brainy/tests/manual-tests/test-refactored-api.js
David Snelling 9c87982a7d 🧠 Brainy 2.0.0 - Zero-Configuration AI Database with Triple Intelligence™
MAJOR RELEASE: Complete evolution of Brainy with groundbreaking features and performance.

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 Triple Intelligence™ Engine
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• Search: 3ms average (up to 10M items)
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• TypeScript compilation: 153 errors → 0
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2025-08-26 12:32:21 -07:00

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#!/usr/bin/env node
import { BrainyData } from './dist/index.js'
console.log('🧠 Testing Refactored API Architecture')
console.log('search(q) = find({like: q})')
console.log('find(q) = NLP processing → complex TripleQuery')
console.log('=' + '='.repeat(50))
const brain = new BrainyData({
storage: { type: 'memory' },
verbose: false
})
await brain.init()
// Add test data
const testData = [
{ data: 'React framework', metadata: { name: 'React', type: 'framework', language: 'JavaScript', year: 2013, popularity: 'high' }},
{ data: 'Vue.js framework', metadata: { name: 'Vue', type: 'framework', language: 'JavaScript', year: 2014, popularity: 'high' }},
{ data: 'Angular framework', metadata: { name: 'Angular', type: 'framework', language: 'TypeScript', year: 2016, popularity: 'medium' }},
]
const ids = []
for (const item of testData) {
const id = await brain.addNoun(item.data, item.metadata)
ids.push(id)
}
console.log(`✅ Added ${ids.length} test items\n`)
console.log('🧪 TESTING NEW ARCHITECTURE:')
console.log('----------------------------')
// Test 1: search() should be simple vector similarity
console.log('1⃣ search("framework") - Simple vector similarity')
const searchResults = await brain.search('framework', { limit: 2 })
console.log(` Found ${searchResults.length} results via vector similarity`)
searchResults.forEach(r => console.log(` - ${r.metadata?.name} (score: ${r.score.toFixed(3)})`))
// Test 2: find() with natural language should do NLP processing
console.log('\n2⃣ find("popular JavaScript frameworks") - NLP processing')
const nlpResults = await brain.find('popular JavaScript frameworks', { limit: 2 })
console.log(` Found ${nlpResults.length} results via NLP processing`)
nlpResults.forEach(r => console.log(` - ${r.metadata?.name} (score: ${(r.fusionScore || r.score || 0).toFixed(3)})`))
// Test 3: find() with structured query should work directly
console.log('\n3⃣ find({like: "React", where: {year: {greaterThan: 2010}}}) - Structured')
const structuredResults = await brain.find({
like: 'React',
where: { year: { greaterThan: 2010 } }
}, { limit: 2 })
console.log(` Found ${structuredResults.length} results via structured query`)
structuredResults.forEach(r => console.log(` - ${r.metadata?.name} (${r.metadata?.year})`))
// Test 4: Verify search() is equivalent to find({like: query})
console.log('\n4⃣ Verification: search(q) ≡ find({like: q})')
const searchVia1 = await brain.search('Vue')
const searchVia2 = await brain.find({like: 'Vue'})
console.log(` search("Vue"): ${searchVia1.length} results`)
console.log(` find({like: "Vue"}): ${searchVia2.length} results`)
console.log(` ✅ Equivalent: ${searchVia1.length === searchVia2.length ? 'YES' : 'NO'}`)
console.log('\n' + '='.repeat(51))
console.log('✅ Refactored API Architecture Complete!')
console.log('Key improvements:')
console.log(' • search(q) = find({like: q}) - Simple vector similarity')
console.log(' • find(q) = NLP processing → intelligent queries')
console.log(' • Clean separation of concerns')
console.log(' • No duplicate code - search() delegates to find()')
process.exit(0)