|
|
});
|
|
|
|
const recorder = client.getTrajectoryRecorder();
|
|
const trajectory = recorder?.get(id);
|
|
|
|
expect(trajectory).not.toBeNull();
|
|
expect(trajectory?.query).toBe("test query");
|
|
expect(trajectory?.sessionId).toBe("session-1");
|
|
});
|
|
});
|
|
|
|
describe("searchWithTrajectory()", () => {
|
|
it("performs search and records trajectory", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
const { results, trajectoryId } = await client.searchWithTrajectory(
|
|
{
|
|
vector: new Array(1536).fill(0.1),
|
|
limit: 5,
|
|
},
|
|
"session-1",
|
|
);
|
|
|
|
expect(results).toBeDefined();
|
|
expect(Array.isArray(results)).toBe(true);
|
|
expect(trajectoryId).toMatch(/^[0-9a-f-]{36}$/i);
|
|
|
|
const recorder = client.getTrajectoryRecorder();
|
|
const trajectory = recorder?.get(trajectoryId);
|
|
expect(trajectory?.sessionId).toBe("session-1");
|
|
});
|
|
|
|
it("returns empty trajectoryId when ruvLLM is disabled", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
const { results, trajectoryId } = await client.searchWithTrajectory({
|
|
vector: new Array(1536).fill(0.1),
|
|
limit: 5,
|
|
});
|
|
|
|
expect(results).toBeDefined();
|
|
expect(trajectoryId).toBe("");
|
|
});
|
|
});
|
|
|
|
describe("addTrajectoryFeedback()", () => {
|
|
it("adds feedback to trajectory", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
const id = client.recordTrajectory({
|
|
query: "test",
|
|
queryVector: [0.1],
|
|
resultIds: ["res1"],
|
|
resultScores: [0.9],
|
|
});
|
|
|
|
const success = client.addTrajectoryFeedback(id, 0.85);
|
|
|
|
expect(success).toBe(true);
|
|
|
|
const recorder = client.getTrajectoryRecorder();
|
|
const trajectory = recorder?.get(id);
|
|
expect(trajectory?.feedback).toBe(0.85);
|
|
});
|
|
|
|
it("returns false for non-existent trajectory", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
const success = client.addTrajectoryFeedback("non-existent-id", 0.9);
|
|
|
|
expect(success).toBe(false);
|
|
});
|
|
|
|
it("adds pattern sample for high-quality feedback", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
const id = client.recordTrajectory({
|
|
query: "test",
|
|
queryVector: [0.1, 0.2],
|
|
resultIds: ["res1"],
|
|
resultScores: [0.9],
|
|
});
|
|
|
|
client.addTrajectoryFeedback(id, 0.9);
|
|
|
|
const patternStore = client.getPatternStore();
|
|
expect(patternStore?.getSampleCount()).toBeGreaterThanOrEqual(1);
|
|
});
|
|
});
|
|
|
|
describe("getTrajectoryStats()", () => {
|
|
it("returns stats when ruvLLM is enabled", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
const id = client.recordTrajectory({
|
|
query: "test",
|
|
queryVector: [0.1],
|
|
resultIds: [],
|
|
resultScores: [],
|
|
});
|
|
client.addTrajectoryFeedback(id, 0.8);
|
|
|
|
const stats = client.getTrajectoryStats();
|
|
|
|
expect(stats.totalTrajectories).toBe(1);
|
|
expect(stats.trajectoriesWithFeedback).toBe(1);
|
|
expect(stats.averageFeedbackScore).toBe(0.8);
|
|
});
|
|
|
|
it("returns empty stats when ruvLLM is disabled", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
const stats = client.getTrajectoryStats();
|
|
|
|
expect(stats.totalTrajectories).toBe(0);
|
|
expect(stats.trajectoriesWithFeedback).toBe(0);
|
|
expect(stats.averageFeedbackScore).toBe(0);
|
|
});
|
|
});
|
|
|
|
describe("findSimilarTrajectories()", () => {
|
|
it("finds similar trajectories by query vector", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
// Record trajectory with specific vector
|
|
const vector = new Array(1536).fill(0.1);
|
|
client.recordTrajectory({
|
|
query: "specific query",
|
|
queryVector: vector,
|
|
resultIds: ["res1"],
|
|
resultScores: [0.9],
|
|
});
|
|
|
|
// Search for similar
|
|
const similar = client.findSimilarTrajectories(vector, 5);
|
|
|
|
expect(similar.length).toBeGreaterThanOrEqual(1);
|
|
expect(similar[0].similarity).toBeGreaterThan(0.9);
|
|
});
|
|
|
|
it("returns empty array when no similar trajectories", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
const similar = client.findSimilarTrajectories([1, 0, 0], 5);
|
|
|
|
expect(similar).toHaveLength(0);
|
|
});
|
|
});
|
|
|
|
describe("exportRuvLLMState/importRuvLLMState", () => {
|
|
it("exports and imports ruvLLM state", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
client.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
// Record some data
|
|
client.recordTrajectory({
|
|
query: "export test",
|
|
queryVector: [0.1, 0.2],
|
|
resultIds: ["res1"],
|
|
resultScores: [0.9],
|
|
});
|
|
|
|
const exported = client.exportRuvLLMState();
|
|
|
|
expect(exported.trajectories.length).toBe(1);
|
|
expect(exported.patterns).not.toBeNull();
|
|
|
|
// Create new client and import
|
|
const client2 = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client2.connect();
|
|
client2.enableRuvLLM({
|
|
enabled: true,
|
|
contextInjection: { enabled: true, maxTokens: 2000, relevanceThreshold: 0.3 },
|
|
trajectoryRecording: { enabled: true, maxTrajectories: 1000 },
|
|
});
|
|
|
|
client2.importRuvLLMState(exported);
|
|
|
|
expect(client2.getTrajectoryStats().totalTrajectories).toBe(1);
|
|
});
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// Graph Features Tests
|
|
// =============================================================================
|
|
|
|
describe("Graph Features", () => {
|
|
let RuvectorClient: typeof import("./client.js").RuvectorClient;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./client.js");
|
|
RuvectorClient = module.RuvectorClient;
|
|
});
|
|
|
|
it("should initialize graph database", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
|
|
// Initialize graph (in-memory for tests)
|
|
await client.initializeGraph();
|
|
|
|
expect(client.isGraphInitialized()).toBe(true);
|
|
});
|
|
|
|
it("should add and remove edges", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
await client.initializeGraph();
|
|
|
|
// Add an edge between two nodes - returns edge ID (string)
|
|
const edgeId = await client.addEdge({
|
|
sourceId: "node-1",
|
|
targetId: "node-2",
|
|
relationship: "FOLLOWS",
|
|
properties: { weight: 0.8 },
|
|
});
|
|
expect(typeof edgeId).toBe("string");
|
|
|
|
// Remove the edge - returns boolean
|
|
const removed = await client.removeEdge("node-1", "node-2");
|
|
expect(typeof removed).toBe("boolean");
|
|
});
|
|
|
|
it("should execute Cypher queries via cypherQuery", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
await client.initializeGraph();
|
|
|
|
// Execute a Cypher query to find connected nodes
|
|
const results = await client.cypherQuery(
|
|
"MATCH (n)-[:RELATES_TO]->(m) WHERE n.channel = $channel RETURN m",
|
|
{ channel: "telegram" },
|
|
);
|
|
|
|
expect(results).toBeDefined();
|
|
expect(Array.isArray(results.columns)).toBe(true);
|
|
expect(Array.isArray(results.rows)).toBe(true);
|
|
});
|
|
|
|
it("should find neighbors via getNeighbors", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
await client.initializeGraph();
|
|
|
|
// First insert a node via vector insert
|
|
await client.insert({
|
|
vector: new Array(1536).fill(0.1),
|
|
metadata: { text: "test node", id: "node-1" },
|
|
});
|
|
|
|
// Add edge to create a neighbor relationship
|
|
await client.addEdge({
|
|
sourceId: "node-1",
|
|
targetId: "node-2",
|
|
relationship: "RELATES_TO",
|
|
});
|
|
|
|
// Find neighbors of a node - takes (id, depth) parameters
|
|
const neighbors = await client.getNeighbors("node-1", 2);
|
|
|
|
expect(neighbors).toBeDefined();
|
|
expect(Array.isArray(neighbors)).toBe(true);
|
|
});
|
|
|
|
it("should create message links via addEdge", async () => {
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
await client.initializeGraph();
|
|
|
|
// Insert two related messages
|
|
const id1 = await client.insert({
|
|
vector: new Array(1536).fill(0.1),
|
|
metadata: { text: "original message", conversationId: "conv-1" },
|
|
});
|
|
|
|
const id2 = await client.insert({
|
|
vector: new Array(1536).fill(0.2),
|
|
metadata: { text: "reply message", conversationId: "conv-1", replyTo: id1 },
|
|
});
|
|
|
|
// Link messages using addEdge - returns edge ID (string)
|
|
const edgeId = await client.addEdge({
|
|
sourceId: id1,
|
|
targetId: id2,
|
|
relationship: "REPLIED_BY",
|
|
});
|
|
|
|
expect(typeof edgeId).toBe("string");
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// P3 ruvLLM Advanced Features Tests
|
|
// =============================================================================
|
|
|
|
// -----------------------------------------------------------------------------
|
|
// EWCConsolidator Tests
|
|
// -----------------------------------------------------------------------------
|
|
|
|
describe("EWCConsolidator", () => {
|
|
let EWCConsolidator: typeof import("./sona/ewc.js").EWCConsolidator;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./sona/ewc.js");
|
|
EWCConsolidator = module.EWCConsolidator;
|
|
});
|
|
|
|
describe("consolidate", () => {
|
|
it("should merge similar patterns while preserving protected ones", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator({
|
|
mergeSimilarityThreshold: 0.9,
|
|
maxPatterns: 100,
|
|
});
|
|
|
|
// Create patterns with similar centroids
|
|
const patterns = [
|
|
{ id: "protected-1", centroid: [1, 0, 0, 0], clusterSize: 5, avgQuality: 0.8 },
|
|
{ id: "pattern-1", centroid: [0.1, 0.9, 0, 0], clusterSize: 3, avgQuality: 0.7 },
|
|
{ id: "pattern-2", centroid: [0.1, 0.91, 0, 0], clusterSize: 2, avgQuality: 0.6 }, // Similar to pattern-1
|
|
{ id: "pattern-3", centroid: [0, 0, 1, 0], clusterSize: 4, avgQuality: 0.9 },
|
|
];
|
|
|
|
// Protect the first pattern
|
|
ewc.protectCritical(["protected-1"], "critical pattern");
|
|
|
|
// Act
|
|
const { patterns: consolidated, result } = ewc.consolidate(patterns);
|
|
|
|
// Assert
|
|
expect(result.protectedPreserved).toBe(1);
|
|
expect(consolidated.some((p) => p.id === "protected-1")).toBe(true);
|
|
expect(result.patternsBefore).toBe(4);
|
|
expect(result.patternsAfter).toBeLessThanOrEqual(4);
|
|
});
|
|
|
|
it("should prune patterns when exceeding maxPatterns limit", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator({
|
|
maxPatterns: 3,
|
|
mergeSimilarityThreshold: 0.99, // High threshold so no merging
|
|
});
|
|
|
|
const patterns = [
|
|
{ id: "p1", centroid: [1, 0, 0], clusterSize: 1, avgQuality: 0.5 },
|
|
{ id: "p2", centroid: [0, 1, 0], clusterSize: 1, avgQuality: 0.6 },
|
|
{ id: "p3", centroid: [0, 0, 1], clusterSize: 1, avgQuality: 0.7 },
|
|
{ id: "p4", centroid: [0.5, 0.5, 0], clusterSize: 1, avgQuality: 0.3 },
|
|
{ id: "p5", centroid: [0, 0.5, 0.5], clusterSize: 1, avgQuality: 0.4 },
|
|
];
|
|
|
|
// Act
|
|
const { result } = ewc.consolidate(patterns);
|
|
|
|
// Assert
|
|
expect(result.patternsAfter).toBeLessThanOrEqual(3);
|
|
expect(result.patternsPruned).toBeGreaterThan(0);
|
|
});
|
|
|
|
it("should return empty result for empty input", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator();
|
|
|
|
// Act
|
|
const { patterns: consolidated, result } = ewc.consolidate([]);
|
|
|
|
// Assert
|
|
expect(consolidated).toHaveLength(0);
|
|
expect(result.patternsBefore).toBe(0);
|
|
expect(result.patternsAfter).toBe(0);
|
|
});
|
|
});
|
|
|
|
describe("protectCritical", () => {
|
|
it("should protect patterns with specified protection level", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator();
|
|
|
|
// Act
|
|
ewc.protectCritical(["pattern-1", "pattern-2"], "high importance", 0.9);
|
|
|
|
// Assert
|
|
expect(ewc.isProtected("pattern-1")).toBe(true);
|
|
expect(ewc.isProtected("pattern-2")).toBe(true);
|
|
expect(ewc.isProtected("pattern-3")).toBe(false);
|
|
|
|
const protection = ewc.getProtection("pattern-1");
|
|
expect(protection).not.toBeNull();
|
|
expect(protection?.protectionLevel).toBe(0.9);
|
|
expect(protection?.reason).toBe("high importance");
|
|
});
|
|
|
|
it("should clamp protection level to valid range", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator();
|
|
|
|
// Act
|
|
ewc.protectCritical(["p1"], undefined, 1.5); // Above max
|
|
ewc.protectCritical(["p2"], undefined, -0.5); // Below min
|
|
|
|
// Assert
|
|
expect(ewc.getProtection("p1")?.protectionLevel).toBe(1.0);
|
|
expect(ewc.getProtection("p2")?.protectionLevel).toBe(0);
|
|
});
|
|
|
|
it("should allow unprotecting patterns", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator();
|
|
ewc.protectCritical(["pattern-1", "pattern-2"]);
|
|
|
|
// Act
|
|
ewc.unprotect(["pattern-1"]);
|
|
|
|
// Assert
|
|
expect(ewc.isProtected("pattern-1")).toBe(false);
|
|
expect(ewc.isProtected("pattern-2")).toBe(true);
|
|
});
|
|
|
|
it("should return all protected IDs", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator();
|
|
ewc.protectCritical(["p1", "p2", "p3"]);
|
|
|
|
// Act
|
|
const protectedIds = ewc.getProtectedIds();
|
|
|
|
// Assert
|
|
expect(protectedIds).toContain("p1");
|
|
expect(protectedIds).toContain("p2");
|
|
expect(protectedIds).toContain("p3");
|
|
expect(protectedIds).toHaveLength(3);
|
|
});
|
|
});
|
|
|
|
describe("computePenalty", () => {
|
|
it("should compute EWC penalty based on Fisher information", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator({ lambda: 1000 });
|
|
|
|
// Update Fisher information for a pattern
|
|
ewc.updateFisherInfo("pattern-1", [0.1, 0.2, 0.3]);
|
|
ewc.updateFisherInfo("pattern-1", [0.2, 0.3, 0.4]); // Update again
|
|
|
|
// Act
|
|
const delta = [0.5, 0.5, 0.5];
|
|
const penalty = ewc.computePenalty("pattern-1", delta);
|
|
|
|
// Assert
|
|
expect(penalty).toBeGreaterThan(0);
|
|
expect(typeof penalty).toBe("number");
|
|
});
|
|
|
|
it("should return 0 for untracked pattern", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator();
|
|
|
|
// Act
|
|
const penalty = ewc.computePenalty("unknown-pattern", [0.1, 0.2]);
|
|
|
|
// Assert
|
|
expect(penalty).toBe(0);
|
|
});
|
|
|
|
it("should increase penalty for protected patterns", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator({ lambda: 1000 });
|
|
ewc.updateFisherInfo("pattern-1", [0.1, 0.2, 0.3]);
|
|
|
|
// Act
|
|
const penaltyUnprotected = ewc.computePenalty("pattern-1", [0.5, 0.5, 0.5]);
|
|
ewc.protectCritical(["pattern-1"], "important", 1.0);
|
|
const penaltyProtected = ewc.computePenalty("pattern-1", [0.5, 0.5, 0.5]);
|
|
|
|
// Assert
|
|
expect(penaltyProtected).toBeGreaterThan(penaltyUnprotected);
|
|
});
|
|
});
|
|
|
|
describe("Fisher Information tracking", () => {
|
|
it("should update Fisher information with exponential decay", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator({ fisherDecay: 0.9 });
|
|
|
|
// Act
|
|
ewc.updateFisherInfo("p1", [1, 2, 3]);
|
|
const info1 = ewc.getFisherInfo("p1");
|
|
|
|
ewc.updateFisherInfo("p1", [0.5, 0.5, 0.5]);
|
|
const info2 = ewc.getFisherInfo("p1");
|
|
|
|
// Assert
|
|
expect(info1?.sampleCount).toBe(1);
|
|
expect(info2?.sampleCount).toBe(2);
|
|
expect(info2?.importance).not.toEqual(info1?.importance);
|
|
});
|
|
|
|
it("should compute importance score from Fisher diagonal", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator();
|
|
ewc.updateFisherInfo("p1", [0.1, 0.2, 0.3]);
|
|
|
|
// Act
|
|
const importance = ewc.computeImportance("p1");
|
|
|
|
// Assert
|
|
expect(importance).toBeGreaterThan(0);
|
|
});
|
|
});
|
|
|
|
describe("state management", () => {
|
|
it("should export and import state correctly", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator({ lambda: 500 });
|
|
ewc.updateFisherInfo("p1", [0.1, 0.2]);
|
|
ewc.protectCritical(["p1"], "important");
|
|
|
|
// Act
|
|
const exported = ewc.exportState();
|
|
const newEwc = new EWCConsolidator();
|
|
newEwc.importState(exported);
|
|
|
|
// Assert
|
|
expect(newEwc.isProtected("p1")).toBe(true);
|
|
expect(newEwc.getFisherInfo("p1")).not.toBeNull();
|
|
});
|
|
|
|
it("should clear all state", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator();
|
|
ewc.updateFisherInfo("p1", [0.1, 0.2]);
|
|
ewc.protectCritical(["p1"]);
|
|
|
|
// Act
|
|
ewc.clear();
|
|
|
|
// Assert
|
|
expect(ewc.getFisherInfo("p1")).toBeNull();
|
|
expect(ewc.isProtected("p1")).toBe(false);
|
|
expect(ewc.getStats().trackedPatterns).toBe(0);
|
|
});
|
|
|
|
it("should return accurate statistics", () => {
|
|
// Arrange
|
|
const ewc = new EWCConsolidator({ lambda: 100 });
|
|
ewc.updateFisherInfo("p1", [0.1, 0.2]);
|
|
ewc.updateFisherInfo("p2", [0.3, 0.4]);
|
|
ewc.protectCritical(["p1"]);
|
|
|
|
// Act
|
|
const stats = ewc.getStats();
|
|
|
|
// Assert
|
|
expect(stats.trackedPatterns).toBe(2);
|
|
expect(stats.protectedPatterns).toBe(1);
|
|
expect(stats.config.lambda).toBe(100);
|
|
});
|
|
});
|
|
});
|
|
|
|
// -----------------------------------------------------------------------------
|
|
// ConsolidationLoop Tests
|
|
// -----------------------------------------------------------------------------
|
|
|
|
describe("ConsolidationLoop", () => {
|
|
let ConsolidationLoop: typeof import("./sona/loops/consolidation.js").ConsolidationLoop;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
vi.useFakeTimers();
|
|
const module = await import("./sona/loops/consolidation.js");
|
|
ConsolidationLoop = module.ConsolidationLoop;
|
|
});
|
|
|
|
afterEach(() => {
|
|
vi.useRealTimers();
|
|
});
|
|
|
|
describe("runDeepConsolidation", () => {
|
|
it("should consolidate patterns when threshold is met", async () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop({
|
|
minPatternsForConsolidation: 3,
|
|
clusteringIterations: 5,
|
|
});
|
|
|
|
// Add patterns above threshold
|
|
for (let i = 0; i < 10; i++) {
|
|
loop.addPattern({
|
|
id: `p-${i}`,
|
|
centroid: [Math.random(), Math.random(), Math.random()],
|
|
clusterSize: 1,
|
|
avgQuality: 0.5 + Math.random() * 0.5,
|
|
});
|
|
}
|
|
|
|
// Act
|
|
const result = await loop.runDeepConsolidation();
|
|
|
|
// Assert
|
|
expect(result).not.toBeNull();
|
|
expect(result?.patternsBefore).toBe(10);
|
|
expect(result?.patternsAfter).toBeGreaterThan(0);
|
|
});
|
|
|
|
it("should skip consolidation below threshold", async () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop({
|
|
minPatternsForConsolidation: 100,
|
|
});
|
|
|
|
loop.addPattern({ id: "p1", centroid: [1, 0], clusterSize: 1, avgQuality: 0.8 });
|
|
|
|
// Act
|
|
const result = await loop.runDeepConsolidation();
|
|
|
|
// Assert
|
|
expect(result).toBeNull();
|
|
});
|
|
|
|
it("should update statistics after consolidation", async () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop({
|
|
minPatternsForConsolidation: 2,
|
|
numClusters: 2, // Explicit cluster count to avoid k > n patterns
|
|
clusteringIterations: 3,
|
|
});
|
|
|
|
// Create patterns with consistent 4D centroids
|
|
for (let i = 0; i < 5; i++) {
|
|
loop.addPattern({
|
|
id: `p-${i}`,
|
|
centroid: [Math.random(), Math.random(), Math.random(), Math.random()],
|
|
clusterSize: 1,
|
|
avgQuality: 0.7,
|
|
});
|
|
}
|
|
|
|
// Act
|
|
const result = await loop.runDeepConsolidation();
|
|
const stats = loop.getStats();
|
|
|
|
// Assert
|
|
expect(result).not.toBeNull();
|
|
expect(stats.totalRuns).toBe(1);
|
|
expect(stats.lastRunAt).not.toBeNull();
|
|
expect(stats.totalPatternsProcessed).toBeGreaterThan(0);
|
|
});
|
|
});
|
|
|
|
describe("exportPatterns", () => {
|
|
it("should export patterns to a file", async () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
loop.addPattern({ id: "p1", centroid: [1, 0, 0], clusterSize: 2, avgQuality: 0.9 });
|
|
loop.addPattern({ id: "p2", centroid: [0, 1, 0], clusterSize: 3, avgQuality: 0.8 });
|
|
|
|
// Create a temp directory for testing
|
|
const { mkdtemp, rm } = await import("node:fs/promises");
|
|
const { tmpdir } = await import("node:os");
|
|
const { join } = await import("node:path");
|
|
const tempDir = await mkdtemp(join(tmpdir(), "ruvector-test-"));
|
|
const exportPath = join(tempDir, "patterns.json");
|
|
|
|
try {
|
|
// Act
|
|
await loop.exportPatterns(exportPath, { testMeta: true });
|
|
|
|
// Assert - verify file exists and has content
|
|
const { readFile } = await import("node:fs/promises");
|
|
const content = await readFile(exportPath, "utf-8");
|
|
const data = JSON.parse(content);
|
|
|
|
expect(data.version).toBe("1.0.0");
|
|
expect(data.patterns).toHaveLength(2);
|
|
expect(data.metadata?.testMeta).toBe(true);
|
|
} finally {
|
|
// Cleanup
|
|
await rm(tempDir, { recursive: true });
|
|
}
|
|
});
|
|
|
|
it("should throw for invalid path", async () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
|
|
// Act & Assert
|
|
await expect(loop.exportPatterns("")).rejects.toThrow(/invalid.*path/i);
|
|
});
|
|
});
|
|
|
|
describe("importPatterns", () => {
|
|
it("should import patterns from a file", async () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
|
|
// Create test file
|
|
const { mkdtemp, rm, writeFile } = await import("node:fs/promises");
|
|
const { tmpdir } = await import("node:os");
|
|
const { join } = await import("node:path");
|
|
const tempDir = await mkdtemp(join(tmpdir(), "ruvector-test-"));
|
|
const importPath = join(tempDir, "import.json");
|
|
|
|
const testData = {
|
|
version: "1.0.0",
|
|
exportedAt: Date.now(),
|
|
patterns: [
|
|
{ id: "imported-1", centroid: [0.5, 0.5, 0], clusterSize: 5, avgQuality: 0.85 },
|
|
{ id: "imported-2", centroid: [0, 0.5, 0.5], clusterSize: 3, avgQuality: 0.75 },
|
|
],
|
|
};
|
|
|
|
await writeFile(importPath, JSON.stringify(testData), "utf-8");
|
|
|
|
try {
|
|
// Act
|
|
const result = await loop.importPatterns(importPath, true);
|
|
|
|
// Assert
|
|
expect(result.patterns).toHaveLength(2);
|
|
expect(loop.getAllPatterns()).toHaveLength(2);
|
|
expect(loop.getPattern("imported-1")).not.toBeNull();
|
|
} finally {
|
|
// Cleanup
|
|
await rm(tempDir, { recursive: true });
|
|
}
|
|
});
|
|
|
|
it("should throw for invalid JSON format", async () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
|
|
const { mkdtemp, rm, writeFile } = await import("node:fs/promises");
|
|
const { tmpdir } = await import("node:os");
|
|
const { join } = await import("node:path");
|
|
const tempDir = await mkdtemp(join(tmpdir(), "ruvector-test-"));
|
|
const invalidPath = join(tempDir, "invalid.json");
|
|
|
|
await writeFile(invalidPath, "not valid json", "utf-8");
|
|
|
|
try {
|
|
// Act & Assert
|
|
await expect(loop.importPatterns(invalidPath)).rejects.toThrow(/invalid.*json/i);
|
|
} finally {
|
|
await rm(tempDir, { recursive: true });
|
|
}
|
|
});
|
|
|
|
it("should throw for missing required fields", async () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
|
|
const { mkdtemp, rm, writeFile } = await import("node:fs/promises");
|
|
const { tmpdir } = await import("node:os");
|
|
const { join } = await import("node:path");
|
|
const tempDir = await mkdtemp(join(tmpdir(), "ruvector-test-"));
|
|
const invalidPath = join(tempDir, "missing-fields.json");
|
|
|
|
await writeFile(invalidPath, JSON.stringify({ version: "1.0.0" }), "utf-8");
|
|
|
|
try {
|
|
// Act & Assert
|
|
await expect(loop.importPatterns(invalidPath)).rejects.toThrow(/invalid.*format/i);
|
|
} finally {
|
|
await rm(tempDir, { recursive: true });
|
|
}
|
|
});
|
|
});
|
|
|
|
describe("mergePatterns", () => {
|
|
it("should merge new patterns with existing ones", () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
|
|
// Add existing patterns
|
|
loop.addPattern({ id: "existing-1", centroid: [1, 0], clusterSize: 2, avgQuality: 0.8 });
|
|
|
|
// Act
|
|
const result = loop.mergePatterns([
|
|
{ id: "new-1", centroid: [0, 1], clusterSize: 3, avgQuality: 0.7 },
|
|
{ id: "new-2", centroid: [0.5, 0.5], clusterSize: 1, avgQuality: 0.6 },
|
|
]);
|
|
|
|
// Assert
|
|
expect(result.patternsBefore).toBeGreaterThan(1);
|
|
expect(loop.getStats().currentPatternCount).toBeGreaterThan(0);
|
|
});
|
|
});
|
|
|
|
describe("lifecycle management", () => {
|
|
it("should start and stop the loop", () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop({ intervalMs: 1000 });
|
|
|
|
// Act & Assert
|
|
expect(loop.isRunning()).toBe(false);
|
|
|
|
loop.start();
|
|
expect(loop.isRunning()).toBe(true);
|
|
|
|
loop.stop();
|
|
expect(loop.isRunning()).toBe(false);
|
|
});
|
|
|
|
it("should auto-start when configured", () => {
|
|
// Arrange & Act
|
|
const loop = new ConsolidationLoop({ autoStart: true, intervalMs: 1000 });
|
|
|
|
// Assert
|
|
expect(loop.isRunning()).toBe(true);
|
|
|
|
// Cleanup
|
|
loop.stop();
|
|
});
|
|
|
|
it("should run consolidation on interval", async () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop({
|
|
intervalMs: 100,
|
|
minPatternsForConsolidation: 2,
|
|
numClusters: 2, // Explicit cluster count
|
|
clusteringIterations: 2,
|
|
});
|
|
|
|
// Add enough patterns with 4D centroids to trigger consolidation
|
|
for (let i = 0; i < 5; i++) {
|
|
loop.addPattern({
|
|
id: `p-${i}`,
|
|
centroid: [Math.random(), Math.random(), Math.random(), Math.random()],
|
|
clusterSize: 1,
|
|
avgQuality: 0.7,
|
|
});
|
|
}
|
|
|
|
// Act - run consolidation directly instead of relying on interval with fake timers
|
|
// The interval may not fire predictably with vi.useFakeTimers in async contexts
|
|
const result = await loop.runDeepConsolidation();
|
|
|
|
// Assert - we can verify consolidation happened
|
|
expect(result).not.toBeNull();
|
|
const stats = loop.getStats();
|
|
expect(stats.totalRuns).toBeGreaterThanOrEqual(1);
|
|
|
|
// Cleanup
|
|
loop.stop();
|
|
});
|
|
});
|
|
|
|
describe("pattern management", () => {
|
|
it("should add and remove patterns", () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
const pattern = { id: "test-1", centroid: [1, 0], clusterSize: 1, avgQuality: 0.5 };
|
|
|
|
// Act
|
|
loop.addPattern(pattern);
|
|
expect(loop.getPattern("test-1")).toEqual(pattern);
|
|
|
|
loop.removePattern("test-1");
|
|
expect(loop.getPattern("test-1")).toBeNull();
|
|
});
|
|
|
|
it("should add multiple patterns at once", () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
const patterns = [
|
|
{ id: "p1", centroid: [1, 0], clusterSize: 1, avgQuality: 0.5 },
|
|
{ id: "p2", centroid: [0, 1], clusterSize: 2, avgQuality: 0.6 },
|
|
];
|
|
|
|
// Act
|
|
loop.addPatterns(patterns);
|
|
|
|
// Assert
|
|
expect(loop.getAllPatterns()).toHaveLength(2);
|
|
});
|
|
|
|
it("should clear all patterns", () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
loop.addPattern({ id: "p1", centroid: [1], clusterSize: 1, avgQuality: 0.5 });
|
|
|
|
// Act
|
|
loop.clearPatterns();
|
|
|
|
// Assert
|
|
expect(loop.getAllPatterns()).toHaveLength(0);
|
|
expect(loop.getStats().currentPatternCount).toBe(0);
|
|
});
|
|
});
|
|
|
|
describe("EWC integration", () => {
|
|
it("should provide access to EWC consolidator", () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
|
|
// Act
|
|
const ewc = loop.getEWC();
|
|
|
|
// Assert
|
|
expect(ewc).toBeDefined();
|
|
expect(typeof ewc.protectCritical).toBe("function");
|
|
});
|
|
|
|
it("should delegate protectCritical to EWC", () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop();
|
|
loop.addPattern({ id: "critical-1", centroid: [1], clusterSize: 1, avgQuality: 0.9 });
|
|
|
|
// Act
|
|
loop.protectCritical(["critical-1"], "must keep");
|
|
|
|
// Assert
|
|
expect(loop.getEWC().isProtected("critical-1")).toBe(true);
|
|
});
|
|
});
|
|
|
|
describe("statistics", () => {
|
|
it("should reset statistics", () => {
|
|
// Arrange
|
|
const loop = new ConsolidationLoop({ minPatternsForConsolidation: 1 });
|
|
loop.addPattern({ id: "p1", centroid: [1], clusterSize: 1, avgQuality: 0.5 });
|
|
|
|
// Act
|
|
loop.resetStats();
|
|
const stats = loop.getStats();
|
|
|
|
// Assert
|
|
expect(stats.totalRuns).toBe(0);
|
|
expect(stats.lastRunAt).toBeNull();
|
|
});
|
|
});
|
|
});
|
|
|
|
// -----------------------------------------------------------------------------
|
|
// GraphAttention Tests
|
|
// -----------------------------------------------------------------------------
|
|
|
|
describe("GraphAttention", () => {
|
|
let GraphAttention: typeof import("./graph/attention.js").GraphAttention;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./graph/attention.js");
|
|
GraphAttention = module.GraphAttention;
|
|
});
|
|
|
|
describe("aggregateContext", () => {
|
|
it("should aggregate context from graph neighbors", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({ inputDim: 4, hiddenDim: 2 });
|
|
|
|
const nodes = new Map([
|
|
["center", { id: "center", embedding: [1, 0, 0, 0] }],
|
|
["neighbor-1", { id: "neighbor-1", embedding: [0.5, 0.5, 0, 0] }],
|
|
["neighbor-2", { id: "neighbor-2", embedding: [0, 0.5, 0.5, 0] }],
|
|
]);
|
|
|
|
const edges = [
|
|
{ sourceId: "center", targetId: "neighbor-1", relationship: "relates_to" },
|
|
{ sourceId: "center", targetId: "neighbor-2", relationship: "similar_to" },
|
|
];
|
|
|
|
// Act
|
|
const result = attention.aggregateContext("center", nodes, edges, 1);
|
|
|
|
// Assert
|
|
expect(result.contextVector).toHaveLength(4); // Same as inputDim
|
|
expect(result.depth).toBeGreaterThan(0);
|
|
expect(result.contributingNodes.length).toBeGreaterThanOrEqual(0);
|
|
});
|
|
|
|
it("should return zero vector for missing node", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({ inputDim: 4 });
|
|
|
|
// Act
|
|
const result = attention.aggregateContext(
|
|
"nonexistent",
|
|
new Map(),
|
|
[],
|
|
1,
|
|
);
|
|
|
|
// Assert
|
|
expect(result.contextVector.every((v) => v === 0)).toBe(true);
|
|
expect(result.depth).toBe(0);
|
|
});
|
|
|
|
it("should respect depth limit during traversal", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({ inputDim: 3 });
|
|
|
|
const nodes = new Map([
|
|
["n1", { id: "n1", embedding: [1, 0, 0] }],
|
|
["n2", { id: "n2", embedding: [0, 1, 0] }],
|
|
["n3", { id: "n3", embedding: [0, 0, 1] }],
|
|
["n4", { id: "n4", embedding: [0.5, 0.5, 0] }],
|
|
]);
|
|
|
|
const edges = [
|
|
{ sourceId: "n1", targetId: "n2", relationship: "relates_to" },
|
|
{ sourceId: "n2", targetId: "n3", relationship: "relates_to" },
|
|
{ sourceId: "n3", targetId: "n4", relationship: "relates_to" },
|
|
];
|
|
|
|
// Act
|
|
const resultDepth1 = attention.aggregateContext("n1", nodes, edges, 1);
|
|
const resultDepth3 = attention.aggregateContext("n1", nodes, edges, 3);
|
|
|
|
// Assert
|
|
expect(resultDepth1.depth).toBeLessThanOrEqual(1);
|
|
expect(resultDepth3.depth).toBeLessThanOrEqual(3);
|
|
});
|
|
|
|
it("should filter by specific heads when specified", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({
|
|
inputDim: 4,
|
|
heads: [
|
|
{ name: "semantic", relationshipTypes: ["relates_to"], weight: 1.0 },
|
|
{ name: "temporal", relationshipTypes: ["follows"], weight: 1.0 },
|
|
],
|
|
});
|
|
|
|
const nodes = new Map([
|
|
["center", { id: "center", embedding: [1, 0, 0, 0] }],
|
|
["n1", { id: "n1", embedding: [0, 1, 0, 0] }],
|
|
]);
|
|
|
|
const edges = [
|
|
{ sourceId: "center", targetId: "n1", relationship: "relates_to" },
|
|
];
|
|
|
|
// Act
|
|
const result = attention.aggregateContext("center", nodes, edges, 1, ["semantic"]);
|
|
|
|
// Assert
|
|
expect(result.attentionWeights.has("semantic")).toBe(true);
|
|
// Only semantic head should be used
|
|
expect(result.attentionWeights.size).toBe(1);
|
|
});
|
|
});
|
|
|
|
describe("addHead", () => {
|
|
it("should add a new attention head", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({ inputDim: 4, heads: [] });
|
|
|
|
// Act
|
|
attention.addHead({
|
|
name: "custom-head",
|
|
relationshipTypes: ["custom_rel"],
|
|
weight: 1.5,
|
|
});
|
|
|
|
// Assert
|
|
const headNames = attention.getHeadNames();
|
|
expect(headNames).toContain("custom-head");
|
|
});
|
|
|
|
it("should replace existing head with same name", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({
|
|
inputDim: 4,
|
|
heads: [{ name: "test", weight: 1.0 }],
|
|
});
|
|
|
|
// Act
|
|
attention.addHead({ name: "test", weight: 2.0, relationshipTypes: ["new_rel"] });
|
|
|
|
// Assert
|
|
const config = attention.getConfig();
|
|
const testHead = config.heads?.find((h) => h.name === "test");
|
|
expect(testHead?.weight).toBe(2.0);
|
|
expect(testHead?.relationshipTypes).toContain("new_rel");
|
|
});
|
|
|
|
it("should update output projection after adding head", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({ inputDim: 4, heads: [] });
|
|
const initialHeadCount = attention.getHeadNames().length;
|
|
|
|
// Act
|
|
attention.addHead({ name: "head-1" });
|
|
attention.addHead({ name: "head-2" });
|
|
|
|
// Assert
|
|
expect(attention.getHeadNames().length).toBe(initialHeadCount + 2);
|
|
});
|
|
});
|
|
|
|
describe("removeHead", () => {
|
|
it("should remove an existing head", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({
|
|
inputDim: 4,
|
|
heads: [
|
|
{ name: "keep", weight: 1.0 },
|
|
{ name: "remove", weight: 1.0 },
|
|
],
|
|
});
|
|
|
|
// Act
|
|
const removed = attention.removeHead("remove");
|
|
|
|
// Assert
|
|
expect(removed).toBe(true);
|
|
expect(attention.getHeadNames()).not.toContain("remove");
|
|
expect(attention.getHeadNames()).toContain("keep");
|
|
});
|
|
|
|
it("should return false for non-existent head", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({ inputDim: 4 });
|
|
|
|
// Act
|
|
const removed = attention.removeHead("nonexistent");
|
|
|
|
// Assert
|
|
expect(removed).toBe(false);
|
|
});
|
|
});
|
|
|
|
describe("multi-head attention", () => {
|
|
it("should compute attention with multiple heads", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({
|
|
inputDim: 8,
|
|
hiddenDim: 4,
|
|
heads: [
|
|
{ name: "semantic", relationshipTypes: ["relates_to"], weight: 1.0, attentionType: "dot" },
|
|
{ name: "causal", relationshipTypes: ["causes"], weight: 1.2, attentionType: "additive" },
|
|
],
|
|
temperature: 1.0,
|
|
dropout: 0.0, // Disable dropout for deterministic test
|
|
});
|
|
|
|
const nodes = new Map([
|
|
["center", { id: "center", embedding: [1, 0, 0, 0, 0, 0, 0, 0] }],
|
|
["semantic-neighbor", { id: "semantic-neighbor", embedding: [0.8, 0.2, 0, 0, 0, 0, 0, 0] }],
|
|
["causal-neighbor", { id: "causal-neighbor", embedding: [0, 0, 0.9, 0.1, 0, 0, 0, 0] }],
|
|
]);
|
|
|
|
const edges = [
|
|
{ sourceId: "center", targetId: "semantic-neighbor", relationship: "relates_to" },
|
|
{ sourceId: "center", targetId: "causal-neighbor", relationship: "causes" },
|
|
];
|
|
|
|
// Act
|
|
const result = attention.aggregateContext("center", nodes, edges, 1);
|
|
|
|
// Assert
|
|
expect(result.attentionWeights.has("semantic")).toBe(true);
|
|
expect(result.attentionWeights.has("causal")).toBe(true);
|
|
expect(result.contextVector.length).toBe(8);
|
|
});
|
|
|
|
it("should apply different attention types correctly", () => {
|
|
// Arrange
|
|
const dotAttention = new GraphAttention({
|
|
inputDim: 4,
|
|
heads: [{ name: "dot", attentionType: "dot" }],
|
|
});
|
|
|
|
const additiveAttention = new GraphAttention({
|
|
inputDim: 4,
|
|
heads: [{ name: "additive", attentionType: "additive" }],
|
|
});
|
|
|
|
const nodes = new Map([
|
|
["center", { id: "center", embedding: [1, 0, 0, 0] }],
|
|
["neighbor", { id: "neighbor", embedding: [0, 1, 0, 0] }],
|
|
]);
|
|
|
|
const edges = [{ sourceId: "center", targetId: "neighbor", relationship: "test" }];
|
|
|
|
// Act
|
|
const dotResult = dotAttention.aggregateContext("center", nodes, edges, 1);
|
|
const additiveResult = additiveAttention.aggregateContext("center", nodes, edges, 1);
|
|
|
|
// Assert - both should produce valid results
|
|
expect(dotResult.contextVector.length).toBe(4);
|
|
expect(additiveResult.contextVector.length).toBe(4);
|
|
});
|
|
});
|
|
|
|
describe("configuration", () => {
|
|
it("should return current configuration", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({
|
|
inputDim: 16,
|
|
hiddenDim: 8,
|
|
dropout: 0.2,
|
|
normalize: false,
|
|
temperature: 0.5,
|
|
});
|
|
|
|
// Act
|
|
const config = attention.getConfig();
|
|
|
|
// Assert
|
|
expect(config.inputDim).toBe(16);
|
|
expect(config.hiddenDim).toBe(8);
|
|
expect(config.dropout).toBe(0.2);
|
|
expect(config.normalize).toBe(false);
|
|
expect(config.temperature).toBe(0.5);
|
|
});
|
|
|
|
it("should use default configuration values", () => {
|
|
// Arrange
|
|
const attention = new GraphAttention({ inputDim: 32 });
|
|
|
|
// Act
|
|
const config = attention.getConfig();
|
|
|
|
// Assert
|
|
expect(config.hiddenDim).toBe(8); // inputDim / 4
|
|
expect(config.dropout).toBe(0.1);
|
|
expect(config.normalize).toBe(true);
|
|
expect(config.temperature).toBe(1.0);
|
|
});
|
|
});
|
|
});
|
|
|
|
// -----------------------------------------------------------------------------
|
|
// Client Pattern Export/Import Tests
|
|
// -----------------------------------------------------------------------------
|
|
|
|
describe("RuvectorClient Pattern Export/Import", () => {
|
|
let RuvectorClient: typeof import("./client.js").RuvectorClient;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./client.js");
|
|
RuvectorClient = module.RuvectorClient;
|
|
});
|
|
|
|
describe("exportPatterns", () => {
|
|
it("should export patterns to a file", async () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
await client.connect();
|
|
|
|
client.initializePatternStore();
|
|
client.addPatternSample({
|
|
id: "sample-1",
|
|
queryVector: [1, 0, 0, 0],
|
|
resultVector: [0.9, 0.1, 0, 0],
|
|
relevanceScore: 0.85,
|
|
timestamp: Date.now(),
|
|
});
|
|
client.addPatternSample({
|
|
id: "sample-2",
|
|
queryVector: [0, 1, 0, 0],
|
|
resultVector: [0.1, 0.9, 0, 0],
|
|
relevanceScore: 0.75,
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
// Create temp file
|
|
const { mkdtemp, rm } = await import("node:fs/promises");
|
|
const { tmpdir } = await import("node:os");
|
|
const { join } = await import("node:path");
|
|
const tempDir = await mkdtemp(join(tmpdir(), "ruvector-client-test-"));
|
|
const exportPath = join(tempDir, "client-patterns.json");
|
|
|
|
try {
|
|
// Act
|
|
const result = await client.exportPatterns(exportPath);
|
|
|
|
// Assert
|
|
expect(result.sampleCount).toBe(2);
|
|
|
|
// Verify file content
|
|
const { readFile } = await import("node:fs/promises");
|
|
const content = JSON.parse(await readFile(exportPath, "utf-8"));
|
|
expect(content.version).toBe("1.0.0");
|
|
expect(content.samples).toHaveLength(2);
|
|
} finally {
|
|
await rm(tempDir, { recursive: true });
|
|
}
|
|
});
|
|
|
|
it("should throw for invalid path", async () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
await client.connect();
|
|
client.initializePatternStore();
|
|
|
|
// Act & Assert
|
|
await expect(client.exportPatterns("")).rejects.toThrow(/invalid.*path/i);
|
|
});
|
|
|
|
it("should throw when pattern store not initialized", async () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
await client.connect();
|
|
// Note: NOT calling initializePatternStore()
|
|
|
|
// Act & Assert
|
|
await expect(client.exportPatterns("/tmp/test.json")).rejects.toThrow(/not initialized/i);
|
|
});
|
|
});
|
|
|
|
describe("importPatterns", () => {
|
|
it("should import patterns from a file", async () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
await client.connect();
|
|
|
|
// Create test export file
|
|
const { mkdtemp, rm, writeFile } = await import("node:fs/promises");
|
|
const { tmpdir } = await import("node:os");
|
|
const { join } = await import("node:path");
|
|
const tempDir = await mkdtemp(join(tmpdir(), "ruvector-import-test-"));
|
|
const importPath = join(tempDir, "import-patterns.json");
|
|
|
|
const exportData = {
|
|
version: "1.0.0",
|
|
exportedAt: Date.now(),
|
|
dimension: 4,
|
|
clusters: [
|
|
{ id: "cluster-1", centroid: [0.5, 0.5, 0, 0, 0, 0, 0, 0], members: ["s1"], avgQuality: 0.8, lastUpdated: Date.now() },
|
|
],
|
|
samples: [
|
|
{ id: "s1", queryVector: [1, 0, 0, 0], resultVector: [0.9, 0.1, 0, 0], relevanceScore: 0.9, timestamp: Date.now() },
|
|
],
|
|
};
|
|
|
|
await writeFile(importPath, JSON.stringify(exportData), "utf-8");
|
|
|
|
try {
|
|
// Act
|
|
const result = await client.importPatterns(importPath);
|
|
|
|
// Assert
|
|
expect(result.clusterCount).toBe(1);
|
|
expect(result.sampleCount).toBe(1);
|
|
expect(result.version).toBe("1.0.0");
|
|
} finally {
|
|
await rm(tempDir, { recursive: true });
|
|
}
|
|
});
|
|
|
|
it("should throw for missing file", async () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
await client.connect();
|
|
|
|
// Act & Assert
|
|
await expect(client.importPatterns("/nonexistent/path.json")).rejects.toThrow(/failed to read/i);
|
|
});
|
|
|
|
it("should throw for invalid JSON", async () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
await client.connect();
|
|
|
|
const { mkdtemp, rm, writeFile } = await import("node:fs/promises");
|
|
const { tmpdir } = await import("node:os");
|
|
const { join } = await import("node:path");
|
|
const tempDir = await mkdtemp(join(tmpdir(), "ruvector-invalid-test-"));
|
|
const invalidPath = join(tempDir, "invalid.json");
|
|
|
|
await writeFile(invalidPath, "not json content", "utf-8");
|
|
|
|
try {
|
|
// Act & Assert
|
|
await expect(client.importPatterns(invalidPath)).rejects.toThrow(/invalid.*format/i);
|
|
} finally {
|
|
await rm(tempDir, { recursive: true });
|
|
}
|
|
});
|
|
});
|
|
|
|
describe("mergePatterns", () => {
|
|
it("should merge patterns from file with existing ones", async () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
await client.connect();
|
|
client.initializePatternStore();
|
|
|
|
// Add existing sample
|
|
client.addPatternSample({
|
|
id: "existing-1",
|
|
queryVector: [1, 0, 0, 0],
|
|
resultVector: [0.9, 0.1, 0, 0],
|
|
relevanceScore: 0.8,
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
// Create merge file
|
|
const { mkdtemp, rm, writeFile } = await import("node:fs/promises");
|
|
const { tmpdir } = await import("node:os");
|
|
const { join } = await import("node:path");
|
|
const tempDir = await mkdtemp(join(tmpdir(), "ruvector-merge-test-"));
|
|
const mergePath = join(tempDir, "merge-patterns.json");
|
|
|
|
const mergeData = {
|
|
version: "1.0.0",
|
|
samples: [
|
|
{ id: "merged-1", queryVector: [0, 1, 0, 0], resultVector: [0.1, 0.9, 0, 0], relevanceScore: 0.85, timestamp: Date.now() },
|
|
{ id: "merged-2", queryVector: [0, 0, 1, 0], resultVector: [0, 0.1, 0.9, 0], relevanceScore: 0.75, timestamp: Date.now() },
|
|
],
|
|
};
|
|
|
|
await writeFile(mergePath, JSON.stringify(mergeData), "utf-8");
|
|
|
|
try {
|
|
// Act
|
|
const result = await client.mergePatterns(mergePath);
|
|
|
|
// Assert
|
|
expect(result.importedSamples).toBe(2);
|
|
expect(result.finalSamples).toBeGreaterThanOrEqual(2); // May include existing
|
|
} finally {
|
|
await rm(tempDir, { recursive: true });
|
|
}
|
|
});
|
|
|
|
it("should throw for invalid path", async () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
await client.connect();
|
|
|
|
// Act & Assert
|
|
await expect(client.mergePatterns("")).rejects.toThrow(/invalid.*path/i);
|
|
});
|
|
});
|
|
|
|
describe("getPatternStats", () => {
|
|
it("should return stats when pattern store is initialized", () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
client.initializePatternStore();
|
|
|
|
client.addPatternSample({
|
|
id: "s1",
|
|
queryVector: [1, 0, 0, 0],
|
|
resultVector: [0.9, 0.1, 0, 0],
|
|
relevanceScore: 0.8,
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
// Act
|
|
const stats = client.getPatternStats();
|
|
|
|
// Assert
|
|
expect(stats.initialized).toBe(true);
|
|
expect(stats.sampleCount).toBe(1);
|
|
});
|
|
|
|
it("should return uninitialized stats when pattern store not created", () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
|
|
// Act
|
|
const stats = client.getPatternStats();
|
|
|
|
// Assert
|
|
expect(stats.initialized).toBe(false);
|
|
expect(stats.clusterCount).toBe(0);
|
|
expect(stats.sampleCount).toBe(0);
|
|
});
|
|
});
|
|
|
|
describe("pattern store operations", () => {
|
|
it("should initialize pattern store with config", () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
|
|
// Act
|
|
client.initializePatternStore({ maxClusters: 5, qualityThreshold: 0.6 });
|
|
|
|
// Assert
|
|
expect(client.getPatternStore()).not.toBeNull();
|
|
});
|
|
|
|
it("should not re-initialize if already initialized", () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
client.initializePatternStore();
|
|
const originalStore = client.getPatternStore();
|
|
|
|
// Act
|
|
client.initializePatternStore();
|
|
|
|
// Assert
|
|
expect(client.getPatternStore()).toBe(originalStore);
|
|
});
|
|
|
|
it("should add samples and trigger clustering", () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 4 }, logger);
|
|
client.initializePatternStore({ minSamplesPerCluster: 2 });
|
|
|
|
// Act - add samples (enough to trigger clustering)
|
|
for (let i = 0; i < 6; i++) {
|
|
client.addPatternSample({
|
|
id: `sample-${i}`,
|
|
queryVector: [Math.random(), Math.random(), Math.random(), Math.random()],
|
|
resultVector: [Math.random(), Math.random(), Math.random(), Math.random()],
|
|
relevanceScore: 0.7 + Math.random() * 0.3,
|
|
timestamp: Date.now(),
|
|
});
|
|
}
|
|
|
|
// Assert
|
|
const stats = client.getPatternStats();
|
|
expect(stats.sampleCount).toBe(6);
|
|
});
|
|
|
|
it("should rerank results using patterns", async () => {
|
|
// Arrange
|
|
const logger = createMockLogger();
|
|
const client = new RuvectorClient({ dimension: 1536 }, logger);
|
|
await client.connect();
|
|
client.initializePatternStore();
|
|
|
|
// Create search results
|
|
const results = [
|
|
{ entry: { id: "r1", vector: new Array(1536).fill(0.1), metadata: { text: "result 1" } }, score: 0.8 },
|
|
{ entry: { id: "r2", vector: new Array(1536).fill(0.2), metadata: { text: "result 2" } }, score: 0.7 },
|
|
];
|
|
|
|
const queryVector = new Array(1536).fill(0.15);
|
|
|
|
// Act
|
|
const reranked = client.rerank(results, queryVector, 0.1);
|
|
|
|
// Assert - results should be returned (may or may not be reranked depending on patterns)
|
|
expect(reranked).toHaveLength(2);
|
|
expect(reranked[0].score).toBeGreaterThanOrEqual(0);
|
|
});
|
|
});
|
|
});
|
|
|
|
// -----------------------------------------------------------------------------
|
|
// PatternStore Tests
|
|
// -----------------------------------------------------------------------------
|
|
|
|
describe("PatternStore", () => {
|
|
let PatternStore: typeof import("./sona/patterns.js").PatternStore;
|
|
|
|
beforeEach(async () => {
|
|
vi.clearAllMocks();
|
|
const module = await import("./sona/patterns.js");
|
|
PatternStore = module.PatternStore;
|
|
});
|
|
|
|
describe("addSample and clustering", () => {
|
|
it("should add high-quality samples", () => {
|
|
// Arrange
|
|
const store = new PatternStore({ qualityThreshold: 0.5 });
|
|
|
|
// Act
|
|
store.addSample({
|
|
id: "s1",
|
|
queryVector: [1, 0, 0],
|
|
resultVector: [0.9, 0.1, 0],
|
|
relevanceScore: 0.8,
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
// Assert
|
|
expect(store.getSampleCount()).toBe(1);
|
|
});
|
|
|
|
it("should reject low-quality samples", () => {
|
|
// Arrange
|
|
const store = new PatternStore({ qualityThreshold: 0.5 });
|
|
|
|
// Act
|
|
store.addSample({
|
|
id: "s1",
|
|
queryVector: [1, 0, 0],
|
|
resultVector: [0.9, 0.1, 0],
|
|
relevanceScore: 0.3, // Below threshold
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
// Assert
|
|
expect(store.getSampleCount()).toBe(0);
|
|
});
|
|
|
|
it("should trigger clustering after threshold samples", () => {
|
|
// Arrange
|
|
const store = new PatternStore({
|
|
minSamplesPerCluster: 2,
|
|
qualityThreshold: 0.5,
|
|
});
|
|
|
|
// Act - add enough samples to trigger clustering (2 * minSamplesPerCluster)
|
|
for (let i = 0; i < 4; i++) {
|
|
store.addSample({
|
|
id: `s${i}`,
|
|
queryVector: [Math.random(), Math.random()],
|
|
resultVector: [Math.random(), Math.random()],
|
|
relevanceScore: 0.7,
|
|
timestamp: Date.now(),
|
|
});
|
|
}
|
|
|
|
// Assert
|
|
expect(store.getSampleCount()).toBe(4);
|
|
// Clusters may or may not be created depending on sample similarity
|
|
});
|
|
});
|
|
|
|
describe("findSimilar", () => {
|
|
it("should find similar patterns to a query", () => {
|
|
// Arrange
|
|
const store = new PatternStore({ minSamplesPerCluster: 2, qualityThreshold: 0.5 });
|
|
|
|
// Add samples and cluster
|
|
for (let i = 0; i < 6; i++) {
|
|
store.addSample({
|
|
id: `s${i}`,
|
|
queryVector: [i * 0.1, 1 - i * 0.1],
|
|
resultVector: [i * 0.15, 1 - i * 0.15],
|
|
relevanceScore: 0.8,
|
|
timestamp: Date.now(),
|
|
});
|
|
}
|
|
store.cluster();
|
|
|
|
// Act
|
|
const similar = store.findSimilar([0.5, 0.5], 3);
|
|
|
|
// Assert
|
|
expect(similar).toBeDefined();
|
|
expect(Array.isArray(similar)).toBe(true);
|
|
});
|
|
|
|
it("should return empty array when no clusters exist", () => {
|
|
// Arrange
|
|
const store = new PatternStore();
|
|
|
|
// Act
|
|
const similar = store.findSimilar([1, 0, 0], 5);
|
|
|
|
// Assert
|
|
expect(similar).toHaveLength(0);
|
|
});
|
|
});
|
|
|
|
describe("updateFromFeedback", () => {
|
|
it("should update sample relevance score", () => {
|
|
// Arrange
|
|
const store = new PatternStore({ qualityThreshold: 0.3 });
|
|
store.addSample({
|
|
id: "update-test",
|
|
queryVector: [1, 0],
|
|
resultVector: [0.9, 0.1],
|
|
relevanceScore: 0.5,
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
// Act
|
|
store.updateFromFeedback("update-test", 0.9);
|
|
|
|
// Assert
|
|
const samples = store.getSamples();
|
|
const updated = samples.find((s) => s.id === "update-test");
|
|
expect(updated?.relevanceScore).toBe(0.9);
|
|
});
|
|
|
|
it("should handle non-existent sample gracefully", () => {
|
|
// Arrange
|
|
const store = new PatternStore();
|
|
|
|
// Act & Assert - should not throw
|
|
expect(() => store.updateFromFeedback("nonexistent", 0.8)).not.toThrow();
|
|
});
|
|
});
|
|
|
|
describe("export and import", () => {
|
|
it("should export store state", () => {
|
|
// Arrange
|
|
const store = new PatternStore({ minSamplesPerCluster: 2, qualityThreshold: 0.5 });
|
|
for (let i = 0; i < 4; i++) {
|
|
store.addSample({
|
|
id: `s${i}`,
|
|
queryVector: [i * 0.2, 0.5],
|
|
resultVector: [0.5, i * 0.2],
|
|
relevanceScore: 0.7,
|
|
timestamp: Date.now(),
|
|
});
|
|
}
|
|
store.cluster();
|
|
|
|
// Act
|
|
const exported = store.export();
|
|
|
|
// Assert
|
|
expect(exported.samples).toHaveLength(4);
|
|
expect(Array.isArray(exported.clusters)).toBe(true);
|
|
});
|
|
|
|
it("should import previously exported state", () => {
|
|
// Arrange
|
|
const store = new PatternStore();
|
|
const importData = {
|
|
clusters: [
|
|
{ id: "cluster-0", centroid: [0.5, 0.5, 0.5, 0.5], members: ["s1"], avgQuality: 0.8, lastUpdated: Date.now() },
|
|
],
|
|
samples: [
|
|
{ id: "s1", queryVector: [1, 0], resultVector: [0.9, 0.1], relevanceScore: 0.8, timestamp: Date.now() },
|
|
],
|
|
};
|
|
|
|
// Act
|
|
store.import(importData);
|
|
|
|
// Assert
|
|
expect(store.getSampleCount()).toBe(1);
|
|
expect(store.getClusterCount()).toBe(1);
|
|
});
|
|
|
|
it("should throw for invalid import data", () => {
|
|
// Arrange
|
|
const store = new PatternStore();
|
|
|
|
// Act & Assert
|
|
expect(() => store.import(null as unknown as { clusters: []; samples: [] })).toThrow();
|
|
expect(() => store.import({ clusters: "invalid", samples: [] } as unknown as { clusters: []; samples: [] })).toThrow();
|
|
});
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// P2 ruvLLM Features: BackgroundLoop Tests
|
|
// =============================================================================
|
|
|
|
describe("BackgroundLoop", () => {
|
|
let BackgroundLoop: typeof import("./sona/loops/background.js").BackgroundLoop;
|
|
|
|
beforeEach(async () => {
|
|
vi.resetModules();
|
|
vi.clearAllMocks();
|
|
vi.useFakeTimers();
|
|
|
|
const backgroundModule = await import("./sona/loops/background.js");
|
|
BackgroundLoop = backgroundModule.BackgroundLoop;
|
|
});
|
|
|
|
afterEach(() => {
|
|
vi.useRealTimers();
|
|
});
|
|
|
|
function createMockDeps() {
|
|
return {
|
|
client: {
|
|
search: vi.fn().mockResolvedValue([]),
|
|
get: vi.fn().mockResolvedValue(null),
|
|
insert: vi.fn().mockResolvedValue("test-id"),
|
|
getSONAStats: vi.fn().mockResolvedValue({ enabled: true }),
|
|
applyMicroLora: vi.fn(),
|
|
},
|
|
db: {
|
|
insert: vi.fn().mockResolvedValue(undefined),
|
|
search: vi.fn().mockResolvedValue([]),
|
|
},
|
|
embeddings: {
|
|
embed: vi.fn().mockResolvedValue([0.1, 0.2, 0.3, 0.4]),
|
|
},
|
|
config: {
|
|
enabled: true,
|
|
hiddenDim: 256,
|
|
backgroundIntervalMs: 30000,
|
|
learningRate: 0.01,
|
|
qualityThreshold: 0.5,
|
|
},
|
|
logger: createMockLogger(),
|
|
};
|
|
}
|
|
|
|
describe("lifecycle methods", () => {
|
|
it("should start and set isActive to true", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Act
|
|
loop.start();
|
|
|
|
// Assert
|
|
expect(loop.isActive()).toBe(true);
|
|
});
|
|
|
|
it("should not start twice if already running", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Act
|
|
loop.start();
|
|
loop.start();
|
|
|
|
// Assert
|
|
expect(loop.isActive()).toBe(true);
|
|
expect(deps.logger.warn).toHaveBeenCalledWith("background-loop: already running");
|
|
});
|
|
|
|
it("should not start if SONA is disabled", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.config.enabled = false;
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Act
|
|
loop.start();
|
|
|
|
// Assert
|
|
expect(loop.isActive()).toBe(false);
|
|
});
|
|
|
|
it("should stop and set isActive to false", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
loop.start();
|
|
|
|
// Act
|
|
await loop.stop();
|
|
|
|
// Assert
|
|
expect(loop.isActive()).toBe(false);
|
|
});
|
|
|
|
it("should do nothing when stopping an already stopped loop", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Act & Assert - should not throw
|
|
await loop.stop();
|
|
expect(loop.isActive()).toBe(false);
|
|
});
|
|
});
|
|
|
|
describe("recordTrajectory", () => {
|
|
it("should record a trajectory", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
const trajectory = {
|
|
id: "traj-1",
|
|
queryVector: [0.1, 0.2, 0.3],
|
|
resultVectors: [[0.4, 0.5, 0.6]],
|
|
scores: [0.8],
|
|
timestamp: Date.now(),
|
|
};
|
|
|
|
// Act
|
|
loop.recordTrajectory(trajectory);
|
|
|
|
// Assert - trajectory should be stored (getCycleStats indirectly tests this)
|
|
expect(loop.getCycleStats()).toHaveLength(0); // No cycles run yet
|
|
});
|
|
|
|
it("should limit trajectory buffer to maxTrajectories", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Act - add more than maxTrajectories (1000)
|
|
for (let i = 0; i < 1005; i++) {
|
|
loop.recordTrajectory({
|
|
id: `traj-${i}`,
|
|
queryVector: [0.1, 0.2, 0.3],
|
|
resultVectors: [[0.4, 0.5, 0.6]],
|
|
scores: [0.8],
|
|
timestamp: Date.now(),
|
|
});
|
|
}
|
|
|
|
// Assert - buffer should be limited
|
|
expect(deps.logger.debug).toHaveBeenCalled();
|
|
});
|
|
});
|
|
|
|
describe("runCycle", () => {
|
|
it("should return empty stats when no trajectories", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Act
|
|
const stats = await loop.runCycle();
|
|
|
|
// Assert
|
|
expect(stats.trajectoriesProcessed).toBe(0);
|
|
expect(stats.clustersUpdated).toBe(0);
|
|
expect(stats.newPatternsDetected).toBe(0);
|
|
});
|
|
|
|
it("should process recent trajectories and create patterns", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Record trajectory within the last hour
|
|
loop.recordTrajectory({
|
|
id: "traj-1",
|
|
queryVector: [0.1, 0.2, 0.3, 0.4],
|
|
resultVectors: [[0.5, 0.6, 0.7, 0.8]],
|
|
scores: [0.9],
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
// Act
|
|
const stats = await loop.runCycle();
|
|
|
|
// Assert
|
|
expect(stats.trajectoriesProcessed).toBe(1);
|
|
expect(stats.newPatternsDetected).toBe(1);
|
|
expect(loop.getPatterns()).toHaveLength(1);
|
|
});
|
|
|
|
it("should skip cycle if one is already in progress", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Start a cycle that takes time
|
|
const cycle1Promise = loop.runCycle();
|
|
|
|
// Act - try to start another cycle immediately
|
|
const cycle2Promise = loop.runCycle();
|
|
|
|
// Assert
|
|
const [stats1, stats2] = await Promise.all([cycle1Promise, cycle2Promise]);
|
|
expect(stats2.trajectoriesProcessed).toBe(0); // Skipped
|
|
});
|
|
|
|
it("should update existing patterns when trajectories are similar", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Record similar trajectories
|
|
const baseVector = [0.9, 0.9, 0.9, 0.9];
|
|
for (let i = 0; i < 5; i++) {
|
|
loop.recordTrajectory({
|
|
id: `traj-${i}`,
|
|
queryVector: baseVector.map(v => v + Math.random() * 0.01),
|
|
resultVectors: [[0.5, 0.6, 0.7, 0.8]],
|
|
scores: [0.8],
|
|
timestamp: Date.now(),
|
|
});
|
|
}
|
|
|
|
// Act
|
|
const stats = await loop.runCycle();
|
|
|
|
// Assert - should merge into fewer patterns due to similarity
|
|
expect(stats.trajectoriesProcessed).toBe(5);
|
|
expect(loop.getPatterns().length).toBeLessThanOrEqual(5);
|
|
});
|
|
});
|
|
|
|
describe("getCycleStats", () => {
|
|
it("should return cycle statistics", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Act
|
|
await loop.runCycle();
|
|
const stats = loop.getCycleStats();
|
|
|
|
// Assert
|
|
expect(stats).toHaveLength(1);
|
|
expect(stats[0]).toHaveProperty("trajectoriesProcessed");
|
|
expect(stats[0]).toHaveProperty("completedAt");
|
|
});
|
|
});
|
|
|
|
describe("getPatterns", () => {
|
|
it("should return empty array initially", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new BackgroundLoop(deps as any);
|
|
|
|
// Act
|
|
const patterns = loop.getPatterns();
|
|
|
|
// Assert
|
|
expect(patterns).toEqual([]);
|
|
});
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// P2 ruvLLM Features: InstantLoop Tests
|
|
// =============================================================================
|
|
|
|
describe("InstantLoop", () => {
|
|
let InstantLoop: typeof import("./sona/loops/instant.js").InstantLoop;
|
|
|
|
beforeEach(async () => {
|
|
vi.resetModules();
|
|
vi.clearAllMocks();
|
|
|
|
const instantModule = await import("./sona/loops/instant.js");
|
|
InstantLoop = instantModule.InstantLoop;
|
|
});
|
|
|
|
function createMockDeps() {
|
|
return {
|
|
client: {
|
|
search: vi.fn().mockResolvedValue([]),
|
|
get: vi.fn().mockResolvedValue(null),
|
|
getSONAStats: vi.fn().mockResolvedValue({ enabled: true }),
|
|
recordSearchFeedback: vi.fn().mockResolvedValue(undefined),
|
|
},
|
|
db: {},
|
|
embeddings: {
|
|
embed: vi.fn().mockResolvedValue([0.1, 0.2, 0.3, 0.4]),
|
|
},
|
|
config: {
|
|
enabled: true,
|
|
hiddenDim: 256,
|
|
learningRate: 0.01,
|
|
qualityThreshold: 0.5,
|
|
},
|
|
logger: createMockLogger(),
|
|
};
|
|
}
|
|
|
|
describe("processImmediateFeedback", () => {
|
|
it("should process feedback and update stats", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new InstantLoop(deps as any);
|
|
const feedback = {
|
|
queryVector: [0.1, 0.2, 0.3, 0.4],
|
|
resultVector: [0.5, 0.6, 0.7, 0.8],
|
|
score: 0.9,
|
|
feedbackType: "selection" as const,
|
|
};
|
|
|
|
// Act
|
|
await loop.processImmediateFeedback(feedback);
|
|
|
|
// Assert
|
|
const stats = loop.getStats();
|
|
expect(stats.feedbackProcessed).toBe(1);
|
|
expect(stats.positiveBoosts).toBe(1);
|
|
});
|
|
|
|
it("should not process if SONA is disabled", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.config.enabled = false;
|
|
const loop = new InstantLoop(deps as any);
|
|
const feedback = {
|
|
queryVector: [0.1, 0.2, 0.3, 0.4],
|
|
resultVector: [0.5, 0.6, 0.7, 0.8],
|
|
score: 0.9,
|
|
feedbackType: "selection" as const,
|
|
};
|
|
|
|
// Act
|
|
await loop.processImmediateFeedback(feedback);
|
|
|
|
// Assert
|
|
const stats = loop.getStats();
|
|
expect(stats.feedbackProcessed).toBe(0);
|
|
});
|
|
|
|
it("should record negative boost for low scores", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new InstantLoop(deps as any);
|
|
const feedback = {
|
|
queryVector: [0.1, 0.2, 0.3, 0.4],
|
|
resultVector: [0.5, 0.6, 0.7, 0.8],
|
|
score: 0.1, // Below quality threshold of 0.5
|
|
feedbackType: "correction" as const,
|
|
};
|
|
|
|
// Act
|
|
await loop.processImmediateFeedback(feedback);
|
|
|
|
// Assert
|
|
const stats = loop.getStats();
|
|
expect(stats.negativeBoosts).toBe(1);
|
|
});
|
|
|
|
it("should track patterns", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new InstantLoop(deps as any);
|
|
|
|
// Act - process multiple feedbacks
|
|
for (let i = 0; i < 5; i++) {
|
|
await loop.processImmediateFeedback({
|
|
queryVector: [0.1 * i, 0.2 * i, 0.3 * i, 0.4 * i],
|
|
resultVector: [0.5, 0.6, 0.7, 0.8],
|
|
score: 0.8,
|
|
feedbackType: "selection" as const,
|
|
});
|
|
}
|
|
|
|
// Assert
|
|
const stats = loop.getStats();
|
|
expect(stats.patternsTracked).toBeGreaterThan(0);
|
|
});
|
|
});
|
|
|
|
describe("getBoostForVector", () => {
|
|
it("should return 1.0 for unknown vectors", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new InstantLoop(deps as any);
|
|
|
|
// Act
|
|
const boost = loop.getBoostForVector([0.1, 0.2, 0.3, 0.4]);
|
|
|
|
// Assert
|
|
expect(boost).toBe(1.0);
|
|
});
|
|
|
|
it("should return boost for similar vectors", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new InstantLoop(deps as any);
|
|
const vector = [0.9, 0.9, 0.9, 0.9];
|
|
|
|
// Process feedback to create a pattern
|
|
await loop.processImmediateFeedback({
|
|
queryVector: vector,
|
|
resultVector: [0.5, 0.6, 0.7, 0.8],
|
|
score: 0.95, // High score
|
|
feedbackType: "selection" as const,
|
|
});
|
|
|
|
// Act - query with very similar vector
|
|
const boost = loop.getBoostForVector([0.9, 0.9, 0.9, 0.9]);
|
|
|
|
// Assert - should find a boost (may or may not be > 1 depending on similarity threshold)
|
|
expect(typeof boost).toBe("number");
|
|
});
|
|
});
|
|
|
|
describe("getPatternBoosts", () => {
|
|
it("should return all pattern boosts", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new InstantLoop(deps as any);
|
|
|
|
// Act
|
|
await loop.processImmediateFeedback({
|
|
queryVector: [0.1, 0.2, 0.3, 0.4],
|
|
resultVector: [0.5, 0.6, 0.7, 0.8],
|
|
score: 0.8,
|
|
feedbackType: "selection" as const,
|
|
});
|
|
|
|
// Assert
|
|
const boosts = loop.getPatternBoosts();
|
|
expect(Array.isArray(boosts)).toBe(true);
|
|
expect(boosts.length).toBeGreaterThan(0);
|
|
});
|
|
});
|
|
|
|
describe("applyDecay", () => {
|
|
it("should decay pattern boosts over time", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new InstantLoop(deps as any);
|
|
|
|
// Create a pattern
|
|
await loop.processImmediateFeedback({
|
|
queryVector: [0.9, 0.9, 0.9, 0.9],
|
|
resultVector: [0.5, 0.6, 0.7, 0.8],
|
|
score: 0.95,
|
|
feedbackType: "selection" as const,
|
|
});
|
|
|
|
const boostsBefore = loop.getPatternBoosts();
|
|
|
|
// Act
|
|
loop.applyDecay();
|
|
|
|
// Assert - boosts should have decayed (values move toward 1.0)
|
|
const boostsAfter = loop.getPatternBoosts();
|
|
expect(boostsAfter.length).toBeLessThanOrEqual(boostsBefore.length);
|
|
});
|
|
|
|
it("should remove nearly-neutral boosts", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
// Lower learning rate to create smaller boosts
|
|
deps.config.learningRate = 0.001;
|
|
const loop = new InstantLoop(deps as any);
|
|
|
|
// Create patterns with small boosts
|
|
await loop.processImmediateFeedback({
|
|
queryVector: [0.5, 0.5, 0.5, 0.5],
|
|
resultVector: [0.5, 0.6, 0.7, 0.8],
|
|
score: 0.51, // Just above threshold
|
|
feedbackType: "selection" as const,
|
|
});
|
|
|
|
// Act - apply decay multiple times
|
|
for (let i = 0; i < 100; i++) {
|
|
loop.applyDecay();
|
|
}
|
|
|
|
// Assert - nearly-neutral patterns should be removed
|
|
const stats = loop.getStats();
|
|
expect(stats.patternsTracked).toBeLessThanOrEqual(2);
|
|
});
|
|
});
|
|
|
|
describe("reset", () => {
|
|
it("should clear all patterns and reset stats", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new InstantLoop(deps as any);
|
|
|
|
// Build up some state
|
|
await loop.processImmediateFeedback({
|
|
queryVector: [0.1, 0.2, 0.3, 0.4],
|
|
resultVector: [0.5, 0.6, 0.7, 0.8],
|
|
score: 0.9,
|
|
feedbackType: "selection" as const,
|
|
});
|
|
|
|
// Act
|
|
loop.reset();
|
|
|
|
// Assert
|
|
const stats = loop.getStats();
|
|
expect(stats.feedbackProcessed).toBe(0);
|
|
expect(stats.positiveBoosts).toBe(0);
|
|
expect(stats.negativeBoosts).toBe(0);
|
|
expect(stats.patternsTracked).toBe(0);
|
|
expect(loop.getPatternBoosts()).toHaveLength(0);
|
|
});
|
|
});
|
|
|
|
describe("getStats", () => {
|
|
it("should return initial stats", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new InstantLoop(deps as any);
|
|
|
|
// Act
|
|
const stats = loop.getStats();
|
|
|
|
// Assert
|
|
expect(stats).toEqual({
|
|
feedbackProcessed: 0,
|
|
positiveBoosts: 0,
|
|
negativeBoosts: 0,
|
|
patternsTracked: 0,
|
|
avgProcessingTimeMs: 0,
|
|
});
|
|
});
|
|
|
|
it("should track average processing time", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const loop = new InstantLoop(deps as any);
|
|
|
|
// Act
|
|
await loop.processImmediateFeedback({
|
|
queryVector: [0.1, 0.2, 0.3, 0.4],
|
|
resultVector: [0.5, 0.6, 0.7, 0.8],
|
|
score: 0.8,
|
|
feedbackType: "selection" as const,
|
|
});
|
|
|
|
// Assert
|
|
const stats = loop.getStats();
|
|
expect(stats.avgProcessingTimeMs).toBeGreaterThanOrEqual(0);
|
|
});
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// P2 ruvLLM Features: RelationshipInferrer Tests
|
|
// =============================================================================
|
|
|
|
describe("RelationshipInferrer", () => {
|
|
let RelationshipInferrer: typeof import("./graph/relationships.js").RelationshipInferrer;
|
|
|
|
beforeEach(async () => {
|
|
vi.resetModules();
|
|
vi.clearAllMocks();
|
|
|
|
const relModule = await import("./graph/relationships.js");
|
|
RelationshipInferrer = relModule.RelationshipInferrer;
|
|
});
|
|
|
|
function createMockDeps() {
|
|
return {
|
|
client: {
|
|
get: vi.fn().mockResolvedValue({
|
|
id: "test-id",
|
|
vector: [0.1, 0.2, 0.3],
|
|
metadata: { text: "Test content" },
|
|
}),
|
|
search: vi.fn().mockResolvedValue([]),
|
|
addEdge: vi.fn().mockResolvedValue("edge-1"),
|
|
isGraphInitialized: vi.fn().mockReturnValue(true),
|
|
getNeighbors: vi.fn().mockResolvedValue([]),
|
|
},
|
|
db: {},
|
|
embeddings: {
|
|
embed: vi.fn().mockResolvedValue([0.1, 0.2, 0.3, 0.4]),
|
|
},
|
|
logger: createMockLogger(),
|
|
};
|
|
}
|
|
|
|
describe("extractEntities", () => {
|
|
it("should extract email addresses", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const content = "Contact us at support@example.com for help.";
|
|
|
|
// Act
|
|
const entities = inferrer.extractEntities(content);
|
|
|
|
// Assert
|
|
const emails = entities.filter(e => e.type === "email");
|
|
expect(emails).toHaveLength(1);
|
|
expect(emails[0].text).toBe("support@example.com");
|
|
expect(emails[0].confidence).toBeGreaterThan(0.9);
|
|
});
|
|
|
|
it("should extract URLs", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const content = "Visit https://example.com/page for more info.";
|
|
|
|
// Act
|
|
const entities = inferrer.extractEntities(content);
|
|
|
|
// Assert
|
|
const urls = entities.filter(e => e.type === "url");
|
|
expect(urls).toHaveLength(1);
|
|
expect(urls[0].text).toContain("example.com");
|
|
});
|
|
|
|
it("should extract dates", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const content = "The meeting is on 2024-01-15 and follows up on January 10, 2024.";
|
|
|
|
// Act
|
|
const entities = inferrer.extractEntities(content);
|
|
|
|
// Assert
|
|
const dates = entities.filter(e => e.type === "date");
|
|
expect(dates.length).toBeGreaterThanOrEqual(1);
|
|
});
|
|
|
|
it("should extract person names", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const content = "Dr. John Smith met with Jane Doe yesterday.";
|
|
|
|
// Act
|
|
const entities = inferrer.extractEntities(content);
|
|
|
|
// Assert
|
|
const persons = entities.filter(e => e.type === "person");
|
|
expect(persons.length).toBeGreaterThanOrEqual(1);
|
|
});
|
|
|
|
it("should filter by entity types", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const content = "Email support@test.com or visit https://test.com";
|
|
|
|
// Act
|
|
const entities = inferrer.extractEntities(content, ["email"]);
|
|
|
|
// Assert
|
|
expect(entities.every(e => e.type === "email")).toBe(true);
|
|
});
|
|
|
|
it("should not extract duplicates", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const content = "Email test@example.com or test@example.com again.";
|
|
|
|
// Act
|
|
const entities = inferrer.extractEntities(content);
|
|
|
|
// Assert
|
|
const emails = entities.filter(e => e.type === "email");
|
|
expect(emails).toHaveLength(1);
|
|
});
|
|
|
|
it("should sort entities by position", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const content = "Visit https://example.com then email test@example.com";
|
|
|
|
// Act
|
|
const entities = inferrer.extractEntities(content);
|
|
|
|
// Assert
|
|
for (let i = 1; i < entities.length; i++) {
|
|
expect(entities[i].startPos).toBeGreaterThanOrEqual(entities[i - 1].startPos);
|
|
}
|
|
});
|
|
});
|
|
|
|
describe("inferFromContent", () => {
|
|
it("should return empty results for entries without text", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const entry = {
|
|
id: "test-1",
|
|
vector: [0.1, 0.2],
|
|
metadata: {},
|
|
};
|
|
|
|
// Act
|
|
const result = await inferrer.inferFromContent(entry);
|
|
|
|
// Assert
|
|
expect(result.entities).toHaveLength(0);
|
|
expect(result.relationships).toHaveLength(0);
|
|
});
|
|
|
|
it("should extract entities from entry text", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const entry = {
|
|
id: "test-1",
|
|
vector: [0.1, 0.2],
|
|
metadata: { text: "Contact support@example.com for help." },
|
|
};
|
|
|
|
// Act
|
|
const result = await inferrer.inferFromContent(entry);
|
|
|
|
// Assert
|
|
expect(result.entities.length).toBeGreaterThan(0);
|
|
});
|
|
|
|
it("should detect relationships between entities", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const entry = {
|
|
id: "test-1",
|
|
vector: [0.1, 0.2],
|
|
metadata: { text: "Dr. John Smith works at Acme Corp in New York." },
|
|
};
|
|
|
|
// Act
|
|
const result = await inferrer.inferFromContent(entry);
|
|
|
|
// Assert
|
|
expect(result.entities.length).toBeGreaterThan(0);
|
|
expect(result.processingTimeMs).toBeGreaterThanOrEqual(0);
|
|
});
|
|
|
|
it("should respect maxRelationships option", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const entry = {
|
|
id: "test-1",
|
|
vector: [0.1, 0.2],
|
|
metadata: {
|
|
text: "Alice met Bob at Company Inc, then Charlie at Org Ltd, followed by Diana at Corp Co.",
|
|
},
|
|
};
|
|
|
|
// Act
|
|
const result = await inferrer.inferFromContent(entry, { maxRelationships: 2 });
|
|
|
|
// Assert
|
|
expect(result.edgesCreated).toBeLessThanOrEqual(2);
|
|
});
|
|
});
|
|
|
|
describe("linkSimilar", () => {
|
|
it("should return 0 for non-existent entries", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.client.get.mockResolvedValue(null);
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
|
|
// Act
|
|
const edgesCreated = await inferrer.linkSimilar("non-existent");
|
|
|
|
// Assert
|
|
expect(edgesCreated).toBe(0);
|
|
});
|
|
|
|
it("should create SIMILAR_TO edges for similar documents", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.client.search.mockResolvedValue([
|
|
{ entry: { id: "similar-1" }, score: 0.85 },
|
|
{ entry: { id: "similar-2" }, score: 0.75 },
|
|
]);
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
|
|
// Act
|
|
const edgesCreated = await inferrer.linkSimilar("test-id", 0.7);
|
|
|
|
// Assert
|
|
expect(edgesCreated).toBe(2);
|
|
expect(deps.client.addEdge).toHaveBeenCalledTimes(2);
|
|
});
|
|
|
|
it("should skip self-links", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.client.search.mockResolvedValue([
|
|
{ entry: { id: "test-id" }, score: 1.0 }, // Self
|
|
{ entry: { id: "similar-1" }, score: 0.85 },
|
|
]);
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
|
|
// Act
|
|
const edgesCreated = await inferrer.linkSimilar("test-id", 0.7);
|
|
|
|
// Assert
|
|
expect(edgesCreated).toBe(1);
|
|
});
|
|
|
|
it("should use default threshold of 0.7", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.client.search.mockResolvedValue([]);
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
|
|
// Act
|
|
await inferrer.linkSimilar("test-id");
|
|
|
|
// Assert
|
|
expect(deps.client.search).toHaveBeenCalledWith(
|
|
expect.objectContaining({ minScore: 0.7 }),
|
|
);
|
|
});
|
|
});
|
|
|
|
describe("batchInfer", () => {
|
|
it("should process multiple entries", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.client.isGraphInitialized.mockReturnValue(false); // Disable similarity linking
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const entries = [
|
|
{ id: "1", vector: [0.1], metadata: { text: "Test one" } },
|
|
{ id: "2", vector: [0.2], metadata: { text: "Test two" } },
|
|
];
|
|
|
|
// Act
|
|
const totalEdges = await inferrer.batchInfer(entries);
|
|
|
|
// Assert
|
|
expect(totalEdges).toBeGreaterThanOrEqual(0);
|
|
});
|
|
|
|
it("should link similar documents when graph is initialized", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.client.isGraphInitialized.mockReturnValue(true);
|
|
deps.client.search.mockResolvedValue([
|
|
{ entry: { id: "other-1" }, score: 0.85 },
|
|
]);
|
|
const inferrer = new RelationshipInferrer(deps as any);
|
|
const entries = [
|
|
{ id: "1", vector: [0.1], metadata: { text: "Test" } },
|
|
];
|
|
|
|
// Act
|
|
const totalEdges = await inferrer.batchInfer(entries, { similarityThreshold: 0.8 });
|
|
|
|
// Assert
|
|
expect(deps.client.search).toHaveBeenCalled();
|
|
});
|
|
});
|
|
});
|
|
|
|
// =============================================================================
|
|
// P2 ruvLLM Features: createRuvectorLearnTool Tests
|
|
// =============================================================================
|
|
|
|
describe("createRuvectorLearnTool", () => {
|
|
let createRuvectorLearnTool: typeof import("./tool.js").createRuvectorLearnTool;
|
|
|
|
beforeEach(async () => {
|
|
vi.resetModules();
|
|
vi.clearAllMocks();
|
|
|
|
const toolModule = await import("./tool.js");
|
|
createRuvectorLearnTool = toolModule.createRuvectorLearnTool;
|
|
});
|
|
|
|
function createMockDeps() {
|
|
const mockClient = {
|
|
search: vi.fn().mockResolvedValue([]),
|
|
insert: vi.fn().mockResolvedValue("new-entry-id"),
|
|
addEdge: vi.fn().mockResolvedValue("edge-id"),
|
|
isGraphInitialized: vi.fn().mockReturnValue(true),
|
|
getPatternStore: vi.fn().mockReturnValue(null),
|
|
get: vi.fn().mockResolvedValue(null),
|
|
};
|
|
|
|
return {
|
|
api: {
|
|
logger: createMockLogger(),
|
|
},
|
|
service: {
|
|
isRunning: vi.fn().mockReturnValue(true),
|
|
getClient: vi.fn().mockReturnValue(mockClient),
|
|
},
|
|
db: {},
|
|
embeddings: {
|
|
embed: vi.fn().mockResolvedValue([0.1, 0.2, 0.3, 0.4]),
|
|
},
|
|
mockClient,
|
|
};
|
|
}
|
|
|
|
describe("tool metadata", () => {
|
|
it("should have correct name and label", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Assert
|
|
expect(tool.name).toBe("ruvector_learn");
|
|
expect(tool.label).toBe("Manual Knowledge Learning");
|
|
});
|
|
|
|
it("should have parameters schema", () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Assert
|
|
expect(tool.parameters).toBeDefined();
|
|
expect(tool.parameters.properties).toHaveProperty("content");
|
|
expect(tool.parameters.properties).toHaveProperty("category");
|
|
expect(tool.parameters.properties).toHaveProperty("importance");
|
|
expect(tool.parameters.properties).toHaveProperty("relationships");
|
|
});
|
|
});
|
|
|
|
describe("execute", () => {
|
|
it("should index new content", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "Important fact about AI",
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.indexed).toBe(true);
|
|
expect(deps.embeddings.embed).toHaveBeenCalledWith("Important fact about AI");
|
|
expect(deps.mockClient.insert).toHaveBeenCalled();
|
|
});
|
|
|
|
it("should detect near-duplicates", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.mockClient.search.mockResolvedValue([
|
|
{
|
|
entry: { id: "existing-id", metadata: { text: "Very similar content" } },
|
|
score: 0.98,
|
|
},
|
|
]);
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "Very similar content here",
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.duplicate).toBe(true);
|
|
expect(result.details.existingId).toBe("existing-id");
|
|
});
|
|
|
|
it("should handle service not running", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.service.isRunning.mockReturnValue(false);
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "Test content",
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.indexed).toBe(false);
|
|
expect(result.details.error).toContain("not running");
|
|
});
|
|
|
|
it("should use provided category", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "User prefers dark mode",
|
|
category: "preference",
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.category).toBe("preference");
|
|
});
|
|
|
|
it("should use default category for invalid values", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "Test content",
|
|
category: "invalid-category",
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.category).toBe("fact");
|
|
});
|
|
|
|
it("should clamp importance to valid range", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "Test content",
|
|
importance: 1.5, // Over max
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.importance).toBe(1);
|
|
});
|
|
|
|
it("should create explicit relationships when provided", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "Related fact",
|
|
relationships: ["related-id-1", "related-id-2"],
|
|
relationshipType: "REFERENCES",
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.edges).toBe(2);
|
|
expect(result.details.linkedIds).toContain("related-id-1");
|
|
expect(deps.mockClient.addEdge).toHaveBeenCalledWith(
|
|
expect.objectContaining({ relationship: "REFERENCES" }),
|
|
);
|
|
});
|
|
|
|
it("should infer relationships by default", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
await tool.execute("call-1", {
|
|
content: "Dr. John Smith works at Acme Corp support@acme.com",
|
|
});
|
|
|
|
// Assert - inferFromContent is called internally
|
|
expect(deps.mockClient.insert).toHaveBeenCalled();
|
|
});
|
|
|
|
it("should skip relationship inference when disabled", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "Test content with entities like support@test.com",
|
|
inferRelationships: false,
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.indexed).toBe(true);
|
|
});
|
|
|
|
it("should link similar documents when enabled", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "Test content",
|
|
linkSimilar: true,
|
|
similarityThreshold: 0.9,
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.indexed).toBe(true);
|
|
});
|
|
|
|
it("should handle errors gracefully", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
deps.embeddings.embed.mockRejectedValue(new Error("Embedding failed"));
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "Test content",
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.indexed).toBe(false);
|
|
expect(result.details.error).toBe("Embedding failed");
|
|
});
|
|
|
|
it("should track processing time", async () => {
|
|
// Arrange
|
|
const deps = createMockDeps();
|
|
const tool = createRuvectorLearnTool(deps as any);
|
|
|
|
// Act
|
|
const result = await tool.execute("call-1", {
|
|
content: "Test content",
|
|
}) as { details: Record<string, unknown> };
|
|
|
|
// Assert
|
|
expect(result.details.processingTimeMs).toBeGreaterThanOrEqual(0);
|
|
});
|
|
});
|
|
});
|