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diegosouzapw--omniroute/tests/unit/memory-vectorstore-ensure-ready.test.ts
2026-07-13 13:39:12 +08:00

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6.1 KiB
TypeScript

/**
* 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<typeof getVectorStore> {
_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");
});