Saket Aryan
532 lines
19 KiB
TypeScript
532 lines
19 KiB
TypeScript
/// <reference types="jest" />
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/**
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* End-to-end tests for Qdrant dimension mismatch fix.
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*
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* Requires a running Qdrant instance at localhost:6333 (v1.13.x).
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* These tests replicate the exact scenarios from issues #4212, #4173, #4056.
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*
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* Skipped automatically when Qdrant is not available.
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*
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* Run: npx jest --config jest.config.js src/oss/tests/qdrant-e2e.test.ts --forceExit
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*/
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import { QdrantClient } from "@qdrant/js-client-rest";
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import { Qdrant } from "../src/vector_stores/qdrant";
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import { v4 as uuidv4 } from "uuid";
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jest.setTimeout(30000);
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const QDRANT_HOST = "localhost";
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const QDRANT_PORT = 6333;
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// Check if Qdrant is reachable synchronously at load time using
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// a sync check via child_process so describe.skip works correctly.
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function isQdrantAvailable(): boolean {
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try {
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const { execSync } = require("child_process");
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execSync(
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`node -e "const s=require('net').createConnection({host:'${QDRANT_HOST}',port:${QDRANT_PORT}});s.on('connect',()=>{s.destroy();process.exit(0)});s.on('error',()=>process.exit(1));s.setTimeout(2000,()=>process.exit(1))"`,
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{ timeout: 3000, stdio: "ignore" },
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);
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return true;
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} catch {
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return false;
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}
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}
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const qdrantAvailable = isQdrantAvailable();
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if (!qdrantAvailable) {
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console.warn("Qdrant not available at localhost:6333 — skipping e2e tests");
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}
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let qdrantClient: QdrantClient;
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beforeAll(async () => {
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if (!qdrantAvailable) return;
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qdrantClient = new QdrantClient({ host: QDRANT_HOST, port: QDRANT_PORT });
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const collections = await qdrantClient.getCollections();
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expect(collections).toBeDefined();
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});
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// Helper: delete a collection if it exists
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async function deleteCollectionIfExists(name: string) {
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try {
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await qdrantClient.deleteCollection(name);
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} catch {
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// Collection doesn't exist — fine
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}
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}
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// Helper: create a fake embedder that produces vectors of a given dimension
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function createFakeEmbedder(dims: number) {
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return {
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embed: jest.fn().mockImplementation(async (_text: string) => {
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const vec = new Array(dims).fill(0);
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for (let i = 0; i < _text.length && i < dims; i++) {
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vec[i] = _text.charCodeAt(i) / 255;
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}
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return vec;
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}),
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embedBatch: jest.fn().mockImplementation(async (texts: string[]) => {
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return Promise.all(
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texts.map(async (t) => {
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const vec = new Array(dims).fill(0);
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for (let i = 0; i < t.length && i < dims; i++) {
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vec[i] = t.charCodeAt(i) / 255;
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}
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return vec;
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}),
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);
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}),
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};
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}
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// Conditionally skip tests when Qdrant is unavailable
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const describeIfQdrant = qdrantAvailable ? describe : describe.skip;
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afterAll(async () => {
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await deleteCollectionIfExists("e2e_test_768");
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await deleteCollectionIfExists("e2e_test_1536");
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await deleteCollectionIfExists("e2e_test_race");
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await deleteCollectionIfExists("e2e_test_race2");
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await deleteCollectionIfExists("e2e_test_noexplicit");
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await deleteCollectionIfExists("e2e_test_explicit");
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await deleteCollectionIfExists("e2e_test_embdims");
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await deleteCollectionIfExists("e2e_test_autodetect");
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await deleteCollectionIfExists("memory_migrations");
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});
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// ───────────────────────────────────────────────────────────────────────────
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// 1. Reproduce #4212 / #4173: dimension mismatch with 768-dim embedder
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// ───────────────────────────────────────────────────────────────────────────
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describeIfQdrant("Issue #4212/#4173: Qdrant dimension mismatch", () => {
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it("BEFORE FIX scenario: 768-dim vector into 1536-dim collection → Bad Request", async () => {
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const collectionName = "e2e_test_1536";
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await deleteCollectionIfExists(collectionName);
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await qdrantClient.createCollection(collectionName, {
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vectors: { size: 1536, distance: "Cosine" },
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});
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// Insert a 768-dim vector — this is what nomic-embed-text produces
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const vector768 = new Array(768).fill(0.1);
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try {
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await qdrantClient.upsert(collectionName, {
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points: [
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{ id: "test-1", vector: vector768, payload: { data: "hello" } },
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],
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});
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fail("Expected Qdrant to reject 768-dim vector into 1536-dim collection");
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} catch (error: any) {
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// This is the exact "Bad Request" error users were hitting
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expect(error.status).toBe(400);
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}
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await deleteCollectionIfExists(collectionName);
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});
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it("AFTER FIX: Qdrant store with dimension=768 works end-to-end", async () => {
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const collectionName = "e2e_test_768";
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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// Create Qdrant store with correct dimension (what our auto-detect provides)
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const store = new Qdrant({
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host: QDRANT_HOST,
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port: QDRANT_PORT,
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collectionName,
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embeddingModelDims: 768,
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dimension: 768,
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});
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await store.initialize();
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// Verify collection was created with 768 dims
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const info = await qdrantClient.getCollection(collectionName);
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expect(info.config?.params?.vectors?.size).toBe(768);
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// Insert 768-dim vectors (what nomic-embed-text produces)
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const vec1 = new Array(768).fill(0);
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vec1[0] = 1.0;
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const vec2 = new Array(768).fill(0);
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vec2[1] = 1.0;
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const id1 = uuidv4();
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const id2 = uuidv4();
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await store.insert(
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[vec1, vec2],
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[id1, id2],
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[
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{ data: "hello", userId: "u1" },
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{ data: "world", userId: "u1" },
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],
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);
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// Search with 768-dim query — this USED TO fail with Bad Request
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const results = await store.search(vec1, 2, { userId: "u1" });
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expect(results.length).toBe(2);
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expect(results[0].id).toBe(id1); // Most similar to itself
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expect(results[0].score).toBeGreaterThan(0.9);
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// Get by ID
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const item = await store.get(id1);
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expect(item).not.toBeNull();
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expect(item!.payload.data).toBe("hello");
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// Update with 768-dim vector
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const vec3 = new Array(768).fill(0);
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vec3[2] = 1.0;
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await store.update(id1, vec3, { data: "updated", userId: "u1" });
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const updated = await store.get(id1);
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expect(updated!.payload.data).toBe("updated");
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// Delete
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await store.delete(id2);
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const deleted = await store.get(id2);
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expect(deleted).toBeNull();
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// List
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const [listed, count] = await store.list({ userId: "u1" });
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expect(count).toBe(1);
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expect(listed[0].payload.data).toBe("updated");
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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});
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it("AFTER FIX: Memory auto-detects 768 dims via probe (full integration)", async () => {
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const collectionName = "e2e_test_autodetect";
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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const fakeEmbedder = createFakeEmbedder(768);
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// Mock only the non-Qdrant factories to avoid Google SDK import crash
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jest.resetModules();
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jest.doMock("../src/utils/factory", () => {
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// Import Qdrant directly (avoids loading Google embedder via factory)
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const { Qdrant: QdrantStore } = require("../src/vector_stores/qdrant");
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return {
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EmbedderFactory: { create: jest.fn().mockReturnValue(fakeEmbedder) },
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VectorStoreFactory: {
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create: jest
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.fn()
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.mockImplementation((_provider: string, config: any) => {
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return new QdrantStore(config);
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}),
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},
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LLMFactory: {
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create: jest.fn().mockReturnValue({
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generateResponse: jest.fn().mockResolvedValue('{"facts":[]}'),
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}),
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},
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HistoryManagerFactory: {
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create: jest.fn().mockReturnValue({
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addHistory: jest.fn().mockResolvedValue(undefined),
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getHistory: jest.fn().mockResolvedValue([]),
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reset: jest.fn().mockResolvedValue(undefined),
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}),
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},
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};
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});
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jest.doMock("../src/utils/telemetry", () => ({
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captureClientEvent: jest.fn().mockResolvedValue(undefined),
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}));
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const { Memory } = require("../src/memory");
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// This is the EXACT config from issue #4212 — NO dimension specified
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const mem = new Memory({
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embedder: {
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provider: "ollama",
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config: { model: "nomic-embed-text" },
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},
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vectorStore: {
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provider: "qdrant",
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config: {
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host: QDRANT_HOST,
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port: QDRANT_PORT,
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collectionName,
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},
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},
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llm: { provider: "openai", config: { apiKey: "fake" } },
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disableHistory: true,
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});
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// This triggers init — probe should detect 768 dims
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await mem.getAll({ userId: "test-user" });
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// Verify the probe was called
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expect(fakeEmbedder.embed).toHaveBeenCalledWith("dimension probe");
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// Verify Qdrant collection was created with auto-detected 768 dims
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const collectionInfo = await qdrantClient.getCollection(collectionName);
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expect(collectionInfo.config?.params?.vectors?.size).toBe(768);
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// Search should work (this used to throw Bad Request)
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const searchResult = await mem.search("hello world", {
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userId: "test-user",
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});
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expect(searchResult).toBeDefined();
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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jest.resetModules();
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});
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it("AFTER FIX: explicit dimension=768 skips probe (backward compat)", async () => {
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const collectionName = "e2e_test_explicit";
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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const fakeEmbedder = createFakeEmbedder(768);
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jest.resetModules();
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jest.doMock("../src/utils/factory", () => {
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const { Qdrant: QdrantStore } = require("../src/vector_stores/qdrant");
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return {
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EmbedderFactory: { create: jest.fn().mockReturnValue(fakeEmbedder) },
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VectorStoreFactory: {
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create: jest
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.fn()
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.mockImplementation((_provider: string, config: any) => {
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return new QdrantStore(config);
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}),
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},
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LLMFactory: {
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create: jest.fn().mockReturnValue({
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generateResponse: jest.fn().mockResolvedValue('{"facts":[]}'),
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}),
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},
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HistoryManagerFactory: {
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create: jest.fn().mockReturnValue({
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addHistory: jest.fn().mockResolvedValue(undefined),
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getHistory: jest.fn().mockResolvedValue([]),
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reset: jest.fn().mockResolvedValue(undefined),
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}),
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},
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};
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});
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jest.doMock("../src/utils/telemetry", () => ({
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captureClientEvent: jest.fn().mockResolvedValue(undefined),
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}));
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const { Memory } = require("../src/memory");
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// Workaround config from #4212 — explicit dimension
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const mem = new Memory({
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embedder: {
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provider: "ollama",
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config: { model: "nomic-embed-text" },
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},
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vectorStore: {
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provider: "qdrant",
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config: {
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host: QDRANT_HOST,
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port: QDRANT_PORT,
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collectionName,
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dimension: 768,
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},
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},
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llm: { provider: "openai", config: { apiKey: "fake" } },
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disableHistory: true,
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});
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await mem.getAll({ userId: "test-user" });
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// Probe should NOT have been called
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expect(fakeEmbedder.embed).not.toHaveBeenCalledWith("dimension probe");
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const collectionInfo = await qdrantClient.getCollection(collectionName);
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expect(collectionInfo.config?.params?.vectors?.size).toBe(768);
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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jest.resetModules();
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});
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it("AFTER FIX: embeddingDims in embedder config skips probe", async () => {
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const collectionName = "e2e_test_embdims";
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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const fakeEmbedder = createFakeEmbedder(768);
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jest.resetModules();
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jest.doMock("../src/utils/factory", () => {
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const { Qdrant: QdrantStore } = require("../src/vector_stores/qdrant");
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return {
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EmbedderFactory: { create: jest.fn().mockReturnValue(fakeEmbedder) },
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VectorStoreFactory: {
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create: jest
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.fn()
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.mockImplementation((_provider: string, config: any) => {
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return new QdrantStore(config);
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}),
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},
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LLMFactory: {
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create: jest.fn().mockReturnValue({
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generateResponse: jest.fn().mockResolvedValue('{"facts":[]}'),
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}),
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},
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HistoryManagerFactory: {
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create: jest.fn().mockReturnValue({
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addHistory: jest.fn().mockResolvedValue(undefined),
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getHistory: jest.fn().mockResolvedValue([]),
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reset: jest.fn().mockResolvedValue(undefined),
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}),
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},
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};
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});
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jest.doMock("../src/utils/telemetry", () => ({
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captureClientEvent: jest.fn().mockResolvedValue(undefined),
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}));
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const { Memory } = require("../src/memory");
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const mem = new Memory({
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embedder: {
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provider: "ollama",
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config: { model: "nomic-embed-text", embeddingDims: 768 },
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},
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vectorStore: {
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provider: "qdrant",
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config: {
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host: QDRANT_HOST,
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port: QDRANT_PORT,
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collectionName,
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},
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},
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llm: { provider: "openai", config: { apiKey: "fake" } },
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disableHistory: true,
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});
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await mem.getAll({ userId: "test-user" });
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// Probe should NOT have been called — dimension inferred from embeddingDims
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expect(fakeEmbedder.embed).not.toHaveBeenCalledWith("dimension probe");
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const collectionInfo = await qdrantClient.getCollection(collectionName);
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expect(collectionInfo.config?.params?.vectors?.size).toBe(768);
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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jest.resetModules();
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});
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});
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// ───────────────────────────────────────────────────────────────────────────
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// 2. Reproduce #4056 issue 1: Collection creation race condition
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// ───────────────────────────────────────────────────────────────────────────
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describeIfQdrant("Issue #4056: Qdrant race condition", () => {
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it("concurrent ensureCollection calls don't crash (no 409 error leak)", async () => {
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const collectionName = "e2e_test_race";
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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// Create 5 Qdrant instances concurrently — this simulates the race
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// that caused "Collection memory_migrations already exists!" in #4056
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const instances = Array.from(
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{ length: 5 },
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() =>
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new Qdrant({
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host: QDRANT_HOST,
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port: QDRANT_PORT,
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collectionName,
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embeddingModelDims: 768,
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dimension: 768,
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}),
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);
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// All should initialize without throwing 409 Conflict
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await Promise.all(instances.map((inst) => inst.initialize()));
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// Verify collection exists with correct dimension
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const info = await qdrantClient.getCollection(collectionName);
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expect(info.config?.params?.vectors?.size).toBe(768);
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// memory_migrations should also exist (created by initialize)
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const migrInfo = await qdrantClient.getCollection("memory_migrations");
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expect(migrInfo.config?.params?.vectors?.size).toBe(1);
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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});
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it("getUserId works after concurrent initialization", async () => {
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const collectionName = "e2e_test_race2";
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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const instance = new Qdrant({
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host: QDRANT_HOST,
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port: QDRANT_PORT,
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collectionName,
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embeddingModelDims: 768,
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dimension: 768,
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});
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await instance.initialize();
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// getUserId should work without 409 crash
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const userId = await instance.getUserId();
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expect(typeof userId).toBe("string");
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expect(userId.length).toBeGreaterThan(0);
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// setUserId + getUserId roundtrip
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await instance.setUserId("custom-e2e-user");
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const updated = await instance.getUserId();
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expect(updated).toBe("custom-e2e-user");
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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});
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});
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// ───────────────────────────────────────────────────────────────────────────
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// 3. Reproduce #4056 issue 2: memory_migrations dimension isolation
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// ───────────────────────────────────────────────────────────────────────────
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describeIfQdrant("Issue #4056: memory_migrations dimension isolation", () => {
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it("memory_migrations uses dim=1 independently of main collection dim=768", async () => {
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const collectionName = "e2e_test_noexplicit";
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await deleteCollectionIfExists(collectionName);
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await deleteCollectionIfExists("memory_migrations");
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const instance = new Qdrant({
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host: QDRANT_HOST,
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port: QDRANT_PORT,
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collectionName,
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embeddingModelDims: 768,
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dimension: 768,
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});
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await instance.initialize();
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// Allow Qdrant a moment to fully commit collections
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await new Promise((r) => setTimeout(r, 500));
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// Main collection should be 768
|
|
const mainInfo = await qdrantClient.getCollection(collectionName);
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expect(mainInfo.config?.params?.vectors?.size).toBe(768);
|
|
|
|
// memory_migrations should be 1 (NOT 768!)
|
|
// This was the bug in #4056 issue 2 — telemetry used wrong dimension
|
|
const migrationsInfo =
|
|
await qdrantClient.getCollection("memory_migrations");
|
|
expect(migrationsInfo.config?.params?.vectors?.size).toBe(1);
|
|
|
|
// getUserId should work — vector dim=1 in memory_migrations
|
|
const userId = await instance.getUserId();
|
|
expect(typeof userId).toBe("string");
|
|
|
|
// setUserId should also work
|
|
await instance.setUserId("custom-test-user");
|
|
const newUserId = await instance.getUserId();
|
|
expect(newUserId).toBe("custom-test-user");
|
|
|
|
await deleteCollectionIfExists(collectionName);
|
|
await deleteCollectionIfExists("memory_migrations");
|
|
});
|
|
});
|