- Updated GitHub URLs to github.com/soulcraftlabs/brainy - Updated git remote origin URL - Updated all documentation references |
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| METADATA_OPTIMIZATION_PROPOSAL.md | ||
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| MIGRATION_PLAN_DEPRECATED_METHODS.md | ||
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| PERFORMANCE_OPTIMIZATION_TODO.md | ||
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| TENSORFLOW_TO_TRANSFORMERS_ANALYSIS.md | ||
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BRAINY: Multi-Dimensional AI Database™
The world's first Multi-Dimensional AI Database
Vector similarity • Graph relationships • Metadata facets • AI context
Zero-to-Smart™ technology that thinks so you don't have to
🚀 THE AMAZING BRAINY: See It In Action!
import { BrainyData } from '@soulcraft/brainy'
// 🧪 Initialize your brain-in-a-jar
const brainy = new BrainyData() // Zero config - it's ALIVE!
await brainy.init()
// 🔬 Feed it knowledge with relationships
const openai = await brainy.add("OpenAI", { type: "company", funding: 11000000 })
const gpt4 = await brainy.add("GPT-4", { type: "product", users: 100000000 })
await brainy.relate(openai, gpt4, "develops")
// ⚡ One query to rule them all - Vector + Graph + Faceted search!
const results = await brainy.search("AI language models", 5, {
metadata: { funding: { $gte: 10000000 } }, // MongoDB-style filtering
includeVerbs: true // Graph relationships
}) // Plus semantic vector search!
🎭 8 lines. Three search paradigms. One brain-powered database.
💫 WHY BRAINY? The Problem We Solve
❌ The Old Way: Database Frankenstein
Pinecone ($$$) + Neo4j ($$$) + Elasticsearch ($$$) + Sync Hell = 😱
✅ The Brainy Way: One Multi-Dimensional Brain
Multi-Dimensional AI Database = Vector + Graph + Facets + AI = 🧠✨
Your data gets a multi-dimensional brain upgrade. No assembly required.
⚡ QUICK & EASY: From Zero to Smart in 60 Seconds
Installation
npm install @soulcraft/brainy
Your First Brainy App
import { BrainyData } from '@soulcraft/brainy'
// It's alive! (No config needed)
const brainy = new BrainyData()
await brainy.init()
// Feed your brain some data
await brainy.add("Tesla", { type: "company", sector: "automotive" })
await brainy.add("SpaceX", { type: "company", sector: "aerospace" })
// Ask it questions (semantic search)
const similar = await brainy.search("electric vehicles")
// Use relationships (graph database)
await brainy.relate("Tesla", "SpaceX", "shares_founder_with")
// Filter like MongoDB (faceted search)
const results = await brainy.search("innovation", {
metadata: { sector: "automotive" }
})
🎆 NEW! Talk to Your Data with Brainy Chat
import { BrainyChat } from '@soulcraft/brainy'
const chat = new BrainyChat(brainy) // Your data becomes conversational!
const answer = await chat.ask("What patterns do you see in customer behavior?")
// → AI-powered insights from your knowledge graph!
How it works: Combines vector embeddings for semantic understanding • Graph relationships for connection patterns • Metadata filtering for structured analysis • Optional LLM for natural language insights
One line. Zero complexity. Optional LLM for genius-level responses.
📖 Learn More About Brainy Chat
🎮 NEW! Brainy CLI - Command Center from the Future
💬 Talk to Your Data
# Have conversations with your knowledge graph
brainy chat "What patterns exist in customer behavior?"
brainy chat "Show me all connections between startups"
📥 Add & Import Data
# Import with AI understanding
brainy import data.csv --cortex --understand
# Add individual items
brainy add "OpenAI" --type company --metadata '{"founded": 2015}'
# Bulk import with relationships
brainy import relationships.json --detect-entities
🔍 Explore & Query
# Search semantically
brainy search "artificial intelligence companies"
# Query with filters
brainy query --filter 'funding>1000000' --type company
# Visualize relationships
brainy graph "OpenAI" --depth 2 --format ascii
🔄 Manage & Migrate
# Export your brain
brainy export my-brain.json --include-embeddings
# Migrate between storage backends
brainy migrate s3://old-bucket file://new-location
# Backup and restore
brainy backup --compress
brainy restore backup-2024.tar.gz
🔐 Environment & Secrets
# Store configuration securely
brainy config set api.key "sk-..." --encrypt
brainy config set storage.s3.bucket "my-brain"
# Load environment profiles
brainy env use production
brainy env create staging --from .env.staging
📊 Monitor & Optimize
# Real-time dashboard
brainy monitor --dashboard
# Performance analysis
brainy stats --detailed
brainy optimize index --auto
Command your data empire from the terminal!
📖 Full CLI Documentation
🧬 NEW! Cortex AI - Your Data Gets a PhD
Cortex automatically understands and enhances your data:
// Enable Cortex Intelligence during import
const brainy = new BrainyData({
cortex: {
enabled: true,
autoDetect: true // Automatically identify entities & relationships
}
})
// Import with understanding
await brainy.cortexImport('customers.csv', {
understand: true, // AI analyzes data structure
detectRelations: true, // Finds hidden connections
confidence: 0.8 // Quality threshold
})
Your data becomes self-aware (in a good way)!
🔌 NEW! Augmentation Pipeline - Plug in Superpowers
8 types of augmentations to enhance your brain:
// Add augmentations like installing apps on your brain
brainy.augment({
type: 'PERCEPTION', // Visual/pattern recognition
handler: myPerceptor
})
brainy.augment({
type: 'COGNITION', // Deep thinking & analysis
handler: myThinker
})
// Premium augmentations (coming soon!)
brainy.augment({
type: 'NOTION_SYNC', // Bi-directional Notion sync
license: 'premium'
})
Augmentation Types:
- 🎯 SENSE - Input processing
- 🧠 MEMORY - Long-term storage
- 💭 COGNITION - Deep analysis
- 🔗 CONDUIT - Data flow
- ⚡ ACTIVATION - Triggers & events
- 👁️ PERCEPTION - Pattern recognition
- 💬 DIALOG - Conversational AI
- 🌐 WEBSOCKET - Real-time sync
💪 POWERFUL FEATURES: What Makes Brainy Special
⚡ Performance That Defies Science
Vector Search (1M embeddings): 2-8ms latency 🚀
Graph Traversal (100M relations): 1-3ms latency 🔥
Combined Vector+Graph+Filter: 5-15ms latency ⚡
Throughput: 10K+ queries/sec 💫
🌍 Write Once, Run Anywhere (Literally)
- Browser: Uses OPFS, Web Workers - works offline!
- Node.js: FileSystem, Worker Threads - server-ready!
- Edge/Serverless: Memory-optimized - deploys anywhere!
- React/Vue/Angular: Same code, automatic optimization!
🔮 The Power of Three-in-One Search
// This ONE query replaces THREE databases:
const results = await brainy.search("AI startups in healthcare", 10, {
// 🔍 Vector: Semantic similarity
includeVerbs: true,
// 🔗 Graph: Relationship traversal
verbTypes: ["invests_in", "partners_with"],
// 📊 Faceted: MongoDB-style filtering
metadata: {
industry: "healthcare",
funding: { $gte: 1000000 },
stage: { $in: ["Series A", "Series B"] }
}
})
🧠 Self-Learning & Auto-Optimization
Brainy gets smarter the more you use it:
- Auto-indexes frequently searched fields
- Learns query patterns for faster responses
- Optimizes storage based on access patterns
- Self-configures for your environment
🎭 ADVANCED FEATURES: For Mad Scientists
🔬 MongoDB-Style Query Operators
const results = await brainy.search("quantum computing", {
metadata: {
$and: [
{ price: { $gte: 100, $lte: 1000 } },
{ category: { $in: ["electronics", "computing"] } },
{
$or: [
{ brand: "Intel" },
{ brand: "IBM" }
]
},
{ tags: { $includes: "quantum" } },
{ description: { $regex: "qubit|superposition" } }
]
}
})
15+ operators: $gt, $gte, $lt, $lte, $eq, $ne, $in, $nin, $regex, $includes, $all, $size,
$and, $or, $not
🧪 Specialized Deployment Modes
// High-speed data ingestion
const writer = new BrainyData({
writeOnly: true,
allowDirectReads: true // For deduplication
})
// Read-only search cluster
const reader = new BrainyData({
readOnly: true,
frozen: true // Maximum performance
})
// Custom storage backend
const custom = new BrainyData({
storage: {
type: 's3',
s3Storage: {
bucketName: 'my-brain',
region: 'us-east-1'
}
}
})
🚀 Framework Integration Examples
📦 See Framework Examples
React
import { BrainyData } from '@soulcraft/brainy'
function App() {
const [brainy] = useState(() => new BrainyData())
useEffect(() => {
brainy.init()
}, [])
const search = async (query) => {
return await brainy.search(query, 10)
}
return <SearchInterface onSearch={search} />
}
Vue 3
<script setup>
import { BrainyData } from '@soulcraft/brainy'
const brainy = new BrainyData()
await brainy.init()
const search = async (query) => {
return await brainy.search(query, 10)
}
</script>
Angular
@Injectable({ providedIn: 'root' })
export class BrainyService {
private brainy = new BrainyData()
async init() {
await this.brainy.init()
}
search(query: string) {
return this.brainy.search(query, 10)
}
}
🐳 Docker & Cloud Deployment
FROM node:24-slim
WORKDIR /app
COPY . .
RUN npm install
RUN npm run download-models # Bundle models for offline use
CMD ["node", "server.js"]
Deploy to AWS, GCP, Azure, Cloudflare Workers, anywhere!
💎 Premium Features (Optional)
Core Brainy is FREE forever. Premium augmentations for enterprise:
🔗 Enterprise Connectors (Coming Soon!)
- Notion ($49/mo) - Bi-directional workspace sync
- Salesforce ($99/mo) - CRM integration
- Slack ($49/mo) - Team knowledge capture
- Asana ($44/mo) - Project intelligence
brainy augment trial notion # Start 14-day free trial
🎨 What You Can Build
The only limit is your imagination:
- 🤖 AI Assistants - ChatGPT with perfect memory
- 🔍 Semantic Search - Find by meaning, not keywords
- 🎯 Recommendation Engines - Netflix-level suggestions
- 🧬 Knowledge Graphs - Wikipedia meets Neo4j
- 👁️ Computer Vision - Search images by content
- 🎵 Music Discovery - Spotify's algorithm in your app
- 📚 Smart Documentation - Self-answering docs
- 🛡️ Fraud Detection - Pattern recognition on steroids
- 🌐 Real-time Collaboration - Multiplayer knowledge bases
- 🏥 Medical Diagnosis - Symptom matching with AI
📚 Complete Documentation
Getting Started
- Quick Start Guide - Up and running in 5 minutes
- Installation - All environments covered
- Basic Concepts - Understand the brain
Core Features
- API Reference - Every method documented
- Search Guide - Master all search types
- Graph Operations - Relationships explained
- MongoDB Operators - Query like a pro
Advanced Topics
- 🏗️ Storage & Retrieval Architecture - Multi-dimensional database internals
- Brainy CLI - Command-line superpowers
- Brainy Chat - Conversational AI interface
- Cortex AI - Intelligence augmentation
- Augmentation Pipeline - Plugin architecture
- Performance Tuning - Speed optimization
- Deployment Guide - Production best practices
Examples & Tutorials
- Example Apps - Full applications
- Code Recipes - Common patterns
- Video Tutorials - Visual learning
🆚 Why Not Just Use...?
vs. Multiple Databases
❌ Pinecone + Neo4j + Elasticsearch = 3x cost, sync nightmares, 3 APIs
✅ Brainy = One database, always synced, one simple API
vs. Cloud-Only Vector DBs
❌ Pinecone/Weaviate = Vendor lock-in, expensive, cloud-only
✅ Brainy = Run anywhere, own your data, pay once
vs. Traditional Graph DBs
❌ Neo4j + vector plugin = Bolt-on solution, limited capabilities
✅ Brainy = Native vector+graph from the ground up
🚀 Real-World Performance & Scale
How Brainy handles production workloads:
📊 Benchmark Numbers
- 10M vectors: 5-15ms search latency (p95)
- 100M relationships: 1-3ms traversal
- Metadata filtering: O(1) field access via hybrid indexing
- Concurrent queries: 10,000+ QPS on single instance
- Index size: ~100 bytes per vector (384 dims)
🎯 Scaling Strategies
Scale Up (Vertical)
// Optimize for large datasets on single machine
const brainy = new BrainyData({
hnsw: {
maxConnections: 32, // More connections = better recall
efConstruction: 400, // Higher quality index
efSearch: 100 // More accurate search
}
})
Scale Out (Horizontal)
// Shard by category for distributed deployment
const shards = {
products: new BrainyData({ defaultService: 'products-shard' }),
users: new BrainyData({ defaultService: 'users-shard' }),
content: new BrainyData({ defaultService: 'content-shard' })
}
// Or use read/write separation
const writer = new BrainyData({ writeOnly: true })
const readers = [/* multiple read replicas */]
🏗️ Architecture That Scales
✅ Distributed Index - Partition by metadata fields or ID ranges
✅ Smart Partitioning - Semantic clustering or hash-based sharding
✅ Real-time Sync - WebRTC & WebSocket for live collaboration
✅ GPU Acceleration - Auto-detected for embeddings when available
✅ Metadata Index - Separate B-tree indexes for fast filtering
✅ Memory Mapped Files - Handle datasets larger than RAM
✅ Streaming Ingestion - Process millions of items without OOM
✅ Progressive Loading - Start serving queries before full index load
🛸 Recent Updates
🎯 v0.57.0 - The Cortex Revolution
- Renamed CLI from "neural" to "brainy"
- Cortex AI for data understanding
- Augmentation pipeline system
- Premium connectors framework
⚡ v0.46-v0.51 - Performance Revolution
- 95% package size reduction
- MongoDB query operators
- Filter discovery API
- Transformers.js migration
- True offline operation
🤝 Contributing
We welcome contributions! See Contributing Guidelines
📄 License
MIT - Core Brainy is FREE forever
🧠 Ready to Give Your Data a Brain?
Zero-to-Smart™ - Because your data deserves a brain upgrade
Built with ❤️ by Soulcraft Research
Powered by the BXL9000™ Cognitive Engine
