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< div align = "center" >
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< img src = "./brainy.png" alt = "Brainy Logo" width = "200" / >
< br / > < br / >
[](LICENSE)
**feat(tests, docs, storage): add statistics storage tests and enhance documentation**
- **Tests**: Added new `statistics-storage.test.ts` to validate statistics storage functionality across scenarios including saving, retrieving, time-based partitioning, and backward compatibility. Ensured tests dynamically handle missing environment variables by skipping S3-related tests when credentials are unavailable.
- **Docs**: Enhanced `statistics.md` with detailed explanations of scalability improvements, including adaptive flush timing, batched updates, and time-based partitioning. Improved readability and structure.
- **Storage**: Updated all storage adapters to integrate time-based partitioning and maintain backward compatibility with legacy statistics storage formats.
- **Dependencies**: Added `dotenv` to support environmental variable management for storage adapter tests.
**Purpose**: Strengthen system reliability by adding comprehensive test coverage for statistics storage, improve scalability documentation, and ensure consistency across storage adapters with robust implementations.
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[](https://nodejs.org/)
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[](https://www.typescriptlang.org/)
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[](CONTRIBUTING.md)
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**The world's only true Vector + Graph database - unified semantic search and knowledge graphs**
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< / div >
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---
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# The Search Problem Every Developer Faces
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**"I need to find similar content, explore relationships, AND filter by metadata - but that means juggling 3+ databases"**
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❌ **Current Reality** : Pinecone + Neo4j + Elasticsearch + Custom Sync Logic
✅ **Brainy Reality** : One database. One API. All three search types.
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## 🔥 The Power of Three-in-One Search
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```javascript
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// This ONE query does what used to require 3 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
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metadata: {
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industry: "healthcare",
funding: { $gte: 1000000 },
stage: { $in: ["Series A", "Series B"] }
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}
})
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// Returns: Companies similar to your query + their relationships + matching your criteria
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```
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**Three search paradigms. One lightning-fast query. Zero complexity.**
**feat(web-service): add new web service package and deployment scripts**
- **New Web Service Package**:
- Introduced `@soulcraft/brainy-web-service`, a REST API wrapper for the Brainy vector graph database.
- Added documentation and features to support secure, read-only search and retrieval operations.
- **Deployment Support**:
- Included comprehensive deployment instructions in the `web-service-package/README.md`:
- Options for Docker, serverless platforms, and cloud providers (AWS, GCP, Azure, Cloudflare).
- Example configurations for systemd, Nginx, and Docker Compose.
- **Scripts and Documentation Updates**:
- Added `deploy:web-service` script to `package.json` for streamlined build and publishing.
- Enhanced `README.md` to reflect the introduction of the web service package and its capabilities.
- **Purpose**:
- This update extends Brainy’s functionality by providing a production-ready, easy-to-deploy REST API for search operations. It ensures flexibility for diverse deployment scenarios while maintaining security and high performance.
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## 🚀 Install & Go
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```bash
npm install @soulcraft/brainy
```
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```javascript
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import { BrainyData } from '@soulcraft/brainy '
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const brainy = new BrainyData() // Auto-detects your environment
await brainy.init() // Auto-configures everything
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// Add data with relationships
const openai = await brainy.add("OpenAI", { type: "company", funding: 11000000 })
const gpt4 = await brainy.add("GPT-4", { type: "product", users: 100000000 })
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await brainy.relate(openai, gpt4, "develops")
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// Search across all dimensions
const results = await brainy.search("AI language models", 5, {
metadata: { funding: { $gte: 10000000 } },
includeVerbs: true
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})
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```
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**That's it. You just built a knowledge graph with semantic search and faceted filtering in 8 lines.**
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## 🔥 MAJOR UPDATES: What's New in v0.51, v0.49 & v0.48
### 🎯 **v0.51: Revolutionary Developer Experience**
**Problem-focused approach that gets you productive in seconds!**
- ✅ **Problem-Solution Narrative** - Immediately understand why Brainy exists
- ✅ **8-Line Quickstart** - Three search types in one simple demo
- ✅ **Streamlined Documentation** - Focus on what matters most
- ✅ **Clear Positioning** - The only true Vector + Graph database
### 🎯 **v0.49: Filter Discovery & Performance Improvements**
**Discover available filters and scale to millions of items!**
```javascript
// Discover what filters are available - O(1) field lookup
const categories = await brainy.getFilterValues('category')
// Returns: ['electronics', 'books', 'clothing', ...]
const fields = await brainy.getFilterFields() // O(1) operation
// Returns: ['category', 'price', 'brand', 'rating', ...]
```
- ✅ **Filter Discovery API** : O(1) field discovery for instant filter UI generation
- ✅ **Improved Performance** : Removed deprecated methods, now uses pagination everywhere
- ✅ **Better Scalability** : Hybrid indexing with O(1) field access scales to millions
- ✅ **Smart Caching** : LRU cache for frequently accessed filters
- ✅ **Zero Configuration** : Everything auto-optimizes based on usage patterns
### 🚀 **v0.48: MongoDB-Style Metadata Filtering**
**Powerful querying with familiar syntax - filter DURING search for maximum performance!**
```javascript
const results = await brainy.search("wireless headphones", 10, {
metadata: {
category: { $in: ["electronics", "audio"] },
price: { $lte: 200 },
rating: { $gte: 4.0 },
brand: { $ne: "Generic" }
}
})
```
- ✅ **15+ MongoDB Operators** : `$gt` , `$in` , `$regex` , `$and` , `$or` , `$includes` , etc.
- ✅ **Automatic Indexing** : Zero configuration, maximum performance
- ✅ **Nested Fields** : Use dot notation for complex objects
- ✅ **100% Backward Compatible** : Your existing code works unchanged
### ⚡ **v0.46: Transformers.js Migration**
**Replaced TensorFlow.js for better performance and true offline operation!**
- ✅ **95% Smaller Package** : 643 kB vs 12.5 MB
- ✅ **84% Smaller Models** : 87 MB vs 525 MB models
- ✅ **True Offline** : Zero network calls after initial download
- ✅ **5x Fewer Dependencies** : Clean tree, no peer dependency issues
- ✅ **Same API** : Drop-in replacement, existing code works unchanged
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### 🚀 Why Developers Love Brainy
- **🧠 Zero-to-Smart™** - No config files, no tuning parameters, no DevOps headaches. Brainy auto-detects your environment and optimizes itself
- **🌍 True Write-Once, Run-Anywhere** - Same code runs in Angular, React, Vue, Node.js, Deno, Bun, serverless, edge workers, and web workers with automatic environment detection
- **⚡ Scary Fast** - Handles millions of vectors with sub-millisecond search. GPU acceleration for embeddings, optimized CPU for distance calculations
- **🎯 Self-Learning** - Like having a database that goes to the gym. Gets faster and smarter the more you use it
- **🔮 AI-First Design** - Built for the age of embeddings, RAG, and semantic search. Your LLMs will thank you
- **🎮 Actually Fun to Use** - Clean API, great DX, and it does the heavy lifting so you can build cool stuff
### 🚀 NEW: Ultra-Fast Search Performance + Auto-Configuration
**Your searches just got 100x faster AND Brainy now configures itself!** Advanced performance with zero setup:
- **🤖 Intelligent Auto-Configuration** - Detects environment and usage patterns, optimizes automatically
- **⚡ Smart Result Caching** - Repeated queries return in < 1ms with automatic cache invalidation
- **📄 Cursor-Based Pagination** - Navigate millions of results with constant O(k) performance
- **🔄 Real-Time Data Sync** - Cache automatically updates when data changes, even in distributed scenarios
- **📊 Performance Monitoring** - Built-in hit rate and memory usage tracking with adaptive optimization
- **🎯 Zero Breaking Changes** - All existing code works unchanged, just faster and smarter
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## 🏆 Why Brainy Wins
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- 🧠 **Triple Search Power** - Vector + Graph + Faceted filtering in one query
- 🌍 **Runs Everywhere** - Same code: React, Node.js, serverless, edge
- ⚡ **Zero Config** - Auto-detects environment, optimizes itself
- 🔄 **Always Synced** - No data consistency nightmares between systems
- 📦 **Truly Offline** - Works without internet after initial setup
- 🔒 **Your Data** - Run locally, in browser, or your own cloud
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## 🔮 Coming Soon
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- **🤖 MCP Integration** - Let Claude, GPT, and other AI models query your data directly
- **⚡ LLM Generation** - Built-in content generation powered by your knowledge graph
- **🌊 Real-time Sync** - Live updates across distributed instances
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## 🎨 Build Amazing Things
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**🤖 AI Chat Applications** - Build ChatGPT-like apps with long-term memory and context awareness
**🔍 Semantic Search Engines** - Search by meaning, not keywords. Find "that thing that's like a cat but bigger" → returns "tiger"
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**🎯 Recommendation Engines** - "Users who liked this also liked..." but actually good
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**🧬 Knowledge Graphs** - Connect everything to everything. Wikipedia meets Neo4j meets magic
**👁️ Computer Vision Apps** - Store and search image embeddings. "Find all photos with dogs wearing hats"
**🎵 Music Discovery** - Find songs that "feel" similar. Spotify's Discover Weekly in your app
**📚 Smart Documentation** - Docs that answer questions. "How do I deploy to production?" → relevant guides
**🛡️ Fraud Detection** - Find patterns humans can't see. Anomaly detection on steroids
**🌐 Real-Time Collaboration** - Sync vector data across devices. Figma for AI data
**🏥 Medical Diagnosis Tools** - Match symptoms to conditions using embedding similarity
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## 🌍 Works Everywhere - Same Code
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**Write once, run anywhere.** Brainy auto-detects your environment and optimizes automatically:
### 🌐 Browser Frameworks (React, Angular, Vue)
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```javascript
import { BrainyData } from '@soulcraft/brainy '
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// SAME CODE in React, Angular, Vue, Svelte, etc.
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const brainy = new BrainyData()
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await brainy.init() // Auto-uses OPFS in browsers
// Add entities and relationships
const john = await brainy.add("John is a software engineer", { type: "person" })
const jane = await brainy.add("Jane is a data scientist", { type: "person" })
const ai = await brainy.add("AI Project", { type: "project" })
await brainy.relate(john, ai, "works_on")
await brainy.relate(jane, ai, "leads")
// Search by meaning
const engineers = await brainy.search("software developers", 5)
// Traverse relationships
const team = await brainy.getVerbsByTarget(ai) // Who works on AI Project?
```
< details >
< summary > 📦 < strong > Full React Component Example< / strong > < / summary >
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```jsx
import { BrainyData } from '@soulcraft/brainy '
import { useEffect, useState } from 'react'
function Search() {
const [brainy, setBrainy] = useState(null)
const [results, setResults] = useState([])
useEffect(() => {
const init = async () => {
const db = new BrainyData()
await db.init()
// Add your data...
setBrainy(db)
}
init()
}, [])
const search = async (query) => {
const results = await brainy?.search(query, 5) || []
setResults(results)
}
return < input onChange = {(e) = > search(e.target.value)} placeholder="Search..." />
}
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```
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< / details >
< details >
< summary > 📦 < strong > Full Angular Component Example< / strong > < / summary >
```typescript
import { Component, signal, OnInit } from '@angular/core '
import { BrainyData } from '@soulcraft/brainy '
@Component ({
selector: 'app-search',
template: `<input (input)="search($event.target.value)" placeholder="Search...">`
})
export class SearchComponent implements OnInit {
brainy = new BrainyData()
async ngOnInit() {
await this.brainy.init()
// Add your data...
}
async search(query: string) {
const results = await this.brainy.search(query, 5)
// Display results...
}
}
```
< / details >
< details >
< summary > 📦 < strong > Full Vue Example< / strong > < / summary >
```vue
< script setup >
import { BrainyData } from '@soulcraft/brainy '
import { ref, onMounted } from 'vue'
const brainy = ref(null)
const results = ref([])
onMounted(async () => {
const db = new BrainyData()
await db.init()
// Add your data...
brainy.value = db
})
const search = async (query) => {
const results = await brainy.value?.search(query, 5) || []
setResults(results)
}
< / script >
< template >
< input @input =" search ($ event . target . value )" placeholder = "Search..." />
< / template >
```
< / details >
### 🟢 Node.js / Serverless / Edge
```javascript
import { BrainyData } from '@soulcraft/brainy '
// SAME CODE works in Node.js, Vercel, Netlify, Cloudflare Workers, Deno, Bun
const brainy = new BrainyData()
await brainy.init() // Auto-detects environment and optimizes
// Add entities and relationships
await brainy.add("Python is great for data science", { type: "fact" })
await brainy.add("JavaScript rules the web", { type: "fact" })
// Search by meaning
const results = await brainy.search("programming languages", 5)
// Optional: Production with S3/R2 storage (auto-detected in cloud environments)
const productionBrainy = new BrainyData({
storage: {
s3Storage: { bucketName: process.env.BUCKET_NAME }
}
})
```
**That's it! Same code, everywhere. Zero-to-Smart™**
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Brainy automatically detects and optimizes for your environment:
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| Environment | Storage | Optimization |
|-------------|---------|-------------|
| 🌐 Browser | OPFS | Web Workers, Memory Cache |
| 🟢 Node.js | FileSystem / S3 | Worker Threads, Clustering |
| ⚡ Serverless | S3 / Memory | Cold Start Optimization |
| 🔥 Edge | Memory / KV | Minimal Footprint |
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## 🌐 Distributed Mode (NEW!)
**Scale horizontally with zero configuration!** Brainy now supports distributed deployments with automatic coordination:
- **🌐 Multi-Instance Coordination** - Multiple readers and writers working in harmony
- **🏷️ Smart Domain Detection** - Automatically categorizes data (medical, legal, product, etc.)
- **📊 Real-Time Health Monitoring** - Track performance across all instances
- **🔄 Automatic Role Optimization** - Readers optimize for cache, writers for throughput
- **🗂️ Intelligent Partitioning** - Hash-based partitioning for perfect load distribution
```javascript
// Writer Instance - Ingests data from multiple sources
const writer = new BrainyData({
storage: { s3Storage: { bucketName: 'my-bucket' } },
distributed: { role: 'writer' } // Explicit role for safety
})
// Reader Instance - Optimized for search queries
const reader = new BrainyData({
storage: { s3Storage: { bucketName: 'my-bucket' } },
distributed: { role: 'reader' } // 80% memory for cache
})
// Data automatically gets domain tags
await writer.add("Patient shows symptoms of...", {
diagnosis: "flu" // Auto-tagged as 'medical' domain
})
// Domain-aware search across all partitions
const results = await reader.search("medical symptoms", 10, {
filter: { domain: 'medical' } // Only search medical data
})
// Monitor health across all instances
const health = reader.getHealthStatus()
console.log(`Instance ${health.instanceId}: ${health.status}` )
```
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### 🐳 NEW: Zero-Config Docker Deployment
**Deploy to any cloud with embedded models - no runtime downloads needed!**
```dockerfile
# One line extracts models automatically during build
RUN npm run download-models
# Deploy anywhere: Google Cloud, AWS, Azure, Cloudflare, etc.
```
- **⚡ 7x Faster Cold Starts** - Models embedded in container, no downloads
- **🌐 Universal Cloud Support** - Same Dockerfile works everywhere
- **🔒 Offline Ready** - No external dependencies at runtime
- **📦 Zero Configuration** - Automatic model detection and loading
```javascript
// Zero configuration - everything optimized automatically!
const brainy = new BrainyData() // Auto-detects environment & optimizes
await brainy.init()
// Caching happens automatically - no setup needed!
const results1 = await brainy.search('query', 10) // ~50ms first time
const results2 = await brainy.search('query', 10) // < 1ms cached hit !
// Advanced pagination works instantly
const page1 = await brainy.searchWithCursor('query', 100)
const page2 = await brainy.searchWithCursor('query', 100, {
cursor: page1.cursor // Constant time, no matter how deep!
})
// Monitor auto-optimized performance
const stats = brainy.getCacheStats()
console.log(`Auto-tuned cache hit rate: ${(stats.search.hitRate * 100).toFixed(1)}%` )
```
## 🎭 Key Features
### Core Capabilities
- **Vector Search** - Find semantically similar content using embeddings
- **MongoDB-Style Metadata Filtering** 🆕 - Advanced filtering with `$gt` , `$in` , `$regex` , `$and` , `$or` operators
- **Graph Relationships** - Connect data with meaningful relationships
- **JSON Document Search** - Search within specific fields with prioritization
- **Distributed Mode** - Scale horizontally with automatic coordination between instances
- **Real-Time Syncing** - WebSocket and WebRTC for distributed instances
- **Streaming Pipeline** - Process data in real-time as it flows through
- **Model Control Protocol** - Let AI models access your data
### Developer Experience
- **TypeScript Support** - Fully typed API with generics
- **Extensible Augmentations** - Customize and extend functionality
- **REST API** - Web service wrapper for HTTP endpoints
- **Auto-Complete** - IntelliSense for all APIs and types
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## 🆚 Why Not Just Use...?
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### vs. Multiple Databases
❌ **Pinecone + Neo4j + Elasticsearch** - 3 databases, sync nightmares, 3x the cost
✅ **Brainy** - One database, always synced, built-in intelligence
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### vs. Traditional Solutions
❌ **PostgreSQL + pgvector + extensions** - Complex setup, performance issues
✅ **Brainy** - Zero config, purpose-built for AI, works everywhere
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### vs. Cloud-Only Vector DBs
❌ **Pinecone/Weaviate/Qdrant** - Vendor lock-in, expensive, cloud-only
✅ **Brainy** - Run anywhere, your data stays yours, cost-effective
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### vs. Graph Databases with "Vector Features"
❌ **Neo4j + vector plugin** - Bolt-on solution, not native, limited
✅ **Brainy** - Native vector+graph architecture from the ground up
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## 📦 Advanced Features
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< details >
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< summary > 🔧 < strong > MongoDB-Style Metadata Filtering< / strong > < / summary >
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```javascript
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const results = await brainy.search("machine learning", 10, {
metadata: {
// Comparison operators
price: { $gte: 100, $lte: 1000 },
category: { $in: ["AI", "ML", "Data"] },
rating: { $gt: 4.5 },
// Logical operators
$and: [
{ status: "active" },
{ verified: true }
],
// Text operators
description: { $regex: "neural.*network", $options: "i" },
// Array operators
tags: { $includes: "tensorflow" }
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}
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})
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```
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**15+ operators supported**: `$gt` , `$gte` , `$lt` , `$lte` , `$eq` , `$ne` , `$in` , `$nin` , `$and` , `$or` , `$not` , `$regex` , `$includes` , `$exists` , `$size`
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< / details >
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< details >
< summary > 🔗 < strong > Graph Relationships & Traversal< / strong > < / summary >
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```javascript
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// Create entities and relationships
const company = await brainy.add("OpenAI", { type: "company" })
const product = await brainy.add("GPT-4", { type: "product" })
const person = await brainy.add("Sam Altman", { type: "person" })
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// Create meaningful relationships
await brainy.relate(company, product, "develops")
await brainy.relate(person, company, "leads")
await brainy.relate(product, person, "created_by")
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// Traverse relationships
const products = await brainy.getVerbsBySource(company) // What OpenAI develops
const leaders = await brainy.getVerbsByTarget(company) // Who leads OpenAI
const connections = await brainy.findSimilar(product, {
relationType: "develops"
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})
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// Search with relationship context
const results = await brainy.search("AI models", 10, {
includeVerbs: true,
verbTypes: ["develops", "created_by"],
searchConnectedNouns: true
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})
```
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< / details >
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< details >
< summary > 🌐 < strong > Universal Storage & Deployment< / strong > < / summary >
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```javascript
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// Development: File system
const dev = new BrainyData({
storage: { fileSystem: { path: './data' } }
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})
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// Production: S3/R2
const prod = new BrainyData({
storage: { s3Storage: { bucketName: 'my-vectors' } }
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})
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// Browser: OPFS
const browser = new BrainyData() // Auto-detects OPFS
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// Edge: Memory
const edge = new BrainyData({
storage: { memory: {} }
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})
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// Redis: High performance
const redis = new BrainyData({
storage: { redis: { connectionString: 'redis://...' } }
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})
```
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**Extend with any storage**: MongoDB, PostgreSQL, DynamoDB - [see storage adapters guide ](docs/api-reference/storage-adapters.md )
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< / details >
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< details >
< summary > 🐳 < strong > Docker & Cloud Deployment< / strong > < / summary >
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```dockerfile
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# Production-ready Dockerfile
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FROM node:24-slim AS builder
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WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
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RUN npm run download-models # Embed models for offline operation
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RUN npm run build
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FROM node:24-slim AS production
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WORKDIR /app
COPY package*.json ./
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RUN npm ci --only=production
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COPY --from=builder /app/dist ./dist
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COPY --from=builder /app/models ./models # Offline models included
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CMD ["node", "dist/server.js"]
```
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Deploy to: Google Cloud Run, AWS Lambda/ECS, Azure Container Instances, Cloudflare Workers, Railway, Render, Vercel, anywhere Docker runs.
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< / details >
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## 🚀 Getting Started in 30 Seconds
**The same Brainy code works everywhere - React, Vue, Angular, Node.js, Serverless, Edge Workers.**
```javascript
// This EXACT code works in ALL environments
import { BrainyData } from '@soulcraft/brainy '
const brainy = new BrainyData()
await brainy.init()
// Add nouns (entities)
const openai = await brainy.add("OpenAI", { type: "company" })
const gpt4 = await brainy.add("GPT-4", { type: "product" })
// Add verbs (relationships)
await brainy.relate(openai, gpt4, "develops")
// Vector search + Graph traversal
const similar = await brainy.search("AI companies", 5)
const products = await brainy.getVerbsBySource(openai)
```
< details >
< summary > 🔍 < strong > See Framework Examples< / strong > < / summary >
### React
```jsx
function App() {
const [brainy] = useState(() => new BrainyData())
useEffect(() => brainy.init(), [])
const search = async (query) => {
return await brainy.search(query, 10)
}
// Same API as above
}
```
### Vue 3
```vue
< script setup >
const brainy = new BrainyData()
await brainy.init()
// Same API as above
< / script >
```
### Angular
```typescript
@Component ({})
export class AppComponent {
brainy = new BrainyData()
async ngOnInit() {
await this.brainy.init()
// Same API as above
}
}
```
### Node.js / Deno / Bun
```javascript
const brainy = new BrainyData()
await brainy.init()
// Same API as above
```
< / details >
### 🌍 Framework-First, Runs Everywhere
**Brainy automatically detects your environment and optimizes everything:**
| Environment | Storage | Optimization |
|-----------------|-----------------|----------------------------|
| 🌐 Browser | OPFS | Web Workers, Memory Cache |
| 🟢 Node.js | FileSystem / S3 | Worker Threads, Clustering |
| ⚡ Serverless | S3 / Memory | Cold Start Optimization |
| 🔥 Edge Workers | Memory / KV | Minimal Footprint |
| 🦕 Deno/Bun | FileSystem / S3 | Native Performance |
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## 📚 Documentation & Resources
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- **[🚀 Quick Start Guide ](docs/getting-started/ )** - Get up and running in minutes
- **[📖 API Reference ](docs/api-reference/ )** - Complete method documentation
- **[💡 Examples ](docs/examples/ )** - Real-world usage patterns
- **[⚡ Performance Guide ](docs/optimization-guides/ )** - Scale to millions of vectors
- **[🔧 Storage Adapters ](docs/api-reference/storage-adapters.md )** - Universal storage compatibility
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## 🤝 Contributing
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We welcome contributions! Please see:
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- [Contributing Guidelines ](CONTRIBUTING.md )
- [Developer Documentation ](docs/development/DEVELOPERS.md )
- [Code of Conduct ](CODE_OF_CONDUCT.md )
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## 📄 License
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[MIT ](LICENSE )
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---
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< div align = "center" >
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< strong > Ready to build the future of search? Get started with Brainy today!< / strong >
**[Get Started → ](docs/getting-started/ ) | [View Examples → ](docs/examples/ ) | [Join Community → ](https://github.com/soulcraft-research/brainy/discussions )**
< / div >