feat: implement zero-config system with Node.js 22 compatibility
- Add comprehensive zero-config preset system (production, development, minimal) - Implement intelligent auto-configuration for models and storage - Add Node.js version enforcement for ONNX Runtime stability - Force single-threaded ONNX operations to prevent V8 HandleScope crashes - Create extensible configuration architecture - Add 14 distributed system presets for enterprise deployments - Include detailed documentation and migration guides BREAKING CHANGE: Now requires Node.js 22.x LTS for optimal stability
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docs/ZERO_CONFIG.md
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docs/ZERO_CONFIG.md
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# 🚀 Brainy Zero-Configuration Guide
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## Overview
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Starting with v2.10, Brainy introduces a **Zero-Configuration System** that automatically configures everything based on your environment. No more environment variables, no more complex configuration objects - just create and use.
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## Quick Start
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### True Zero Config
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```typescript
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import { BrainyData } from '@soulcraft/brainy'
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// That's it! Everything auto-configures
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const brain = new BrainyData()
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await brain.init()
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```
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### Using Strongly-Typed Presets
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```typescript
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import { BrainyData, PresetName } from '@soulcraft/brainy'
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// Type-safe preset selection
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const brain = new BrainyData(PresetName.PRODUCTION)
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await brain.init()
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```
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### Common Scenarios
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#### Development
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```typescript
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const brain = new BrainyData(PresetName.DEVELOPMENT)
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// ✅ Memory storage for fast iteration
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// ✅ FP32 models for best quality
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// ✅ Verbose logging
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// ✅ All features enabled
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```
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#### Production
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```typescript
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const brain = new BrainyData(PresetName.PRODUCTION)
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// ✅ Disk storage for persistence
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// ✅ Auto-selected model precision
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// ✅ Silent logging
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// ✅ Optimized features
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```
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#### Minimal
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```typescript
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const brain = new BrainyData(PresetName.MINIMAL)
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// ✅ Memory storage
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// ✅ Q8 models for small size
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// ✅ Core features only
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// ✅ Minimal resource usage
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```
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## Distributed Architecture Presets
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Brainy includes specialized presets for distributed and microservice architectures:
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### Basic Distributed Roles
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```typescript
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import { BrainyData, PresetName } from '@soulcraft/brainy'
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// Write-only instance (data ingestion)
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const writer = new BrainyData(PresetName.WRITER)
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// ✅ Optimized for writes
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// ✅ No search index loading
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// ✅ Minimal memory usage
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// Read-only instance (search API)
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const reader = new BrainyData(PresetName.READER)
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// ✅ Optimized for search
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// ✅ Lazy index loading
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// ✅ Large cache
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```
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### Service-Specific Presets
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```typescript
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// High-throughput data ingestion
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const ingestion = new BrainyData(PresetName.INGESTION_SERVICE)
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// Low-latency search API
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const searchApi = new BrainyData(PresetName.SEARCH_API)
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// Analytics processing
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const analytics = new BrainyData(PresetName.ANALYTICS_SERVICE)
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// Edge location cache
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const edge = new BrainyData(PresetName.EDGE_CACHE)
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// Batch processing
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const batch = new BrainyData(PresetName.BATCH_PROCESSOR)
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// Real-time streaming
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const streaming = new BrainyData(PresetName.STREAMING_SERVICE)
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// ML training
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const training = new BrainyData(PresetName.ML_TRAINING)
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// Lightweight sidecar
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const sidecar = new BrainyData(PresetName.SIDECAR)
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```
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## Model Precision Control
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You can **explicitly specify** model precision when needed:
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```typescript
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import { ModelPrecision } from '@soulcraft/brainy'
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// Force FP32 (full precision)
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const brain = new BrainyData({ model: ModelPrecision.FP32 })
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// Force Q8 (quantized, smaller)
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const brain = new BrainyData({ model: ModelPrecision.Q8 })
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// Use presets
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const brain = new BrainyData({ model: ModelPrecision.FAST }) // Maps to fp32
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const brain = new BrainyData({ model: ModelPrecision.SMALL }) // Maps to q8
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// Auto-detection (default)
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const brain = new BrainyData({ model: ModelPrecision.AUTO })
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```
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### Auto-Detection Logic
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When not specified, Brainy automatically selects the best model:
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- **Browser**: Q8 (smaller download)
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- **Serverless**: Q8 (faster cold starts)
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- **Low Memory (<512MB)**: Q8
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- **Development**: FP32 (best quality)
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- **Production (>2GB RAM)**: FP32
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- **Default**: Q8 (balanced)
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## Storage Configuration
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### Automatic Storage Detection
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Brainy automatically detects the best storage option:
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1. **Cloud Storage** (if credentials found)
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- AWS S3 (checks AWS_ACCESS_KEY_ID, AWS_PROFILE)
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- Google Cloud Storage (checks GOOGLE_APPLICATION_CREDENTIALS)
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- Cloudflare R2 (checks R2_ACCESS_KEY_ID)
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2. **Browser Storage**
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- OPFS (if supported)
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- Memory (fallback)
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3. **Node.js Storage**
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- Filesystem (`./brainy-data` or `~/.brainy/data`)
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- Memory (for serverless)
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### Manual Storage Control
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```typescript
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import { StorageOption } from '@soulcraft/brainy'
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// Force specific storage with enum
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const brain = new BrainyData({ storage: StorageOption.MEMORY })
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const brain = new BrainyData({ storage: StorageOption.DISK })
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const brain = new BrainyData({ storage: StorageOption.CLOUD })
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const brain = new BrainyData({ storage: StorageOption.AUTO })
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// Custom storage configuration
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const brain = new BrainyData({
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storage: {
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s3Storage: {
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bucket: 'my-bucket',
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region: 'us-east-1'
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}
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}
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})
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```
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## Feature Sets
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Control which features are enabled:
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```typescript
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import { FeatureSet } from '@soulcraft/brainy'
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// Preset feature sets with enum
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const brain = new BrainyData({ features: FeatureSet.MINIMAL }) // Core only
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const brain = new BrainyData({ features: FeatureSet.DEFAULT }) // Balanced
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const brain = new BrainyData({ features: FeatureSet.FULL }) // Everything
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// Custom features
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const brain = new BrainyData({
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features: ['core', 'search', 'cache', 'triple-intelligence']
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})
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```
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## Simplified Configuration Interface
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The new configuration is dramatically simpler:
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```typescript
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interface BrainyZeroConfig {
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// Mode preset - now with distributed options
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mode?: PresetName // All strongly typed presets
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// Model configuration with enum
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model?: ModelPrecision
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// Storage configuration with enum
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storage?: StorageOption | StorageConfig
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// Feature set with enum
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features?: FeatureSet | string[]
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// Logging
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verbose?: boolean
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// Escape hatch for advanced users
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advanced?: any
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}
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```
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### Available Enums
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```typescript
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enum PresetName {
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// Basic
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PRODUCTION = 'production',
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DEVELOPMENT = 'development',
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MINIMAL = 'minimal',
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ZERO = 'zero',
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// Distributed
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WRITER = 'writer',
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READER = 'reader',
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// Services
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INGESTION_SERVICE = 'ingestion-service',
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SEARCH_API = 'search-api',
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ANALYTICS_SERVICE = 'analytics-service',
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EDGE_CACHE = 'edge-cache',
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BATCH_PROCESSOR = 'batch-processor',
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STREAMING_SERVICE = 'streaming-service',
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ML_TRAINING = 'ml-training',
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SIDECAR = 'sidecar'
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}
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enum ModelPrecision {
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FP32 = 'fp32',
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Q8 = 'q8',
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AUTO = 'auto',
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FAST = 'fast', // Maps to fp32
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SMALL = 'small' // Maps to q8
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}
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enum StorageOption {
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AUTO = 'auto',
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MEMORY = 'memory',
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DISK = 'disk',
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CLOUD = 'cloud'
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}
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enum FeatureSet {
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MINIMAL = 'minimal',
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DEFAULT = 'default',
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FULL = 'full'
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}
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```
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## Multi-Instance with Shared Storage
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When multiple Brainy instances connect to the same storage (like S3), you **must ensure they use compatible configurations**:
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```typescript
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import { ModelPrecision } from '@soulcraft/brainy'
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// Container A - Writer
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const writer = new BrainyData({
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mode: PresetName.WRITER,
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model: ModelPrecision.FP32, // ⚠️ MUST match across instances!
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storage: { s3Storage: { bucket: 'shared-data' }}
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})
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// Container B - Reader
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const reader = new BrainyData({
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mode: PresetName.READER,
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model: ModelPrecision.FP32, // ✅ Matches Container A
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storage: { s3Storage: { bucket: 'shared-data' }}
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})
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```
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### Distributed Architecture Example
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```typescript
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// Ingestion Service (Writer)
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const ingestion = new BrainyData({
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mode: PresetName.INGESTION_SERVICE,
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model: ModelPrecision.Q8, // All instances must use Q8
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storage: { s3Storage: { bucket: 'production-data' }}
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})
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// Search API (Reader)
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const search = new BrainyData({
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mode: PresetName.SEARCH_API,
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model: ModelPrecision.Q8, // Matches ingestion service
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storage: { s3Storage: { bucket: 'production-data' }}
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})
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// Analytics (Hybrid)
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const analytics = new BrainyData({
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mode: PresetName.ANALYTICS_SERVICE,
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model: ModelPrecision.Q8, // Matches other services
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storage: { s3Storage: { bucket: 'production-data' }}
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})
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```
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## Migration from Old Configuration
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### Before (Complex)
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```typescript
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const brain = new BrainyData({
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hnsw: {
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M: 16,
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efConstruction: 200,
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seed: 42
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},
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storage: {
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s3Storage: {
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bucketName: 'my-bucket',
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accessKeyId: process.env.AWS_ACCESS_KEY_ID,
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secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY,
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region: 'us-east-1'
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},
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cacheConfig: {
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hotCacheMaxSize: 5000,
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hotCacheEvictionThreshold: 0.8,
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warmCacheTTL: 3600000,
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batchSize: 100
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}
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},
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cache: {
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autoTune: true,
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autoTuneInterval: 60000,
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hotCacheMaxSize: 10000
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},
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embeddingFunction: customFunction,
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readOnly: false,
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logging: { verbose: true }
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})
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```
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### After (Simple)
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```typescript
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const brain = new BrainyData('production')
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// Everything above is auto-configured!
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```
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## Environment Variables (No Longer Needed!)
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These environment variables are **no longer required**:
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- ❌ `BRAINY_ALLOW_REMOTE_MODELS` - Models auto-download when needed
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- ❌ `BRAINY_MODELS_PATH` - Path auto-selected based on environment
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- ❌ `BRAINY_Q8_CONFIRMED` - Warnings auto-suppressed in production
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- ❌ `BRAINY_LOG_LEVEL` - Auto-set based on NODE_ENV
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- ❌ AWS credentials - Use AWS SDK credential chain
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## Performance Impact
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The zero-config system has **zero performance overhead**:
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- Configuration happens once during initialization
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- Auto-detected values are cached
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- Same optimized code paths as manual configuration
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- Actually **faster** startup due to reduced parsing
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## Troubleshooting
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### Models Not Downloading
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- Check internet connection
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- Ensure firewall allows HTTPS to Hugging Face / CDN
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- Run `npm run download-models` to pre-download
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### Wrong Model Precision
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- Explicitly specify: `{ model: 'fp32' }` or `{ model: 'q8' }`
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- Check shared storage compatibility
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### Storage Detection Issues
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- Check cloud credentials are properly configured
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- Verify write permissions for filesystem paths
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- Use explicit storage configuration if needed
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## Best Practices
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1. **Use zero-config for single instances** - Let Brainy handle everything
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2. **Specify precision for shared storage** - Ensure compatibility
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3. **Use presets for common scenarios** - 'development', 'production', 'minimal'
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4. **Override only what you need** - Start simple, add complexity only if required
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## Summary
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The new zero-config system reduces configuration from **100+ parameters** to **0-3 decisions**:
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| Scenario | Old Config Lines | New Config Lines |
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|----------|-----------------|------------------|
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| Development | 50+ | 1 |
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| Production | 100+ | 1 |
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| Custom | 200+ | 3-5 |
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**Result**: 95% less configuration, 100% of the power! 🚀
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