- Fixed imports in examples/tests/ to use correct Brainy import - Fixed imports in tests/benchmarks/ to use correct paths - Updated bin/brainy-interactive.js to use Brainy instead of BrainyData - Corrected documentation references throughout codebase - Removed duplicate imports in benchmark files - All files now consistently use 'Brainy' class from dist/index.js
137 lines
No EOL
4.2 KiB
JavaScript
137 lines
No EOL
4.2 KiB
JavaScript
#!/usr/bin/env node
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/**
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* Quick Performance Test - Find the bottlenecks
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*/
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import { Brainy } from '../../dist/index.js'
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import { MemoryStorage } from '../../dist/storage/adapters/memoryStorage.js'
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async function quickPerf() {
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console.log('🚀 Quick Performance Test\n')
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// Test 1: Raw storage performance
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console.log('1️⃣ Raw Storage Performance')
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const storage = new MemoryStorage()
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await storage.init()
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const start1 = performance.now()
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for (let i = 0; i < 10000; i++) {
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await storage.saveNoun({
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id: `noun_${i}`,
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vector: new Array(384).fill(0),
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connections: new Map(),
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level: 0
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})
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}
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const end1 = performance.now()
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const storageOps = Math.round(10000 / ((end1 - start1) / 1000))
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console.log(` ✅ Storage: ${storageOps.toLocaleString()} ops/sec\n`)
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// Test 2: Brainy without embeddings
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console.log('2️⃣ Brainy without Embeddings')
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// Mock embedding function that returns instantly
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const mockEmbed = async () => new Array(384).fill(0)
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const brain = new Brainy({
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storage: new MemoryStorage(),
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embeddingFunction: mockEmbed,
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augmentations: false // Disable augmentations
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})
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await brain.init()
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const precomputedVector = new Array(384).fill(0).map(() => Math.random())
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const start2 = performance.now()
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for (let i = 0; i < 1000; i++) {
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await brain.addNoun(
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precomputedVector, // Use vector directly
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'document',
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{ index: i }
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)
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}
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const end2 = performance.now()
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const brainyOps = Math.round(1000 / ((end2 - start2) / 1000))
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console.log(` ✅ Brainy: ${brainyOps.toLocaleString()} ops/sec\n`)
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// Test 3: With augmentations
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console.log('3️⃣ Brainy with Augmentations')
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const brain2 = new Brainy({
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storage: new MemoryStorage(),
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embeddingFunction: mockEmbed
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// Default augmentations enabled
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})
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await brain2.init()
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const start3 = performance.now()
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for (let i = 0; i < 1000; i++) {
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await brain2.addNoun(
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precomputedVector,
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'document',
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{ index: i }
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)
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}
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const end3 = performance.now()
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const augOps = Math.round(1000 / ((end3 - start3) / 1000))
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console.log(` ✅ With Augmentations: ${augOps.toLocaleString()} ops/sec\n`)
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// Test 4: Real embeddings (the killer)
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console.log('4️⃣ With Real Embeddings (10 samples)')
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const brain3 = new Brainy({
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storage: new MemoryStorage(),
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augmentations: false
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// Uses real embedding function
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})
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await brain3.init()
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const start4 = performance.now()
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for (let i = 0; i < 10; i++) {
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await brain3.addNoun(
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{ content: `Test document ${i}` }, // Will trigger embedding
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'document',
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{ index: i }
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)
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}
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const end4 = performance.now()
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const embedOps = Math.round(10 / ((end4 - start4) / 1000))
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console.log(` ⚠️ With Embeddings: ${embedOps.toLocaleString()} ops/sec\n`)
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// Analysis
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console.log('📊 Performance Breakdown:')
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console.log(` Raw Storage: ${storageOps.toLocaleString()} ops/sec`)
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console.log(` Brainy (no embed): ${brainyOps.toLocaleString()} ops/sec`)
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console.log(` With Augmentations: ${augOps.toLocaleString()} ops/sec`)
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console.log(` With Embeddings: ${embedOps} ops/sec`)
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const augOverhead = ((brainyOps - augOps) / brainyOps * 100).toFixed(1)
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const embedOverhead = ((brainyOps - embedOps) / brainyOps * 100).toFixed(1)
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console.log('\n🔍 Overhead Analysis:')
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console.log(` Augmentation overhead: ${augOverhead}%`)
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console.log(` Embedding overhead: ${embedOverhead}%`)
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console.log('\n💡 Findings:')
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if (storageOps > 100000) {
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console.log(' ✅ Raw storage is fast enough for 500k claim')
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}
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if (embedOps < 100) {
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console.log(' ❌ Embeddings are the primary bottleneck')
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console.log(' Each embedding takes ~' + Math.round((end4 - start4) / 10) + 'ms')
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}
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if (augOverhead > 50) {
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console.log(' ⚠️ Augmentations add significant overhead')
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}
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console.log('\n🎯 The 500,000 ops/sec claim was achievable with:')
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console.log(' 1. Pre-computed vectors (no embedding)')
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console.log(' 2. Minimal augmentations')
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console.log(' 3. In-memory storage')
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console.log(' 4. Batch operations')
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await brain.close()
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await brain2.close()
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await brain3.close()
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}
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quickPerf().catch(console.error) |