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< div align = "center" >
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[](https://badge.fury.io/js/%40soulcraft%2Fbrainy)
[](https://opensource.org/licenses/MIT)
**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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# BRAINY: The Brain in a Jar Databaseā¢
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**The world's only Vector + Graph + AI database and realtime data platform**
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*Zero-to-Smart⢠technology that thinks so you don't have to*
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< / div >
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---
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## š THE AMAZING BRAINY: See It In Action!
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```javascript
import { BrainyData } from '@soulcraft/brainy '
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// š§Ŗ Initialize your brain-in-a-jar
const brainy = new BrainyData() // Zero config - it's ALIVE!
await brainy.init()
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// š¬ Feed it knowledge with relationships
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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")
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// ā” One query to rule them all - Vector + Graph + Faceted search!
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const results = await brainy.search("AI language models", 5, {
metadata: { funding: { $gte: 10000000 } }, // MongoDB-style filtering
includeVerbs: true // Graph relationships
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}) // Plus semantic vector search!
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```
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**š 8 lines. Three search paradigms. One brain-powered database.**
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## š« WHY BRAINY? The Problem We Solve
### ā The Old Way: Database Frankenstein
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```
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Pinecone ($$$) + Neo4j ($$$) + Elasticsearch ($$$) + Sync Hell = š±
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```
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### ā
The Brainy Way: One Smart Brain
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```
Vector Search + Graph Relations + Metadata Filtering + AI Intelligence = š§ āØ
```
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**Your data gets a brain upgrade. No assembly required.**
## ā” QUICK & EASY: From Zero to Smart in 60 Seconds
### Installation
```bash
npm install @soulcraft/brainy
```
### Your First Brainy App
```javascript
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" })
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// 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" }
})
```
## š NEW! Talk to Your Data with Brainy Chat
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```javascript
import { BrainyChat } from '@soulcraft/brainy '
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const chat = new BrainyChat(brainy) // Your data becomes conversational!
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const answer = await chat.ask("What patterns do you see in customer behavior?")
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// ā AI-powered insights from your knowledge graph!
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```
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< sub > **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< / sub >
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**One line. Zero complexity. Optional LLM for genius-level responses.**
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[š **Learn More About Brainy Chat** ](BRAINY-CHAT.md )
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## š® NEW! Brainy CLI - Command Center from the Future
### š¬ Talk to Your Data
```bash
# Have conversations with your knowledge graph
brainy chat "What patterns exist in customer behavior?"
brainy chat "Show me all connections between startups"
```
### š„ Add & Import Data
```bash
# 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
```
### š Explore & Query
```bash
# 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
```
### š Manage & Migrate
```bash
# 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
```
### š Environment & Secrets
```bash
# 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
```
### š Monitor & Optimize
```bash
# Real-time dashboard
brainy monitor --dashboard
# Performance analysis
brainy stats --detailed
brainy optimize index --auto
```
**Command your data empire from the terminal!**
[š **Full CLI Documentation** ](docs/brainy-cli.md )
## 𧬠NEW! Cortex AI - Your Data Gets a PhD
**Cortex automatically understands and enhances your data:**
```javascript
// 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)!**
## š NEW! Augmentation Pipeline - Plug in Superpowers
**8 types of augmentations to enhance your brain:**
```javascript
// 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:**
- šÆ **SENSE** - Input processing
- š§ **MEMORY** - Long-term storage
- š **COGNITION** - Deep analysis
- š **CONDUIT** - Data flow
- ā” **ACTIVATION** - Triggers & events
- šļø **PERCEPTION** - Pattern recognition
- š¬ **DIALOG** - Conversational AI
- š **WEBSOCKET** - Real-time sync
## šŖ POWERFUL FEATURES: What Makes Brainy Special
### ā” Performance That Defies Science
```
Vector Search (1M embeddings): 2-8ms latency š
Graph Traversal (100M relations): 1-3ms latency š„
Combined Vector+Graph+Filter: 5-15ms latency ā”
Throughput: 10K+ queries/sec š«
```
### š 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!
### š® The Power of Three-in-One Search
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```javascript
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// This ONE query replaces THREE databases:
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const results = await brainy.search("AI startups in healthcare", 10, {
// š Vector: Semantic similarity
includeVerbs: true,
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// š Graph: Relationship traversal
verbTypes: ["invests_in", "partners_with"],
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// š 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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### š§ Self-Learning & Auto-Optimization
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**Brainy gets smarter the more you use it:**
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- Auto-indexes frequently searched fields
- Learns query patterns for faster responses
- Optimizes storage based on access patterns
- Self-configures for your environment
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## š ADVANCED FEATURES: For Mad Scientists
### š¬ MongoDB-Style Query Operators
```javascript
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`
### š§Ŗ Specialized Deployment Modes
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```javascript
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// High-speed data ingestion
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const writer = new BrainyData({
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writeOnly: true,
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allowDirectReads: true // For deduplication
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})
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// Read-only search cluster
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const reader = new BrainyData({
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readOnly: true,
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frozen: true // Maximum performance
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})
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// Custom storage backend
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const custom = new BrainyData({
storage: {
type: 's3',
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s3Storage: {
bucketName: 'my-brain',
region: 'us-east-1'
}
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}
})
```
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### š Framework Integration Examples
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< details >
< summary > š¦ < strong > See Framework Examples< / strong > < / summary >
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#### React
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```jsx
import { BrainyData } from '@soulcraft/brainy '
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function App() {
const [brainy] = useState(() => new BrainyData())
useEffect(() => {
brainy.init()
}, [])
const search = async (query) => {
return await brainy.search(query, 10)
}
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return < SearchInterface onSearch = {search} / >
}
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```
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#### Vue 3
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```vue
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< script setup >
import { BrainyData } from '@soulcraft/brainy '
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const brainy = new BrainyData()
await brainy.init()
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const search = async (query) => {
return await brainy.search(query, 10)
}
< / script >
```
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#### Angular
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```typescript
@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)
}
}
```
< / details >
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### š³ Docker & Cloud Deployment
```dockerfile
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!
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## š Premium Features (Optional)
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**Core Brainy is FREE forever. Premium augmentations for enterprise:**
### š Enterprise Connectors (Coming Soon!)
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- **Notion** ($49/mo) - Bi-directional workspace sync
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- **Salesforce** ($99/mo) - CRM integration
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- **Slack** ($49/mo) - Team knowledge capture
- **Asana** ($44/mo) - Project intelligence
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```bash
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brainy augment trial notion # Start 14-day free trial
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```
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## šØ What You Can Build
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**The only limit is your imagination:**
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- **š¤ AI Assistants** - ChatGPT with perfect memory
- **š Semantic Search** - Find by meaning, not keywords
- **šÆ Recommendation Engines** - Netflix-level suggestions
- **𧬠Knowledge Graphs** - Wikipedia meets Neo4j
- **šļø Computer Vision** - Search images by content
- **šµ Music Discovery** - Spotify's algorithm in your app
- **š Smart Documentation** - Self-answering docs
- **š”ļø Fraud Detection** - Pattern recognition on steroids
- **š Real-time Collaboration** - Multiplayer knowledge bases
- **š„ Medical Diagnosis** - Symptom matching with AI
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## š Complete Documentation
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### Getting Started
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- [**Quick Start Guide** ](docs/getting-started/ ) - Up and running in 5 minutes
- [**Installation** ](docs/getting-started/installation.md ) - All environments covered
- [**Basic Concepts** ](docs/getting-started/concepts.md ) - Understand the brain
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### Core Features
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- [**API Reference** ](docs/api-reference/ ) - Every method documented
- [**Search Guide** ](docs/api-reference/search.md ) - Master all search types
- [**Graph Operations** ](docs/api-reference/graph.md ) - Relationships explained
- [**MongoDB Operators** ](docs/api-reference/operators.md ) - Query like a pro
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### Advanced Topics
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- [**Brainy CLI** ](docs/brainy-cli.md ) - Command-line superpowers
- [**Brainy Chat** ](BRAINY-CHAT.md ) - Conversational AI interface
- [**Cortex AI** ](CORTEX.md ) - Intelligence augmentation
- [**Augmentation Pipeline** ](docs/augmentations/ ) - Plugin architecture
- [**Performance Tuning** ](docs/optimization-guides/ ) - Speed optimization
- [**Deployment Guide** ](docs/deployment/ ) - Production best practices
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### Examples & Tutorials
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- [**Example Apps** ](docs/examples/ ) - Full applications
- [**Code Recipes** ](docs/examples/recipes.md ) - Common patterns
- [**Video Tutorials** ](docs/tutorials/ ) - Visual learning
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## š Why Not Just Use...?
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### vs. Multiple Databases
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ā **Pinecone + Neo4j + Elasticsearch** = 3x cost, sync nightmares, 3 APIs
ā
**Brainy** = One database, always synced, one simple API
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### vs. Cloud-Only Vector DBs
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ā **Pinecone/Weaviate** = Vendor lock-in, expensive, cloud-only
ā
**Brainy** = Run anywhere, own your data, pay once
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### vs. Traditional Graph DBs
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ā **Neo4j + vector plugin** = Bolt-on solution, limited capabilities
ā
**Brainy** = Native vector+graph from the ground up
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## š Real-World Performance & Scale
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**How Brainy handles production workloads:**
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### š Benchmark Numbers
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- **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)
### šÆ Scaling Strategies
**Scale Up (Vertical)**
```javascript
// 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
}
})
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```
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**Scale Out (Horizontal)**
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```javascript
// 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' })
}
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// Or use read/write separation
const writer = new BrainyData({ writeOnly: true })
const readers = [/* multiple read replicas */]
```
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### šļø Architecture That Scales
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ā
**Distributed Index** - Partition by metadata fields or ID ranges
ā
**Smart Partitioning** - Semantic clustering or hash-based sharding
ā
**Real-time Sync** - WebRTC & WebSocket for live collaboration
ā
**GPU Acceleration** - Auto-detected for embeddings when available
ā
**Metadata Index** - Separate B-tree indexes for fast filtering
ā
**Memory Mapped Files** - Handle datasets larger than RAM
ā
**Streaming Ingestion** - Process millions of items without OOM
ā
**Progressive Loading** - Start serving queries before full index load
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## šø Recent Updates
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### šÆ v0.57.0 - The Cortex Revolution
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- Renamed CLI from "neural" to "brainy"
- Cortex AI for data understanding
- Augmentation pipeline system
- Premium connectors framework
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### ā” v0.46-v0.51 - Performance Revolution
- 95% package size reduction
- MongoDB query operators
- Filter discovery API
- Transformers.js migration
- True offline operation
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## š¤ Contributing
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We welcome contributions! See [Contributing Guidelines ](CONTRIBUTING.md )
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## š License
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[MIT ](LICENSE ) - Core Brainy is FREE forever
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---
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< div align = "center" >
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## š§ Ready to Give Your Data a Brain?
**[Get Started ā ](docs/getting-started/ ) | [Examples ā ](docs/examples/ )**
*Zero-to-Smart⢠- Because your data deserves a brain upgrade*
**Built with ā¤ļø by [Soulcraft Research ](https://soulcraft.com )**
*Powered by the BXL9000⢠Cognitive Engine*
< / div >