File size: 6,759 Bytes
97ee7cb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 | import { expect, test, type Page } from '@playwright/test';
let sharedPage: Page;
test.describe('RAG vector store (worker-side)', () => {
test.describe.configure({ mode: 'serial' });
test.beforeAll(async ({ browser }) => {
sharedPage = await browser.newPage();
await sharedPage.goto('/tests/runtime-harness.html');
const supported = await sharedPage.evaluate(async () => {
const { initI18n } = await import('/src/services/i18n.ts');
await initI18n();
const { mlWorker } = await import('/src/services/ml-worker.ts');
const ok = await mlWorker.init();
if (!ok) return false;
await mlWorker.loadModel('embeddings');
return true;
});
if (!supported) test.skip(true, 'ML worker not supported');
});
test.afterAll(async () => {
await sharedPage?.close();
});
async function clearVectorDB() {
await sharedPage.evaluate(async () => {
const { mlWorker } = await import('/src/services/ml-worker.ts');
await mlWorker.vectorStoreReset();
});
}
test('ingest → count → search round-trip', async () => {
await clearVectorDB();
const result = await sharedPage.evaluate(async () => {
const { mlWorker } = await import('/src/services/ml-worker.ts');
const items = [
{ text: 'Iran sanctions debate intensifies in Washington', pubDate: Date.now() - 86400000, source: 'Reuters', url: 'https://example.com/1' },
{ text: 'Ukraine frontline positions shift near Bakhmut', pubDate: Date.now() - 172800000, source: 'AP', url: 'https://example.com/2' },
{ text: 'China trade talks resume with EU delegation', pubDate: Date.now() - 259200000, source: 'BBC', url: 'https://example.com/3' },
];
const stored = await mlWorker.vectorStoreIngest(items);
const count = await mlWorker.vectorStoreCount();
const results = await mlWorker.vectorStoreSearch(['Iran sanctions policy'], 5, 0.3);
return { stored, count, results, topText: results[0]?.text ?? '' };
});
expect(result.stored).toBe(3);
expect(result.count).toBe(3);
expect(result.results.length).toBeGreaterThan(0);
expect(result.topText).toContain('Iran');
expect(result.results[0]!.score).toBeGreaterThanOrEqual(0.3);
});
test('minScore filtering excludes dissimilar results', async () => {
await clearVectorDB();
const result = await sharedPage.evaluate(async () => {
const { mlWorker } = await import('/src/services/ml-worker.ts');
await mlWorker.vectorStoreIngest([
{ text: 'Weather forecast sunny skies tomorrow morning', pubDate: Date.now(), source: 'Weather', url: '' },
]);
const results = await mlWorker.vectorStoreSearch(['Iran nuclear weapons program sanctions'], 5, 0.8);
return { count: results.length };
});
expect(result.count).toBe(0);
});
test('search returns empty when embeddings model not loaded', async () => {
const result = await sharedPage.evaluate(async () => {
const { mlWorker } = await import('/src/services/ml-worker.ts');
await mlWorker.unloadModel('embeddings');
const results = await mlWorker.vectorStoreSearch(['test query'], 5, 0.3);
// Reload embeddings for subsequent tests
await mlWorker.loadModel('embeddings');
return { count: results.length };
});
expect(result.count).toBe(0);
});
test('deduplicates across multi-query matches keeping max score', async () => {
await clearVectorDB();
const result = await sharedPage.evaluate(async () => {
const { mlWorker } = await import('/src/services/ml-worker.ts');
await mlWorker.vectorStoreIngest([
{ text: 'Military operations expand in eastern regions', pubDate: Date.now(), source: 'Reuters', url: 'https://example.com/1' },
]);
const results = await mlWorker.vectorStoreSearch(
['military operations', 'eastern military expansion'],
5,
0.2,
);
return { count: results.length };
});
expect(result.count).toBe(1);
});
test('handles empty URL in items', async () => {
await clearVectorDB();
const result = await sharedPage.evaluate(async () => {
const { mlWorker } = await import('/src/services/ml-worker.ts');
const stored = await mlWorker.vectorStoreIngest([
{ text: 'Headline without a URL', pubDate: Date.now(), source: 'Test', url: '' },
{ text: 'Another headline no URL', pubDate: Date.now(), source: 'Test', url: '' },
]);
const count = await mlWorker.vectorStoreCount();
return { stored, count };
});
expect(result.stored).toBe(2);
expect(result.count).toBe(2);
});
test('worker-unavailable path degrades gracefully', async () => {
const result = await sharedPage.evaluate(async () => {
const mod = await import('/src/services/ml-worker.ts');
const { mlWorker } = mod;
const fresh = Object.create(Object.getPrototypeOf(mlWorker));
Object.assign(fresh, { worker: null, isReady: false, pendingRequests: new Map(), loadedModels: new Set(), capabilities: null });
const ingestResult = await fresh.vectorStoreIngest([
{ text: 'test', pubDate: Date.now(), source: 'Test', url: '' },
]);
const searchResult = await fresh.vectorStoreSearch(['test'], 5, 0.3);
const countResult = await fresh.vectorStoreCount();
return { stored: ingestResult, searchCount: searchResult.length, count: countResult };
});
expect(result.stored).toBe(0);
expect(result.searchCount).toBe(0);
expect(result.count).toBe(0);
});
test('queue resilience after IDB error', async () => {
await clearVectorDB();
const result = await sharedPage.evaluate(async () => {
const { mlWorker } = await import('/src/services/ml-worker.ts');
await mlWorker.vectorStoreIngest([
{ text: 'Valid headline about economic policy', pubDate: Date.now(), source: 'Reuters', url: 'https://example.com/1' },
]);
const countBefore = await mlWorker.vectorStoreCount();
indexedDB.deleteDatabase('worldmonitor_vector_store');
try {
await mlWorker.vectorStoreIngest([
{ text: 'Headline during IDB disruption', pubDate: Date.now(), source: 'Test', url: '' },
]);
} catch {
// Expected — IDB handle was invalidated
}
await mlWorker.vectorStoreIngest([
{ text: 'Recovery headline after IDB reset', pubDate: Date.now(), source: 'AP', url: 'https://example.com/3' },
]);
const countAfter = await mlWorker.vectorStoreCount();
return { countBefore, countAfter, recovered: countAfter > 0 };
});
expect(result.countBefore).toBe(1);
expect(result.recovered).toBe(true);
});
});
|