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