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https://github.com/garrytan/gbrain.git
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Salvage of PR #2875 (which subsumes the base projection from #2873), rebased onto current master with the release bookkeeping (VERSION / package.json / CHANGELOG) dropped, plus one hot-path hardening fix. Salvaged (verified on this head): - project trusted message_id / thread_id / Message-ID-gated source_subject through keyword, chunk-keyword, CJK, and vector paths in BOTH engines - preserve the citation DTO through alias injection, relational recall/fanout, two-pass hydration, vector fusion/reranking, and semantic-cache hits - raw source_subject is never trusted; only allowlisted `subject` may supply it, and only when a nonblank Message-ID proves the page is an email; malformed/non-object frontmatter fails closed (no double-decode) - source visibility / quarantine / deletion rechecked across indirect retrieval paths (alias hop, relational hydrate, two-pass expansion, graph walk, cache-hit gate) - typed JSON cache scope keys (scalar/set/all) — injective encoding, no forged-key collisions; store-side write gate skips writeback when the page-generation clock advanced during the producing search - KNOBS_HASH_VERSION 12 -> 13 so pre-projection cached DTOs miss instead of replaying the old shape Fixed on top of the original head (the flagged hot-path defect): - cacheScopeKey's forged-id rejection was evaluated inline at the cache lookup/store call sites inside hybridSearchCached, outside any catch — an invalid scope id broke the whole search instead of skipping the cache. The key is now computed once, fail-open: invalid scope => cache skipped, search unaffected. Pinned by test/search/hybrid-cache-scope-failopen.serial.test.ts (fails on the original head, passes here). Verified on this exact head: typecheck clean; 379 touched unit tests, 3 serial files (one process each), pglite cache-gate/source-isolation e2e, and real-PostgreSQL engine-parity (26 pass) + source-routing — all green. jsonb-pattern/params, key-files-current-state, test-isolation, progress-to-stdout guards clean. Closes #2962 Co-authored-by: amtagrwl <amtagrwl@users.noreply.github.com> Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
384 lines
14 KiB
TypeScript
384 lines
14 KiB
TypeScript
/**
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* v0.32.x search-lite \u2014 semantic query cache.
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*
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* PGLite-backed test. Confirms:
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* - migration v51 creates the query_cache table
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* - store + lookup roundtrip with EXACT same embedding \u2192 hit
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* - lookup with a similar embedding (cosine > 0.92) \u2192 hit
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* - lookup with a far embedding \u2192 miss
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* - TTL expiration: a stale row is skipped at read time
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* - clear / prune / stats work as advertised
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* - source_id isolation: brain A's cache doesn't leak to brain B
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* - disabled cache is a pure no-op
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*
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* Uses synthetic Float32Array embeddings so the test doesn't depend on
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* any external embedding provider.
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*/
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import { describe, test, expect, beforeAll, afterAll, beforeEach } from 'bun:test';
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import { PGLiteEngine } from '../src/core/pglite-engine.ts';
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import { SemanticQueryCache, cacheRowId } from '../src/core/search/query-cache.ts';
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import { configureGateway, resetGateway } from '../src/core/ai/gateway.ts';
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import type { SearchResult, HybridSearchMeta } from '../src/core/types.ts';
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let engine: PGLiteEngine;
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let visiblePageId: number;
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// Build a stable, normalized embedding. PGLite ships pgvector with 1536-dim
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// support (the default); a smaller test dim won't match the column. We
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// truncate / pad to 1536 to match the migration's resolved dim.
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const DIM = 1536;
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function makeEmbedding(seed: number, dim = DIM): Float32Array {
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const e = new Float32Array(dim);
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// Simple deterministic generator with a unique fingerprint per seed
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// so similar seeds produce similar (cosine > 0.95) vectors and distinct
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// seeds produce orthogonal-ish ones.
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for (let i = 0; i < dim; i++) {
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e[i] = Math.sin(seed * 0.001 + i * 0.01);
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}
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// L2-normalize so cosine = dot product.
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let mag = 0;
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for (let i = 0; i < dim; i++) mag += e[i] * e[i];
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mag = Math.sqrt(mag);
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if (mag > 0) for (let i = 0; i < dim; i++) e[i] /= mag;
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return e;
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}
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function makeOrthogonalEmbedding(seed: number, dim = DIM): Float32Array {
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// Use a totally different basis so cosine is near-zero.
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const e = new Float32Array(dim);
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for (let i = 0; i < dim; i++) {
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e[i] = Math.cos(seed * 13.7 + i * 0.97);
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}
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let mag = 0;
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for (let i = 0; i < dim; i++) mag += e[i] * e[i];
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mag = Math.sqrt(mag);
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if (mag > 0) for (let i = 0; i < dim; i++) e[i] /= mag;
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return e;
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}
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function makeResult(slug: string): SearchResult {
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return {
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slug,
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page_id: visiblePageId,
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title: `Title for ${slug}`,
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type: 'concept',
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chunk_text: `chunk text for ${slug}`,
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chunk_source: 'compiled_truth',
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chunk_id: 1,
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chunk_index: 0,
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score: 1.0,
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stale: false,
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};
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}
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const META: HybridSearchMeta = {
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vector_enabled: true,
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detail_resolved: 'medium',
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expansion_applied: false,
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intent: 'general',
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};
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type StoreOpts = NonNullable<Parameters<SemanticQueryCache['store']>[4]>;
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async function storeCurrent(
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cache: SemanticQueryCache,
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queryText: string,
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queryEmbedding: Float32Array,
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results: SearchResult[],
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meta: HybridSearchMeta,
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opts: StoreOpts = {},
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): Promise<void> {
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const rows = await engine.executeRaw<{ v: number }>(
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`SELECT COALESCE((SELECT last_value FROM page_generation_clock_seq), 0)::bigint AS v`,
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);
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await cache.store(queryText, queryEmbedding, results, meta, {
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...opts,
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maxGenerationAtSearchStart:
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opts.maxGenerationAtSearchStart ?? Number(rows[0]?.v ?? 0),
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});
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}
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beforeAll(async () => {
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// v0.36.2.0: DEFAULT_EMBEDDING_DIMENSIONS flipped to 1280 (ZE Matryoshka).
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// This test hardcodes DIM=1536 in its embeddings. If another test file in
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// the same shard configured the gateway before us, initSchema() would size
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// query_cache.embedding at vector(1280) and every insert below would fail
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// with "expected 1280 dimensions, not 1536". Pin the gateway to 1536d
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// explicitly so this file is hermetic regardless of cross-file state.
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resetGateway();
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configureGateway({
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embedding_model: 'openai:text-embedding-3-large',
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embedding_dimensions: 1536,
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env: { OPENAI_API_KEY: 'sk-fake' },
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});
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engine = new PGLiteEngine();
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await engine.connect({});
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await engine.initSchema();
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const page = await engine.putPage('cache/visible-fixture', {
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type: 'note',
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title: 'Visible cache fixture',
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compiled_truth: 'visible cache fixture',
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timeline: '',
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frontmatter: {},
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});
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visiblePageId = page.id;
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});
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afterAll(async () => {
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try { await engine.disconnect(); } catch { /* ignore */ }
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resetGateway();
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});
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beforeEach(async () => {
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// Wipe the cache between tests so ordering doesn't matter.
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await engine.executeRaw(`DELETE FROM query_cache`);
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});
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describe('migration v51 \u2014 query_cache table exists', () => {
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test('table is present and has expected columns', async () => {
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const rows = await engine.executeRaw<{ column_name: string }>(
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`SELECT column_name FROM information_schema.columns
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WHERE table_name = 'query_cache'`,
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);
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const names = rows.map(r => r.column_name);
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expect(names).toContain('id');
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expect(names).toContain('query_text');
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expect(names).toContain('source_id');
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expect(names).toContain('embedding');
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expect(names).toContain('results');
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expect(names).toContain('meta');
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expect(names).toContain('ttl_seconds');
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expect(names).toContain('created_at');
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expect(names).toContain('hit_count');
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});
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});
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describe('cacheRowId', () => {
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test('is deterministic across same input', () => {
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expect(cacheRowId('hello', 'default')).toBe(cacheRowId('hello', 'default'));
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});
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test('differs across source_id', () => {
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expect(cacheRowId('hello', 'a')).not.toBe(cacheRowId('hello', 'b'));
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});
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});
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describe('SemanticQueryCache \u2014 store + lookup', () => {
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test('roundtrip: exact embedding match returns a hit', async () => {
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const cache = new SemanticQueryCache(engine);
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const emb = makeEmbedding(1);
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const results = [makeResult('a'), makeResult('b')];
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await storeCurrent(cache, 'what is foo', emb, results, META);
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const hit = await cache.lookup(emb);
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expect(hit.hit).toBe(true);
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expect(hit.results).toHaveLength(2);
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expect(hit.results?.[0].slug).toBe('a');
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expect(hit.similarity).toBeGreaterThan(0.99);
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});
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test('similar embedding (cosine > 0.92) is a hit', async () => {
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const cache = new SemanticQueryCache(engine);
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const base = makeEmbedding(100);
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// Construct a near-neighbor: tweak a few dims so cosine stays > 0.92.
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const near = new Float32Array(base);
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for (let i = 0; i < 10; i++) near[i] += 0.005;
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// Re-normalize.
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let mag = 0;
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for (let i = 0; i < DIM; i++) mag += near[i] * near[i];
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mag = Math.sqrt(mag);
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for (let i = 0; i < DIM; i++) near[i] /= mag;
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await storeCurrent(cache, 'what is foo', base, [makeResult('a')], META);
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const hit = await cache.lookup(near);
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expect(hit.hit).toBe(true);
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expect(hit.similarity).toBeGreaterThan(0.92);
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});
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test('orthogonal embedding is a miss', async () => {
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const cache = new SemanticQueryCache(engine);
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const a = makeEmbedding(1);
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const b = makeOrthogonalEmbedding(2);
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await storeCurrent(cache, 'q1', a, [makeResult('a')], META);
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const hit = await cache.lookup(b);
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expect(hit.hit).toBe(false);
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});
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});
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describe('SemanticQueryCache \u2014 TTL', () => {
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test('stale row (past TTL) is not returned', async () => {
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const cache = new SemanticQueryCache(engine, { ttlSeconds: 1 });
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const emb = makeEmbedding(42);
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await storeCurrent(cache, 'q', emb, [makeResult('a')], META, { ttlSeconds: 1 });
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// Manually rewind created_at to simulate expiration.
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await engine.executeRaw(
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`UPDATE query_cache SET created_at = now() - interval '10 seconds'`,
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);
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const hit = await cache.lookup(emb);
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expect(hit.hit).toBe(false);
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});
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});
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describe('SemanticQueryCache — source isolation', () => {
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test('different source_id cannot read each other’s rows', async () => {
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const cache = new SemanticQueryCache(engine);
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const emb = makeEmbedding(7);
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await storeCurrent(cache, 'q', emb, [makeResult('a')], META, { sourceId: 'src-A' });
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const hitB = await cache.lookup(emb, { sourceId: 'src-B' });
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expect(hitB.hit).toBe(false);
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const hitA = await cache.lookup(emb, { sourceId: 'src-A' });
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expect(hitA.hit).toBe(true);
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});
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test('archiving a source invalidates its cached result without a page write', async () => {
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const sourceId = 'cache-archive-src';
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await engine.executeRaw(
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`INSERT INTO sources (id, name, archived)
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VALUES ($1, $1, false)
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ON CONFLICT (id) DO UPDATE SET archived = false`,
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[sourceId],
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);
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const page = await engine.putPage(
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'cache/archive-visibility',
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{
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type: 'note',
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title: 'Archive visibility',
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compiled_truth: 'archive visibility cache canary',
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timeline: '',
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frontmatter: {},
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},
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{ sourceId },
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);
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const result = { ...makeResult(page.slug), page_id: page.id, source_id: sourceId };
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const cache = new SemanticQueryCache(engine);
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const emb = makeEmbedding(71);
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await storeCurrent(cache, 'archive visibility', emb, [result], META, { sourceId });
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expect((await cache.lookup(emb, { sourceId })).hit).toBe(true);
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await engine.executeRaw(`UPDATE sources SET archived = true WHERE id = $1`, [sourceId]);
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try {
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expect((await cache.lookup(emb, { sourceId })).hit).toBe(false);
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} finally {
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await engine.executeRaw(`UPDATE sources SET archived = false WHERE id = $1`, [sourceId]);
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}
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});
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test('a result hard-deleted before cache snapshot cannot be served', async () => {
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const page = await engine.putPage('cache/deleted-before-store', {
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type: 'note',
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title: 'Deleted before store',
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compiled_truth: 'private cache race canary',
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timeline: '',
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frontmatter: {},
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});
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const result = { ...makeResult(page.slug), page_id: page.id, source_id: 'default' };
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await engine.executeRaw(`DELETE FROM pages WHERE id = $1`, [page.id]);
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const cache = new SemanticQueryCache(engine);
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const emb = makeEmbedding(72);
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await storeCurrent(cache, 'deleted before store', emb, [result], META);
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expect((await cache.lookup(emb)).hit).toBe(false);
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});
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test('writeback without a pre-search generation fails closed', async () => {
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const cache = new SemanticQueryCache(engine);
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const emb = makeEmbedding(77);
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await cache.store('missing generation', emb, [makeResult('a')], META);
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expect((await cache.lookup(emb)).hit).toBe(false);
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expect((await cache.stats()).total_rows).toBe(0);
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});
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test('a concurrent page mutation prevents stale result writeback', async () => {
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const clock = await engine.executeRaw<{ v: number }>(
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`SELECT COALESCE((SELECT last_value FROM page_generation_clock_seq), 0)::bigint AS v`,
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);
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const generationAtSearchStart = Number(clock[0]?.v ?? 0);
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const staleResult = { ...makeResult('cache/visible-fixture'), page_id: visiblePageId };
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await engine.executeRaw(
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`UPDATE pages SET compiled_truth = 'redacted after search' WHERE id = $1`,
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[visiblePageId],
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);
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const cache = new SemanticQueryCache(engine);
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const emb = makeEmbedding(73);
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await storeCurrent(cache, 'concurrent mutation', emb, [staleResult], META, {
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maxGenerationAtSearchStart: generationAtSearchStart,
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});
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expect((await cache.lookup(emb)).hit).toBe(false);
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});
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});
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describe('SemanticQueryCache \u2014 management', () => {
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test('clear() wipes all rows', async () => {
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const cache = new SemanticQueryCache(engine);
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const emb = makeEmbedding(9);
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await storeCurrent(cache, 'q1', emb, [makeResult('a')], META);
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await storeCurrent(cache, 'q2', makeEmbedding(10), [makeResult('b')], META);
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const removed = await cache.clear();
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expect(removed).toBeGreaterThanOrEqual(2);
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const stats = await cache.stats();
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expect(stats.total_rows).toBe(0);
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});
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test('source-scoped clear removes typed scalar and federated scopes containing the source', async () => {
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const cache = new SemanticQueryCache(engine);
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const emb = makeEmbedding(74);
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await storeCurrent(cache, 'scalar-a', emb, [makeResult('a')], META, { sourceId: '["scalar","source-a"]' });
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await storeCurrent(cache, 'set-ab', makeEmbedding(75), [makeResult('ab')], META, { sourceId: '["set","source-a","source-b"]' });
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await storeCurrent(cache, 'scalar-b', makeEmbedding(76), [makeResult('b')], META, { sourceId: '["scalar","source-b"]' });
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expect(await cache.clear({ sourceId: 'source-a' })).toBe(2);
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const rows = await engine.executeRaw<{ source_id: string }>(`SELECT source_id FROM query_cache ORDER BY source_id`);
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expect(rows.map(r => r.source_id)).toEqual(['["scalar","source-b"]']);
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});
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test('prune() deletes only stale rows', async () => {
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const cache = new SemanticQueryCache(engine);
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await storeCurrent(cache, 'fresh', makeEmbedding(11), [makeResult('a')], META);
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await storeCurrent(cache, 'stale', makeEmbedding(12), [makeResult('b')], META, { ttlSeconds: 1 });
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await engine.executeRaw(
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`UPDATE query_cache SET created_at = now() - interval '10 seconds' WHERE query_text = 'stale'`,
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);
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const removed = await cache.prune();
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expect(removed).toBe(1);
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const stats = await cache.stats();
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expect(stats.total_rows).toBe(1);
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expect(stats.fresh_rows).toBe(1);
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});
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test('stats() reports fresh / stale / total / hit counters', async () => {
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const cache = new SemanticQueryCache(engine);
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const emb = makeEmbedding(13);
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await storeCurrent(cache, 'q', emb, [makeResult('a')], META);
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await cache.lookup(emb); // bump hit
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// Hit bump is async/fire-and-forget; give it a moment to land.
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await new Promise(r => setTimeout(r, 50));
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const stats = await cache.stats();
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expect(stats.total_rows).toBe(1);
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expect(stats.fresh_rows).toBe(1);
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expect(stats.stale_rows).toBe(0);
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expect(stats.total_hits).toBeGreaterThanOrEqual(1);
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});
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});
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describe('SemanticQueryCache \u2014 disabled', () => {
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test('disabled cache is a pure no-op on lookup', async () => {
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const cache = new SemanticQueryCache(engine, { enabled: false });
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const emb = makeEmbedding(99);
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await storeCurrent(cache, 'q', emb, [makeResult('a')], META);
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// Even after a store call, lookup must miss because enabled=false.
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const hit = await cache.lookup(emb);
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expect(hit.hit).toBe(false);
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});
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});
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