/** * tests/unit/memory-vectorstore-ensure-ready.test.ts * * Plan 21 — Memory Engine Redesign (F4) * Tests for VectorStore.ensureReady(): * - First call with signature "X" creates vec_memories with correct dim. * - Second call same signature is idempotent (no-op). * - Call with new signature "Y" drops + recreates and marks all memories needs_reindex=1. * - Returns {ready: false} when sqlite-vec is not available. */ import test from "node:test"; import assert from "node:assert/strict"; import fs from "node:fs"; import os from "node:os"; import path from "node:path"; import { mock } from "node:test"; const TEST_DATA_DIR = fs.mkdtempSync(path.join(os.tmpdir(), "omr-vecstore-ensure-")); process.env.DATA_DIR = TEST_DATA_DIR; process.env.DISABLE_SQLITE_AUTO_BACKUP = "true"; const core = await import("../../src/lib/db/core.ts"); const { getMemoryVecMeta } = await import("../../src/lib/db/memoryVec.ts"); const vsModule = await import("../../src/lib/memory/vectorStore.ts"); const { getVectorStore, _resetVectorStoreSingleton } = vsModule; import type { EmbeddingResolution } from "../../src/lib/memory/embedding/types.ts"; function makeResolution(sig: string, dim: number): EmbeddingResolution { return { source: "remote", model: "openai/text-embedding-3-small", dimensions: dim, signature: sig, reason: "test", }; } function cleanup() { mock.restoreAll(); _resetVectorStoreSingleton(); core.resetDbInstance(); if (fs.existsSync(TEST_DATA_DIR)) { fs.rmSync(TEST_DATA_DIR, { recursive: true, force: true }); } fs.mkdirSync(TEST_DATA_DIR, { recursive: true }); } test.afterEach(() => { cleanup(); }); test.after(() => { core.resetDbInstance(); if (fs.existsSync(TEST_DATA_DIR)) { fs.rmSync(TEST_DATA_DIR, { recursive: true, force: true }); } }); // Helper: get VectorStore or skip if sqlite-vec is not available. function getStoreOrSkip(t: { skip: (msg: string) => void }): ReturnType { _resetVectorStoreSingleton(); const store = getVectorStore(); if (store === null) { t.skip("sqlite-vec not available in this environment — skipping"); return null; } return store; } // ──────────────── Tests ──────────────── test("ensureReady: first call creates vec_memories with correct dim", async (t) => { const store = getStoreOrSkip(t); if (!store) return; const db = core.getDbInstance(); const res = makeResolution("openai:text-embedding-3-small:1536", 1536); const result = await store.ensureReady(res); assert.equal(result.ready, true, "should be ready after first ensureReady"); // Verify the virtual table was created. const rows = db.prepare("SELECT COUNT(*) AS cnt FROM vec_memories").get() as { cnt: number }; assert.equal(rows.cnt, 0, "vec_memories should exist (empty after creation)"); // Verify meta was updated. const meta = getMemoryVecMeta(); assert.equal(meta.embeddingSignature, "openai:text-embedding-3-small:1536"); assert.equal(meta.activeDim, 1536); assert.equal(meta.vecLoaded, true); }); test("ensureReady: second call with same signature is idempotent", async (t) => { const store = getStoreOrSkip(t); if (!store) return; const res = makeResolution("openai:text-embedding-3-small:1536", 1536); await store.ensureReady(res); // Read meta after first call. const meta1 = getMemoryVecMeta(); // Second call — should be no-op. const result = await store.ensureReady(res); assert.equal(result.ready, true); const meta2 = getMemoryVecMeta(); // Meta should not have changed (lastResetAt remains the same). assert.equal(meta1.embeddingSignature, meta2.embeddingSignature); assert.equal(meta1.activeDim, meta2.activeDim); assert.equal(meta1.vecLoaded, meta2.vecLoaded); }); test("ensureReady: signature change triggers reset + marks memories needs_reindex=1", async (t) => { const store = getStoreOrSkip(t); if (!store) return; const db = core.getDbInstance(); // Insert a few memories first. for (let i = 0; i < 3; i++) { db.prepare( `INSERT INTO memories (id, api_key_id, type, key, content, created_at) VALUES (?, 'key1', 'factual', ?, ?, datetime('now'))`, ).run(`mem-${i}`, `key-${i}`, `content-${i}`); } // First ensureReady with signature X. const resX = makeResolution("openai:ada-002:1024", 1024); await store.ensureReady(resX); // Check X is set. assert.equal(getMemoryVecMeta().embeddingSignature, "openai:ada-002:1024"); assert.equal(getMemoryVecMeta().activeDim, 1024); // Now switch to signature Y (different model + dim). const resY = makeResolution("openai:text-embedding-3-small:1536", 1536); const resetResult = await store.ensureReady(resY); assert.equal(resetResult.ready, true, "should be ready after signature change"); // Verify new signature is stored. const metaAfter = getMemoryVecMeta(); assert.equal(metaAfter.embeddingSignature, "openai:text-embedding-3-small:1536"); assert.equal(metaAfter.activeDim, 1536); assert.ok(metaAfter.lastResetAt !== null, "lastResetAt should be set after reset"); // All 3 memories should have needs_reindex = 1. const needsRows = db .prepare("SELECT COUNT(*) AS cnt FROM memories WHERE needs_reindex = 1") .get() as { cnt: number }; assert.equal(needsRows.cnt, 3, "all memories should be marked needs_reindex=1 after signature change"); }); test("ensureReady: returns {ready: false} when dimensions are null (no probe done yet)", async (t) => { const store = getStoreOrSkip(t); if (!store) return; // Resolution with null dimensions — lazy probe not done yet. const resNullDim: EmbeddingResolution = { source: "remote", model: "openai/text-embedding-3-small", dimensions: null, signature: "openai:text-embedding-3-small:null", reason: "test - dim not probed yet", }; const result = await store.ensureReady(resNullDim); // Should not crash, but cannot create table without dim. // Either ready (if signature already matches a loaded table) or not ready. assert.ok( typeof result.ready === "boolean", "ensureReady must return {ready: boolean, reason: string}", ); assert.ok(typeof result.reason === "string"); });