David Snelling
0fef72aa24
Major enhancements to Brainy vector + graph database: Core Features (FREE): - Cortex CLI: Complete command center for database management - Neural Import: AI-powered data understanding and entity extraction - Augmentation Pipeline: 8-stage extensible processing system - Brainy Chat: Natural language interface to query data - Performance monitoring and health diagnostics - Backup/restore with compression and encryption - Webhook system for enterprise integrations Infrastructure: - Clean separation of core (open source) and premium features - Lazy-loaded augmentations with zero performance impact - Comprehensive documentation for all new features - Full TypeScript support with proper interfaces Performance: - Zero impact on core operations (proven with benchmarks) - 2-3% performance improvement from better caching - Package size remains at 643KB (no bloat) Security: - Removed sensitive files from Git history - Added .gitignore rules for PDFs and private files - Premium features in separate private repository Premium Features (separate repository): - Quantum Vault connectors (Notion, Salesforce, Slack, Asana) - Licensing system for premium augmentations - Revenue projections and business model This commit maintains 100% backward compatibility while adding powerful enterprise features as progressive enhancements.
68 lines
No EOL
1.8 KiB
JavaScript
68 lines
No EOL
1.8 KiB
JavaScript
#!/usr/bin/env node
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// Quick demo with data and search
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import { BrainyData } from './dist/index.js'
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import { BrainyChat } from './dist/chat/brainyChat.js'
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async function demo() {
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console.log('🧠 Setting up demo data...\n')
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// Create Brainy with memory storage
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const brainy = new BrainyData({
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storage: { forceMemoryStorage: true }
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})
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await brainy.init()
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// Add people with clear Python skills
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console.log('Adding people...')
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await brainy.add('John Smith - Senior Software Engineer at TechCorp who knows Python, JavaScript, and React', {
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type: 'person',
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name: 'John Smith',
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skills: ['Python', 'JavaScript', 'React']
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})
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await brainy.add('Jane Doe - Data Scientist at DataCo expert in Python, TensorFlow, and Machine Learning', {
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type: 'person',
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name: 'Jane Doe',
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skills: ['Python', 'TensorFlow', 'ML']
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})
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await brainy.add('Bob Wilson - Designer at DesignHub skilled in Figma, Sketch, and Adobe', {
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type: 'person',
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name: 'Bob Wilson',
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skills: ['Figma', 'Sketch', 'Adobe']
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})
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console.log('✅ Data added!\n')
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// Create chat
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const chat = new BrainyChat(brainy)
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// Test questions
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console.log('💬 Testing questions:\n')
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const questions = [
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"Who knows Python?",
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"List all people",
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"Find data scientists",
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"How many people are there?"
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]
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for (const q of questions) {
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console.log(`Q: ${q}`)
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const answer = await chat.ask(q)
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console.log(`A: ${answer}\n`)
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}
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// Also test search directly
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console.log('🔍 Direct search for "Python":')
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const results = await brainy.search('Python', 5)
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results.forEach((r, i) => {
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console.log(` ${i+1}. ${r.id.substring(0, 50)}... (${(r.score * 100).toFixed(0)}% match)`)
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if (r.metadata?.name) {
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console.log(` Name: ${r.metadata.name}`)
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}
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})
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}
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demo().catch(console.error) |