diff --git a/.gitignore b/.gitignore index 357cd5dd..87393aa3 100644 --- a/.gitignore +++ b/.gitignore @@ -60,3 +60,7 @@ models/CLAUDE.md # Development planning files (not for commit) PLAN.md + +# Backup folders +backup-* +backup/ diff --git a/BRAIN_PATTERNS_OPTIMIZATION.md b/BRAIN_PATTERNS_OPTIMIZATION.md deleted file mode 100644 index 299a4b29..00000000 --- a/BRAIN_PATTERNS_OPTIMIZATION.md +++ /dev/null @@ -1,62 +0,0 @@ -# Brain Patterns Optimization Plan - -## Brain Pattern Operators (Complete List) -1. **Equality**: `equals`, `is`, `eq` -2. **Comparison**: `greaterThan`/`gt`, `lessThan`/`lt`, `greaterEqual`/`gte`, `lessEqual`/`lte` -3. **Range**: `between` (inclusive range) -4. **Membership**: `oneOf`/`in` (value in list) -5. **Contains**: `contains` (for arrays) -6. **Existence**: `exists` (field exists) -7. **Negation**: `not` (logical NOT) -8. **Logical**: `allOf` (AND), `anyOf` (OR) - -## Current Architecture Issues -- MetadataIndex: O(1) hash lookups ONLY -- No sorted indices for ranges -- TripleIntelligence: String-based filtering (">2020") - TERRIBLE -- No numeric type detection - -## Optimization Strategy - -### Phase 1: Sorted Index Infrastructure โœ… DONE -```typescript -interface SortedFieldIndex { - values: Array<[value: any, ids: Set]> - isDirty: boolean - fieldType: 'number' | 'string' | 'date' | 'mixed' -} -``` - -### Phase 2: Binary Search Implementation โœ… DONE -- O(log n) range boundary finding -- Support inclusive/exclusive ranges -- Handle all comparison operators - -### Phase 3: Automatic Type Detection -- Detect numeric fields on first value -- Maintain appropriate sorting -- Convert strings to numbers when possible - -### Phase 4: Query Optimization -- Pre-filter with metadata index BEFORE vector search -- Use sorted indices for ALL range queries -- Cache sorted indices in memory - -## Performance Targets -- Exact match: O(1) - hash lookup -- Range query: O(log n + m) - binary search + result size -- Combined filters: O(k * log n) - k conditions -- Memory overhead: ~2x current (hash + sorted) - -## Implementation Status -- [x] Add SortedFieldIndex type -- [x] Add binary search methods -- [x] Update getIdsForFilter for all operators -- [ ] Fix TripleIntelligence to use index directly -- [ ] Add index statistics/monitoring -- [ ] Optimize memory usage - -## Expected Performance Gains -- Range queries: 100-1000x faster -- Combined vector+metadata: 10-50x faster -- Memory usage: +50% (acceptable tradeoff) \ No newline at end of file diff --git a/COMPREHENSIVE_TESTING_STRATEGY.md b/COMPREHENSIVE_TESTING_STRATEGY.md deleted file mode 100644 index f4c6079a..00000000 --- a/COMPREHENSIVE_TESTING_STRATEGY.md +++ /dev/null @@ -1,227 +0,0 @@ -# ๐Ÿง  COMPREHENSIVE TESTING STRATEGY - ALL FEATURES - -**Brainy 2.0 Complete Feature & API Validation Plan** - -## ๐ŸŽฏ **COMPLETE PUBLIC API TESTING** - -### **๐Ÿ“‹ Core Public API Methods (From docs/api/README.md):** - -#### **Data Operations:** -- [ ] `addNoun(dataOrVector, metadata?)` - Text auto-embedding + vector input -- [ ] `getNoun(id)` - Retrieve single noun -- [ ] `updateNoun(id, dataOrVector?, metadata?)` - Update noun data/metadata -- [ ] `deleteNoun(id)` - Remove noun -- [ ] `addVerb(fromId, toId, type, metadata?)` - Create relationships -- [ ] `getVerb(id)` - Retrieve relationship -- [ ] `deleteVerb(id)` - Remove relationship - -#### **Search & Query Operations:** -- [ ] `search(query, options?)` - Vector similarity search -- [ ] `find({ like?, where?, connected? })` - **NEW Triple Intelligence** -- [ ] `findSimilar(id, options?)` - Find similar nouns -- [ ] `searchText(query, options?)` - Text-based search -- [ ] `searchWithCursor(query, cursor?)` - Paginated search - -#### **Batch Operations:** -- [ ] `addBatch(items)` - Bulk add operations -- [ ] `addBatchToBoth(nouns, verbs)` - Add nouns + verbs together - -#### **Graph Operations:** -- [ ] `relate(fromId, toId, verb, metadata?)` - Create relationship -- [ ] `getConnections(id, options?)` - Get related items -- [ ] `getConnected(id, verb?)` - Get connected nouns - -#### **Management Operations:** -- [ ] `clear()` - Clear all data -- [ ] `size()` - Get total count -- [ ] `getStatistics()` - Get detailed stats -- [ ] `backup()` / `restore()` - Data persistence -- [ ] `init()` / `shutdown()` - Lifecycle - -## ๐Ÿš€ **ADVANCED FEATURES TESTING** - -### **๐Ÿ”ง Operational Modes:** -- [ ] **Write-Only Mode** - `setWriteOnly(true)` - write-only-direct-reads.test.ts โœ… -- [ ] **Read-Only Mode** - `setReadOnly(true)` -- [ ] **Frozen Mode** - `isFrozen()` state -- [ ] **Memory-Only Mode** - No persistence -- [ ] **Persistent Mode** - File/S3/OPFS storage - -### **โšก Performance Optimizations:** -- [ ] **Throttling** - S3 rate limiting - throttling-metrics.test.ts โœ… -- [ ] **Batch Processing** - Bulk operations - augmentations-batch-processing.test.ts โœ… -- [ ] **Caching** - Search result caching -- [ ] **Connection Pooling** - Multi-connection management -- [ ] **Request Deduplication** - augmentations-request-deduplicator.test.ts โœ… -- [ ] **Write-Ahead Logging** - augmentations-wal.test.ts โœ… - -### **๐ŸŒ Distributed Systems:** -- [ ] **Distributed Mode** - distributed.test.ts โœ… -- [ ] **Distributed Caching** - distributed-caching.test.ts โœ… -- [ ] **Node Discovery** - Multi-node coordination -- [ ] **Data Sharding** - Partition management -- [ ] **Consistency Models** - CAP theorem handling - -### **๐Ÿ”’ Data Integrity & Hashing:** -- [ ] **Entity Registry** - UUID mapping - augmentations-entity-registry.test.ts โœ… -- [ ] **Metadata Hashing** - Content deduplication -- [ ] **Vector Normalization** - Dimension standardization -- [ ] **Checksum Validation** - Data integrity verification -- [ ] **Version Management** - Data versioning - -### **๐Ÿงฌ Clustering Algorithms:** -- [ ] **HNSW Clustering** - Hierarchical Navigable Small World -- [ ] **K-Means Clustering** - Centroid-based grouping -- [ ] **Hierarchical Clustering** - Tree-based grouping -- [ ] **Neural Clustering** - neural-clustering.test.ts โœ… - -### **๐Ÿง  Intelligence Features:** -- [ ] **220 NLP Patterns** - nlp-patterns-comprehensive.test.ts โœ… -- [ ] **Neural Import** - AI-powered data understanding - neural-import.test.ts โœ… -- [ ] **Intelligent Verb Scoring** - intelligent-verb-scoring.test.ts โœ… -- [ ] **Triple Intelligence** - find-comprehensive.test.ts โœ… -- [ ] **Neural API** - neural-api.test.ts โœ… - -## ๐Ÿ› ๏ธ **MEMORY-EFFICIENT TESTING STRATEGIES** - -### **๐Ÿ“Š Industry Standard Approaches:** - -#### **1. Test Categorization:** -```typescript -// Unit Tests - Fast, isolated -describe('Unit Tests', () => { - // Mock dependencies, test logic only - // Memory: <50MB, Time: <5s -}) - -// Integration Tests - Medium, real components -describe('Integration Tests', () => { - // Real augmentations, mocked storage - // Memory: <200MB, Time: <30s -}) - -// E2E Tests - Slow, full system -describe('E2E Tests', () => { - // Full system, real storage - // Memory: <1GB, Time: <5min -}) -``` - -#### **2. Memory Management:** -```typescript -// Resource cleanup patterns -afterEach(async () => { - await brain?.cleanup() - brain = null - if (global.gc) global.gc() // Force cleanup -}) - -// Limited dataset sizes -const createTestData = (size = 10) => { // Not 10,000! - return Array.from({ length: size }, createSmallVector) -} -``` - -#### **3. Mock Strategies:** -```typescript -// Mock heavy operations -vi.mock('./utils/embedding.js', () => ({ - createEmbeddingFunction: () => vi.fn().mockResolvedValue(mockVector) -})) - -// Mock storage for performance tests -const mockStorage = { - read: vi.fn().mockResolvedValue(testData), - write: vi.fn().mockResolvedValue(true) -} -``` - -#### **4. Parallel Test Execution:** -```typescript -// vitest.config.ts -export default { - test: { - pool: 'forks', // Isolate tests - poolOptions: { - forks: { - singleFork: true // Prevent memory accumulation - } - }, - testTimeout: 30000, // 30s max per test - hookTimeout: 10000 // 10s max for setup/cleanup - } -} -``` - -### **๐Ÿš€ Fast & Reliable Testing Patterns:** - -#### **Memory-Efficient Patterns:** -```typescript -// 1. Small datasets -const SMALL_VECTOR_SIZE = 10 // Not 384 for unit tests -const TEST_DATA_SIZE = 5 // Not 1000s of items - -// 2. Deterministic mocks -const mockEmbedding = [0.1, 0.2, 0.3, 0.4, 0.5] // Predictable - -// 3. Scoped tests -describe('Search Functionality', () => { - const brain = new BrainyData({ - storage: 'memory', // No disk I/O - dimensions: 5, // Tiny vectors - maxConnections: 4 // Minimal graph - }) -}) -``` - -#### **Performance Test Patterns:** -```typescript -// Measure operations, not full datasets -it('should handle batch operations efficiently', async () => { - const start = performance.now() - - // Test with 10 items, not 10,000 - await brain.addBatch(createTestBatch(10)) - - const duration = performance.now() - start - expect(duration).toBeLessThan(1000) // 1s max -}) -``` - -## ๐Ÿ“‹ **IMPLEMENTATION PLAN** - -### **Phase 1: Fix TypeScript โ†’ Build Success** -- Complete remaining 101 TypeScript errors -- Achieve clean build - -### **Phase 2: Core API Validation (Fast)** -- Test all public methods with small datasets -- Validate method signatures -- Test error handling - -### **Phase 3: Advanced Features (Medium)** -- Test operational modes (write-only, read-only) -- Test performance optimizations -- Test distributed features - -### **Phase 4: Full Integration (Comprehensive)** -- All 49 tests passing -- Memory-efficient execution -- Performance benchmarks - -## โœ… **SUCCESS METRICS** - -### **Speed Goals:** -- **Unit tests**: <5 minutes total -- **Integration tests**: <15 minutes total -- **Full suite**: <30 minutes total -- **Memory usage**: <2GB peak - -### **Coverage Goals:** -- **100% public API methods** tested -- **100% operational modes** tested -- **100% augmentations** tested -- **100% clustering algorithms** tested -- **All performance optimizations** validated - -This gives us **comprehensive testing** of ALL Brainy features while maintaining **fast, reliable execution** using industry-standard patterns! \ No newline at end of file diff --git a/COORDINATED_INDEX_OPTIMIZATION.md b/COORDINATED_INDEX_OPTIMIZATION.md deleted file mode 100644 index e18d39a3..00000000 --- a/COORDINATED_INDEX_OPTIMIZATION.md +++ /dev/null @@ -1,212 +0,0 @@ -# Coordinated Index Optimization Strategy - -## The Problem -Two independent index systems competing for resources: -- **HNSW Index**: Wants to cache hot vectors in RAM -- **MetadataIndex**: Wants to cache hot field values in RAM -- **Conflict**: Both trying to use same memory/disk without coordination! - -## The Solution: Unified Resource Manager - -### 1. Shared Resource Pool -```typescript -class UnifiedIndexManager { - private totalMemoryBudget: number = 2 * 1024 * 1024 * 1024 // 2GB total - private hnswMemoryUsage: number = 0 - private metadataMemoryUsage: number = 0 - - // Intelligent allocation based on usage patterns - allocateMemory(requester: 'hnsw' | 'metadata', size: number): boolean { - const available = this.totalMemoryBudget - this.hnswMemoryUsage - this.metadataMemoryUsage - - if (size <= available) { - if (requester === 'hnsw') { - this.hnswMemoryUsage += size - } else { - this.metadataMemoryUsage += size - } - return true - } - - // Try to steal from other index if one is underutilized - return this.rebalance(requester, size) - } - - private rebalance(requester: string, needed: number): boolean { - // If HNSW is using 80% and metadata only 20%, rebalance - const hnswRatio = this.hnswMemoryUsage / this.totalMemoryBudget - const metadataRatio = this.metadataMemoryUsage / this.totalMemoryBudget - - // Intelligent rebalancing logic - // ... - } -} -``` - -### 2. Coordinated LRU Eviction -```typescript -class CoordinatedLRUCache { - private hnswLRU: LRUCache - private metadataLRU: LRUCache - private accessPatterns: AccessTracker - - // When memory pressure, evict from the index with lowest utility - async evict(bytesNeeded: number): Promise { - const hnswUtility = this.calculateUtility(this.hnswLRU) - const metadataUtility = this.calculateUtility(this.metadataLRU) - - if (hnswUtility < metadataUtility) { - // HNSW items are less frequently accessed - await this.hnswLRU.evict(bytesNeeded) - } else { - // Metadata items are less frequently accessed - await this.metadataLRU.evict(bytesNeeded) - } - } - - private calculateUtility(cache: LRUCache): number { - // Factors: - // - Access frequency - // - Recency - // - Cost to rebuild (HNSW is expensive, metadata is cheap) - // - Current query patterns - } -} -``` - -### 3. Query-Aware Optimization -```typescript -class QueryOptimizer { - private queryHistory: QueryPattern[] = [] - - optimizeForQuery(query: TripleQuery) { - // Analyze query type - const usesVector = !!(query.like || query.similar) - const usesMetadata = !!query.where - - // Pre-warm appropriate caches - if (usesVector && usesMetadata) { - // Hybrid query - balance resources 50/50 - this.resourceManager.setRatio(0.5, 0.5) - } else if (usesVector) { - // Vector-heavy - give HNSW more memory - this.resourceManager.setRatio(0.8, 0.2) - } else { - // Metadata-heavy - give MetadataIndex more memory - this.resourceManager.setRatio(0.2, 0.8) - } - } -} -``` - -### 4. Unified Persistence Strategy -```typescript -class UnifiedPersistence { - private writeBuffer: WriteBuffer - private flushScheduler: FlushScheduler - - async flush() { - // Coordinate flushes to avoid disk contention - const tasks = [] - - // Flush metadata first (smaller, faster) - if (this.metadataIndex.isDirty) { - tasks.push(this.flushMetadata()) - } - - // Then flush HNSW (larger, slower) - if (this.hnswIndex.isDirty) { - tasks.push(this.flushHNSW()) - } - - // Sequential to avoid disk thrashing - for (const task of tasks) { - await task - } - } - - private async flushMetadata() { - // Flush sorted indices - await this.storage.save('metadata_sorted', this.metadataIndex.sortedIndices) - // Flush hash indices - await this.storage.save('metadata_hash', this.metadataIndex.hashIndices) - } -} -``` - -## Implementation Plan - -### Phase 1: Shared Memory Manager (Quick Win) -```typescript -// In BrainyData constructor -this.resourceManager = new UnifiedResourceManager({ - totalMemory: config.maxMemory || 2 * GB, - hnswRatio: 0.6, // 60% for vectors by default - metadataRatio: 0.4 // 40% for metadata by default -}) - -// Pass to both indices -this.hnswIndex = new HNSWIndexOptimized({ - resourceManager: this.resourceManager -}) - -this.metadataIndex = new MetadataIndexOptimized({ - resourceManager: this.resourceManager -}) -``` - -### Phase 2: Coordinated Eviction -- Single LRU that tracks both index types -- Utility-based eviction (not just recency) -- Consider rebuild cost in eviction decisions - -### Phase 3: Query-Driven Optimization -- Track query patterns -- Dynamically adjust memory allocation -- Pre-warm caches based on query type - -## Benefits of Coordination - -1. **No Resource Conflicts**: Indices cooperate instead of compete -2. **Better Memory Usage**: Allocate based on actual query patterns -3. **Smarter Eviction**: Keep data that's actually needed -4. **Unified Monitoring**: Single place to track all index performance -5. **Auto-Optimization**: System learns and adapts to usage - -## Configuration Example -```typescript -const brain = new BrainyData({ - indexOptimization: { - mode: 'coordinated', // vs 'independent' - totalMemory: 4 * GB, // Total for ALL indices - autoBalance: true, // Dynamic rebalancing - persistenceInterval: 60000, // Coordinated flush every minute - monitoring: { - trackQueryPatterns: true, - optimizeForPatterns: true, - rebalanceInterval: 300000 // Every 5 minutes - } - } -}) -``` - -## Monitoring & Metrics -```typescript -const stats = brain.getIndexStats() -// { -// hnsw: { -// memoryUsed: 1.2 * GB, -// cacheHitRate: 0.89, -// avgQueryTime: 12ms -// }, -// metadata: { -// memoryUsed: 0.8 * GB, -// cacheHitRate: 0.95, -// avgQueryTime: 2ms -// }, -// coordination: { -// rebalances: 5, -// memoryUtilization: 0.95, -// queryPatternDetected: 'hybrid-heavy' -// } -// } \ No newline at end of file diff --git a/MEMORY_FIX_OPTIONS.md b/MEMORY_FIX_OPTIONS.md deleted file mode 100644 index 7935c4ee..00000000 --- a/MEMORY_FIX_OPTIONS.md +++ /dev/null @@ -1,104 +0,0 @@ -# Transformer Model Memory Issue - Solutions - -## The Problem -ONNX runtime allocates 4GB for a 30MB model during inference. This is a known issue with transformers.js. - -## Solution 1: Use Smaller Quantized Model (RECOMMENDED) -```javascript -// Current: all-MiniLM-L6-v2 with q8 quantization -// Switch to: all-MiniLM-L6-v2 with q4 quantization (50% smaller) -// Or use: paraphrase-MiniLM-L3-v2 (even smaller, still good quality) - -const embeddingFunction = createEmbeddingFunction({ - modelName: 'Xenova/paraphrase-MiniLM-L3-v2', - dtype: 'q4' // 4-bit quantization instead of 8-bit -}) -``` - -## Solution 2: Increase Node Memory Limit -```bash -# Run with 8GB heap limit -node --max-old-space-size=8192 test-range-queries.js - -# Or set in package.json test script: -"test": "NODE_OPTIONS='--max-old-space-size=8192' vitest" -``` - -## Solution 3: Use Remote Embeddings (For Testing) -```javascript -// Mock embedding function for tests -const mockEmbeddingFunction = async (text) => { - // Generate deterministic fake embedding from text hash - const hash = text.split('').reduce((a, b) => a + b.charCodeAt(0), 0) - return new Array(384).fill(0).map((_, i) => Math.sin(hash + i) * 0.1) -} -``` - -## Solution 4: Model Pooling & Unloading -```javascript -class ModelPool { - private model: any = null - private lastUsed: number = 0 - private readonly UNLOAD_AFTER_MS = 30000 // 30 seconds - - async getModel() { - if (!this.model) { - this.model = await loadModel() - } - this.lastUsed = Date.now() - this.scheduleUnload() - return this.model - } - - private scheduleUnload() { - setTimeout(() => { - if (Date.now() - this.lastUsed > this.UNLOAD_AFTER_MS) { - this.model?.dispose?.() - this.model = null - } - }, this.UNLOAD_AFTER_MS) - } -} -``` - -## Solution 5: Use Native Bindings (Future) -Replace transformers.js with native bindings: -- onnxruntime-node (more efficient memory) -- @tensorflow/tfjs-node (better memory management) -- Custom Rust/C++ binding - -## Recommendation for Brainy 2.0 - -### For Production: -1. Use q4 quantization (reduces memory 50%) -2. Implement model pooling/unloading -3. Document memory requirements (4GB recommended) - -### For Testing: -1. Increase Node heap to 8GB for test suite -2. Use mock embeddings for unit tests -3. Real embeddings only for integration tests - -### Long-term: -1. Investigate native bindings -2. Support multiple embedding backends -3. Cloud embedding API option - -## Memory Requirements - -| Configuration | Memory Needed | Use Case | -|--------------|--------------|----------| -| Mock embeddings | 200 MB | Unit tests | -| Q4 quantization | 2 GB | Development | -| Q8 quantization | 4 GB | Production (current) | -| Native bindings | 500 MB | Future optimization | - -## The Real Issue - -This is NOT a Brainy problem - it's a transformers.js/ONNX issue that affects ALL JavaScript ML applications. Even Google's similar libraries have this problem. - -The good news: -- Only affects initial model load -- Singleton pattern prevents multiple copies -- Memory is released after inference -- Production servers typically have 8-16GB RAM \ No newline at end of file diff --git a/ONNX-OPTIMIZATION-PLAN.md b/ONNX-OPTIMIZATION-PLAN.md deleted file mode 100644 index 063ff41b..00000000 --- a/ONNX-OPTIMIZATION-PLAN.md +++ /dev/null @@ -1,216 +0,0 @@ -# ๐Ÿง  Zero-Config ONNX Memory Optimization Plan - -## Philosophy -Brainy should **automatically detect and optimize** memory usage without any user configuration. - -## Implementation Strategy - -### 1. **Automatic Environment Variable Setting** โœ… DONE -Already implemented in `src/utils/embedding.ts`: -```javascript -// Automatically set on module load - zero config! -if (typeof process !== 'undefined' && process.env) { - process.env.ORT_DISABLE_MEMORY_ARENA = '1' - process.env.ORT_DISABLE_MEMORY_PATTERN = '1' - process.env.ORT_INTRA_OP_NUM_THREADS = '2' - process.env.ORT_INTER_OP_NUM_THREADS = '2' -} -``` - -### 2. **Automatic Quantization Selection** โœ… DONE -Changed default from `fp32` to `q8`: -```javascript -dtype: options.dtype || 'q8' // 75% memory reduction, <1% quality loss -``` - -### 3. **Dynamic Memory Detection** ๐Ÿšง TODO -```javascript -class TransformerEmbedding { - constructor(options) { - // Auto-detect available memory - const availableMemory = this.getAvailableMemory() - - // Auto-select best configuration - if (availableMemory < 2048) { // Less than 2GB - this.options.dtype = 'q4' // Maximum compression - this.options.batchSize = 5 // Small batches - } else if (availableMemory < 4096) { // 2-4GB - this.options.dtype = 'q8' // Good balance - this.options.batchSize = 10 - } else { // 4GB+ - this.options.dtype = 'fp16' // Better quality - this.options.batchSize = 20 - } - } - - private getAvailableMemory(): number { - if (typeof process !== 'undefined') { - const os = require('os') - return os.freemem() / (1024 * 1024) // MB - } - // Browser: estimate from performance.memory - if (typeof performance !== 'undefined' && performance.memory) { - return (performance.memory.jsHeapSizeLimit - performance.memory.usedJSHeapSize) / (1024 * 1024) - } - return 2048 // Safe default: 2GB - } -} -``` - -### 4. **Automatic Model Unloading** ๐Ÿšง TODO -```javascript -class TransformerEmbedding { - private lastUsed = Date.now() - private unloadTimer?: NodeJS.Timeout - - async embed(text: string[]): Promise { - this.lastUsed = Date.now() - - // Cancel any pending unload - if (this.unloadTimer) { - clearTimeout(this.unloadTimer) - } - - // Ensure model is loaded - if (!this.extractor) { - await this.loadModel() - } - - const result = await this.doEmbed(text) - - // Schedule unload after 5 minutes of inactivity - this.unloadTimer = setTimeout(() => { - this.unloadModel() - }, 5 * 60 * 1000) - - return result - } - - private unloadModel() { - if (this.extractor) { - this.extractor.dispose() - this.extractor = null - console.log('๐Ÿงน Model unloaded to free memory') - } - } -} -``` - -### 5. **Automatic Batch Size Adjustment** ๐Ÿšง TODO -```javascript -class TransformerEmbedding { - private optimalBatchSize = 10 - - async embed(texts: string[]): Promise { - const results = [] - - for (let i = 0; i < texts.length; i += this.optimalBatchSize) { - const batch = texts.slice(i, i + this.optimalBatchSize) - - try { - const embeddings = await this.embedBatch(batch) - results.push(...embeddings) - } catch (error) { - if (error.message.includes('memory')) { - // Reduce batch size on memory error - this.optimalBatchSize = Math.max(1, Math.floor(this.optimalBatchSize / 2)) - console.log(`๐Ÿ“‰ Reduced batch size to ${this.optimalBatchSize} due to memory pressure`) - - // Retry with smaller batch - i -= this.optimalBatchSize // Retry this batch - continue - } - throw error - } - } - - // Gradually increase batch size if successful - if (this.optimalBatchSize < 20) { - this.optimalBatchSize++ - } - - return results - } -} -``` - -### 6. **Pre-computed Common Embeddings** ๐Ÿšง TODO -Build into `embeddedPatterns.ts`: -```javascript -// Pre-compute embeddings for common terms -const COMMON_EMBEDDINGS = { - 'javascript': [0.123, 0.456, ...], - 'python': [0.234, 0.567, ...], - 'database': [0.345, 0.678, ...], - // ... top 1000 common terms -} - -async embed(text: string): Promise { - // Check cache first - INSTANT, zero memory! - const lower = text.toLowerCase() - if (COMMON_EMBEDDINGS[lower]) { - return COMMON_EMBEDDINGS[lower] - } - - // Only compute if not cached - return this.computeEmbedding(text) -} -``` - -## Testing Plan - -### Phase 1: Current Optimizations (TODAY) -- [x] Environment variables auto-set -- [x] Default to q8 quantization -- [x] Session options configured -- [ ] Test with real search - -### Phase 2: Dynamic Adaptation (NEXT) -- [ ] Memory detection -- [ ] Auto dtype selection -- [ ] Batch size adjustment -- [ ] Model unloading - -### Phase 3: Performance (FUTURE) -- [ ] Pre-computed embeddings -- [ ] Lazy loading -- [ ] WebAssembly fallback - -## User Experience - -### Before (Manual Configuration) -```javascript -// User had to know about ONNX issues -process.env.ORT_DISABLE_MEMORY_ARENA = '1' -const brain = new BrainyData({ - embeddingOptions: { - dtype: 'q8', - batchSize: 10 - } -}) -``` - -### After (Zero Config) -```javascript -// Just works! -const brain = new BrainyData() -await brain.search('anything') // Automatically optimized -``` - -## Benefits -1. **Zero Configuration** - Works out of the box -2. **Adaptive** - Adjusts to available resources -3. **Resilient** - Recovers from memory errors -4. **Efficient** - Uses minimum required memory -5. **Smart** - Caches common queries - -## Current Status -- โœ… Basic optimizations in place -- ๐Ÿšง Need to test if they work -- ๐Ÿ“ Plan documented for full implementation - -## Next Steps -1. Test current optimizations with real search -2. Implement memory detection -3. Add batch size adjustment -4. Build pre-computed embeddings \ No newline at end of file diff --git a/PRODUCTION-DEPLOYMENT.md b/PRODUCTION-DEPLOYMENT.md deleted file mode 100644 index b3769a2d..00000000 --- a/PRODUCTION-DEPLOYMENT.md +++ /dev/null @@ -1,391 +0,0 @@ -# ๐Ÿš€ Brainy Production Deployment Guide - -## Memory Requirements (Critical) - -**Brainy requires 8-16GB RAM in production** due to ONNX Runtime + transformer models. - -This is NOT a bug - it's the cost of running state-of-the-art AI locally: -- Same as any production ML system (TensorFlow, PyTorch) -- Same as ChatGPT embeddings (but yours runs locally!) -- Same as GitHub Copilot inference servers - -## ๐Ÿ—๏ธ Architecture Overview - -``` -Brainy 2.0 Production Stack -โ”œโ”€โ”€ Universal Memory Manager โœ… -โ”‚ โ”œโ”€โ”€ Worker-based isolation (Node.js) -โ”‚ โ”œโ”€โ”€ Aggressive cleanup (Serverless) -โ”‚ โ”œโ”€โ”€ Browser optimization (Web) -โ”‚ โ””โ”€โ”€ Automatic restarts (prevents leaks) -โ”œโ”€โ”€ Triple Backup Model Loading โœ… -โ”‚ โ”œโ”€โ”€ Local cache (fastest) -โ”‚ โ”œโ”€โ”€ GitHub releases (reliable) -โ”‚ โ”œโ”€โ”€ Soulcraft CDN (future) -โ”‚ โ””โ”€โ”€ HuggingFace (fallback) -โ”œโ”€โ”€ Brain Patterns (Query Engine) โœ… -โ”‚ โ”œโ”€โ”€ O(1) field lookups -โ”‚ โ”œโ”€โ”€ O(log n) range queries -โ”‚ โ”œโ”€โ”€ Vector search -โ”‚ โ””โ”€โ”€ Triple Intelligence -โ””โ”€โ”€ 11 Production Augmentations โœ… - โ”œโ”€โ”€ WAL (durability) - โ”œโ”€โ”€ Batch processing - โ”œโ”€โ”€ Request deduplication - โ”œโ”€โ”€ Connection pooling - โ””โ”€โ”€ 7 more enterprise features -``` - -## ๐ŸŒ Deployment Options - -### Option 1: High-Memory VPS (Recommended) -```yaml -# Deploy on servers with 16GB+ RAM -Providers: DigitalOcean, Linode, AWS EC2 -Instance: 16GB RAM minimum -Cost: $50-100/month -Benefits: Full control, all features -``` - -### Option 2: Cloud Functions (Serverless) -```yaml -AWS Lambda: 10GB max memory -Google Cloud Functions: 32GB max memory -Vercel: 3GB max (may struggle) -Benefits: Auto-scaling, pay-per-use -``` - -### Option 3: Container Orchestration -```yaml -Docker: --memory=16g -Kubernetes: memory: "16Gi" -Benefits: Easy scaling, restarts -``` - -### Option 4: Dedicated AI Servers -```yaml -Separate embedding server: 32GB+ RAM -API communication -Benefits: Best performance, cost optimization -``` - -## ๐Ÿ“ฆ Docker Deployment - -### Dockerfile -```dockerfile -FROM node:18 - -# Set memory limits -ENV NODE_OPTIONS="--max-old-space-size=16384" - -WORKDIR /app -COPY . . - -# Install dependencies and build -RUN npm ci && npm run build - -# Health check for memory management -HEALTHCHECK --interval=30s --timeout=30s --start-period=60s \ - CMD node -e "console.log('Memory:', process.memoryUsage().heapUsed/1024/1024, 'MB')" - -EXPOSE 3000 -CMD ["node", "dist/server.js"] -``` - -### Docker Compose -```yaml -version: '3.8' -services: - brainy-app: - build: . - ports: - - "3000:3000" - environment: - - NODE_OPTIONS=--max-old-space-size=16384 - - BRAINY_MODELS_PATH=/app/models - deploy: - resources: - limits: - memory: 16G - reservations: - memory: 8G - volumes: - - ./models:/app/models - restart: unless-stopped - healthcheck: - test: ["CMD", "curl", "-f", "http://localhost:3000/health"] - interval: 30s - timeout: 10s - retries: 3 -``` - -## โ˜๏ธ Kubernetes Deployment - -```yaml -apiVersion: apps/v1 -kind: Deployment -metadata: - name: brainy-deployment -spec: - replicas: 3 - selector: - matchLabels: - app: brainy - template: - metadata: - labels: - app: brainy - spec: - containers: - - name: brainy - image: your-registry/brainy:latest - env: - - name: NODE_OPTIONS - value: "--max-old-space-size=16384" - - name: BRAINY_MODELS_PATH - value: "/app/models" - resources: - requests: - memory: "8Gi" - cpu: "2000m" - limits: - memory: "16Gi" - cpu: "4000m" - ports: - - containerPort: 3000 - volumeMounts: - - name: models - mountPath: /app/models - volumes: - - name: models - persistentVolumeClaim: - claimName: brainy-models ---- -apiVersion: v1 -kind: Service -metadata: - name: brainy-service -spec: - selector: - app: brainy - ports: - - port: 80 - targetPort: 3000 - type: LoadBalancer -``` - -## ๐Ÿ”ง Environment Configuration - -### Essential Environment Variables -```bash -# Memory Management -NODE_OPTIONS="--max-old-space-size=16384" # 16GB heap -BRAINY_MODELS_PATH="/app/models" # Model location -BRAINY_ALLOW_REMOTE_MODELS="false" # Use local only - -# Production Optimization -NODE_ENV="production" -BRAINY_VERBOSE="false" # Reduce logging -BRAINY_CACHE_SIZE="10000" # Larger cache -``` - -### Optional Configuration -```bash -# Memory Manager Tuning -BRAINY_MAX_EMBEDDINGS_NODE="100" # Worker restart threshold -BRAINY_MAX_EMBEDDINGS_SERVERLESS="50" # Serverless threshold -BRAINY_MAX_EMBEDDINGS_BROWSER="25" # Browser threshold - -# Storage Configuration -BRAINY_STORAGE_TYPE="filesystem" # or 's3', 'memory' -BRAINY_STORAGE_PATH="/data" # Data directory -``` - -## ๐Ÿ”„ Process Management - -### PM2 Configuration (Recommended) -```javascript -// ecosystem.config.js -module.exports = { - apps: [{ - name: 'brainy-app', - script: 'dist/server.js', - instances: 2, - exec_mode: 'cluster', - env: { - NODE_OPTIONS: '--max-old-space-size=16384', - NODE_ENV: 'production' - }, - max_memory_restart: '14G', // Restart at 14GB to prevent OOM - time: true, - log_date_format: 'YYYY-MM-DD HH:mm:ss Z', - error_file: './logs/err.log', - out_file: './logs/out.log', - log_file: './logs/combined.log' - }] -} -``` - -### Systemd Service -```ini -[Unit] -Description=Brainy AI Service -After=network.target - -[Service] -Type=simple -User=brainy -WorkingDirectory=/opt/brainy -Environment=NODE_ENV=production -Environment=NODE_OPTIONS=--max-old-space-size=16384 -ExecStart=/usr/bin/node dist/server.js -Restart=on-failure -RestartSec=10 -StandardOutput=journal -StandardError=journal - -[Install] -WantedBy=multi-user.target -``` - -## ๐Ÿ“Š Monitoring & Health Checks - -### Memory Monitoring -```javascript -// health-check.js -import { getEmbeddingMemoryStats } from './dist/embeddings/universal-memory-manager.js' - -export function healthCheck() { - const memory = process.memoryUsage() - const stats = getEmbeddingMemoryStats() - - return { - status: memory.heapUsed < 14 * 1024 * 1024 * 1024 ? 'healthy' : 'warning', - memory: { - heapUsed: `${(memory.heapUsed / 1024 / 1024).toFixed(2)} MB`, - heapTotal: `${(memory.heapTotal / 1024 / 1024).toFixed(2)} MB`, - rss: `${(memory.rss / 1024 / 1024).toFixed(2)} MB` - }, - embedding: stats - } -} -``` - -### Prometheus Metrics -```javascript -// metrics.js -import prometheus from 'prom-client' - -export const memoryUsage = new prometheus.Gauge({ - name: 'brainy_memory_usage_bytes', - help: 'Memory usage in bytes' -}) - -export const embeddingCount = new prometheus.Counter({ - name: 'brainy_embeddings_total', - help: 'Total number of embeddings processed' -}) - -export const workerRestarts = new prometheus.Counter({ - name: 'brainy_worker_restarts_total', - help: 'Number of worker restarts for memory management' -}) -``` - -## ๐Ÿšจ Production Checklist - -### Before Deployment -- [ ] Server has 16GB+ RAM -- [ ] Models downloaded (`npm run download-models`) -- [ ] Environment variables configured -- [ ] Health checks implemented -- [ ] Logging configured -- [ ] Monitoring set up - -### During Deployment -- [ ] Memory usage stays below 14GB -- [ ] Worker restarts happening automatically -- [ ] Search operations completing successfully -- [ ] No memory leak warnings in logs - -### After Deployment -- [ ] Set up alerts for high memory usage -- [ ] Monitor worker restart frequency -- [ ] Track performance metrics -- [ ] Plan for scaling based on usage - -## ๐Ÿ” Troubleshooting - -### Common Issues - -**Out of Memory (OOM) Kills** -```bash -# Symptoms: Process suddenly stops -# Solution: Increase memory or reduce load -NODE_OPTIONS="--max-old-space-size=20480" # 20GB -``` - -**Slow Search Performance** -```bash -# Symptoms: Timeouts on search operations -# Solution: Check model loading -curl http://localhost:3000/health | jq '.embedding.strategy' -``` - -**Worker Restart Loops** -```bash -# Symptoms: Constant worker restarts -# Solution: Increase restart threshold -BRAINY_MAX_EMBEDDINGS_NODE="200" -``` - -## ๐ŸŽฏ Performance Tuning - -### For High-Traffic Applications -- Use multiple instances with load balancing -- Implement request queuing -- Cache common search results -- Consider dedicated embedding servers - -### For Memory-Constrained Environments -- Use aggressive cleanup thresholds -- Implement request batching -- Mock embeddings for non-critical features -- Consider external embedding APIs - -## ๐Ÿ“ˆ Scaling Strategies - -### Horizontal Scaling -```yaml -# Multiple instances behind load balancer -instances: 3-5 -memory_per_instance: 16GB -load_balancer: nginx, AWS ALB, GCP LB -``` - -### Vertical Scaling -```yaml -# Larger single instance -memory: 32-64GB -cpu: 8-16 cores -storage: SSD for model caching -``` - -### Hybrid Architecture -```yaml -# Separate concerns -api_servers: 4GB RAM (no AI features) -embedding_servers: 32GB RAM (AI only) -communication: REST API or gRPC -``` - -## ๐ŸŽ‰ Success Metrics - -A successful Brainy production deployment should show: -- โœ… Memory usage stable under 14GB -- โœ… Search latency < 100ms -- โœ… Worker restarts every 100-1000 operations -- โœ… Zero downtime with proper monitoring -- โœ… Embedding accuracy maintained - -Your users get **ChatGPT-quality semantic search** running locally with complete privacy and control! \ No newline at end of file diff --git a/SCALABILITY_PLAN.md b/SCALABILITY_PLAN.md deleted file mode 100644 index d17d7e07..00000000 --- a/SCALABILITY_PLAN.md +++ /dev/null @@ -1,141 +0,0 @@ -# Brainy 2.0 Scalability Plan - Millions of Records - -## Current Performance Profile -- **Exact match**: O(1) - โœ… Excellent (same as MongoDB) -- **Range queries**: O(log n) - โœ… Excellent (same as MongoDB B-tree) -- **Memory usage**: ~1KB per record - โš ๏ธ Problematic at scale - -## Scalability Bottlenecks - -### 1. Memory Limits (CRITICAL) -**Problem**: All indices in RAM -- 1M records = 1.1 GB RAM โœ… -- 10M records = 11 GB RAM โŒ -- 100M records = 110 GB RAM โŒโŒโŒ - -**Solution**: Hybrid memory/disk approach -```typescript -interface ScalableIndex { - hotCache: Map> // Top 10K entries in RAM - coldStorage: DiskIndex // Rest on disk (LevelDB/RocksDB) - bloomFilter: BloomFilter // Quick existence check -} -``` - -### 2. Sorted Index Scalability -**Problem**: Single array for entire field -- 10M values = massive array sort -- Binary search still O(log n) but cache misses - -**Solution**: B+ Tree structure -```typescript -interface BPlusTreeIndex { - root: BPlusNode - leafLevel: LinkedList // For range scans - height: number // Typically 3-4 levels -} -``` - -### 3. Index Persistence -**Problem**: Rebuilding on startup -- 1M records = 30 seconds startup โŒ -- 10M records = 5 minutes startup โŒโŒโŒ - -**Solution**: Incremental index snapshots -```typescript -// Save index periodically -await storage.saveIndex('field_price_sorted', sortedIndex) -// Load on startup -const cached = await storage.loadIndex('field_price_sorted') -``` - -## Recommended Architecture for Scale - -### Tier 1: <100K records (Current) -- โœ… All in memory -- โœ… Hash + sorted indices -- โœ… No changes needed - -### Tier 2: 100K-1M records (Minor changes) -```typescript -class OptimizedMetadataIndex { - // Lazy load sorted indices - private async ensureSortedIndex(field: string) { - if (!this.sortedIndices.has(field)) { - await this.loadOrBuildSortedIndex(field) - } - } - - // Persist indices to storage - private async persistIndex(field: string) { - const index = this.sortedIndices.get(field) - await this.storage.saveMetadata(`__index_${field}`, index) - } -} -``` - -### Tier 3: 1M-10M records (Major refactor) -```typescript -class ScalableMetadataIndex { - private leveldb: LevelDB // Or RocksDB - private hotCache: LRUCache> - private bloomFilters: Map - - async getIds(field: string, value: any): Promise { - // Check bloom filter first (O(1)) - if (!this.bloomFilters.get(field)?.mightContain(value)) { - return [] - } - - // Check hot cache (O(1)) - const cached = this.hotCache.get(`${field}:${value}`) - if (cached) return Array.from(cached) - - // Load from disk (O(log n)) - const ids = await this.leveldb.get(`idx:${field}:${value}`) - this.hotCache.set(`${field}:${value}`, new Set(ids)) - return ids - } -} -``` - -### Tier 4: 10M+ records (Distributed) -- Shard by ID range or hash -- Multiple Brainy instances -- Coordinator node for queries -- Similar to MongoDB sharding - -## Performance at Scale - -| Records | Current | Optimized | MongoDB | -|---------|---------|-----------|---------| -| 10K | 10ms | 10ms | 15ms | -| 100K | 15ms | 15ms | 20ms | -| 1M | 25ms | 20ms | 25ms | -| 10M | OOM โŒ | 30ms | 35ms | -| 100M | OOM โŒ | 50ms | 60ms | - -## Implementation Priority - -1. **Quick Win**: Index persistence (prevent rebuild) -2. **Medium**: LRU cache for hot data -3. **Long-term**: B+ tree indices -4. **Future**: Sharding support - -## Memory Usage Comparison - -| Records | Current | Optimized | MongoDB | -|---------|---------|-----------|---------| -| 100K | 110 MB | 110 MB | 150 MB | -| 1M | 1.1 GB | 500 MB | 1.5 GB | -| 10M | 11 GB โŒ | 2 GB โœ… | 8 GB | -| 100M | 110 GB โŒ | 5 GB โœ… | 50 GB | - -## Conclusion - -**Current state**: Excellent for <100K records, good for <1M -**With optimizations**: Can handle 10M+ records -**Comparable to**: MongoDB, Firestore for most operations -**Better than**: Traditional databases for vector + metadata hybrid queries - -The architecture is **sound** - just needs memory optimization for scale! \ No newline at end of file diff --git a/TESTING-GUIDE.md b/TESTING-GUIDE.md deleted file mode 100644 index a1211f45..00000000 --- a/TESTING-GUIDE.md +++ /dev/null @@ -1,129 +0,0 @@ -# ๐Ÿง  Brainy Testing Guide - -## Memory Requirements - -**IMPORTANT**: Brainy requires 8-16GB RAM for full functionality due to the transformer model (ONNX runtime). - -This is NOT a bug - it's the cost of running state-of-the-art AI locally. - -## Why So Much Memory? - -Brainy uses the `all-MiniLM-L6-v2` transformer model for semantic search: -- **Model file**: 90MB compressed -- **Runtime memory**: 4-8GB when loaded -- **Why**: ONNX runtime pre-allocates buffers for matrix operations -- **Benefit**: Enables semantic search (understanding meaning, not just keywords) - -## Running Tests - -### Full Test Suite (Requires 16GB RAM) -```bash -# Allocate 16GB heap for Node.js -export NODE_OPTIONS='--max-old-space-size=16384' -npm test -``` - -### Test Without AI Features (Low Memory) -```bash -# Test core database features without embeddings -node test-without-embeddings.js -``` - -### Test Individual Files -```bash -# Test specific functionality -npm test -- --run tests/core.test.ts -npm test -- --run tests/metadata-filter.test.ts -``` - -### Sequential Test Runner (Memory-Efficient) -```bash -# Runs tests in batches to prevent memory exhaustion -./run-all-tests.sh -``` - -## Common Test Issues - -### Out of Memory Errors -**Symptom**: `FATAL ERROR: Ineffective mark-compacts near heap limit` - -**Solution**: -1. Increase Node.js heap: `NODE_OPTIONS='--max-old-space-size=16384'` -2. Run tests sequentially instead of in parallel -3. Use a machine with more RAM (16GB+ recommended) - -### Tests Hanging on Search -**Symptom**: Tests freeze when calling `brain.search()` or `brain.find()` - -**Cause**: ONNX model initialization can take 30-60 seconds first time - -**Solution**: Be patient - model loads once then runs fast - -### ClearAll Requires Force -**Symptom**: `clearAll requires force: true option for safety` - -**Solution**: Always use `brain.clearAll({ force: true })` - -## Performance Expectations - -With adequate memory (16GB): -- Model initialization: 30-60 seconds (first time) -- Embedding generation: 10-50ms per text -- Vector search: 1-10ms for 10k items -- Metadata filtering: <1ms (indexed) - -## Production Deployment - -For production with limited memory: - -### Option 1: Dedicated AI Server -Run Brainy on a server with 16GB+ RAM and access via API - -### Option 2: Cloud Functions -Use services that provide high-memory instances: -- AWS Lambda: Up to 10GB -- Google Cloud Functions: Up to 32GB -- Vercel: Up to 3GB (may struggle) - -### Option 3: Pre-computed Embeddings -Generate embeddings offline and ship them with your app - -## The Reality - -**Brainy includes cutting-edge AI that requires significant memory.** - -This is the same technology used by: -- Google Search (semantic understanding) -- GitHub Copilot (code understanding) -- ChatGPT (text embeddings) - -The difference: **Brainy runs it locally with zero configuration.** - -If you need a lighter solution without AI: -- Use traditional databases (PostgreSQL, MongoDB) -- Use keyword search instead of semantic search -- Use external embedding APIs (OpenAI, Cohere) - -But if you want the power of AI-driven search that understands meaning, not just keywords, then 8-16GB RAM is the price of admission. - -## Test Monitoring - -To monitor memory during tests: -```bash -# Watch memory usage -watch -n 1 "ps aux | grep node | grep -v grep" - -# Check Node.js heap -node -e "console.log(require('v8').getHeapStatistics())" -``` - -## Optimizations Already Applied - -Brainy already includes these memory optimizations: -- โœ… Quantized models (q8 instead of fp32) - 75% reduction -- โœ… ONNX memory arena disabled -- โœ… Limited thread pools -- โœ… Efficient batch processing -- โœ… Smart caching - -These optimizations reduce memory from 16GB+ to 4-8GB, which is as low as possible while maintaining quality. \ No newline at end of file diff --git a/TESTING-STRATEGY.md b/TESTING-STRATEGY.md deleted file mode 100644 index 1901eff1..00000000 --- a/TESTING-STRATEGY.md +++ /dev/null @@ -1,208 +0,0 @@ -# ๐Ÿง  Brainy Testing Strategy - -## Overview - -Brainy uses ONNX Runtime with transformer models, requiring 4-8GB memory for full functionality. This document explains our testing strategy based on 2024-2025 best practices. - -## Memory Requirements - -| Component | Memory Usage | Notes | -|-----------|-------------|-------| -| ONNX Model | 4-8GB | all-MiniLM-L6-v2 transformer | -| Node.js Heap | 2-4GB | JavaScript runtime | -| Test Framework | 1-2GB | Vitest overhead | -| **Total** | **8-16GB** | Recommended for full suite | - -## Test Commands - -### Quick Reference -```bash -npm test # Standard test run -npm run test:memory # With 16GB heap allocation -npm run test:core # Core functionality only -npm run test:ci # CI optimized -npm run test:shard # Supports VITEST_SHARD env -``` - -### Memory-Intensive Tests -```bash -# Allocate 16GB for transformer models -NODE_OPTIONS='--max-old-space-size=16384' npm test - -# Or use our helper script -npm run test:memory -``` - -### Test Sharding (CI/CD) -```bash -# Split tests across 4 machines/processes -VITEST_SHARD=1/4 npm run test:shard # 1st quarter -VITEST_SHARD=2/4 npm run test:shard # 2nd quarter -VITEST_SHARD=3/4 npm run test:shard # 3rd quarter -VITEST_SHARD=4/4 npm run test:shard # 4th quarter -``` - -## Vitest Configuration - -Our `vitest.config.ts` implements industry best practices: - -### Memory Optimization -- **Pool**: `forks` for better memory isolation -- **Max Forks**: 1 (sequential execution) -- **Isolation**: Enabled (prevents memory leaks) - -### Timeouts -- **Test**: 120 seconds (ONNX loading) -- **Hooks**: 60 seconds (model initialization) -- **Teardown**: 10 seconds - -### Performance -- **Parallelism**: Disabled (prevents OOM) -- **Retry**: Once in CI (handles flaky tests) -- **Reporters**: Dot for CI, verbose for local - -## Test Organization - -### Current Structure (All Tests) -``` -tests/ -โ”œโ”€โ”€ core.test.ts # Core functionality -โ”œโ”€โ”€ triple-intelligence.test.ts # AI features -โ”œโ”€โ”€ metadata-filter.test.ts # Brain Patterns -โ”œโ”€โ”€ neural-api.test.ts # Neural operations -โ””โ”€โ”€ ... (45+ test files) -``` - -### Future Structure (Recommended) -``` -tests/ -โ”œโ”€โ”€ unit/ # No models, fast -โ”‚ โ”œโ”€โ”€ utils/ -โ”‚ โ”œโ”€โ”€ storage/ -โ”‚ โ””โ”€โ”€ metadata/ -โ”œโ”€โ”€ integration/ # With models, slow -โ”‚ โ”œโ”€โ”€ search/ -โ”‚ โ”œโ”€โ”€ embeddings/ -โ”‚ โ””โ”€โ”€ triple/ -โ””โ”€โ”€ e2e/ # Full system tests -``` - -## Common Issues & Solutions - -### Out of Memory (OOM) -**Error**: `FATAL ERROR: Ineffective mark-compacts near heap limit` - -**Solutions**: -1. Increase heap: `NODE_OPTIONS='--max-old-space-size=16384'` -2. Run fewer tests: `npm test tests/core.test.ts` -3. Use sharding: `VITEST_SHARD=1/2` - -### Test Timeouts -**Error**: `Test timed out after 30000ms` - -**Solutions**: -1. Already extended to 120s in config -2. Skip model tests: `npm test -- --exclude "**/neural*"` -3. Mock embeddings for unit tests - -### ClearAll Safety -**Error**: `clearAll requires force: true option` - -**Solution**: Always use `brain.clearAll({ force: true })` -โœ… Already fixed in all test files - -## CI/CD Recommendations - -### GitHub Actions -```yaml -name: Tests -on: [push, pull_request] - -jobs: - test: - runs-on: ubuntu-latest - strategy: - matrix: - shard: [1/4, 2/4, 3/4, 4/4] - - steps: - - uses: actions/checkout@v3 - - uses: actions/setup-node@v3 - with: - node-version: 18 - - - run: npm ci - - run: npm run build - - # Run sharded tests with memory - - run: VITEST_SHARD=${{ matrix.shard }} npm run test:ci - env: - NODE_OPTIONS: --max-old-space-size=16384 -``` - -### Docker -```dockerfile -FROM node:18 -WORKDIR /app - -# Increase memory limits -ENV NODE_OPTIONS="--max-old-space-size=16384" - -COPY . . -RUN npm ci -RUN npm run build - -# Run tests -CMD ["npm", "run", "test:memory"] -``` - -## Performance Benchmarks - -With proper configuration: -- **Model Load**: 30-60 seconds (first time) -- **Embedding**: 10-50ms per text -- **Test Suite**: 5-10 minutes (sequential) -- **Memory Usage**: 4-8GB peak - -## Best Practices - -1. **Always build before testing** - ```bash - npm run build && npm test - ``` - -2. **Monitor memory during tests** - ```bash - watch -n 1 "ps aux | grep node | head -5" - ``` - -3. **Use appropriate test command** - - Development: `npm test` - - CI: `npm run test:ci` - - Debugging: `npm run test:memory -- --reporter=verbose` - -4. **Mock for unit tests** - ```javascript - // Mock embeddings for non-AI tests - const mockEmbed = () => new Array(384).fill(0.1) - ``` - -## Industry Standards - -We follow these 2024-2025 best practices: - -1. **Vitest Forks Pool**: Better memory isolation than threads -2. **Test Sharding**: Distribute across multiple processes -3. **Sequential Execution**: Prevent memory competition -4. **Extended Timeouts**: Account for model loading -5. **Memory Monitoring**: Track usage during tests - -## Conclusion - -Brainy's testing requires significant memory due to transformer models. This is not a bug - it's the cost of running state-of-the-art AI locally. Our configuration follows industry best practices to manage this requirement effectively. - -For projects that cannot allocate 8-16GB for testing: -- Use mock embeddings for unit tests -- Run integration tests separately in CI -- Consider cloud-based testing environments -- Use test sharding to distribute load \ No newline at end of file diff --git a/TEST_SUITE_ANALYSIS.md b/TEST_SUITE_ANALYSIS.md deleted file mode 100644 index d0da1d16..00000000 --- a/TEST_SUITE_ANALYSIS.md +++ /dev/null @@ -1,225 +0,0 @@ -# ๐Ÿง  COMPREHENSIVE TEST SUITE ULTRATHINK ANALYSIS - -**Date**: 2025-08-25 -**Context**: Brainy 2.0 Augmentation System Migration -**Total Test Files**: 49 - -## ๐Ÿ—๏ธ ARCHITECTURAL CHANGES IMPACT ANALYSIS - -### **Major Changes Affecting Tests:** - -1. **Augmentation System Migration** - - Core functionality moved to augmentations (cache, index, metrics, storage) - - Two-phase initialization (storage augmentations first) - - Method delegation through augmentations - -2. **API Evolution** - - Methods like `cleanup()` may have changed - - Export structure in index.ts updated - - New unified BrainyAugmentation interface - -3. **Configuration Changes** - - Auto-registration of default augmentations - - New augmentation-based storage initialization - -## ๐Ÿ“Š TEST CATEGORIES ANALYSIS - -### ๐ŸŸข **LIKELY WORKING** (Minimal Changes Expected) -1. **Core Functionality Tests** - Tests basic BrainyData usage - - `core.test.ts` - Library exports, basic functionality - - `database-operations.test.ts` - CRUD operations - - `vector-operations.test.ts` - Vector search (if using public API) - - `triple-intelligence.test.ts` - Advanced queries - -2. **Environment Tests** - Platform compatibility - - `environment.browser.test.ts` - - `environment.node.test.ts` - - `multi-environment.test.ts` - -3. **Storage Integration Tests** - Should work with new augmentation system - - `s3-comprehensive.test.ts` - S3 through augmentations - - `opfs-storage.test.ts` - OPFS through augmentations - -### ๐ŸŸก **NEEDS UPDATES** (Medium Impact) -1. **API Consistency Tests** - - `consistent-api.test.ts` - May have method signature changes - - `unified-api.test.ts` - API evolution issues - - May use `cleanup()` vs new shutdown methods - -2. **Configuration & Initialization Tests** - - `auto-configuration.test.ts` - New augmentation auto-registration - - `zero-config-models.test.ts` - Initialization pattern changes - -3. **Performance Tests** - - `performance.test.ts` - Augmentation overhead validation needed - - `metadata-performance.test.ts` - Now through IndexAugmentation - - `throttling-metrics.test.ts` - May need augmentation context - -4. **Feature Integration Tests** - - `brainy-chat.test.ts` - BrainyChat integration - - `nlp-patterns-comprehensive.test.ts` - NLP pattern system - - `neural-*.test.ts` - Neural integration tests - -### ๐ŸŸ  **MAJOR UPDATES NEEDED** (High Impact) -1. **Export/Import Tests** - - `core.test.ts` - Tests exports that may not exist: - - `createSenseAugmentation` - - `addWebSocketSupport` - - `executeAugmentation` - - `loadAugmentationModule` - -2. **Storage System Tests** - - `storage-adapter-coverage.test.ts` - Storage now through augmentations - - Tests that directly create storage adapters vs using augmentations - -3. **Metadata & Statistics Tests** - - `statistics.test.ts` - Now through MetricsAugmentation - - `service-statistics.test.ts` - Service stats through augmentations - - `metadata-filter.test.ts` - Filtering through IndexAugmentation - -### ๐ŸŸข **AUGMENTATION TESTS** (Should be working) -- `augmentations-batch-processing.test.ts` -- `augmentations-entity-registry.test.ts` -- `augmentations-request-deduplicator.test.ts` -- `augmentations-wal.test.ts` - -### ๐Ÿ”ด **CRITICAL VALIDATION NEEDED** -1. **Release Tests** - - `release-critical.test.ts` - Must pass for 2.0 release - - `release-validation.test.ts` - End-to-end validation - -2. **Edge Cases** - - `edge-cases.test.ts` - Ensure augmentation system handles edge cases - - `error-handling.test.ts` - Error handling through augmentations - -## ๐ŸŽฏ COMPREHENSIVE TEST VALIDATION PLAN - -### **Phase 1: Fix Export Issues (CRITICAL)** -#### Files to Fix: -- `core.test.ts` - Remove/update non-existent exports -- `unified-api.test.ts` - Fix import paths -- `consistent-api.test.ts` - Update method calls - -#### Actions: -- [ ] Update index.ts to remove non-existent exports -- [ ] Fix import paths in test files -- [ ] Update method names (cleanup โ†’ shutdown, etc.) - -### **Phase 2: Fix Augmentation Integration** -#### Files to Update: -- `auto-configuration.test.ts` - Test new augmentation auto-registration -- `statistics.test.ts` - Test statistics through MetricsAugmentation -- `metadata-*.test.ts` - Test metadata through IndexAugmentation - -#### Actions: -- [ ] Update tests to use augmentation-delegated methods -- [ ] Test augmentation auto-registration -- [ ] Validate two-phase initialization - -### **Phase 3: Fix API Evolution Issues** -#### Files to Update: -- `consistent-api.test.ts` - Update method signatures -- `unified-api.test.ts` - Update API calls -- `storage-adapter-coverage.test.ts` - Storage through augmentations - -#### Actions: -- [ ] Update method calls for new API -- [ ] Fix initialization patterns -- [ ] Update configuration objects - -### **Phase 4: Add Missing Tests** -#### New Tests Needed: -- [ ] **Augmentation lifecycle tests** - register โ†’ init โ†’ execute โ†’ shutdown -- [ ] **Augmentation priority tests** - Execution order validation -- [ ] **Two-phase initialization tests** - Storage first, then others -- [ ] **Method delegation tests** - Core methods โ†’ augmentations - -### **Phase 5: Remove Obsolete Tests** -#### Tests to Remove/Update: -- [ ] Tests for removed augmentation factory functions -- [ ] Tests for deprecated API methods -- [ ] Tests for old typed augmentation system - -## ๐Ÿšจ HIGH-RISK AREAS - -### **Most Likely to Fail:** -1. **core.test.ts** - Export mismatches -2. **statistics.test.ts** - Statistics through augmentations -3. **metadata-*.test.ts** - Metadata through augmentations -4. **auto-configuration.test.ts** - New initialization patterns -5. **storage-adapter-coverage.test.ts** - Storage delegation - -### **Must Pass for Release:** -1. **release-critical.test.ts** -2. **release-validation.test.ts** -3. **All augmentation tests** -4. **core.test.ts** -5. **unified-api.test.ts** - -## โœ… SUCCESS CRITERIA - COMPREHENSIVE 2.0 FEATURE VALIDATION - -### **ALL Brainy Features Through Updated 2.0 APIs:** - -#### **๐Ÿง  Core Features (Through New Implementations):** -- [ ] **Data Operations** - add/get/update/delete through AugmentationRegistry -- [ ] **Storage Systems** - All storage through StorageAugmentations (not direct) -- [ ] **Vector Search** - Updated search APIs and performance -- [ ] **NEW find()** - Triple Intelligence with `like`, `where`, `connected` -- [ ] **Clustering** - All 3 algorithms: HNSW, K-means, Hierarchical -- [ ] **Metadata Indexing** - Through IndexAugmentation (not direct) -- [ ] **Statistics** - Through MetricsAugmentation (not direct) -- [ ] **Caching** - Through CacheAugmentation (not SearchCache direct) - -#### **๐Ÿ”Œ Augmentation System (All 27 Augmentations):** -- [ ] **Storage (8)** - Memory, FileSystem, OPFS, S3, R2, GCS, Auto, Dynamic -- [ ] **Performance (7)** - Cache, Index, Metrics, WAL, Batch, Pool, Dedup -- [ ] **Data Integrity (3)** - EntityRegistry, AutoRegister, Enhanced Clear -- [ ] **Intelligence (2)** - Neural Import, Intelligent Verb Scoring -- [ ] **Communication (4)** - API Server, Conduits, Server Search, Monitoring -- [ ] **External Integration (3)** - Synapses, MCP, WebSocket - -#### **๐Ÿš€ New 2.0 Features:** -- [ ] **Unified BrainyAugmentation interface** - All augmentations working -- [ ] **Two-phase initialization** - Storage first, then others -- [ ] **Augmentation lifecycle** - register โ†’ init โ†’ execute โ†’ shutdown -- [ ] **Method delegation** - Core methods โ†’ augmentations -- [ ] **Auto-registration** - Default augmentations auto-registered -- [ ] **Enhanced Chat** - BrainyChat with all features -- [ ] **220 NLP Patterns** - All patterns through updated neural system - -#### **๐ŸŽฏ API Consistency (Updated 2.0 APIs):** -- [ ] **All exports work** - No missing/incorrect exports in index.ts -- [ ] **Method signatures correct** - Updated parameter patterns -- [ ] **Configuration objects** - New augmentation-based config -- [ ] **Error handling** - Through augmentation system -- [ ] **Performance** - No regressions from augmentation overhead - -### **Before 2.0 Release:** -- [ ] **100% test pass rate** across all 49 test files -- [ ] **Tests use CURRENT implementation** - Not old/deprecated APIs -- [ ] **Complete feature coverage** - ALL features tested through 2.0 APIs -- [ ] **No missing augmentation tests** - All 27 augmentations validated -- [ ] **Performance validation** - Augmentation system performs well - -### **Quality Gates:** -1. **All export tests pass** - No missing/incorrect exports -2. **All augmentation tests pass** - 27 augmentations working -3. **All core functionality tests pass** - Basic features working -4. **All storage tests pass** - Storage through augmentations -5. **All API consistency tests pass** - Method signatures correct - -## ๐Ÿƒโ€โ™‚๏ธ EXECUTION STRATEGY - -### **Parallel Approach:** -1. **Fix TypeScript issues** (current priority) -2. **Run test suite and identify failures** -3. **Categorize failures by impact** -4. **Fix critical path tests first** -5. **Validate all tests in phases** - -### **Test-Driven Validation:** -1. **Run each test file individually** -2. **Fix failures systematically** -3. **Update test plan based on findings** -4. **Validate full test suite** -5. **Performance regression testing** \ No newline at end of file diff --git a/UNIFIED_CACHE_DEEP_ANALYSIS.md b/UNIFIED_CACHE_DEEP_ANALYSIS.md deleted file mode 100644 index 72631a29..00000000 --- a/UNIFIED_CACHE_DEEP_ANALYSIS.md +++ /dev/null @@ -1,350 +0,0 @@ -# ๐Ÿง  Unified Cache Architecture - Deep Analysis - -## The Core Concept -ONE cache to rule them all - no coordination needed because there's nothing to coordinate! - -## โœ… PROS - Why This is Brilliant - -### 1. **Emergent Intelligence** -- System automatically finds optimal balance -- No human has to guess the right ratios -- Adapts to changing workloads in real-time - -### 2. **Simplicity = Reliability** -```typescript -// Traditional approach: 500+ lines of coordination code -// Our approach: 50 lines that just work -``` - -### 3. **Cost-Aware by Design** -```typescript -interface CacheItem { - key: string - type: 'hnsw' | 'metadata' - data: any - size: number - rebuildCost: number // HNSW: 1000ms, Metadata: 1ms - lastAccess: number - accessCount: number -} -``` - -### 4. **Natural Load Balancing** -- Popular data stays in cache regardless of type -- Unpopular data gets evicted regardless of type -- The "right" balance emerges from usage patterns - -## โš ๏ธ DANGERS - What Could Go Wrong - -### 1. **Cache Stampede Risk** -```typescript -// DANGER: 1000 concurrent requests for same cold item -// All 1000 try to load from disk simultaneously! - -// SOLUTION: Request coalescing -class UnifiedCache { - private loadingPromises = new Map>() - - async get(key: string) { - // If already loading, wait for existing promise - if (this.loadingPromises.has(key)) { - return this.loadingPromises.get(key) - } - - if (!this.items.has(key)) { - const loadPromise = this.loadFromDisk(key) - this.loadingPromises.set(key, loadPromise) - const data = await loadPromise - this.loadingPromises.delete(key) - return data - } - } -} -``` - -### 2. **Memory Fragmentation** -```typescript -// DANGER: Many small metadata items + few large HNSW items -// Could lead to inefficient memory use - -// SOLUTION: Size-aware eviction -evict(bytesNeeded: number) { - // Try to evict items that closely match needed size - // Prevents evicting 100 tiny items when 1 large would do -} -``` - -### 3. **Starvation Scenario** -```typescript -// DANGER: HNSW queries so expensive that metadata never gets cached -// Even though metadata queries are 100x more frequent - -// SOLUTION: Fairness mechanism -class FairUnifiedCache { - private typeAccessCounts = { hnsw: 0, metadata: 0 } - - evict() { - // If one type is getting 90%+ of accesses but has <10% of cache - // Force evict from the greedy type - const hnswRatio = this.getTypeRatio('hnsw') - const hnswAccessRatio = this.typeAccessCounts.hnsw / this.totalAccesses - - if (hnswRatio > 0.9 && hnswAccessRatio < 0.1) { - // HNSW is hogging cache despite low usage - this.evictType('hnsw') - } - } -} -``` - -### 4. **Cold Start Problem** -```typescript -// DANGER: Empty cache = bad initial performance -// Don't know what to pre-load - -// SOLUTION: Persistence + Smart Warming -class PersistentUnifiedCache { - async init() { - // Load access patterns from last session - const patterns = await this.loadAccessPatterns() - - // Pre-warm top 10% most accessed items - for (const item of patterns.top10Percent) { - await this.preload(item.key) - } - } - - async shutdown() { - // Save access patterns for next startup - await this.saveAccessPatterns() - } -} -``` - -## ๐Ÿ”„ ALTERNATIVE APPROACHES - -### 1. **Two-Level Cache** (More Complex) -```typescript -class TwoLevelCache { - private l1Cache = new Map() // Ultra-hot, pinned - private l2Cache = new LRU() // Everything else -} -// Pro: Guarantees critical data stays -// Con: Need to decide what's "critical" -``` - -### 2. **Type-Segregated Pools** (Traditional) -```typescript -class SegregatedCache { - private hnswPool = new LRU(/* 60% memory */) - private metadataPool = new LRU(/* 40% memory */) -} -// Pro: Guaranteed resources for each type -// Con: Rigid, can't adapt to workload changes -``` - -### 3. **Time-Window Based** (Interesting!) -```typescript -class TimeWindowCache { - // Track access patterns in rolling windows - private windows = [ - new AccessWindow('1min'), - new AccessWindow('5min'), - new AccessWindow('1hour') - ] - - evict() { - // Items not accessed in ANY window = cold - // Items accessed in ALL windows = hot - } -} -// Pro: Handles bursty workloads well -// Con: More complex, more memory overhead -``` - -## ๐Ÿš€ ENHANCEMENTS TO CONSIDER - -### 1. **Predictive Pre-fetching** -```typescript -class PredictiveCache extends UnifiedCache { - private sequences = new Map() - - async get(key: string) { - const data = await super.get(key) - - // Track access sequences - this.recordSequence(this.lastKey, key) - - // Predictively load likely next items - const predicted = this.predictNext(key) - if (predicted && !this.items.has(predicted)) { - this.preloadAsync(predicted) // Non-blocking - } - - return data - } -} -``` - -### 2. **Adaptive Tier Boundaries** -```typescript -class AdaptiveTierCache { - private hotThreshold = 100 // Start with defaults - private warmThreshold = 10 - - adapt() { - // If cache is thrashing, tighten hot tier - if (this.evictionRate > 10_per_second) { - this.hotThreshold *= 1.5 // Make it harder to become hot - } - - // If cache is stable, loosen hot tier - if (this.evictionRate < 1_per_minute) { - this.hotThreshold *= 0.9 // Make it easier to become hot - } - } -} -``` - -### 3. **Query-Aware Caching** -```typescript -class QueryAwareCache { - beforeQuery(query: TripleQuery) { - // Pre-emptively make room based on query type - if (query.like && query.where) { - // Hybrid query coming - ensure both types have space - this.ensureMinSpace('hnsw', 100_MB) - this.ensureMinSpace('metadata', 50_MB) - } - } -} -``` - -### 4. **Compression for Cold Storage** -```typescript -class CompressedCache { - async saveToDisk(key: string, item: CacheItem) { - if (item.type === 'hnsw') { - // Quantize vectors before saving - item.data = this.quantizeVectors(item.data) - } - if (item.type === 'metadata') { - // Compress with zlib - item.data = await compress(item.data) - } - } -} -``` - -## ๐Ÿ“Š PERFORMANCE CHARACTERISTICS - -### Memory Efficiency -``` -Traditional Dual-Cache: 60-70% efficiency (due to rigid splits) -Unified Cache: 85-95% efficiency (adapts to actual usage) -``` - -### Query Latency -``` -Cache Hit: 0.1ms (both approaches) -Cache Miss (metadata): 5ms from disk -Cache Miss (HNSW): 100ms from disk (needs reconstruction) -``` - -### Adaptation Speed -``` -Workload change detected: ~100 queries -Full rebalance: ~1000 queries -Steady state: ~10,000 queries -``` - -## ๐ŸŽฏ IMPLEMENTATION STRATEGY - -### Phase 1: Basic Unified Cache (Week 1) -```typescript -class UnifiedCache { - private items = new Map() - private totalSize = 0 - private maxSize = 2 * GB - - get(key: string): any - set(key: string, value: any, type: CacheType): void - evict(): void -} -``` - -### Phase 2: Add Intelligence (Week 2) -- Access counting -- Cost-aware eviction -- Request coalescing -- Basic persistence - -### Phase 3: Advanced Features (Week 3) -- Predictive prefetching -- Adaptive thresholds -- Compression -- Monitoring/metrics - -## ๐Ÿ† WHY THIS WINS - -1. **Simplicity**: One system instead of two -2. **Adaptability**: Responds to real usage, not predictions -3. **Efficiency**: No wasted memory on unused indices -4. **Maintainability**: 200 lines instead of 2000 -5. **Performance**: Natural optimization emerges - -## โšก QUICK WIN IMPLEMENTATION - -```typescript -// Start with this - 50 lines that solve 80% of the problem -class QuickUnifiedCache { - private cache = new Map() - private access = new Map() - private size = 0 - private maxSize = 2_000_000_000 // 2GB - - get(key: string) { - this.access.set(key, (this.access.get(key) || 0) + 1) - return this.cache.get(key) - } - - set(key: string, value: any, size: number, cost: number) { - while (this.size + size > this.maxSize) { - this.evictLowestValue() - } - this.cache.set(key, { value, size, cost }) - this.size += size - } - - evictLowestValue() { - let victim = null - let lowestScore = Infinity - - for (const [key, item] of this.cache) { - const score = (this.access.get(key) || 1) / item.cost - if (score < lowestScore) { - lowestScore = score - victim = key - } - } - - if (victim) { - this.size -= this.cache.get(victim).size - this.cache.delete(victim) - this.access.delete(victim) - } - } -} -``` - -## ๐Ÿšจ FINAL VERDICT - -**GO FOR IT!** This unified approach is: -- Simpler than coordination -- More adaptive than fixed splits -- Naturally self-optimizing -- Easy to enhance incrementally - -The dangers are manageable with simple solutions, and the benefits far outweigh the complexity of traditional approaches. - -**Start simple, measure everything, enhance based on real usage.** \ No newline at end of file diff --git a/docs/MEMORY-REQUIREMENTS.md b/docs/MEMORY-REQUIREMENTS.md deleted file mode 100644 index 79ad9dee..00000000 --- a/docs/MEMORY-REQUIREMENTS.md +++ /dev/null @@ -1,183 +0,0 @@ -# ๐Ÿง  Brainy Memory Requirements - -## Executive Summary - -Brainy 2.0 includes **built-in AI capabilities** powered by transformer models. While the core database operations are memory-efficient (200-500MB), the AI features require additional memory due to the ONNX runtime. - -## Memory Requirements by Use Case - -### 1. **Minimal Usage** (No AI Features) -- **Required**: 512MB - 1GB -- **Use Case**: Basic noun/verb storage without semantic search -- **Configuration**: `embeddings: false` - -### 2. **Standard Usage** (With AI) -- **Recommended**: 4GB -- **Typical**: 6GB -- **Use Case**: Full semantic search, natural language queries, embeddings -- **Reality**: ONNX runtime allocates 4-8GB for model inference - -### 3. **Production Usage** (High Volume) -- **Recommended**: 8GB -- **Optimal**: 16GB -- **Use Case**: Large datasets, concurrent operations, caching - -## Why Does Brainy Need This Memory? - -### The ONNX Runtime Reality - -The transformer model file is only **30MB** on disk, but ONNX runtime allocates significantly more memory: - -1. **Model Loading**: ~500MB for model architecture -2. **Inference Tensors**: 2-4GB for computation graphs -3. **Batch Processing**: Additional memory for parallel inference -4. **Memory Fragmentation**: ONNX doesn't release memory efficiently - -### What You Get for This Memory - -Unlike other databases that require this memory just to run, Brainy's memory usage gives you: - -- **Built-in embeddings** - No external API costs ($0 vs $0.10/1M tokens) -- **Natural language search** - Plain English queries -- **Semantic understanding** - Find "similar" not just "exact" -- **Offline AI** - Works without internet connection -- **Zero latency** - Models loaded in-process - -## Configuration for Different Memory Constraints - -### Low Memory Environment (2GB) -```javascript -const brain = new BrainyData({ - embeddings: false, // Disable transformer models - cache: { - maxSize: 100 // Smaller cache - } -}) -``` - -### Standard Environment (4-6GB) -```javascript -const brain = new BrainyData() // Default configuration -``` - -### High Performance Environment (8GB+) -```javascript -const brain = new BrainyData({ - cache: { - maxSize: 10000 // Large cache - }, - batchSize: 100, // Process more in parallel - efSearch: 100 // More accurate search -}) -``` - -## Running Tests with Adequate Memory - -### For Development/Testing -```bash -# Allocate 8GB for Node.js -export NODE_OPTIONS='--max-old-space-size=8192' -npm test -``` - -### For Production -```bash -# Start with 8GB heap -node --max-old-space-size=8192 server.js -``` - -### Docker Configuration -```dockerfile -# In your Dockerfile -ENV NODE_OPTIONS="--max-old-space-size=8192" - -# Or in docker-compose.yml -environment: - - NODE_OPTIONS=--max-old-space-size=8192 -``` - -## Memory Optimization Tips - -### 1. **Lazy Model Loading** -Models are loaded on first use, not at initialization: -```javascript -const brain = new BrainyData() -// No memory used yet - -await brain.search('test') -// Now model loads (4GB allocated) -``` - -### 2. **Shared Model Instance** -Multiple BrainyData instances share the same model: -```javascript -const brain1 = new BrainyData() -const brain2 = new BrainyData() -// Only one model in memory -``` - -### 3. **Clear Unused Data** -```javascript -await brain.clear() // Free memory from data -// Model stays loaded for next operation -``` - -## Comparison with Other Databases - -| Database | Memory (No AI) | Memory (With AI) | AI Capability | -|----------|---------------|------------------|---------------| -| **Brainy** | 500MB | 4-6GB | Built-in | -| PostgreSQL | 2GB | 2GB + External AI | Via extension | -| MongoDB | 4GB | 4GB + External AI | Via Atlas | -| Elasticsearch | 8GB | 8GB + External AI | Via pipeline | -| Weaviate | 4GB | 8-16GB | Built-in | - -**Key Difference**: Brainy's memory usage is for AI features. Others use similar memory just for basic operations, then need MORE for AI. - -## Troubleshooting Memory Issues - -### Symptoms of Insufficient Memory -- "JavaScript heap out of memory" errors -- Process crashes during search operations -- Slow performance during embedding generation - -### Solutions - -1. **Increase Node.js heap size**: - ```bash - node --max-old-space-size=8192 app.js - ``` - -2. **Disable AI features temporarily**: - ```javascript - const brain = new BrainyData({ embeddings: false }) - ``` - -3. **Use quantized models** (future feature): - ```javascript - // Coming soon: 4x smaller models - const brain = new BrainyData({ - modelType: 'quantized' // Uses 1GB instead of 4GB - }) - ``` - -## The Bottom Line - -**Yes, Brainy needs 4-6GB of memory for AI features.** This is because it includes a complete transformer model for semantic understanding. - -**But consider the alternative:** -- OpenAI API: $0.10 per 1M tokens + latency + internet required -- Running separate embedding service: Another 4GB + complexity -- No semantic search: Missing core functionality - -**Brainy gives you local, private, zero-cost AI in exchange for that memory.** - -## Future Optimizations - -We're working on: -1. **Quantized models** - 75% memory reduction -2. **Model unloading** - Free memory when idle -3. **Streaming inference** - Lower peak memory usage -4. **WebGPU support** - Offload to GPU memory - -Until then, **allocate 6-8GB for the best experience** with Brainy's AI features. \ No newline at end of file diff --git a/docs/ONNX-OPTIMIZATIONS.md b/docs/ONNX-OPTIMIZATIONS.md deleted file mode 100644 index 1da0191f..00000000 --- a/docs/ONNX-OPTIMIZATIONS.md +++ /dev/null @@ -1,250 +0,0 @@ -# ๐ŸŽฏ ONNX Runtime Optimizations for Brainy - -## The Problem -ONNX runtime allocates 4-8GB of memory for a 30MB model file, causing memory exhaustion even with adequate heap allocation. - -## Available Solutions & Workarounds - -### 1. **Use Quantized Models** (IMMEDIATE FIX) -The most effective solution - reduces memory by 75%: - -```javascript -// In src/utils/embedding.ts -const pipelineOptions: any = { - cache_dir: cacheDir, - local_files_only: this.options.localFilesOnly, - dtype: 'q8' // Change from 'fp32' to 'q8' or 'q4' -} -``` - -**Memory Impact:** -- `fp32` (default): 4-8GB memory usage -- `fp16`: ~3-4GB memory usage -- `q8`: ~1-2GB memory usage โœ… RECOMMENDED -- `q4`: ~500MB-1GB memory usage (lower quality) - -### 2. **Enable ONNX Execution Providers** (PLATFORM SPECIFIC) - -#### For CPU Optimization: -```javascript -// Add to pipeline options -const pipelineOptions = { - // ... existing options - session_options: { - executionProviders: ['cpu'], - interOpNumThreads: 2, // Limit threads - intraOpNumThreads: 2, // Limit parallelism - graphOptimizationLevel: 'all', - enableCpuMemArena: false, // CRITICAL: Disable memory arena - enableMemPattern: false // CRITICAL: Disable memory patterns - } -} -``` - -#### For WebAssembly (Browser): -```javascript -const pipelineOptions = { - session_options: { - executionProviders: ['wasm'], - wasmPaths: '/path/to/wasm/files/', - numThreads: 1 // Single-threaded for lower memory - } -} -``` - -### 3. **Memory Arena Disable** (CRITICAL FIX) -ONNX pre-allocates huge memory arenas by default: - -```javascript -// In src/utils/embedding.ts, update the pipeline creation: -import { env } from '@huggingface/transformers' - -// Before loading model -env.onnx.wasm.numThreads = 1 // Limit WASM threads -env.onnx.wasm.simd = true // Use SIMD if available - -// Disable memory arena globally -if (typeof process !== 'undefined') { - process.env.ORT_DISABLE_MEMORY_ARENA = '1' - process.env.ORT_DISABLE_MEMORY_PATTERN = '1' -} -``` - -### 4. **Batch Size Optimization** -Process embeddings in smaller batches: - -```javascript -// Instead of processing all at once -const embeddings = await this.embed(texts) - -// Process in small batches -const BATCH_SIZE = 10 // Reduced from 50 -const embeddings = [] -for (let i = 0; i < texts.length; i += BATCH_SIZE) { - const batch = texts.slice(i, i + BATCH_SIZE) - const batchEmbeddings = await this.embed(batch) - embeddings.push(...batchEmbeddings) - - // Force garbage collection between batches (Node.js only) - if (global.gc) { - global.gc() - } -} -``` - -### 5. **Model Unloading** (MEMORY RECOVERY) -Unload model when not in use: - -```javascript -class TransformerEmbedding { - private idleTimer: NodeJS.Timeout | null = null - - async embed(text: string | string[]): Promise { - // Clear idle timer - if (this.idleTimer) { - clearTimeout(this.idleTimer) - } - - // Do embedding... - const result = await this.doEmbed(text) - - // Set idle timer to unload after 5 minutes - this.idleTimer = setTimeout(() => { - this.unloadModel() - }, 5 * 60 * 1000) - - return result - } - - private async unloadModel(): Promise { - if (this.extractor) { - // Dispose of the pipeline - await this.extractor.dispose() - this.extractor = null - - // Force garbage collection - if (global.gc) { - global.gc() - } - - console.log('Model unloaded to free memory') - } - } -} -``` - -### 6. **Use ONNX Runtime Web** (Browser Alternative) -For browser environments, use the lighter ONNX Runtime Web: - -```javascript -// Use onnxruntime-web instead of full onnxruntime-node -import * as ort from 'onnxruntime-web' - -// Configure for minimal memory -ort.env.wasm.numThreads = 1 -ort.env.wasm.simd = true -ort.env.wasm.proxy = false // Don't use worker -``` - -### 7. **Pre-computed Embeddings** (BEST FOR PRODUCTION) -For known data, pre-compute embeddings: - -```javascript -// During build/deploy time -const precomputedEmbeddings = { - 'javascript': [0.1, 0.2, ...], - 'python': [0.15, 0.25, ...], - // ... more common terms -} - -// At runtime -async embed(text) { - // Check cache first - if (precomputedEmbeddings[text.toLowerCase()]) { - return precomputedEmbeddings[text.toLowerCase()] - } - - // Only compute if not cached - return this.computeEmbedding(text) -} -``` - -## Recommended Implementation - -### Quick Fix (Immediate) -1. Change dtype to 'q8' in embedding.ts -2. Set `ORT_DISABLE_MEMORY_ARENA=1` environment variable -3. Reduce batch size to 10 - -### Code Changes for embedding.ts: -```javascript -// At the top of the file -if (typeof process !== 'undefined') { - process.env.ORT_DISABLE_MEMORY_ARENA = '1' - process.env.ORT_DISABLE_MEMORY_PATTERN = '1' -} - -// In constructor -this.options = { - model: options.model || 'Xenova/all-MiniLM-L6-v2', - verbose: this.verbose, - cacheDir: options.cacheDir || './models', - localFilesOnly: localFilesOnly, - dtype: options.dtype || 'q8', // Changed from fp32 - device: options.device || 'auto', - batchSize: 10 // Reduced from default -} - -// In loadModel -const pipelineOptions: any = { - cache_dir: cacheDir, - local_files_only: isBrowser() ? false : this.options.localFilesOnly, - dtype: this.options.dtype, - session_options: { - enableCpuMemArena: false, - enableMemPattern: false, - interOpNumThreads: 2, - intraOpNumThreads: 2 - } -} -``` - -## Testing Memory Optimizations - -### Before Optimizations: -```bash -# Uses 4-8GB -node test-quick.js -# CRASH: JavaScript heap out of memory -``` - -### After Optimizations: -```bash -# Should use 1-2GB -ORT_DISABLE_MEMORY_ARENA=1 node test-quick.js -# SUCCESS: Tests pass -``` - -## Performance Impact - -| Optimization | Memory Reduction | Speed Impact | Quality Impact | -|-------------|-----------------|--------------|----------------| -| Quantization (q8) | 75% | ~5% slower | <1% accuracy loss | -| Disable Arena | 30-50% | No impact | None | -| Batch Size 10 | 20% | 10% slower | None | -| Thread Limit | 10-20% | 20% slower | None | -| Model Unload | 100% when idle | Reload delay | None | - -## Conclusion - -**Immediate Action**: -1. Use q8 quantization -2. Disable memory arena -3. Reduce batch size - -This should reduce memory usage from 4-8GB to **1-2GB** with minimal performance impact. - -**Long-term Solution**: -- Implement model unloading -- Pre-compute common embeddings -- Consider using ONNX Runtime Web for lighter footprint \ No newline at end of file diff --git a/docs/api-design-archive/API-CRITICAL-FIXES.md b/docs/api-design-archive/API-CRITICAL-FIXES.md deleted file mode 100644 index 4a004e4f..00000000 --- a/docs/api-design-archive/API-CRITICAL-FIXES.md +++ /dev/null @@ -1,95 +0,0 @@ -# ๐Ÿšจ CRITICAL API FIXES NEEDED FOR BRAINY 2.0 - -## 1. โŒ WRONG: MongoDB Operators (Legal Risk!) -We accidentally introduced MongoDB-style operators which we specifically avoided for legal reasons! - -### MUST REPLACE: -```typescript -// โŒ WRONG (MongoDB style) -where: { - field: {$in: [values]}, - field: {$gt: value}, - field: {$regex: pattern} -} - -// โœ… CORRECT (Brainy style) -where: { - field: {oneOf: [values]}, - field: {greaterThan: value}, - field: {matches: pattern} -} -``` - -### Complete Operator Mapping: -- `$eq` โ†’ `equals` or `is` -- `$ne` โ†’ `notEquals` -- `$gt` โ†’ `greaterThan` -- `$gte` โ†’ `greaterEqual` -- `$lt` โ†’ `lessThan` -- `$lte` โ†’ `lessEqual` -- `$in` โ†’ `oneOf` -- `$nin` โ†’ `notOneOf` -- `$regex` โ†’ `matches` -- `$contains` โ†’ `contains` -- (NEW) โ†’ `startsWith` -- (NEW) โ†’ `endsWith` -- (NEW) โ†’ `between` - -## 2. ๐Ÿ“Š Missing Neural API Features -The backup shows we had extensive neural capabilities: - -```typescript -brain.neural.similar(a, b) // Semantic similarity -brain.neural.clusters() // Auto-clustering -brain.neural.hierarchy(id) // Semantic hierarchy -brain.neural.neighbors(id) // Neighbor graph -brain.neural.outliers() // Outlier detection -brain.neural.semanticPath(a, b) // Path finding -brain.neural.visualize() // Visualization data -``` - -## 3. ๐Ÿ”„ Missing Triple Intelligence Features -We need to ensure Triple Intelligence has all its features: -- Query optimization -- Progressive filtering -- Parallel execution -- Query learning/caching -- Explanations - -## 4. ๐Ÿงฉ Missing Augmentation Features -- Synapses (Notion, Slack, Salesforce connectors) -- Conduits (Brainy-to-Brainy sync) -- Real-time bidirectional sync - -## 5. ๐Ÿ“ฅ Missing Import/Export Features -- Neural import with entity extraction -- CSV import with AI parsing -- JSON flattening and structure detection -- Batch neural processing - -## 6. ๐ŸŽฏ API Simplification Issues -While simplifying, we may have lost: -- Verb scoring intelligence -- Clustering management -- Performance monitoring -- Health checks -- Statistics collection - -## 7. ๐Ÿ” Search Method Confusion -Need to clarify: -- `search(query)` = simple convenience for `find({like: query})` -- `find(query)` = full Triple Intelligence -- Remove duplicate methods like `searchByNounTypes`, etc. - -## IMMEDIATE ACTIONS: -1. Replace ALL MongoDB operators with Brainy operators -2. Restore neural API with all methods -3. Ensure Triple Intelligence is complete -4. Verify augmentation system works -5. Test import/export capabilities -6. Document the clean API properly - -## BACKUP LOCATIONS: -- `/home/dpsifr/Projects/BACKUP/brainy (Copy)` - Full backup -- `/home/dpsifr/Projects/BACKUP/brainy-clean` - Clean version -- `/home/dpsifr/Projects/brainy (Copy)` - Another backup \ No newline at end of file diff --git a/docs/api-design-archive/API-QUICK-REFERENCE.md b/docs/api-design-archive/API-QUICK-REFERENCE.md deleted file mode 100644 index 4a843433..00000000 --- a/docs/api-design-archive/API-QUICK-REFERENCE.md +++ /dev/null @@ -1,62 +0,0 @@ -# ๐Ÿง  Brainy 2.0 Quick Reference Card - -## Core Operations -```typescript -// Nouns -await brain.addNoun(vector, metadata) // Create -await brain.getNoun(id) // Read -await brain.updateNoun(id, vector?, meta?) // Update -await brain.deleteNoun(id) // Delete - -// Verbs -await brain.addVerb(source, target, type) // Create relationship -await brain.getVerb(id) // Get relationship -await brain.deleteVerb(id) // Delete relationship - -// Metadata -await brain.getNounMetadata(id) // Get metadata only -await brain.updateNounMetadata(id, meta) // Update metadata only -await brain.hasNoun(id) // Check existence -``` - -## Search -```typescript -await brain.search(query, k?) // Vector search -await brain.searchText('natural language') // NLP search -await brain.findSimilar(id, k?) // Similarity search -await brain.find(tripleQuery) // Triple Intelligence ๐Ÿง  -``` - -## Graph -```typescript -await brain.getConnections(id) // All connections -await brain.getVerbsBySource(id) // Outgoing -await brain.getVerbsByTarget(id) // Incoming -await brain.getVerbsByType(type) // By type -``` - -## Management -```typescript -brain.getCacheStats() // Cache stats -brain.clearCache() // Clear cache -brain.size() // Total count -await brain.getStats() // All statistics -await brain.clear() // Clear all data -``` - -## Lifecycle -```typescript -const brain = new BrainyData() // Create -await brain.init() // Initialize -await brain.shutdown() // Cleanup -``` - -## Configuration -```typescript -new BrainyData({ - storage: 'auto', // auto | memory | filesystem | s3 - cache: true, // Enable caching - index: true, // Enable indexing - dimensions: 384 // Vector dimensions -}) -``` \ No newline at end of file diff --git a/docs/api-design-archive/API-REFERENCE.md b/docs/api-design-archive/API-REFERENCE.md deleted file mode 100644 index bbb3f3c1..00000000 --- a/docs/api-design-archive/API-REFERENCE.md +++ /dev/null @@ -1,277 +0,0 @@ -# ๐Ÿง  Brainy 2.0 API Reference - -> **Philosophy**: Every method is specific, clear, and purposeful. No ambiguity, no duplicates. - -## ๐Ÿ“š Core Data Operations - -### Nouns (Vectors with Metadata) -```typescript -// Create -await brain.addNoun(vector, metadata) // Add single noun -await brain.addNouns(items[]) // Add multiple nouns - -// Read -await brain.getNoun(id) // Get single noun -await brain.getNouns(filter?) // Get multiple nouns -await brain.getNounWithVerbs(id) // Get noun + relationships - -// Update -await brain.updateNoun(id, vector?, metadata?) // Update noun -await brain.updateNounMetadata(id, metadata) // Update metadata only - -// Delete -await brain.deleteNoun(id) // Delete single noun -await brain.deleteNouns(ids[]) // Delete multiple nouns -``` - -### Verbs (Relationships) -```typescript -// Create -await brain.addVerb(source, target, type, metadata?) // Add relationship - -// Read -await brain.getVerb(id) // Get single verb -await brain.getVerbs(filter?) // Get multiple verbs -await brain.getVerbsBySource(sourceId) // Get outgoing relationships -await brain.getVerbsByTarget(targetId) // Get incoming relationships -await brain.getVerbsByType(type) // Get by relationship type - -// Delete -await brain.deleteVerb(id) // Delete relationship -await brain.deleteVerbs(ids[]) // Delete multiple relationships -``` - -## ๐Ÿ” Search Operations - -### Vector Search -```typescript -await brain.search(query, k?, options?) // Primary search method -await brain.searchText(text, k?, options?) // Natural language search -await brain.findSimilar(id, k?, options?) // Find similar to existing noun -await brain.searchWithCursor(query, cursor) // Paginated search -``` - -### Advanced Search -```typescript -await brain.searchByNounTypes(types[], query) // Filter by noun types -await brain.searchByMetadata(filter, query?) // Filter by metadata -await brain.searchWithinNouns(ids[], query) // Search within specific nouns -``` - -### Triple Intelligence ๐Ÿง  -```typescript -await brain.find(query) // Unified Vector + Graph + Metadata search -// Examples: -await brain.find('documents about AI') // Natural language -await brain.find({ like: 'sample-id' }) // Similar to ID -await brain.find({ where: { type: 'doc' }}) // Metadata filter -await brain.find({ connected: { to: id }}) // Graph traversal -``` - -## ๐Ÿ•ธ๏ธ Graph Operations - -```typescript -await brain.getConnections(id, depth?) // Get all connections -await brain.findPath(sourceId, targetId) // Find path between nouns -await brain.getNeighbors(id, hops?) // Get graph neighbors -``` - -## ๐Ÿ“Š Metadata & Filtering - -```typescript -await brain.getNounMetadata(id) // Get metadata only -await brain.getFilterableFields() // Get indexed fields -await brain.getFieldValues(field) // Get unique values for field -``` - -## ๐Ÿš€ Performance & Optimization - -### Cache Management -```typescript -brain.getCacheStats() // Get cache statistics -brain.clearCache() // Clear search cache -``` - -### Statistics -```typescript -await brain.getStats() // Complete statistics -await brain.getServiceStats(service?) // Service-specific stats -brain.getHealthStatus() // System health -brain.size() // Total noun count -``` - -### Intelligent Features -```typescript -// Verb Scoring -await brain.trainVerbScoring(feedback) // Provide training feedback -brain.getVerbScoringStats() // Get scoring statistics - -// Real-time Updates -brain.enableRealtimeUpdates(config) // Enable live sync -brain.disableRealtimeUpdates() // Disable live sync -await brain.syncNow() // Manual sync -``` - -## ๐ŸŒ Distributed Operations - -```typescript -// Remote Connections -await brain.connectRemote(url, options?) // Connect to remote instance -await brain.disconnectRemote() // Disconnect from remote -brain.isRemoteConnected() // Check connection status - -// Search Modes -await brain.searchLocal(query) // Search local only -await brain.searchRemote(query) // Search remote only -await brain.searchHybrid(query) // Search both - -// Operational Modes -brain.setReadOnly(enabled) // Toggle read-only mode -brain.setWriteOnly(enabled) // Toggle write-only mode -brain.freeze() // Freeze all modifications -brain.unfreeze() // Unfreeze modifications -``` - -## ๐Ÿ’พ Import/Export - -```typescript -await brain.backup() // Create full backup -await brain.restore(backup) // Restore from backup -await brain.importData(data, format) // Import external data -await brain.exportData(format) // Export data -``` - -## ๐Ÿงน Data Management - -```typescript -await brain.clearNouns(options?) // Clear all nouns -await brain.clearVerbs(options?) // Clear all verbs -await brain.clearAll(options?) // Clear everything -await brain.rebuildIndex() // Rebuild metadata index -``` - -## ๐Ÿ”ง Utilities - -```typescript -// Embeddings -await brain.embed(text) // Generate embedding -await brain.embedBatch(texts[]) // Batch embeddings - -// Similarity -await brain.calculateSimilarity(a, b) // Compare vectors -await brain.calculateDistance(a, b, metric?) // Calculate distance - -// Encryption (if configured) -await brain.encrypt(data) // Encrypt data -await brain.decrypt(data) // Decrypt data -``` - -## ๐ŸŽฏ Lifecycle - -```typescript -// Initialization -const brain = new BrainyData(config?) // Create instance -await brain.init() // Initialize (required!) - -// Cleanup -await brain.shutdown() // Graceful shutdown -await brain.cleanup() // Clean up resources -``` - -## โšก Static Methods - -```typescript -// Model Management -await BrainyData.preloadModel(options?) // Preload ML model -await BrainyData.warmup(options?) // Warmup system - -// Utilities -BrainyData.version // Get version -BrainyData.checkEnvironment() // Check environment support -``` - -## ๐ŸŽจ Configuration - -```typescript -const brain = new BrainyData({ - // Storage - storage: 'memory' | 'filesystem' | 's3' | 'auto', - - // Performance - cache: true, // Enable caching - index: true, // Enable metadata indexing - metrics: true, // Enable metrics collection - - // Distributed - distributed: { - mode: 'reader' | 'writer' | 'hybrid', - partitions: 8 - }, - - // Advanced - dimensions: 384, // Vector dimensions - similarity: 'cosine', // Similarity metric - verbose: false // Logging verbosity -}) -``` - -## ๐Ÿ“ Quick Examples - -```typescript -// Simple usage -const brain = new BrainyData() -await brain.init() - -// Add data -const id = await brain.addNoun(vector, { - title: 'My Document', - type: 'article' -}) - -// Search -const results = await brain.search('AI research', 10) - -// Graph relationships -await brain.addVerb(id1, id2, 'references') -const connections = await brain.getConnections(id1) - -// Triple Intelligence -const insights = await brain.find({ - like: 'sample-doc', - where: { type: 'article' }, - connected: { to: id1, via: 'references' } -}) - -// Cleanup -await brain.shutdown() -``` - -## ๐Ÿšจ Important: No Aliases! - -Brainy 2.0 follows a **ONE METHOD, ONE PURPOSE** philosophy: -- No duplicate methods -- No confusing aliases -- Clear, specific naming -- If you need the old methods for migration, they're now private - -## ๐Ÿš€ What Changed from 1.x - -### Now Private (Use New Methods) -- `add()` โ†’ Use `addNoun()` -- `get()` โ†’ Use `getNoun()` -- `delete()` โ†’ Use `deleteNoun()` -- `update()` โ†’ Use `updateNoun()` -- `updateMetadata()` โ†’ Use `updateNounMetadata()` -- `getMetadata()` โ†’ Use `getNounMetadata()` -- `relate()` / `connect()` โ†’ Use `addVerb()` -- `has()` / `exists()` โ†’ Use `hasNoun()` -- `clearAll()` โ†’ Use `clear()` -- `addItem()` / `addToBoth()` โ†’ Removed - -### New in 2.0 -- `find()` - Triple Intelligence search -- `getNounWithVerbs()` - Get noun with relationships -- `searchText()` - Natural language search -- `trainVerbScoring()` - Intelligent scoring -- Real-time sync capabilities -- Distributed operations \ No newline at end of file diff --git a/docs/api-design-archive/BRAINY-2.0-COMPLETE-API.md b/docs/api-design-archive/BRAINY-2.0-COMPLETE-API.md deleted file mode 100644 index 43c5fd8b..00000000 --- a/docs/api-design-archive/BRAINY-2.0-COMPLETE-API.md +++ /dev/null @@ -1,220 +0,0 @@ -# ๐Ÿง  Brainy 2.0 Complete Public API - -> **Clean, Specific, Beautiful** - Every method has ONE clear purpose. - -## ๐Ÿ“š NOUNS (Vectors with Metadata) - -```typescript -// Single Operations -addNoun(vector, metadata?) // Add one noun -getNoun(id) // Get one noun by ID -updateNoun(id, vector?, metadata?) // Update entire noun -updateNounMetadata(id, metadata) // Update metadata only -getNounMetadata(id) // Get metadata only -getNounWithVerbs(id) // Get noun with all relationships -deleteNoun(id) // Delete one noun -hasNoun(id) // Check if noun exists - -// Batch Operations -addNouns(items[]) // Add multiple nouns -getNouns(idsOrOptions) // Get multiple nouns (unified method) - // getNouns(['id1', 'id2']) // Get by specific IDs - // getNouns({ filter: {...} }) // Get with filters - // getNouns({ limit: 10, offset: 20 }) // Get with pagination -deleteNouns(ids[]) // Delete multiple nouns -``` - -## ๐Ÿ”— VERBS (Relationships) - -```typescript -// Single Operations -addVerb(source, target, type, metadata?) // Create relationship -getVerb(id) // Get one verb by ID -deleteVerb(id) // Delete one verb - -// Batch Operations -addVerbs(verbs[]) // Add multiple relationships -getVerbs(filter?) // Get filtered verbs -getVerbsBySource(sourceId) // Get outgoing relationships -getVerbsByTarget(targetId) // Get incoming relationships -getVerbsByType(type) // Get by relationship type -deleteVerbs(ids[]) // Delete multiple verbs -``` - -## ๐Ÿ” SEARCH - -```typescript -// Core Search -search(query, k?, options?) // Primary vector search -searchText(text, k?, options?) // Natural language search -find(query) // Triple Intelligence (Vector+Graph+Metadata) ๐Ÿง  -findSimilar(id, k?, options?) // Find similar to existing noun - -// Advanced Search -searchByNounTypes(types[], query, k?) // Filter by noun types -searchWithinItems(query, ids[], k?) // Search within specific nouns -searchWithCursor(query, cursor) // Paginated search -searchByStandardField(field, value, k?) // Metadata-based search - -// Graph Search -searchVerbs(query, options?) // Search relationships -searchNounsByVerbs(conditions) // Find nouns by relationships - -// Distributed Search -searchLocal(query, k?) // Search local instance only -searchRemote(query, k?) // Search remote instance only -searchCombined(query, k?) // Search both local and remote -``` - -## ๐Ÿ“Š METADATA & FILTERING - -```typescript -getFilterFields() // Get all indexed fields -getFilterValues(field) // Get unique values for a field -getAvailableFieldNames() // Get available field names -getStandardFieldMappings() // Get standard field mappings -``` - -## ๐Ÿš€ PERFORMANCE & MONITORING - -```typescript -// Cache -getCacheStats() // Get cache statistics -clearCache() // Clear search cache - -// Statistics -size() // Total noun count -getStatistics(options?) // Comprehensive statistics -getServiceStatistics(service) // Per-service statistics -listServices() // List all services -flushStatistics() // Persist statistics to storage - -// Health -getHealthStatus() // System health check -status() // Full status report -``` - -## โš™๏ธ CONFIGURATION - -```typescript -// Operational Modes -isReadOnly() / setReadOnly(bool) // Read-only mode -isWriteOnly() / setWriteOnly(bool) // Write-only mode -isFrozen() / setFrozen(bool) // Freeze all modifications - -// Real-time Sync -enableRealtimeUpdates(config) // Enable live synchronization -disableRealtimeUpdates() // Disable synchronization -getRealtimeUpdateConfig() // Get current config -checkForUpdatesNow() // Manual sync trigger - -// Remote Connection -connectToRemoteServer(url, options?) // Connect to remote instance -disconnectFromRemoteServer() // Disconnect from remote -isConnectedToRemoteServer() // Check connection status -``` - -## ๐Ÿง  INTELLIGENCE - -```typescript -// Verb Scoring -provideFeedbackForVerbScoring(feedback) // Train relationship scoring -getVerbScoringStats() // Get scoring statistics -exportVerbScoringLearningData() // Export training data -importVerbScoringLearningData(data) // Import training data - -// Embeddings -embed(text) // Generate embedding vector -calculateSimilarity(a, b, metric?) // Calculate vector similarity -``` - -## ๐Ÿ’พ DATA MANAGEMENT - -```typescript -// Clear Operations -clear(options?) // Clear all data -clearNouns(options?) // Clear all nouns only -clearVerbs(options?) // Clear all verbs only - -// Backup & Restore -backup() // Create full backup -restore(backup) // Restore from backup - -// Import/Export -import(data, format) // Import external data -importSparseData(data) // Import sparse format - -// Index Management -rebuildMetadataIndex() // Rebuild metadata index -``` - -## ๐Ÿ”’ SECURITY - -```typescript -encryptData(data) // Encrypt data -decryptData(data) // Decrypt data -``` - -## ๐ŸŽฒ UTILITIES - -```typescript -generateRandomGraph(nodes, edges) // Generate test graph data -``` - -## ๐Ÿš€ LIFECYCLE - -```typescript -// Instance Methods -new BrainyData(config?) // Create instance -init() // Initialize (REQUIRED!) -shutDown() // Graceful shutdown -cleanup() // Clean up resources - -// Static Methods -BrainyData.preloadModel(options?) // Preload ML model -BrainyData.warmup(options?) // Warmup system -``` - -## ๐Ÿ“ PROPERTIES (Read-only) - -```typescript -dimensions // Vector dimensions -maxConnections // HNSW max connections -efConstruction // HNSW ef construction -initialized // Is initialized? -``` - ---- - -## ๐Ÿ“ Key Changes in 2.0 - -### โœ… Simplified & Unified -- `getNouns()` now handles ALL plural queries (by IDs, filters, or pagination) -- No more `getNounsByIds()`, `queryNouns()`, `getBatch()` - just `getNouns()` -- Clear singular vs plural: `getNoun()` for one, `getNouns()` for many - -### โœ… Specific Naming -- Always specify noun/verb: `addNoun()` not `add()` -- No aliases or duplicates -- One method, one purpose - -### โœ… Private Legacy Methods -These are now private (use new methods above): -- `add()`, `get()`, `delete()`, `update()` -- `relate()`, `connect()`, `has()`, `exists()` -- `getMetadata()`, `updateMetadata()` -- `addItem()`, `addToBoth()`, `addBatch()`, `getBatch()` - -### โœ… Triple Intelligence -- New `find()` method unifies Vector + Graph + Metadata search -- Most powerful search capability in one simple method - -### โœ… Zero-Configuration -- Everything works instantly with sensible defaults -- Optional configuration only for advanced users -- No complex setup required - -### โœ… Clean Architecture -- Augmentation system for extensibility -- All features included (no premium tiers) -- Beautiful developer experience \ No newline at end of file diff --git a/docs/api-design-archive/BRAINY-2.0-CORRECT-API.md b/docs/api-design-archive/BRAINY-2.0-CORRECT-API.md deleted file mode 100644 index 078692db..00000000 --- a/docs/api-design-archive/BRAINY-2.0-CORRECT-API.md +++ /dev/null @@ -1,268 +0,0 @@ -# ๐Ÿง  Brainy 2.0 CORRECT API Reference - -> **The actual API we need, with all features, correct operators, and proper methods** - -## ๐Ÿ“š CORE DATA OPERATIONS - -### Nouns (Vectors with Metadata) -```typescript -// Single Operations -addNoun(textOrVector, metadata?) // Auto-embeds text -getNoun(id) // Get one noun -updateNoun(id, textOrVector?, metadata?) // Update noun -deleteNoun(id) // Delete noun -hasNoun(id) // Check existence - -// Metadata -getNounMetadata(id) // Metadata only -updateNounMetadata(id, metadata) // Update metadata -getNounWithVerbs(id) // With relationships - -// Batch -addNouns(items[]) // Add multiple -getNouns(idsOrOptions) // Get multiple (unified) -deleteNouns(ids[]) // Delete multiple -``` - -### Verbs (Relationships) -```typescript -addVerb(source, target, type, metadata?) // Create relationship -getVerb(id) // Get verb -deleteVerb(id) // Delete verb -getVerbsBySource(sourceId) // Outgoing -getVerbsByTarget(targetId) // Incoming -getVerbsByType(type) // By type -``` - -## ๐Ÿ” SEARCH (Simplified & Powerful) - -```typescript -// Just TWO search methods: -search(query, k?) // Simple convenience -find(query) // TRIPLE INTELLIGENCE ๐Ÿง  -``` - -### Find Query Structure (with CORRECT Brainy Operators): -```typescript -find({ - // Vector search - like: 'text' | vector | {id: 'noun-id'}, - - // Metadata filtering with BRAINY OPERATORS (NOT MongoDB!) - where: { - // Direct equality - field: value, - - // Brainy operators (NO $ prefix!) - field: { - equals: value, // Exact match - notEquals: value, // Not equal - greaterThan: value, // Greater than - greaterEqual: value, // Greater or equal - lessThan: value, // Less than - lessEqual: value, // Less or equal - oneOf: [values], // In array (NOT $in) - notOneOf: [values], // Not in array - contains: value, // Contains (arrays/strings) - startsWith: value, // String starts with - endsWith: value, // String ends with - matches: pattern, // Pattern match (NOT $regex) - between: [min, max] // Between two values - } - }, - - // Graph traversal - connected: { - to: 'id', - from: 'id', - via: 'type', - depth: 2 - }, - - // Control - limit: 10, - offset: 0, - explain: true -}) -``` - -## ๐Ÿง  NEURAL API (Complete) - -```typescript -// Access via brain.neural -brain.neural.similar(a, b) // Semantic similarity -brain.neural.clusters(options?) // Auto-clustering -brain.neural.hierarchy(id) // Semantic hierarchy -brain.neural.neighbors(id, k?) // K nearest neighbors -brain.neural.outliers(threshold?) // Outlier detection -brain.neural.semanticPath(from, to) // Path finding -brain.neural.visualize(options?) // Visualization data - -// Enterprise performance methods -brain.neural.clusterFast(options?) // O(n) HNSW clustering -brain.neural.clusterLarge(options?) // Million-item clustering -brain.neural.clusterStream(options?) // Progressive streaming -``` - -### Visualization Data Format: -```typescript -brain.neural.visualize({ - maxNodes: 100, - dimensions: 2 | 3, - algorithm: 'force' | 'hierarchical' | 'radial', - includeEdges: true -}) - -// Returns: -{ - format: 'd3' | 'cytoscape' | 'graphml', - nodes: [{ - id: string, - x: number, - y: number, - z?: number, - label: string, - cluster?: number, - metadata: any - }], - edges: [{ - source: string, - target: string, - type: string, - weight?: number - }], - layout: { - dimensions: 2 | 3, - algorithm: string, - bounds: {min: [x,y,z], max: [x,y,z]} - } -} -``` - -## ๐Ÿ“ฅ NEURAL IMPORT (Simple & Powerful) - -```typescript -// One simple method for smart import -brain.neuralImport(data, options?) - -// Options: -{ - confidenceThreshold: 0.7, // Min confidence for entities - autoApply: false, // Auto-add to database - enableWeights: true, // Use confidence weights - previewOnly: false, // Just preview, don't import - skipDuplicates: true, // Skip existing entities - format?: 'auto' | 'csv' | 'json' | 'text' // Auto-detect by default -} - -// Returns: -{ - detectedEntities: [{ - suggestedId: string, - nounType: string, - confidence: number, - originalData: any - }], - detectedRelationships: [{ - sourceId: string, - targetId: string, - verbType: string, - confidence: number - }], - confidence: number, // Overall confidence - insights: string[], // AI insights - preview: string // Human-readable preview -} -``` - -## ๐ŸŽฏ VERB SCORING - -```typescript -brain.verbScoring.train(feedback) // Train model -brain.verbScoring.getScore(verbId) // Get score -brain.verbScoring.export() // Export training -brain.verbScoring.import(data) // Import training -brain.verbScoring.stats() // Statistics -``` - -## ๐Ÿ”„ SYNC & DISTRIBUTION - -### Conduits (Brainy-to-Brainy) -```typescript -brain.conduit.establish(url) // Connect to another Brainy -brain.conduit.sync() // Sync data -brain.conduit.close() // Disconnect -``` - -### Synapses (External Platforms) -```typescript -brain.synapse.notion.connect(config) // Notion integration -brain.synapse.slack.connect(config) // Slack integration -brain.synapse.salesforce.connect(config) // Salesforce -brain.synapse.custom(name, config) // Custom platform -``` - -## ๐Ÿ“Š MONITORING & STATS - -```typescript -brain.size() // Total nouns -brain.stats() // Full statistics -brain.health() // Health check -brain.cache.stats() // Cache stats -brain.cache.clear() // Clear cache -``` - -## ๐Ÿ’พ DATA MANAGEMENT - -```typescript -brain.clear(options?) // Clear all -brain.clearNouns() // Clear nouns only -brain.clearVerbs() // Clear verbs only -brain.backup() // Create backup -brain.restore(backup) // Restore -``` - -## ๐Ÿš€ LIFECYCLE - -```typescript -const brain = new BrainyData(config?) // Create -await brain.init() // Initialize (REQUIRED!) -await brain.shutdown() // Cleanup - -// Configuration -{ - storage: 'auto' | 'memory' | 'filesystem' | 's3', - dimensions: 384, - cache: true, - index: true, - augmentations: [] -} -``` - -## โš™๏ธ EMBEDDINGS - -```typescript -brain.embed(text) // Generate embedding -brain.similarity(a, b) // Calculate similarity -``` - -## ๐ŸŽฒ UTILITIES - -```typescript -brain.generateRandomGraph(nodes, edges) // Test data -``` - ---- - -## โœ… KEY CORRECTIONS FROM MISTAKES: - -1. **NO MongoDB operators** - We use Brainy operators (legal reasons) -2. **Neural API is complete** - All clustering, visualization methods -3. **Simple neuralImport** - One method, smart detection -4. **Visualization exports** - For D3, Cytoscape, GraphML -5. **search() is just convenience** - Not a complete alias -6. **find() has Triple Intelligence** - Vector + Graph + Metadata -7. **Proper operator names** - greaterThan not $gt -8. **Complete clustering API** - Fast, large, streaming options -9. **Synapses and Conduits** - External and internal sync -10. **Verb scoring** - Intelligent relationship scoring \ No newline at end of file diff --git a/docs/api-design-archive/BRAINY-2.0-DETAILED-API.md b/docs/api-design-archive/BRAINY-2.0-DETAILED-API.md deleted file mode 100644 index 1a5a701e..00000000 --- a/docs/api-design-archive/BRAINY-2.0-DETAILED-API.md +++ /dev/null @@ -1,376 +0,0 @@ -# ๐Ÿง  Brainy 2.0 Detailed API Reference - -> **Complete API with full parameter descriptions** - -## ๐Ÿ“š CORE DATA OPERATIONS - -### Nouns (Vectors with Metadata) - -#### `addNoun(textOrVector, metadata?)` -Add a single noun to the database -- **textOrVector**: `string | number[]` - Text to auto-embed OR pre-computed vector -- **metadata**: `object` (optional) - Associated metadata -- **Returns**: `Promise` - The ID of the created noun - -#### `getNoun(id)` -Retrieve a single noun by ID -- **id**: `string` - The noun's unique identifier -- **Returns**: `Promise` - The noun with vector and metadata - -#### `updateNoun(id, textOrVector?, metadata?)` -Update an existing noun -- **id**: `string` - The noun's ID to update -- **textOrVector**: `string | number[]` (optional) - New text/vector -- **metadata**: `object` (optional) - New metadata (merged with existing) -- **Returns**: `Promise` - -#### `deleteNoun(id)` -Delete a single noun -- **id**: `string` - The noun's ID to delete -- **Returns**: `Promise` - True if deleted - -#### `hasNoun(id)` -Check if a noun exists -- **id**: `string` - The noun's ID to check -- **Returns**: `Promise` - True if exists - -#### `getNounMetadata(id)` -Get only the metadata of a noun (no vector) -- **id**: `string` - The noun's ID -- **Returns**: `Promise` - Just the metadata - -#### `updateNounMetadata(id, metadata)` -Update only the metadata of a noun -- **id**: `string` - The noun's ID -- **metadata**: `object` - New metadata (replaces existing) -- **Returns**: `Promise` - -#### `getNounWithVerbs(id)` -Get a noun with all its relationships -- **id**: `string` - The noun's ID -- **Returns**: `Promise<{noun: VectorDocument, verbs: Verb[]}>` - Noun and relationships - -#### `addNouns(items[])` -Add multiple nouns in batch -- **items**: `Array<{vector: number[] | string, metadata?: object}>` - Array of nouns -- **Returns**: `Promise` - Array of created IDs - -#### `getNouns(idsOrOptions)` -Get multiple nouns (unified method) -- **idsOrOptions**: Can be one of: - - `string[]` - Array of IDs to fetch - - `{filter: object}` - Filter by metadata fields - - `{limit: number, offset: number}` - Pagination -- **Returns**: `Promise` - Array of nouns - -#### `deleteNouns(ids[])` -Delete multiple nouns -- **ids**: `string[]` - Array of IDs to delete -- **Returns**: `Promise` - Success status for each - ---- - -### Verbs (Relationships) - -#### `addVerb(source, target, type, metadata?)` -Create a relationship between nouns -- **source**: `string` - Source noun ID -- **target**: `string` - Target noun ID -- **type**: `string` - Relationship type (e.g., 'references', 'contains') -- **metadata**: `object` (optional) - Relationship metadata -- **Returns**: `Promise` - The verb ID - -#### `getVerb(id)` -Get a single relationship -- **id**: `string` - The verb's ID -- **Returns**: `Promise` - The relationship - -#### `deleteVerb(id)` -Delete a relationship -- **id**: `string` - The verb's ID -- **Returns**: `Promise` - True if deleted - -#### `getVerbsBySource(sourceId)` -Get all outgoing relationships from a noun -- **sourceId**: `string` - The source noun's ID -- **Returns**: `Promise` - Array of relationships - -#### `getVerbsByTarget(targetId)` -Get all incoming relationships to a noun -- **targetId**: `string` - The target noun's ID -- **Returns**: `Promise` - Array of relationships - -#### `getVerbsByType(type)` -Get all relationships of a specific type -- **type**: `string` - The relationship type -- **Returns**: `Promise` - Array of relationships - ---- - -## ๐Ÿ” SEARCH & INTELLIGENCE - -### Core Search Methods - -#### `search(query, k?)` -Simple vector similarity search (convenience wrapper) -- **query**: `string | number[]` - Text query or vector -- **k**: `number` (default: 10) - Number of results -- **Returns**: `Promise` - Ranked results with scores -- **Note**: Equivalent to `find({like: query, limit: k})` - -#### `find(query)` -**TRIPLE INTELLIGENCE** - The ultimate search method -- **query**: `object` - Complex query object supporting: - ```typescript - { - // Vector similarity - like?: string | number[] | {id: string}, // Text, vector, or noun ID - - // Metadata filtering - where?: { - field: value, // Exact match - field: {$in: [values]}, // In array - field: {$gt: value}, // Greater than - field: {$regex: pattern} // Pattern match - }, - - // Graph traversal - connected?: { - to?: string, // Target noun ID - from?: string, // Source noun ID - via?: string, // Relationship type - depth?: number // Traversal depth (default: 1) - }, - - // Control - limit?: number, // Max results (default: 10) - offset?: number, // Skip results - threshold?: number // Min similarity score - } - ``` -- **Returns**: `Promise` - Results with scores and explanations - -#### `findSimilar(id, k?)` -Find nouns similar to an existing noun -- **id**: `string` - Reference noun ID -- **k**: `number` (default: 10) - Number of results -- **Returns**: `Promise` - Similar nouns - ---- - -### Neural API - -#### `neural.search(query, options?)` -Neural-enhanced semantic search -- **query**: `string` - Natural language query -- **options**: `{expand?: boolean, rerank?: boolean}` - Enhancement options -- **Returns**: `Promise` - Enhanced results - -#### `neural.cluster(options?)` -Automatic clustering of nouns -- **options**: `{k?: number, method?: 'kmeans'|'dbscan', minSize?: number}` -- **Returns**: `Promise` - Generated clusters - -#### `neural.extract(text)` -Extract entities from text -- **text**: `string` - Text to analyze -- **Returns**: `Promise<{entities: Entity[], relationships: Relationship[]}>` - -#### `neural.summarize(ids[])` -Generate summary from multiple nouns -- **ids**: `string[]` - Noun IDs to summarize -- **Returns**: `Promise` - Generated summary - -#### `neural.analyze(id)` -Deep analysis of a noun -- **id**: `string` - Noun ID to analyze -- **Returns**: `Promise` - Detailed analysis - -#### `neural.compare(id1, id2)` -Semantic comparison of two nouns -- **id1**: `string` - First noun ID -- **id2**: `string` - Second noun ID -- **Returns**: `Promise<{similarity: number, differences: string[], commonalities: string[]}>` - -#### `neural.topics(options?)` -Topic modeling across all nouns -- **options**: `{k?: number, method?: 'lda'|'nmf'}` - Topic extraction options -- **Returns**: `Promise` - Discovered topics - -#### `neural.patterns(options?)` -Pattern detection in data -- **options**: `{minSupport?: number, minConfidence?: number}` -- **Returns**: `Promise` - Detected patterns - ---- - -## ๐Ÿ“ฅ IMPORT/EXPORT - -### Neural Import - -#### `neuralImport(data, options?)` -Smart AI-powered data import -- **data**: `any` - Data to import (auto-detects format) -- **options**: `{autoExtract?: boolean, autoRelate?: boolean, batchSize?: number}` -- **Returns**: `Promise<{nouns: string[], verbs: string[]}>` - -#### `neuralImport.csv(file, options?)` -Import CSV with intelligent parsing -- **file**: `string | Buffer` - CSV file path or content -- **options**: `{headers?: boolean, delimiter?: string, embedColumns?: string[]}` -- **Returns**: `Promise` - -#### `neuralImport.json(data, options?)` -Import JSON with structure detection -- **data**: `object | string` - JSON data or string -- **options**: `{flatten?: boolean, keyPaths?: string[]}` -- **Returns**: `Promise` - -#### `neuralImport.text(text, options?)` -Import text with NLP processing -- **text**: `string` - Raw text -- **options**: `{chunk?: boolean, chunkSize?: number, extractEntities?: boolean}` -- **Returns**: `Promise` - ---- - -## ๐Ÿ”„ SYNC & DISTRIBUTION - -### Real-time Sync - -#### `sync.enable(config)` -Enable real-time synchronization -- **config**: `{url: string, interval?: number, bidirectional?: boolean}` -- **Returns**: `Promise` - -#### `sync.disable()` -Disable synchronization -- **Returns**: `Promise` - -#### `sync.now()` -Trigger manual sync -- **Returns**: `Promise` - -#### `sync.status()` -Get sync status -- **Returns**: `Promise<{enabled: boolean, lastSync: Date, pending: number}>` - ---- - -### Remote Operations - -#### `remote.connect(url, options?)` -Connect to remote Brainy instance -- **url**: `string` - Remote instance URL -- **options**: `{auth?: string, timeout?: number, retry?: boolean}` -- **Returns**: `Promise` - -#### `remote.search(query)` -Search remote instance -- **query**: `any` - Same as find() query -- **Returns**: `Promise` - ---- - -## ๐Ÿง  INTELLIGENCE FEATURES - -### Verb Scoring - -#### `verbScoring.train(feedback)` -Train the verb scoring model -- **feedback**: `{verbId: string, score: number, context?: object}` -- **Returns**: `Promise` - -#### `verbScoring.getScore(verbId)` -Get intelligent score for a verb -- **verbId**: `string` - The verb to score -- **Returns**: `Promise` - Score between 0-1 - -#### `verbScoring.export()` -Export training data -- **Returns**: `Promise` - -#### `verbScoring.import(data)` -Import training data -- **data**: `TrainingData` - Previously exported data -- **Returns**: `Promise` - ---- - -### Embeddings - -#### `embed(text)` -Generate embedding vector for text -- **text**: `string` - Text to embed -- **Returns**: `Promise` - Embedding vector - -#### `embedBatch(texts[])` -Generate embeddings for multiple texts -- **texts**: `string[]` - Array of texts -- **Returns**: `Promise` - Array of vectors - -#### `similarity(a, b, metric?)` -Calculate similarity between vectors or texts -- **a**: `string | number[]` - First item -- **b**: `string | number[]` - Second item -- **metric**: `'cosine' | 'euclidean' | 'manhattan'` (default: 'cosine') -- **Returns**: `Promise` - Similarity score - ---- - -## ๐Ÿ“Š MONITORING & PERFORMANCE - -#### `size()` -Get total noun count -- **Returns**: `number` - Total nouns in database - -#### `stats()` -Get comprehensive statistics -- **Returns**: `Promise` - Detailed stats - -#### `health()` -System health check -- **Returns**: `Promise<{status: 'healthy'|'degraded'|'unhealthy', details: object}>` - -#### `cache.stats()` -Get cache statistics -- **Returns**: `CacheStats` - Hit rates, size, etc. - -#### `cache.clear()` -Clear all caches -- **Returns**: `void` - ---- - -## ๐Ÿš€ LIFECYCLE - -#### `new BrainyData(config?)` -Create new Brainy instance -- **config**: `object` (optional) - ```typescript - { - storage?: 'auto' | 'memory' | 'filesystem' | 's3', - dimensions?: number, // Vector dimensions (default: 384) - cache?: boolean, // Enable caching (default: true) - index?: boolean, // Enable indexing (default: true) - verbose?: boolean, // Verbose logging (default: false) - augmentations?: Augmentation[] // Custom augmentations - } - ``` - -#### `init()` -Initialize the instance (REQUIRED!) -- **Returns**: `Promise` -- **Note**: Must be called before any operations - -#### `shutdown()` -Graceful shutdown -- **Returns**: `Promise` - Saves state and closes connections - ---- - -## ๐Ÿ“ READ-ONLY PROPERTIES - -- **dimensions**: `number` - Vector dimensions -- **initialized**: `boolean` - Whether init() was called -- **mode**: `string` - Current operational mode \ No newline at end of file diff --git a/docs/api-design-archive/BRAINY-2.0-FINAL-API.md b/docs/api-design-archive/BRAINY-2.0-FINAL-API.md deleted file mode 100644 index ff6cdeab..00000000 --- a/docs/api-design-archive/BRAINY-2.0-FINAL-API.md +++ /dev/null @@ -1,260 +0,0 @@ -# ๐Ÿง  Brainy 2.0 Final Complete API - -> **Clean, Powerful, Complete** - All features, beautifully organized. - -## ๐Ÿ“š CORE DATA - -### Nouns (Vectors with Metadata) -```typescript -// Single Operations -addNoun(textOrVector, metadata?) // Add noun (auto-embeds text!) -getNoun(id) // Get one noun -updateNoun(id, textOrVector?, metadata?) // Update noun -deleteNoun(id) // Delete noun -hasNoun(id) // Check if exists - -// Metadata Operations -getNounMetadata(id) // Get metadata only -updateNounMetadata(id, metadata) // Update metadata only -getNounWithVerbs(id) // Get noun with relationships - -// Batch Operations -addNouns(items[]) // Add multiple nouns -getNouns(idsOrOptions) // Get multiple nouns (unified) -deleteNouns(ids[]) // Delete multiple nouns -``` - -### Verbs (Relationships) -```typescript -addVerb(source, target, type, metadata?) // Create relationship -getVerb(id) // Get verb -deleteVerb(id) // Delete verb -getVerbsBySource(sourceId) // Outgoing relationships -getVerbsByTarget(targetId) // Incoming relationships -getVerbsByType(type) // By relationship type -``` - -## ๐Ÿ” SEARCH & INTELLIGENCE - -### Core Search -```typescript -search(query, k?) // Simple vector search -find(query) // TRIPLE INTELLIGENCE ๐Ÿง  -findSimilar(id, k?) // Find similar to noun -``` - -### Neural API -```typescript -neural.search(query) // Neural-enhanced search -neural.cluster(options?) // Automatic clustering -neural.extract(text) // Entity extraction -neural.summarize(ids[]) // Summarize nouns -neural.analyze(id) // Deep analysis -neural.compare(id1, id2) // Semantic comparison -neural.topics() // Topic modeling -neural.patterns() // Pattern detection -``` - -### Clustering -```typescript -clusters.create(options?) // Create clusters -clusters.get(id) // Get cluster -clusters.list() // List all clusters -clusters.addToCluster(clusterId, nounId) // Add to cluster -clusters.optimize() // Re-optimize clusters -clusters.suggest(nounId) // Suggest best cluster -``` - -## ๐Ÿง  INTELLIGENCE FEATURES - -### Triple Intelligence -```typescript -tripleIntelligence.analyze(query) // Combined V+G+F analysis -tripleIntelligence.explain(results) // Explain search results -tripleIntelligence.optimize(query) // Query optimization -``` - -### Verb Scoring -```typescript -verbScoring.train(feedback) // Train scoring model -verbScoring.getScore(verb) // Get verb score -verbScoring.export() // Export training data -verbScoring.import(data) // Import training data -verbScoring.stats() // Get statistics -``` - -### Embeddings -```typescript -embed(text) // Generate embedding -embedBatch(texts[]) // Batch embeddings -similarity(a, b) // Calculate similarity -distance(a, b, metric?) // Calculate distance -``` - -## ๐Ÿ“ฅ IMPORT/EXPORT - -### Neural Import -```typescript -neuralImport(data, options?) // Smart data import -neuralImport.csv(file, options?) // Import CSV with AI -neuralImport.json(data, options?) // Import JSON with AI -neuralImport.text(text, options?) // Import text with NLP -neuralImport.url(url, options?) // Import from URL -neuralImport.batch(items[], options?) // Batch neural import -``` - -### Data Management -```typescript -import(data, format) // Standard import -export(format) // Export data -importSparse(data) // Import sparse format -backup() // Create backup -restore(backup) // Restore backup -``` - -## ๐Ÿ”„ SYNC & DISTRIBUTION - -### Real-time Sync -```typescript -sync.enable(config) // Enable real-time sync -sync.disable() // Disable sync -sync.now() // Manual sync -sync.status() // Sync status -``` - -### Remote Operations -```typescript -remote.connect(url, options?) // Connect to remote -remote.disconnect() // Disconnect -remote.search(query) // Search remote -remote.sync() // Sync with remote -``` - -### Conduits (Brainy-to-Brainy) -```typescript -conduit.establish(url) // Create conduit -conduit.send(data) // Send via conduit -conduit.receive(callback) // Receive data -conduit.close() // Close conduit -``` - -### Synapses (External Platforms) -```typescript -synapse.notion.connect(config) // Connect to Notion -synapse.slack.connect(config) // Connect to Slack -synapse.salesforce.connect(config) // Connect to Salesforce -synapse.custom(platform, config) // Custom platform -``` - -## ๐Ÿ“Š ANALYTICS & MONITORING - -### Statistics -```typescript -size() // Total count -stats() // Full statistics -stats.byService(service) // Per-service stats -stats.byType(type) // Per-type stats -health() // Health check -``` - -### Performance -```typescript -cache.stats() // Cache statistics -cache.clear() // Clear cache -cache.optimize() // Optimize cache -index.rebuild() // Rebuild index -index.optimize() // Optimize index -``` - -### Monitoring -```typescript -monitor.enable() // Enable monitoring -monitor.metrics() // Get metrics -monitor.alerts() // Get alerts -monitor.logs(options?) // Get logs -``` - -## โš™๏ธ CONFIGURATION - -### Operational Modes -```typescript -setReadOnly(bool) // Read-only mode -setWriteOnly(bool) // Write-only mode -setFrozen(bool) // Freeze all changes -getMode() // Current mode -``` - -### Augmentations -```typescript -augmentations.register(augmentation) // Add augmentation -augmentations.list() // List all -augmentations.get(name) // Get by name -augmentations.enable(name) // Enable -augmentations.disable(name) // Disable -``` - -## ๐Ÿ”ง UTILITIES - -### Data Operations -```typescript -clear(options?) // Clear all -clearNouns() // Clear nouns -clearVerbs() // Clear verbs -generateRandomGraph(nodes, edges) // Generate test data -``` - -### Field Management -```typescript -fields.list() // List indexed fields -fields.values(field) // Get unique values -fields.add(field) // Add field to index -fields.remove(field) // Remove from index -``` - -## ๐Ÿš€ LIFECYCLE - -```typescript -// Creation & Initialization -new BrainyData(config?) // Create instance -init() // Initialize (REQUIRED!) -warmup() // Warmup caches - -// Cleanup -shutdown() // Graceful shutdown -cleanup() // Clean resources - -// Static Methods -BrainyData.preloadModel() // Preload ML model -BrainyData.version // Get version -``` - -## ๐Ÿ“ PROPERTIES - -```typescript -dimensions // Vector dimensions (readonly) -initialized // Is initialized (readonly) -mode // Current mode (readonly) -``` - ---- - -## ๐ŸŽฏ Key Features Preserved - -โœ… **Neural Import** - Smart AI-powered data import -โœ… **Clustering** - Automatic and manual clustering -โœ… **Triple Intelligence** - Vector + Graph + Metadata combined -โœ… **Verb Scoring** - Intelligent relationship scoring -โœ… **Synapses** - External platform connectors -โœ… **Conduits** - Brainy-to-Brainy sync -โœ… **Neural API** - Advanced AI operations -โœ… **Real-time Sync** - Live data synchronization -โœ… **Monitoring** - Performance and health tracking - -## ๐Ÿš€ What's New in 2.0 - -1. **Auto-embedding** - `addNoun()` accepts text directly -2. **Unified `find()`** - One method for all complex queries -3. **Neural API** - Powerful AI operations built-in -4. **Augmentation System** - Extensible architecture -5. **Clean naming** - Specific noun/verb terminology -6. **No duplicates** - One method per operation \ No newline at end of file diff --git a/docs/api-design-archive/BRAINY-2.0-FINAL-CORRECT-API.md b/docs/api-design-archive/BRAINY-2.0-FINAL-CORRECT-API.md deleted file mode 100644 index 43a13d40..00000000 --- a/docs/api-design-archive/BRAINY-2.0-FINAL-CORRECT-API.md +++ /dev/null @@ -1,243 +0,0 @@ -# ๐Ÿง  Brainy 2.0 Final API Reference - -> **The definitive API - Clean, Correct, Complete** - -## โœ… KEY CORRECTIONS FROM REVIEW: -1. **Brainy Operators (NOT MongoDB)** - `greaterThan` not `$gt` -2. **Neural API is complete** - All methods available via `brain.neural` -3. **Code is correct** - Implementation uses right operators, just docs were wrong -4. **Nothing lost** - All features still present, just reorganized - ---- - -## ๐Ÿ“š CORE DATA OPERATIONS - -### Nouns -```typescript -// Single -addNoun(textOrVector, metadata?) // Auto-embeds text! -getNoun(id) -updateNoun(id, textOrVector?, metadata?) -deleteNoun(id) -hasNoun(id) - -// Metadata -getNounMetadata(id) -updateNounMetadata(id, metadata) -getNounWithVerbs(id) - -// Batch -addNouns(items[]) -getNouns(idsOrOptions) // Unified: IDs, filter, or pagination -deleteNouns(ids[]) -``` - -### Verbs -```typescript -addVerb(source, target, type, metadata?) -getVerb(id) -deleteVerb(id) -getVerbsBySource(sourceId) -getVerbsByTarget(targetId) -getVerbsByType(type) -``` - -## ๐Ÿ” SEARCH - -Just TWO methods - simple and powerful: - -```typescript -search(query, k?) // Convenience: same as find({like: query, limit: k}) -find(query) // TRIPLE INTELLIGENCE: Vector + Graph + Metadata -``` - -### Find Query (with CORRECT Brainy Operators): -```typescript -find({ - // Vector - like: 'text' | vector | {id: 'noun-id'}, - - // Fields (BRAINY operators, NOT MongoDB!) - where: { - field: value, // Direct equality - field: { - equals: value, - greaterThan: value, // NOT $gt - lessThan: value, // NOT $lt - greaterEqual: value, - lessEqual: value, - oneOf: [values], // NOT $in - notOneOf: [values], // NOT $nin - contains: value, - startsWith: value, - endsWith: value, - matches: pattern, // NOT $regex - between: [min, max] - } - }, - - // Graph - connected: { - to: 'id', - from: 'id', - via: 'type', - depth: 2 - }, - - // Control - limit: 10, - offset: 0, - explain: true -}) -``` - -## ๐Ÿง  NEURAL API - -Complete and available via `brain.neural`: - -```typescript -brain.neural.similar(a, b) // Similarity 0-1 -brain.neural.clusters() // Auto-clustering -brain.neural.hierarchy(id) // Semantic tree -brain.neural.neighbors(id, k?) // K-nearest -brain.neural.outliers(threshold?) // Outlier detection -brain.neural.semanticPath(from, to) // Path finding -brain.neural.visualize(options?) // For D3/Cytoscape/GraphML - -// Performance -brain.neural.clusterFast() // O(n) HNSW -brain.neural.clusterLarge() // Million+ items -brain.neural.clusterStream() // Progressive -``` - -### Visualization Format: -```typescript -brain.neural.visualize({ - maxNodes: 100, - dimensions: 2, - algorithm: 'force', - includeEdges: true -}) -// Returns: { -// format: 'd3' | 'cytoscape' | 'graphml', -// nodes: [...], edges: [...], layout: {...} -// } -``` - -## ๐Ÿ“ฅ IMPORT - -Simple, AI-powered: - -```typescript -brain.neuralImport(data, options?) // Auto-detects format! -// Options: { -// confidenceThreshold: 0.7, -// autoApply: false, -// skipDuplicates: true -// } -``` - -## ๐ŸŽฏ INTELLIGENCE - -```typescript -// Verb Scoring -provideFeedbackForVerbScoring(feedback) -getVerbScoringStats() -exportVerbScoringLearningData() -importVerbScoringLearningData(data) - -// Embeddings -embed(text) // Generate vector -calculateSimilarity(a, b, metric?) // Compare -``` - -## ๐Ÿ”„ SYNC - -```typescript -// Remote -connectToRemoteServer(url) -disconnectFromRemoteServer() -isConnectedToRemoteServer() - -// Real-time -enableRealtimeUpdates(config) -disableRealtimeUpdates() -checkForUpdatesNow() - -// Search modes -searchLocal(query, k?) -searchRemote(query, k?) -searchCombined(query, k?) -``` - -## ๐Ÿ“Š MONITORING - -```typescript -size() // Total nouns -getStatistics() // Full stats -getHealthStatus() // Health -getCacheStats() // Cache -clearCache() // Clear -``` - -## โš™๏ธ CONFIGURATION - -```typescript -// Modes -setReadOnly(bool) -setWriteOnly(bool) -setFrozen(bool) - -// Augmentations -augmentations.register(aug) -augmentations.list() -augmentations.get(name) -``` - -## ๐Ÿ’พ DATA MANAGEMENT - -```typescript -clear(options?) // Clear all -clearNouns() // Nouns only -clearVerbs() // Verbs only -backup() // Create backup -restore(backup) // Restore -rebuildMetadataIndex() // Rebuild index -``` - -## ๐Ÿš€ LIFECYCLE - -```typescript -const brain = new BrainyData({ - storage: 'auto', // auto | memory | filesystem | s3 - dimensions: 384, - cache: true, - index: true -}) - -await brain.init() // REQUIRED! -await brain.shutdown() // Cleanup - -// Static -BrainyData.preloadModel() // Preload -BrainyData.warmup() // Warmup -``` - ---- - -## โœจ What Makes Brainy 2.0 Special: - -1. **Zero-Config** - Works instantly, no setup -2. **Auto-Embedding** - Text automatically becomes vectors -3. **Triple Intelligence** - Vector + Graph + Metadata combined -4. **Brainy Operators** - Clean, legal, no MongoDB style -5. **Complete Neural API** - All clustering/viz features -6. **Simple Import** - One method, auto-detects everything -7. **Clean Architecture** - Augmentations for extensibility - -## ๐ŸŽฏ Remember: -- **NO $operators** - We use readable names (legal requirement) -- **search() is simple** - Just wraps find({like: query}) -- **find() is powerful** - Full Triple Intelligence -- **neural API complete** - All methods via brain.neural -- **Everything included** - No premium features, all MIT \ No newline at end of file diff --git a/docs/api-design-archive/BRAINY-2.0-SIMPLIFIED-API.md b/docs/api-design-archive/BRAINY-2.0-SIMPLIFIED-API.md deleted file mode 100644 index 8b283082..00000000 --- a/docs/api-design-archive/BRAINY-2.0-SIMPLIFIED-API.md +++ /dev/null @@ -1,149 +0,0 @@ -# ๐Ÿง  Brainy 2.0 Simplified Public API - -> **Ultra-clean, Simple, Powerful** - Minimal methods, maximum capability. - -## ๐Ÿ“š NOUNS (Data with Vectors) - -```typescript -// Single Operations -addNoun(textOrVector, metadata?) // Add noun (auto-embeds text!) -getNoun(id) // Get one noun -updateNoun(id, textOrVector?, metadata?) // Update noun -deleteNoun(id) // Delete noun -hasNoun(id) // Check if exists - -// Metadata Operations -getNounMetadata(id) // Get metadata only -updateNounMetadata(id, metadata) // Update metadata only -getNounWithVerbs(id) // Get noun with relationships - -// Batch Operations -addNouns(items[]) // Add multiple nouns -getNouns(idsOrOptions) // Get multiple nouns (unified) -deleteNouns(ids[]) // Delete multiple nouns -``` - -## ๐Ÿ”— VERBS (Relationships) - -```typescript -// Core Operations -addVerb(source, target, type, metadata?) // Create relationship -getVerb(id) // Get verb -deleteVerb(id) // Delete verb - -// Queries -getVerbsBySource(sourceId) // Outgoing relationships -getVerbsByTarget(targetId) // Incoming relationships -getVerbsByType(type) // By relationship type -``` - -## ๐Ÿ” SEARCH (One Method to Rule Them All) - -```typescript -// THE ONLY SEARCH METHODS YOU NEED: -search(query, k?) // Simple vector search (alias to find) -find(query) // TRIPLE INTELLIGENCE ๐Ÿง  -``` - -### Find Query Examples: -```typescript -// Text search (auto-embeds) -find('documents about AI') - -// Similar to existing noun -find({ like: 'noun-id-123' }) - -// Metadata filtering -find({ where: { type: 'article' }}) - -// Graph traversal -find({ connected: { to: 'id', via: 'references' }}) - -// Combined queries (Triple Intelligence!) -find({ - like: 'sample-doc', // Vector similarity - where: { status: 'published' }, // Metadata filter - connected: { via: 'cites' }, // Graph relationships - limit: 10 // Pagination -}) -``` - -## ๐Ÿ“Š METADATA - -```typescript -getFilterableFields() // Get indexed fields -getFieldValues(field) // Get unique values for field -``` - -## ๐Ÿš€ PERFORMANCE - -```typescript -// Cache -getCacheStats() // Cache statistics -clearCache() // Clear cache - -// Stats -size() // Total count -getStatistics() // Full statistics -getHealthStatus() // Health check -``` - -## โš™๏ธ CONFIGURATION - -```typescript -// Modes -setReadOnly(bool) // Read-only mode -setWriteOnly(bool) // Write-only mode -setFrozen(bool) // Freeze all changes - -// Remote Sync -connectRemote(url) // Connect to remote -disconnectRemote() // Disconnect -syncNow() // Manual sync -``` - -## ๐Ÿ’พ DATA MANAGEMENT - -```typescript -clear(options?) // Clear all -clearNouns() // Clear nouns -clearVerbs() // Clear verbs -backup() // Create backup -restore(backup) // Restore backup -``` - -## ๐Ÿš€ LIFECYCLE - -```typescript -new BrainyData(config?) // Create -init() // Initialize (REQUIRED!) -shutdown() // Cleanup -``` - ---- - -## ๐ŸŽฏ Philosophy - -### Why So Simple? - -1. **`addNoun()` handles everything** - Text? Auto-embeds. Vector? Uses directly. -2. **`find()` is the ultimate search** - Combines vector, graph, and metadata search -3. **`search()` is just convenience** - Simple alias to `find()` for basic queries -4. **No duplicate methods** - One way to do each thing - -### The Power of Find - -The `find()` method is your Swiss Army knife: -- Text search โ†’ Auto-embeds and searches -- Vector search โ†’ `{ like: 'id' }` or `{ like: vector }` -- Metadata search โ†’ `{ where: { field: value }}` -- Graph search โ†’ `{ connected: { to/from: 'id' }}` -- Combine them all โ†’ Triple Intelligence! - -### Zero Configuration - -Everything just works: -- Text auto-embeds -- Vectors auto-index -- Metadata auto-indexes -- Relationships auto-optimize \ No newline at end of file diff --git a/docs/api-design-archive/BRAINY-2.0-UNIFIED-API.md b/docs/api-design-archive/BRAINY-2.0-UNIFIED-API.md deleted file mode 100644 index 0adc2450..00000000 --- a/docs/api-design-archive/BRAINY-2.0-UNIFIED-API.md +++ /dev/null @@ -1,343 +0,0 @@ -# ๐Ÿง  Brainy 2.0 Unified Public API - -> **The complete, accurate API based on actual implementation** - -## ๐Ÿ“š CORE DATA OPERATIONS - -### Nouns (Vectors with Metadata) - -```typescript -// === SINGLE OPERATIONS === -addNoun(textOrVector, metadata?) // Add noun (auto-embeds text) -getNoun(id) // Get one noun -updateNoun(id, textOrVector?, metadata?) // Update noun -deleteNoun(id) // Delete noun -hasNoun(id) // Check if exists - -// === METADATA OPERATIONS === -getNounMetadata(id) // Get metadata only -updateNounMetadata(id, metadata) // Update metadata only -getNounWithVerbs(id) // Get noun with relationships - -// === BATCH OPERATIONS === -addNouns(items[]) // Add multiple nouns -getNouns(idsOrOptions) // Get multiple (unified method) - // getNouns(['id1', 'id2']) // By IDs - // getNouns({filter: {...}}) // By filter - // getNouns({limit: 10, offset: 20}) // Paginated -deleteNouns(ids[]) // Delete multiple -``` - -### Verbs (Relationships) - -```typescript -// === SINGLE OPERATIONS === -addVerb(source, target, type, metadata?) // Create relationship -getVerb(id) // Get verb -deleteVerb(id) // Delete verb - -// === QUERY OPERATIONS === -getVerbsBySource(sourceId) // Outgoing relationships -getVerbsByTarget(targetId) // Incoming relationships -getVerbsByType(type) // By relationship type -getVerbs(filter?) // Get filtered verbs -deleteVerbs(ids[]) // Delete multiple -``` - -## ๐Ÿ” SEARCH & INTELLIGENCE - -### Primary Search Methods - -```typescript -// === TWO MAIN METHODS === -search(query, k?) // Simple vector search - // Equivalent to: find({like: query, limit: k}) - -find(query) // TRIPLE INTELLIGENCE ๐Ÿง  - // Combines Vector + Graph + Metadata search -``` - -### Find Query Structure - -```typescript -find({ - // === VECTOR SEARCH === - like: 'text query' | vector | {id: 'noun-id'}, - similar: 'text' | vector, // Alternative to 'like' - - // === FIELD FILTERING (Brainy Operators) === - where: { - // Direct equality - field: value, - - // Brainy operators (CORRECT - NO MongoDB $) - field: { - equals: value, // Exact match - is: value, // Same as equals - greaterThan: value, // Greater than - lessThan: value, // Less than - oneOf: [values], // In array (NOT $in) - contains: value // Array/string contains - // Note: Additional operators can be added - } - }, - - // === GRAPH TRAVERSAL === - connected: { - to: 'id' | ['id1', 'id2'], // Target nodes - from: 'id' | ['id1', 'id2'], // Source nodes - type: 'type' | ['type1'], // Relationship types - depth: 2, // Traversal depth - direction: 'in' | 'out' | 'both' - }, - - // === CONTROL OPTIONS === - limit: 10, // Max results - offset: 0, // Skip results - explain: false, // Add explanations - boost: 'recent' | 'popular' // Result boosting -}) -``` - -## ๐Ÿง  NEURAL API - -Access via `brain.neural`: - -```typescript -// === SIMILARITY & CLUSTERING === -brain.neural.similar(a, b, options?) // Semantic similarity (0-1) -brain.neural.clusters(input?) // Auto-clustering -brain.neural.hierarchy(id) // Semantic hierarchy tree -brain.neural.neighbors(id, options?) // K-nearest neighbors - -// === ANALYSIS === -brain.neural.outliers(threshold?) // Outlier detection -brain.neural.semanticPath(from, to) // Find semantic path - -// === VISUALIZATION === -brain.neural.visualize(options?) // Export for visualization - // options: { - // maxNodes: 100, - // dimensions: 2 | 3, - // algorithm: 'force' | 'hierarchical' | 'radial', - // includeEdges: true - // } - // Returns: { - // format: 'd3' | 'cytoscape' | 'graphml', - // nodes: [...], edges: [...], layout: {...} - // } - -// === PERFORMANCE METHODS === -brain.neural.clusterFast(options?) // O(n) HNSW clustering -brain.neural.clusterLarge(options?) // Million+ items -brain.neural.clusterStream(options?) // Progressive streaming -``` - -## ๐Ÿ“ฅ IMPORT & EXPORT - -### Neural Import - -```typescript -// === SMART IMPORT (from cortex) === -brain.neuralImport(filePath, options?) // AI-powered import - // options: { - // confidenceThreshold: 0.7, - // autoApply: false, - // enableWeights: true, - // previewOnly: false, - // skipDuplicates: true - // } - // Returns: { - // detectedEntities: [...], - // detectedRelationships: [...], - // confidence: 0.85, - // insights: [...], - // preview: "..." - // } -``` - -### Standard Import/Export - -```typescript -import(data, format) // Standard import -importSparseData(data) // Sparse format import -backup() // Create full backup -restore(backup) // Restore from backup -``` - -## ๐ŸŽฏ VERB SCORING - -```typescript -// === INTELLIGENT SCORING === -provideFeedbackForVerbScoring(feedback) // Train model -getVerbScoringStats() // Get statistics -exportVerbScoringLearningData() // Export training -importVerbScoringLearningData(data) // Import training -``` - -## ๐Ÿ”„ SYNC & DISTRIBUTION - -### Remote Operations - -```typescript -// === REMOTE CONNECTION === -connectToRemoteServer(url, options?) // Connect to remote -disconnectFromRemoteServer() // Disconnect -isConnectedToRemoteServer() // Check status - -// === SEARCH MODES === -searchLocal(query, k?) // Local only -searchRemote(query, k?) // Remote only -searchCombined(query, k?) // Both sources -``` - -### Real-time Sync - -```typescript -enableRealtimeUpdates(config) // Enable sync -disableRealtimeUpdates() // Disable sync -getRealtimeUpdateConfig() // Get config -checkForUpdatesNow() // Manual sync -``` - -## ๐Ÿ“Š MONITORING & STATS - -```typescript -// === STATISTICS === -size() // Total noun count -getStatistics(options?) // Full statistics -getServiceStatistics(service) // Per-service stats -listServices() // List all services -flushStatistics() // Persist stats - -// === HEALTH & CACHE === -getHealthStatus() // System health -status() // Full status report -getCacheStats() // Cache statistics -clearCache() // Clear all caches -``` - -## โš™๏ธ CONFIGURATION - -### Operational Modes - -```typescript -// === MODE CONTROL === -isReadOnly() / setReadOnly(bool) // Read-only mode -isWriteOnly() / setWriteOnly(bool) // Write-only mode -isFrozen() / setFrozen(bool) // Freeze all changes -``` - -### Augmentations - -```typescript -// === AUGMENTATION SYSTEM === -augmentations.register(augmentation) // Add augmentation -augmentations.list() // List all -augmentations.get(name) // Get by name -``` - -## ๐Ÿ’พ DATA MANAGEMENT - -```typescript -// === CLEAR OPERATIONS === -clear(options?) // Clear all data -clearNouns(options?) // Clear nouns only -clearVerbs(options?) // Clear verbs only - -// === INDEX MANAGEMENT === -rebuildMetadataIndex() // Rebuild index -getFilterFields() // Get indexed fields -getFilterValues(field) // Get unique values -``` - -## ๐Ÿงฌ EMBEDDINGS & SIMILARITY - -```typescript -embed(text) // Generate embedding -calculateSimilarity(a, b, metric?) // Calculate similarity - // metric: 'cosine' | 'euclidean' | 'manhattan' -``` - -## ๐Ÿ”’ SECURITY - -```typescript -encryptData(data) // Encrypt data -decryptData(data) // Decrypt data -``` - -## ๐ŸŽฒ UTILITIES - -```typescript -generateRandomGraph(nodes, edges) // Generate test data -getAvailableFieldNames() // Get field names -getStandardFieldMappings() // Get field mappings -``` - -## ๐Ÿš€ LIFECYCLE - -```typescript -// === INITIALIZATION === -const brain = new BrainyData(config?) // Create instance -await brain.init() // Initialize (REQUIRED!) -await brain.shutDown() // Graceful shutdown -await brain.cleanup() // Clean resources - -// === STATIC METHODS === -BrainyData.preloadModel(options?) // Preload ML model -BrainyData.warmup(options?) // Warmup system -``` - -### Configuration Options - -```typescript -new BrainyData({ - // Storage - storage: 'auto' | 'memory' | 'filesystem' | 's3' | { - adapter: 'custom', - // ... storage options - }, - - // Vector configuration - dimensions: 384, // Vector dimensions - similarity: 'cosine', // Similarity metric - - // Performance - cache: true, // Enable caching - index: true, // Enable indexing - metrics: true, // Enable metrics - - // Advanced - augmentations: [...], // Custom augmentations - verbose: false // Logging verbosity -}) -``` - -## ๐Ÿ“ READ-ONLY PROPERTIES - -```typescript -brain.dimensions // Vector dimensions -brain.maxConnections // HNSW max connections -brain.efConstruction // HNSW ef construction -brain.initialized // Is initialized? -``` - ---- - -## โœ… KEY POINTS: - -1. **Brainy Operators** - NOT MongoDB style ($gt, $lt) -2. **Neural API** - Complete with visualization export -3. **Simple Search** - Just `search()` and `find()` -4. **Triple Intelligence** - Vector + Graph + Metadata in `find()` -5. **Auto-embedding** - `addNoun()` accepts text directly -6. **Unified Methods** - `getNouns()` handles all plural queries -7. **Clean Architecture** - Augmentation system for extensibility - -## โš ๏ธ IMPORTANT NOTES: - -- **NO MongoDB operators** - We use `greaterThan` not `$gt` (legal reasons) -- **Neural API is via brain.neural** - All clustering/viz methods available -- **search() is convenience** - Just wraps `find({like: query})` -- **find() is powerful** - Full Triple Intelligence capabilities -- **One import method** - `neuralImport()` auto-detects format \ No newline at end of file diff --git a/docs/api-design-archive/COMPLETE-PUBLIC-API.md b/docs/api-design-archive/COMPLETE-PUBLIC-API.md deleted file mode 100644 index ac94b2d4..00000000 --- a/docs/api-design-archive/COMPLETE-PUBLIC-API.md +++ /dev/null @@ -1,227 +0,0 @@ -# ๐Ÿง  Brainy 2.0 Complete Public API - -> **ONE METHOD, ONE PURPOSE** - No duplicates, no aliases, just clean specific methods. - -## ๐Ÿ“š NOUNS (Vectors with Metadata) - -### Single Operations -```typescript -addNoun(vector, metadata?) // Add one noun -getNoun(id) // Get one noun -updateNoun(id, vector?, metadata?) // Update noun -updateNounMetadata(id, metadata) // Update metadata only -getNounMetadata(id) // Get metadata only -deleteNoun(id) // Delete one noun -hasNoun(id) // Check if exists -getNounWithVerbs(id) // Get with relationships -``` - -### Batch Operations -```typescript -addNouns(items[]) // Add multiple nouns -getNounsByIds(ids[]) // Get multiple by IDs -deleteNouns(ids[]) // Delete multiple nouns -queryNouns(options) // Query with filters/pagination -``` - -## ๐Ÿ”— VERBS (Relationships) - -### Single Operations -```typescript -addVerb(source, target, type, metadata?) // Add relationship -getVerb(id) // Get one verb -deleteVerb(id) // Delete one verb -``` - -### Batch Operations -```typescript -addVerbs(verbs[]) // Add multiple verbs -getVerbs(filter?) // Get filtered verbs -deleteVerbs(ids[]) // Delete multiple verbs -getVerbsBySource(sourceId) // Get outgoing relationships -getVerbsByTarget(targetId) // Get incoming relationships -getVerbsByType(type) // Get by relationship type -``` - -## ๐Ÿ” SEARCH - -### Vector Search -```typescript -search(query, k?, options?) // Primary vector search -searchText(text, k?, options?) // Natural language search -findSimilar(id, k?, options?) // Find similar to noun -searchWithCursor(query, cursor) // Paginated search -``` - -### Advanced Search -```typescript -find(query) // Triple Intelligence ๐Ÿง  -searchByNounTypes(types[], query) // Filter by noun types -searchWithinItems(query, ids[], k?) // Search within specific nouns -searchVerbs(query) // Search relationships -searchNounsByVerbs(conditions) // Graph-based noun search -searchByStandardField(field, value) // Metadata-based search -``` - -### Distributed Search -```typescript -searchLocal(query) // Local only -searchRemote(query) // Remote only -searchCombined(query) // Both sources -``` - -## ๐Ÿ“Š GRAPH OPERATIONS - -```typescript -getConnections(id, depth?) // Get all connections -getVerbsBySource(sourceId) // Outgoing edges -getVerbsByTarget(targetId) // Incoming edges -getVerbsByType(type) // Filter by type -``` - -## ๐ŸŽฏ PERFORMANCE & STATS - -### Cache -```typescript -getCacheStats() // Cache statistics -clearCache() // Clear search cache -``` - -### Statistics -```typescript -size() // Total noun count -getStatistics(options?) // Complete statistics -getServiceStatistics(service) // Per-service stats -listServices() // List all services -flushStatistics() // Flush to storage -``` - -### Health & Status -```typescript -getHealthStatus() // System health -status() // Full status report -``` - -## ๐Ÿ”ง CONFIGURATION & MODES - -### Operational Modes -```typescript -isReadOnly() / setReadOnly(bool) // Read-only mode -isWriteOnly() / setWriteOnly(bool) // Write-only mode -isFrozen() / setFrozen(bool) // Freeze modifications -``` - -### Real-time Updates -```typescript -enableRealtimeUpdates(config) // Enable live sync -disableRealtimeUpdates() // Disable sync -getRealtimeUpdateConfig() // Get config -checkForUpdatesNow() // Manual sync -``` - -### Remote Connection -```typescript -connectToRemoteServer(url, options?) // Connect remote -disconnectFromRemoteServer() // Disconnect -isConnectedToRemoteServer() // Check connection -``` - -## ๐Ÿง  INTELLIGENCE FEATURES - -### Verb Scoring -```typescript -provideFeedbackForVerbScoring(feedback) // Train scoring -getVerbScoringStats() // Get statistics -exportVerbScoringLearningData() // Export training -importVerbScoringLearningData(data) // Import training -``` - -### Embeddings -```typescript -embed(text) // Generate embedding -calculateSimilarity(a, b) // Compare vectors -``` - -## ๐Ÿ’พ DATA MANAGEMENT - -### Clear Operations -```typescript -clear(options?) // Clear all data -clearNouns(options?) // Clear all nouns -clearVerbs(options?) // Clear all verbs -``` - -### Import/Export -```typescript -backup() // Create backup -restore(backup) // Restore backup -import(data, format) // Import data -importSparseData(data) // Import sparse -``` - -### Index Management -```typescript -rebuildMetadataIndex() // Rebuild index -getFilterFields() // Get indexed fields -getFilterValues(field) // Get field values -``` - -## ๐Ÿ”’ SECURITY - -```typescript -encryptData(data) // Encrypt -decryptData(data) // Decrypt -``` - -## ๐ŸŽฒ UTILITIES - -```typescript -generateRandomGraph(nodes, edges) // Generate test data -getAvailableFieldNames() // Available fields -getStandardFieldMappings() // Field mappings -``` - -## ๐Ÿš€ LIFECYCLE - -### Instance Methods -```typescript -init() // Initialize (required!) -shutDown() // Graceful shutdown -cleanup() // Clean resources -``` - -### Static Methods -```typescript -BrainyData.preloadModel(options?) // Preload ML model -BrainyData.warmup(options?) // Warmup system -``` - -## ๐Ÿ“ PROPERTIES - -```typescript -dimensions // Vector dimensions (readonly) -maxConnections // HNSW max connections (readonly) -efConstruction // HNSW ef construction (readonly) -initialized // Is initialized (readonly) -``` - -## โŒ REMOVED/PRIVATE IN 2.0 - -These methods are now **private** - use the new specific methods above: -- ~~add()~~ โ†’ Use `addNoun()` -- ~~get()~~ โ†’ Use `getNoun()` -- ~~delete()~~ โ†’ Use `deleteNoun()` -- ~~update()~~ โ†’ Use `updateNoun()` -- ~~relate()~~ โ†’ Use `addVerb()` -- ~~connect()~~ โ†’ Use `addVerb()` -- ~~has()~~ โ†’ Use `hasNoun()` -- ~~exists()~~ โ†’ Use `hasNoun()` -- ~~getMetadata()~~ โ†’ Use `getNounMetadata()` -- ~~updateMetadata()~~ โ†’ Use `updateNounMetadata()` -- ~~clearAll()~~ โ†’ Use `clear()` -- ~~addItem()~~ โ†’ Removed -- ~~addToBoth()~~ โ†’ Removed -- ~~addBatch()~~ โ†’ Use `addNouns()` -- ~~getBatch()~~ โ†’ Use `getNounsByIds()` -- ~~getNouns()~~ with IDs โ†’ Use `getNounsByIds()` -- ~~getNouns()~~ with filters โ†’ Use `queryNouns()` \ No newline at end of file diff --git a/docs/api-design-archive/CRITICAL-API-AUDIT.md b/docs/api-design-archive/CRITICAL-API-AUDIT.md deleted file mode 100644 index edd3b580..00000000 --- a/docs/api-design-archive/CRITICAL-API-AUDIT.md +++ /dev/null @@ -1,185 +0,0 @@ -# ๐Ÿšจ CRITICAL API AUDIT - What We Changed & Lost - -## ๐Ÿ“… Timeline of Changes (Friday-Saturday) - -### Friday Changes: -1. Started unifying augmentation system to single BrainyAugmentation interface -2. Made old methods (add, get, delete) private -3. Created new specific methods (addNoun, getNoun, deleteNoun) -4. Started removing backward compatibility - -### Saturday Changes: -1. Combined getNounsByIds and queryNouns into single getNouns method -2. Simplified search API (may have oversimplified!) -3. Accidentally introduced MongoDB operators ($gt, $in, etc.) -4. May have removed critical features while "simplifying" - -## โŒ CRITICAL MISTAKES WE MADE: - -### 1. **MongoDB Operators (LEGAL RISK!)** -```typescript -// โŒ WRONG - We accidentally added: -where: { field: {$gt: value} } - -// โœ… CORRECT - Should be: -where: { field: {greaterThan: value} } -``` - -### 2. **Lost Neural API Methods** -```typescript -// โŒ MISSING - These were removed or not properly exposed: -brain.neural.similar(a, b) -brain.neural.clusters() -brain.neural.hierarchy(id) -brain.neural.neighbors(id) -brain.neural.outliers() -brain.neural.semanticPath(from, to) -brain.neural.visualize() // Critical for external tools! -brain.neural.clusterFast() // O(n) performance -brain.neural.clusterLarge() // Million-item support -``` - -### 3. **Lost Import Capabilities** -```typescript -// โŒ WRONG - We made it too complex: -neuralImport.csv() -neuralImport.json() -neuralImport.text() - -// โœ… CORRECT - Should be ONE simple method: -brain.neuralImport(data, options?) // Auto-detects format! -``` - -### 4. **Lost Clustering for Visualization** -The visualization data format for external tools (D3, Cytoscape, GraphML) is missing! -```typescript -// โŒ MISSING - Critical for external visualization: -{ - format: 'd3' | 'cytoscape' | 'graphml', - nodes: [...], - edges: [...], - layout: {...} -} -``` - -### 5. **Oversimplified Search** -```typescript -// โŒ REMOVED too many methods: -searchByNounTypes() -searchWithinItems() -searchByStandardField() -searchVerbs() -searchNounsByVerbs() - -// โœ… BUT this is actually OK if find() handles everything! -// Just need to ensure find() is complete -``` - -## ๐Ÿ” COMPARISON: Backup vs Current - -### Methods in BACKUP but NOT in current: -```typescript -// From backup's brainyData.ts: -brain.neural // โŒ Not properly exposed -brain.visualize() // โŒ Missing -brain.clusters() // โŒ Missing -brain.similar() // โŒ Missing -brain.neuralImport() // โŒ Wrong implementation - -// Operators in backup: -greaterThan, lessThan, equals // โŒ Replaced with $gt, $lt, $eq -oneOf, contains, matches // โŒ Replaced with $in, $contains, $regex -``` - -### Methods we ADDED (some good, some questionable): -```typescript -// New specific methods (GOOD โœ…): -addNoun(), getNoun(), deleteNoun() - -// Unified method (GOOD if complete โœ…): -getNouns(idsOrOptions) - -// But lost flexibility (BAD โŒ): -- Can't do complex queries easily -- Lost specific search methods -``` - -## ๐Ÿ“Š Feature Comparison Table - -| Feature | Backup | Current | Status | -|---------|---------|---------|---------| -| **Operators** | greaterThan, lessThan | $gt, $lt | โŒ WRONG | -| **Neural API** | Complete (10+ methods) | Missing/Hidden | โŒ BROKEN | -| **Clustering** | Full support | Missing | โŒ LOST | -| **Visualization** | D3/Cytoscape export | None | โŒ LOST | -| **Import** | Simple neuralImport() | Complex multi-method | โŒ WRONG | -| **Search** | Multiple specific | Simplified to 2 | โš ๏ธ OK if complete | -| **Verb Scoring** | Full intelligence | Partial | โš ๏ธ CHECK | -| **Synapses** | External connectors | Unknown | โš ๏ธ CHECK | -| **Conduits** | Brainy-to-Brainy | Partial | โš ๏ธ CHECK | - -## ๐Ÿ”ง WHAT WE NEED TO FIX IMMEDIATELY: - -### Priority 1 (CRITICAL): -1. **Replace ALL MongoDB operators with Brainy operators** - - This is a legal requirement! - - greaterThan not $gt - -2. **Restore Neural API completely** - - brain.neural must have all methods - - Visualization MUST work for external tools - -3. **Fix neuralImport to be simple** - - ONE method that auto-detects - - Not multiple complex methods - -### Priority 2 (IMPORTANT): -4. **Restore clustering APIs** - - For visualization tools - - For analysis - -5. **Verify Triple Intelligence is complete** - - find() must handle everything - - All operators must work - -6. **Check augmentation system** - - Synapses (external) - - Conduits (internal) - -## ๐ŸŽฏ RECOVERY PLAN: - -### Step 1: Fix Operators (LEGAL REQUIREMENT) -- [ ] Find all $gt, $lt, $in, $regex references -- [ ] Replace with greaterThan, lessThan, oneOf, matches -- [ ] Update all documentation - -### Step 2: Restore Neural API -- [ ] Ensure brain.neural is properly exposed -- [ ] All methods available: similar, clusters, hierarchy, etc. -- [ ] Visualization must return proper format - -### Step 3: Fix Import -- [ ] Single neuralImport() method -- [ ] Auto-detection of format -- [ ] Simple options - -### Step 4: Verify Nothing Lost -- [ ] Compare method-by-method with backup -- [ ] Test all features -- [ ] Update documentation - -## ๐Ÿ’ก LESSONS LEARNED: - -1. **Don't oversimplify** - We lost important features -2. **Check legal requirements** - MongoDB operators were avoided for a reason -3. **Preserve all features** - Even if reorganizing -4. **Test against backup** - Always compare functionality -5. **Document changes** - Track what and why - -## ๐Ÿš€ NEXT ACTIONS: - -1. STOP all other work -2. Fix operators IMMEDIATELY (legal risk) -3. Restore neural API completely -4. Test everything works -5. Document the final API properly \ No newline at end of file diff --git a/docs/api-design-archive/FINAL-2.0-PUBLIC-API.md b/docs/api-design-archive/FINAL-2.0-PUBLIC-API.md deleted file mode 100644 index 7717a7a1..00000000 --- a/docs/api-design-archive/FINAL-2.0-PUBLIC-API.md +++ /dev/null @@ -1,210 +0,0 @@ -# ๐Ÿง  Brainy 2.0 Final Public API - -> **Clean, Specific, Beautiful** - Every method has ONE clear purpose. - -## ๐Ÿ“š NOUNS (Vectors with Metadata) - -```typescript -// Single Operations -addNoun(vector, metadata?) // Add one noun -getNoun(id) // Get one noun by ID -updateNoun(id, vector?, metadata?) // Update entire noun -updateNounMetadata(id, metadata) // Update metadata only -getNounMetadata(id) // Get metadata only -getNounWithVerbs(id) // Get noun with all relationships -deleteNoun(id) // Delete one noun -hasNoun(id) // Check if noun exists - -// Batch Operations -addNouns(items[]) // Add multiple nouns -getNouns(idsOrOptions) // Get multiple nouns (by IDs or query) - // getNouns(['id1', 'id2']) // Get by specific IDs - // getNouns({ filter: {...} }) // Get with filters - // getNouns({ limit: 10, offset: 20 }) // Get with pagination -deleteNouns(ids[]) // Delete multiple nouns -``` - -## ๐Ÿ”— VERBS (Relationships) - -```typescript -// Single Operations -addVerb(source, target, type, metadata?) // Create relationship -getVerb(id) // Get one verb by ID -deleteVerb(id) // Delete one verb - -// Batch Operations -addVerbs(verbs[]) // Add multiple relationships -getVerbs(filter?) // Get filtered verbs -getVerbsBySource(sourceId) // Get outgoing relationships -getVerbsByTarget(targetId) // Get incoming relationships -getVerbsByType(type) // Get by relationship type -deleteVerbs(ids[]) // Delete multiple verbs -``` - -## ๐Ÿ” SEARCH - -```typescript -// Core Search -search(query, k?, options?) // Primary vector search -searchText(text, k?, options?) // Natural language search -find(query) // Triple Intelligence (Vector+Graph+Metadata) ๐Ÿง  -findSimilar(id, k?, options?) // Find similar to existing noun - -// Advanced Search -searchByNounTypes(types[], query, k?) // Filter by noun types -searchWithinItems(query, ids[], k?) // Search within specific nouns -searchWithCursor(query, cursor) // Paginated search -searchByStandardField(field, value, k?) // Metadata-based search - -// Graph Search -searchVerbs(query, options?) // Search relationships -searchNounsByVerbs(conditions) // Find nouns by relationships - -// Distributed Search -searchLocal(query, k?) // Search local instance only -searchRemote(query, k?) // Search remote instance only -searchCombined(query, k?) // Search both local and remote -``` - -## ๐Ÿ“Š METADATA & FILTERING - -```typescript -getFilterFields() // Get all indexed fields -getFilterValues(field) // Get unique values for a field -getAvailableFieldNames() // Get available field names -getStandardFieldMappings() // Get standard field mappings -``` - -## ๐Ÿš€ PERFORMANCE & MONITORING - -```typescript -// Cache -getCacheStats() // Get cache statistics -clearCache() // Clear search cache - -// Statistics -size() // Total noun count -getStatistics(options?) // Comprehensive statistics -getServiceStatistics(service) // Per-service statistics -listServices() // List all services -flushStatistics() // Persist statistics to storage - -// Health -getHealthStatus() // System health check -status() // Full status report -``` - -## โš™๏ธ CONFIGURATION - -```typescript -// Operational Modes -isReadOnly() / setReadOnly(bool) // Read-only mode -isWriteOnly() / setWriteOnly(bool) // Write-only mode -isFrozen() / setFrozen(bool) // Freeze all modifications - -// Real-time Sync -enableRealtimeUpdates(config) // Enable live synchronization -disableRealtimeUpdates() // Disable synchronization -getRealtimeUpdateConfig() // Get current config -checkForUpdatesNow() // Manual sync trigger - -// Remote Connection -connectToRemoteServer(url, options?) // Connect to remote instance -disconnectFromRemoteServer() // Disconnect from remote -isConnectedToRemoteServer() // Check connection status -``` - -## ๐Ÿง  INTELLIGENCE - -```typescript -// Verb Scoring -provideFeedbackForVerbScoring(feedback) // Train relationship scoring -getVerbScoringStats() // Get scoring statistics -exportVerbScoringLearningData() // Export training data -importVerbScoringLearningData(data) // Import training data - -// Embeddings -embed(text) // Generate embedding vector -calculateSimilarity(a, b, metric?) // Calculate vector similarity -``` - -## ๐Ÿ’พ DATA MANAGEMENT - -```typescript -// Clear Operations -clear(options?) // Clear all data -clearNouns(options?) // Clear all nouns only -clearVerbs(options?) // Clear all verbs only - -// Backup & Restore -backup() // Create full backup -restore(backup) // Restore from backup - -// Import/Export -import(data, format) // Import external data -importSparseData(data) // Import sparse format - -// Index Management -rebuildMetadataIndex() // Rebuild metadata index -``` - -## ๐Ÿ”’ SECURITY - -```typescript -encryptData(data) // Encrypt data -decryptData(data) // Decrypt data -``` - -## ๐ŸŽฒ UTILITIES - -```typescript -generateRandomGraph(nodes, edges) // Generate test graph data -``` - -## ๐Ÿš€ LIFECYCLE - -```typescript -// Instance Methods -new BrainyData(config?) // Create instance -init() // Initialize (REQUIRED!) -shutDown() // Graceful shutdown -cleanup() // Clean up resources - -// Static Methods -BrainyData.preloadModel(options?) // Preload ML model -BrainyData.warmup(options?) // Warmup system -``` - -## ๐Ÿ“ PROPERTIES (Read-only) - -```typescript -dimensions // Vector dimensions -maxConnections // HNSW max connections -efConstruction // HNSW ef construction -initialized // Is initialized? -``` - ---- - -## ๐Ÿ“ Key Changes in 2.0 - -### โœ… Simplified & Unified -- `getNouns()` now handles ALL plural queries (by IDs, filters, or pagination) -- No more `getNounsByIds()`, `queryNouns()`, `getBatch()` - just `getNouns()` -- Clear singular vs plural: `getNoun()` for one, `getNouns()` for many - -### โœ… Specific Naming -- Always specify noun/verb: `addNoun()` not `add()` -- No aliases or duplicates -- One method, one purpose - -### โœ… Private Legacy Methods -These are now private (use new methods above): -- `add()`, `get()`, `delete()`, `update()` -- `relate()`, `connect()`, `has()`, `exists()` -- `getMetadata()`, `updateMetadata()` -- `addItem()`, `addToBoth()`, `addBatch()`, `getBatch()` - -### โœ… Triple Intelligence -- New `find()` method unifies Vector + Graph + Metadata search -- Most powerful search capability in one simple method \ No newline at end of file diff --git a/docs/api-design-archive/README.md b/docs/api-design-archive/README.md deleted file mode 100644 index 018828bf..00000000 --- a/docs/api-design-archive/README.md +++ /dev/null @@ -1,28 +0,0 @@ -# API Design Archive - -This directory contains historical API design documents from the Brainy 2.0 development process. - -## Purpose -These documents represent the iterative refinement of the Brainy 2.0 API during development. They are preserved here for historical reference and to document the design decisions made along the way. - -## Current API Documentation -The definitive API documentation is now located at: -- **`/docs/api/README.md`** - The ONE official API reference - -## Archived Documents -These documents show the evolution of the API design: -- Various iterations of API structure -- Exploration of different naming conventions -- Refinement of the Triple Intelligence concept -- Transition from MongoDB operators to Brainy operators -- Evolution of the Neural API - -## Key Decisions Made -1. **Terminology**: Vector + Graph + Metadata (not Field) -2. **Operators**: Brainy operators (greaterThan, lessThan) not MongoDB ($gt, $lt) -3. **Methods**: Specific noun/verb naming (addNoun, getNoun) -4. **Unification**: Single getNouns() method instead of multiple variants -5. **Neural API**: Complete clustering and visualization features - -## Note -These documents are archived, not deleted, to preserve the development history and rationale behind API decisions. \ No newline at end of file diff --git a/docs/augmentations-archive/API-EXPOSURE-ARCHITECTURE.md b/docs/augmentations-archive/API-EXPOSURE-ARCHITECTURE.md deleted file mode 100644 index 8162f849..00000000 --- a/docs/augmentations-archive/API-EXPOSURE-ARCHITECTURE.md +++ /dev/null @@ -1,549 +0,0 @@ -# ๐ŸŒ Brainy API Exposure Architecture - -## ๐Ÿ“ก Current State: Built-in MCP Support - -Brainy **already has** Model Context Protocol (MCP) support built-in: - -```typescript -// Already exists in Brainy! -import { BrainyMCPService } from 'brainy/mcp' - -const brain = new BrainyData() -const mcpService = new BrainyMCPService(brain) - -// Handles MCP requests -const response = await mcpService.handleRequest({ - type: 'data_access', - operation: 'search', - parameters: { query: 'find documents' } -}) -``` - -### What's Already Built: -- **BrainyMCPAdapter** - Exposes data operations -- **MCPAugmentationToolset** - Exposes augmentations as MCP tools -- **BrainyMCPService** - Unified service layer -- **ServerSearchConduitAugmentation** - Connect to remote Brainy instances - -## ๐Ÿš€ The Missing Piece: API Server Augmentation - -What's **NOT** built yet is a unified API server that exposes REST, WebSocket, and MCP over network. This SHOULD be an augmentation! - -```typescript -/** - * Universal API Server Augmentation - * Exposes Brainy through REST, WebSocket, MCP, and GraphQL - */ -export class APIServerAugmentation extends BaseAugmentation { - readonly name = 'api-server' - readonly timing = 'after' as const - readonly operations = ['all'] as const // Monitor all operations - readonly priority = 5 // Low priority, runs last - - private httpServer?: any - private wsServer?: any - private mcpService?: BrainyMCPService - private clients = new Set() - private apiKeys = new Map() - - protected async onInitialize(): Promise { - const config = this.context.config.apiServer || {} - - if (!config.enabled) { - this.log('API Server disabled in config') - return - } - - // Initialize MCP service - this.mcpService = new BrainyMCPService(this.context.brain, { - enableAuth: config.requireAuth - }) - - // Start servers based on environment - if (typeof process !== 'undefined' && process.versions?.node) { - await this.startNodeServers(config) - } else if (typeof Deno !== 'undefined') { - await this.startDenoServer(config) - } else if (typeof self !== 'undefined') { - await this.startServiceWorker(config) - } - } - - private async startNodeServers(config: any) { - const express = await import('express') - const { WebSocketServer } = await import('ws') - const cors = await import('cors') - - const app = express.default() - - // Middleware - app.use(cors.default(config.cors)) - app.use(express.json()) - app.use(this.authMiddleware.bind(this)) - app.use(this.rateLimitMiddleware.bind(this)) - - // REST API Routes - this.setupRESTRoutes(app) - - // Start HTTP server - this.httpServer = app.listen(config.port || 3000, () => { - this.log(`REST API listening on port ${config.port || 3000}`) - }) - - // WebSocket server for real-time - this.wsServer = new WebSocketServer({ - server: this.httpServer, - path: '/ws' - }) - - this.setupWebSocketServer() - - // MCP over WebSocket - this.setupMCPWebSocket() - } - - private setupRESTRoutes(app: any) { - // Health check - app.get('/health', (req: any, res: any) => { - res.json({ status: 'healthy', version: '2.0.0' }) - }) - - // Search endpoint - app.post('/api/search', async (req: any, res: any) => { - try { - const { query, limit = 10, options = {} } = req.body - const results = await this.context.brain.search(query, limit, options) - res.json({ success: true, results }) - } catch (error) { - res.status(500).json({ - success: false, - error: error.message - }) - } - }) - - // Add data endpoint - app.post('/api/add', async (req: any, res: any) => { - try { - const { content, metadata } = req.body - const id = await this.context.brain.add(content, metadata) - res.json({ success: true, id }) - } catch (error) { - res.status(500).json({ - success: false, - error: error.message - }) - } - }) - - // Get endpoint - app.get('/api/get/:id', async (req: any, res: any) => { - try { - const data = await this.context.brain.get(req.params.id) - res.json({ success: true, data }) - } catch (error) { - res.status(404).json({ - success: false, - error: 'Not found' - }) - } - }) - - // Delete endpoint - app.delete('/api/delete/:id', async (req: any, res: any) => { - try { - await this.context.brain.delete(req.params.id) - res.json({ success: true }) - } catch (error) { - res.status(500).json({ - success: false, - error: error.message - }) - } - }) - - // Relate endpoint - app.post('/api/relate', async (req: any, res: any) => { - try { - const { source, target, verb, metadata } = req.body - await this.context.brain.relate(source, target, verb, metadata) - res.json({ success: true }) - } catch (error) { - res.status(500).json({ - success: false, - error: error.message - }) - } - }) - - // Find endpoint (complex queries) - app.post('/api/find', async (req: any, res: any) => { - try { - const results = await this.context.brain.find(req.body) - res.json({ success: true, results }) - } catch (error) { - res.status(500).json({ - success: false, - error: error.message - }) - } - }) - - // Cluster endpoint - app.post('/api/cluster', async (req: any, res: any) => { - try { - const { algorithm = 'kmeans', options = {} } = req.body - const clusters = await this.context.brain.cluster(algorithm, options) - res.json({ success: true, clusters }) - } catch (error) { - res.status(500).json({ - success: false, - error: error.message - }) - } - }) - - // MCP endpoint (for non-WebSocket MCP) - app.post('/api/mcp', async (req: any, res: any) => { - try { - const response = await this.mcpService.handleRequest(req.body) - res.json(response) - } catch (error) { - res.status(500).json({ - success: false, - error: error.message - }) - } - }) - - // GraphQL endpoint (optional) - if (this.context.config.apiServer?.enableGraphQL) { - this.setupGraphQL(app) - } - } - - private setupWebSocketServer() { - this.wsServer.on('connection', (ws: any) => { - this.clients.add(ws) - - ws.on('message', async (message: string) => { - try { - const msg = JSON.parse(message) - await this.handleWebSocketMessage(msg, ws) - } catch (error) { - ws.send(JSON.stringify({ - type: 'error', - error: error.message - })) - } - }) - - ws.on('close', () => { - this.clients.delete(ws) - }) - }) - } - - private async handleWebSocketMessage(msg: any, ws: any) { - switch (msg.type) { - case 'subscribe': - // Subscribe to operations - ws.subscriptions = msg.operations || ['all'] - ws.send(JSON.stringify({ - type: 'subscribed', - operations: ws.subscriptions - })) - break - - case 'search': - const results = await this.context.brain.search(msg.query, msg.limit) - ws.send(JSON.stringify({ - type: 'searchResults', - results - })) - break - - case 'mcp': - // Handle MCP over WebSocket - const response = await this.mcpService.handleRequest(msg.request) - ws.send(JSON.stringify({ - type: 'mcpResponse', - response - })) - break - } - } - - private setupMCPWebSocket() { - // Dedicated MCP WebSocket endpoint - const { WebSocketServer } = require('ws') - const mcpWs = new WebSocketServer({ - port: (this.context.config.apiServer?.mcpPort || 3001), - path: '/mcp' - }) - - mcpWs.on('connection', (ws: any) => { - ws.on('message', async (message: string) => { - try { - const request = JSON.parse(message) - const response = await this.mcpService.handleRequest(request) - ws.send(JSON.stringify(response)) - } catch (error) { - ws.send(JSON.stringify({ - error: error.message, - type: 'error' - })) - } - }) - }) - - this.log(`MCP WebSocket listening on port ${this.context.config.apiServer?.mcpPort || 3001}`) - } - - // Broadcast changes to all connected clients - async execute(operation: string, params: any, next: () => Promise): Promise { - const result = await next() - - // Broadcast to WebSocket clients - if (this.clients.size > 0) { - const message = JSON.stringify({ - type: 'operation', - operation, - params: this.sanitizeParams(params), - timestamp: Date.now() - }) - - for (const client of this.clients) { - if (client.subscriptions?.includes('all') || - client.subscriptions?.includes(operation)) { - client.send(message) - } - } - } - - return result - } - - private authMiddleware(req: any, res: any, next: any) { - if (!this.context.config.apiServer?.requireAuth) { - return next() - } - - const apiKey = req.headers['x-api-key'] - if (!apiKey || !this.apiKeys.has(apiKey)) { - return res.status(401).json({ error: 'Unauthorized' }) - } - - req.user = this.apiKeys.get(apiKey) - next() - } - - private rateLimitMiddleware(req: any, res: any, next: any) { - // Simple rate limiting - const ip = req.ip - const limit = this.context.config.apiServer?.rateLimit || 100 - - // Implementation details... - next() - } - - private sanitizeParams(params: any) { - // Remove sensitive data before broadcasting - const safe = { ...params } - delete safe.apiKey - delete safe.password - return safe - } - - protected async onShutdown() { - // Close all connections - for (const client of this.clients) { - client.close() - } - - // Close servers - if (this.httpServer) { - await new Promise(resolve => this.httpServer.close(resolve)) - } - if (this.wsServer) { - this.wsServer.close() - } - } -} -``` - -## ๐ŸŽฏ Usage: Deploy Brainy as a Server - -```typescript -import { BrainyData } from 'brainy' -import { APIServerAugmentation } from 'brainy/augmentations' - -const brain = new BrainyData({ - apiServer: { - enabled: true, - port: 3000, - mcpPort: 3001, - requireAuth: true, - rateLimit: 100, - cors: { origin: '*' }, - enableGraphQL: false - } -}) - -// Register the API server augmentation -brain.augmentations.register(new APIServerAugmentation()) - -await brain.init() - -console.log('Brainy API Server running!') -console.log('REST API: http://localhost:3000') -console.log('WebSocket: ws://localhost:3000/ws') -console.log('MCP: ws://localhost:3001/mcp') -``` - -## ๐Ÿ”Œ Client Usage - -### REST API -```javascript -// Search -const response = await fetch('http://localhost:3000/api/search', { - method: 'POST', - headers: { - 'Content-Type': 'application/json', - 'X-API-Key': 'your-key' - }, - body: JSON.stringify({ - query: 'find documents about AI', - limit: 10 - }) -}) -const { results } = await response.json() -``` - -### WebSocket (Real-time) -```javascript -const ws = new WebSocket('ws://localhost:3000/ws') - -ws.onopen = () => { - // Subscribe to operations - ws.send(JSON.stringify({ - type: 'subscribe', - operations: ['add', 'delete', 'relate'] - })) -} - -ws.onmessage = (event) => { - const msg = JSON.parse(event.data) - console.log('Operation:', msg.operation, msg.params) -} -``` - -### MCP (AI Agents) -```javascript -const mcpWs = new WebSocket('ws://localhost:3001/mcp') - -mcpWs.send(JSON.stringify({ - type: 'data_access', - operation: 'search', - requestId: '123', - parameters: { query: 'test' } -})) - -mcpWs.onmessage = (event) => { - const response = JSON.parse(event.data) - console.log('MCP Response:', response) -} -``` - -## ๐Ÿ—๏ธ Architecture Benefits - -### Why as an Augmentation? - -1. **Optional** - Not everyone needs a server -2. **Configurable** - Easy to enable/disable -3. **Extensible** - Add custom endpoints -4. **Integrated** - Hooks into all operations -5. **Real-time** - Broadcasts changes automatically - -### Security Features - -- **API Key Authentication** -- **Rate Limiting** -- **CORS Configuration** -- **Parameter Sanitization** -- **SSL/TLS Support** (with proper certs) - -## ๐ŸŒ Deployment Options - -### Local Development -```bash -npm install brainy -node server.js # Your server file with APIServerAugmentation -``` - -### Docker Container -```dockerfile -FROM node:18-alpine -WORKDIR /app -COPY package*.json ./ -RUN npm install brainy -COPY server.js . -EXPOSE 3000 3001 -CMD ["node", "server.js"] -``` - -### Cloud Deployment -Deploy to any Node.js hosting: -- Vercel Edge Functions -- Cloudflare Workers (with adapter) -- AWS Lambda (with adapter) -- Google Cloud Run -- Traditional VPS - -### Browser Service Worker -```javascript -// In browser, use Service Worker for local API -if ('serviceWorker' in navigator) { - // APIServerAugmentation can create a Service Worker - // that intercepts fetch() calls and handles them locally -} -``` - -## ๐ŸŽฏ The Complete Picture - -``` -โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” -โ”‚ Client Applications โ”‚ -โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค -โ”‚ REST โ”‚ WebSocket โ”‚ MCP โ”‚ -โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ - โ”‚ โ”‚ โ”‚ - โ–ผ โ–ผ โ–ผ -โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” -โ”‚ APIServerAugmentation โ”‚ -โ”‚ (Unified API exposure as augmentation) โ”‚ -โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ - โ”‚ - โ–ผ -โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” -โ”‚ BrainyData Core โ”‚ -โ”‚ (with all augmentations in pipeline) โ”‚ -โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ - โ”‚ - โ–ผ -โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” -โ”‚ Storage Layer โ”‚ -โ”‚ (FileSystem, S3, OPFS, Memory) โ”‚ -โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ -``` - -## ๐Ÿš€ Summary - -1. **MCP is built-in** - Already in Brainy core -2. **API Server should be an augmentation** - Optional, configurable -3. **Exposes everything** - REST, WebSocket, MCP, GraphQL -4. **Real-time by default** - Broadcasts all operations -5. **Secure** - Auth, rate limiting, CORS -6. **Deploy anywhere** - Node, Deno, Browser, Cloud - -The beauty is that the API server is just another augmentation - it hooks into the pipeline like everything else and exposes Brainy's capabilities to the world! \ No newline at end of file diff --git a/docs/augmentations-archive/AUGMENTATION-EXAMPLES.md b/docs/augmentations-archive/AUGMENTATION-EXAMPLES.md deleted file mode 100644 index fe66b173..00000000 --- a/docs/augmentations-archive/AUGMENTATION-EXAMPLES.md +++ /dev/null @@ -1,774 +0,0 @@ -# ๐Ÿš€ Real-World Augmentation Examples - -## 1. ๐Ÿ’ฌ Chat Interface Augmentation -**"Talk to your data through natural language"** - -```typescript -import { BaseAugmentation } from './brainyAugmentation.js' - -export class ChatInterfaceAugmentation extends BaseAugmentation { - readonly name = 'chat-interface' - readonly timing = 'after' as const // Process after operations - readonly operations = ['search', 'add', 'delete'] as const - readonly priority = 30 // Medium priority - - private chatHistory: Array<{role: string, content: string}> = [] - private llmClient: any // User's chosen LLM - - protected async onInitialize(): Promise { - // User provides their own LLM - this.llmClient = this.context.config.llmClient || null - if (!this.llmClient) { - this.log('Chat augmentation needs LLM client in config') - } - } - - async execute(operation: string, params: any, next: () => Promise): Promise { - // If params include natural language query - if (params.chatQuery) { - // Convert natural language to Brainy operations - const intent = await this.parseIntent(params.chatQuery) - - // Transform params based on intent - if (intent.type === 'search') { - params.query = intent.query - params.k = intent.limit || 10 - } else if (intent.type === 'add') { - params.content = intent.content - params.metadata = { ...params.metadata, source: 'chat' } - } - - // Store in chat history - this.chatHistory.push({ - role: 'user', - content: params.chatQuery - }) - } - - // Execute the operation - const result = await next() - - // Generate conversational response - if (params.chatQuery && this.llmClient) { - const response = await this.generateResponse(operation, result) - - this.chatHistory.push({ - role: 'assistant', - content: response - }) - - // Enhance result with chat response - return { - ...result, - chatResponse: response, - chatHistory: this.chatHistory - } as T - } - - return result - } - - private async parseIntent(query: string) { - // Use Brainy's NLP patterns + LLM to understand intent - const prompt = `Parse this query into a Brainy operation: - Query: ${query} - - Return JSON with: - - type: 'search' | 'add' | 'delete' | 'relate' - - query: search terms or content - - filters: any metadata filters - - limit: number of results` - - const response = await this.llmClient.complete(prompt) - return JSON.parse(response) - } - - private async generateResponse(operation: string, result: any) { - const prompt = `Generate a friendly response for this operation: - Operation: ${operation} - Result: ${JSON.stringify(result).slice(0, 500)} - Chat History: ${JSON.stringify(this.chatHistory.slice(-3))} - - Be conversational and helpful.` - - return await this.llmClient.complete(prompt) - } -} - -// Usage: -const brain = new BrainyData({ - augmentations: [ - new ChatInterfaceAugmentation() - ], - llmClient: openai // Bring your own LLM -}) - -// Now you can chat! -const result = await brain.search({ - chatQuery: "Show me all documents about project roadmap from last week" -}) -console.log(result.chatResponse) // "I found 5 documents about the project roadmap..." -``` - -## 2. ๐Ÿค– MCP Agent Memory Augmentation -**"Provide persistent memory for AI agents through MCP"** - -```typescript -import { BaseAugmentation } from './brainyAugmentation.js' -import { Server } from '@modelcontextprotocol/sdk' - -export class MCPAgentMemoryAugmentation extends BaseAugmentation { - readonly name = 'mcp-agent-memory' - readonly timing = 'around' as const // Wrap operations - readonly operations = ['all'] as const // Monitor everything - readonly priority = 70 // High priority - - private mcpServer: Server - private agentSessions: Map = new Map() - - protected async onInitialize(): Promise { - // Initialize MCP server - this.mcpServer = new Server({ - name: 'brainy-memory', - version: '1.0.0' - }) - - // Register MCP tools for agents - this.mcpServer.setRequestHandler('tools/list', () => ({ - tools: [ - { - name: 'remember', - description: 'Store information in long-term memory', - inputSchema: { - type: 'object', - properties: { - content: { type: 'string' }, - category: { type: 'string' }, - importance: { type: 'number' } - } - } - }, - { - name: 'recall', - description: 'Retrieve information from memory', - inputSchema: { - type: 'object', - properties: { - query: { type: 'string' }, - category: { type: 'string' }, - limit: { type: 'number' } - } - } - }, - { - name: 'forget', - description: 'Remove information from memory', - inputSchema: { - type: 'object', - properties: { - query: { type: 'string' }, - category: { type: 'string' } - } - } - } - ] - })) - - // Handle tool calls from agents - this.mcpServer.setRequestHandler('tools/call', async (request) => { - const { name, arguments: args } = request.params - - switch (name) { - case 'remember': - return await this.rememberForAgent(args) - case 'recall': - return await this.recallForAgent(args) - case 'forget': - return await this.forgetForAgent(args) - default: - throw new Error(`Unknown tool: ${name}`) - } - }) - - // Start MCP server - await this.mcpServer.connect(process.stdin, process.stdout) - this.log('MCP Agent Memory server started') - } - - async execute(operation: string, params: any, next: () => Promise): Promise { - // Extract agent context if present - const agentId = params.metadata?._agentId || 'default' - const sessionId = params.metadata?._sessionId - - // Track agent operations - if (agentId && sessionId) { - if (!this.agentSessions.has(sessionId)) { - this.agentSessions.set(sessionId, { - agentId, - startTime: Date.now(), - operations: [] - }) - } - - const session = this.agentSessions.get(sessionId) - session.operations.push({ - operation, - params: { ...params }, - timestamp: Date.now() - }) - } - - // Execute with agent context - const result = await next() - - // Auto-remember important operations - if (operation === 'add' && agentId) { - await this.autoRemember(agentId, params, result) - } - - return result - } - - private async rememberForAgent(args: any) { - // Store in Brainy with agent-specific metadata - const id = await this.context.brain.add(args.content, { - _agentMemory: true, - _agentId: args.agentId || 'default', - category: args.category, - importance: args.importance || 0.5, - timestamp: new Date().toISOString() - }) - - return { - content: [ - { - type: 'text', - text: `Remembered with ID: ${id}` - } - ] - } - } - - private async recallForAgent(args: any) { - // Search agent's memories - const results = await this.context.brain.search(args.query, args.limit || 10, { - where: { - _agentMemory: true, - _agentId: args.agentId || 'default', - category: args.category - } - }) - - return { - content: [ - { - type: 'text', - text: JSON.stringify(results, null, 2) - } - ] - } - } - - private async forgetForAgent(args: any) { - // Remove specific memories - const results = await this.context.brain.find({ - where: { - _agentMemory: true, - _agentId: args.agentId || 'default', - category: args.category - } - }) - - for (const item of results) { - await this.context.brain.delete(item.id) - } - - return { - content: [ - { - type: 'text', - text: `Forgot ${results.length} memories` - } - ] - } - } - - private async autoRemember(agentId: string, params: any, result: any) { - // Automatically remember important information - if (params.metadata?.important) { - await this.context.brain.add(params.content, { - ...params.metadata, - _agentMemory: true, - _agentId: agentId, - _autoRemembered: true, - _originalOperation: 'add', - _resultId: result - }) - } - } -} - -// Usage: -const brain = new BrainyData({ - augmentations: [ - new MCPAgentMemoryAugmentation() - ] -}) - -// Now AI agents can use Brainy as memory through MCP! -// Agents connect via MCP and use remember/recall/forget tools -``` - -## 3. ๐ŸŒ API Server Augmentation -**"Expose Brainy through REST, WebSocket, and MCP APIs"** - -```typescript -import { BaseAugmentation } from './brainyAugmentation.js' -import { BrainyMCPService } from '../mcp/brainyMCPService.js' - -export class APIServerAugmentation extends BaseAugmentation { - readonly name = 'api-server' - readonly timing = 'after' as const - readonly operations = ['all'] as ('all')[] - readonly priority = 5 // Low priority, runs after other augmentations - - private httpServer: any - private wsServer: any - private mcpService: BrainyMCPService - - protected async onInitialize(): Promise { - // Initialize MCP service - this.mcpService = new BrainyMCPService(this.context.brain) - - // Start HTTP server with REST endpoints - await this.startHTTPServer() - - // Start WebSocket server for real-time - await this.startWebSocketServer() - - this.log(`API Server running on port ${this.config.port || 3000}`) - } - - async execute(operation: string, params: any, next: () => Promise): Promise { - const result = await next() - - // Broadcast operation to WebSocket clients - this.broadcast({ - type: 'operation', - operation, - params: this.sanitizeParams(params), - timestamp: Date.now() - }) - - return result - } - - private async startHTTPServer() { - // REST endpoints: /api/search, /api/add, /api/get/:id, etc. - // MCP endpoint: /api/mcp - // Health check: /health - } - - private async startWebSocketServer() { - // WebSocket for real-time subscriptions - // Clients can subscribe to specific operations - } -} - -// Usage: -const brain = new BrainyData() -brain.augmentations.register(new APIServerAugmentation({ port: 3000 })) -await brain.init() - -// Now access Brainy via: -// - REST: http://localhost:3000/api/* -// - WebSocket: ws://localhost:3000/ws -// - MCP: http://localhost:3000/api/mcp -``` - -## 4. ๐Ÿ“Š Graph Visualization Augmentation -**"Real-time graph visualization with clustering"** - -```typescript -import { BaseAugmentation } from './brainyAugmentation.js' -import { WebSocketServer } from 'ws' - -export class GraphVisualizationAugmentation extends BaseAugmentation { - readonly name = 'graph-visualization' - readonly timing = 'after' as const - readonly operations = ['all'] as const // Monitor all changes - readonly priority = 20 - - private wsServer: WebSocketServer - private graphState: { - nodes: Map - edges: Map - clusters: Map> - } - private clients: Set = new Set() - - protected async onInitialize(): Promise { - // Initialize WebSocket server for real-time updates - this.wsServer = new WebSocketServer({ - port: this.context.config.visualizationPort || 8080 - }) - - this.graphState = { - nodes: new Map(), - edges: new Map(), - clusters: new Map() - } - - // Load initial graph state - await this.loadGraphState() - - // Handle client connections - this.wsServer.on('connection', (ws) => { - this.clients.add(ws) - - // Send initial state - ws.send(JSON.stringify({ - type: 'init', - data: this.serializeGraphState() - })) - - // Handle client messages - ws.on('message', async (message) => { - const msg = JSON.parse(message.toString()) - await this.handleClientMessage(msg, ws) - }) - - ws.on('close', () => { - this.clients.delete(ws) - }) - }) - - // Start clustering in background - this.startClusteringWorker() - - this.log('Graph visualization server started on port ' + - (this.context.config.visualizationPort || 8080)) - } - - async execute(operation: string, params: any, next: () => Promise): Promise { - const result = await next() - - // Update graph state based on operation - switch (operation) { - case 'add': - case 'addNoun': - await this.handleNodeAdded(result, params) - break - - case 'relate': - case 'addVerb': - await this.handleEdgeAdded(params) - break - - case 'delete': - await this.handleNodeDeleted(params) - break - - case 'search': - await this.handleSearchPerformed(params, result) - break - } - - return result - } - - private async handleNodeAdded(id: string, data: any) { - // Add node to graph - const node = { - id, - label: data.content?.slice(0, 50) || id, - type: data.metadata?.type || 'default', - metadata: data.metadata, - position: this.calculatePosition(id), - clusterId: null - } - - this.graphState.nodes.set(id, node) - - // Broadcast to clients - this.broadcast({ - type: 'nodeAdded', - data: node - }) - - // Trigger re-clustering - this.scheduleReClustering() - } - - private async handleEdgeAdded(params: any) { - const edge = { - id: `${params.source}-${params.verb}-${params.target}`, - source: params.source, - target: params.target, - label: params.verb, - weight: params.weight || 1 - } - - this.graphState.edges.set(edge.id, edge) - - this.broadcast({ - type: 'edgeAdded', - data: edge - }) - } - - private async handleSearchPerformed(params: any, results: any) { - // Highlight search results in visualization - const highlightNodes = results.map((r: any) => r.id) - - this.broadcast({ - type: 'highlight', - data: { - nodes: highlightNodes, - query: params.query, - duration: 5000 // Highlight for 5 seconds - } - }) - } - - private async loadGraphState() { - // Load all nodes (nouns) - const nouns = await this.context.brain.getAllNouns() - for (const noun of nouns) { - this.graphState.nodes.set(noun.id, { - id: noun.id, - label: noun.content?.slice(0, 50) || noun.id, - type: noun.type, - metadata: noun.metadata, - position: this.calculatePosition(noun.id) - }) - } - - // Load all edges (verbs/relationships) - const verbs = await this.context.brain.getAllVerbs() - for (const verb of verbs) { - this.graphState.edges.set(verb.id, { - id: verb.id, - source: verb.source, - target: verb.target, - label: verb.type, - weight: verb.weight - }) - } - - // Initial clustering - await this.performClustering() - } - - private async performClustering() { - // Use Brainy's clustering capabilities - const clusteringResult = await this.context.brain.cluster({ - algorithm: 'hierarchical', - threshold: 0.7 - }) - - // Update cluster state - this.graphState.clusters.clear() - for (const [clusterId, nodeIds] of Object.entries(clusteringResult)) { - this.graphState.clusters.set(clusterId, new Set(nodeIds as string[])) - - // Update nodes with cluster IDs - for (const nodeId of nodeIds as string[]) { - const node = this.graphState.nodes.get(nodeId) - if (node) { - node.clusterId = clusterId - } - } - } - - // Broadcast cluster update - this.broadcast({ - type: 'clustersUpdated', - data: this.serializeClusters() - }) - } - - private startClusteringWorker() { - // Re-cluster periodically or when graph changes significantly - setInterval(async () => { - if (this.graphState.nodes.size > 0) { - await this.performClustering() - } - }, 30000) // Every 30 seconds - } - - private scheduleReClustering = (() => { - let timeout: NodeJS.Timeout - return () => { - clearTimeout(timeout) - timeout = setTimeout(() => this.performClustering(), 5000) - } - })() - - private calculatePosition(id: string) { - // Simple force-directed layout position - const hash = id.split('').reduce((a, b) => { - a = ((a << 5) - a) + b.charCodeAt(0) - return a & a - }, 0) - - return { - x: (hash % 1000) - 500, - y: ((hash * 7) % 1000) - 500 - } - } - - private broadcast(message: any) { - const data = JSON.stringify(message) - for (const client of this.clients) { - client.send(data) - } - } - - private async handleClientMessage(msg: any, ws: any) { - switch (msg.type) { - case 'requestClustering': - await this.performClustering() - break - - case 'search': - const results = await this.context.brain.search(msg.query) - ws.send(JSON.stringify({ - type: 'searchResults', - data: results - })) - break - - case 'getNodeDetails': - const node = await this.context.brain.get(msg.nodeId) - ws.send(JSON.stringify({ - type: 'nodeDetails', - data: node - })) - break - - case 'expandNode': - const connections = await this.context.brain.getConnections(msg.nodeId) - ws.send(JSON.stringify({ - type: 'nodeConnections', - data: connections - })) - break - } - } - - private serializeGraphState() { - return { - nodes: Array.from(this.graphState.nodes.values()), - edges: Array.from(this.graphState.edges.values()), - clusters: this.serializeClusters() - } - } - - private serializeClusters() { - const clusters: any = {} - for (const [id, nodeIds] of this.graphState.clusters) { - clusters[id] = Array.from(nodeIds) - } - return clusters - } - - protected async onShutdown() { - this.wsServer.close() - this.clients.clear() - } -} - -// Usage: -const brain = new BrainyData({ - augmentations: [ - new GraphVisualizationAugmentation() - ], - visualizationPort: 8080 -}) - -// Now connect a web-based graph viz tool to ws://localhost:8080 -// It receives real-time updates as data changes! -``` - -## 4. ๐ŸŒ Multi-Agent Team Coordination -**"Multiple AI agents sharing knowledge and coordinating tasks"** - -```typescript -export class TeamCoordinationAugmentation extends BaseAugmentation { - readonly name = 'team-coordination' - readonly timing = 'around' as const - readonly operations = ['all'] as const - readonly priority = 85 - - private agents: Map = new Map() - private tasks: Map = new Map() - private sharedMemory: Map = new Map() - - async execute(operation: string, params: any, next: () => Promise): Promise { - const agentId = params.metadata?._agentId - - if (agentId) { - // Track agent activity - this.updateAgentState(agentId, operation, params) - - // Check if operation needs coordination - if (await this.needsCoordination(operation, params)) { - return await this.coordinatedExecute(agentId, operation, params, next) - } - } - - return next() - } - - private async coordinatedExecute( - agentId: string, - operation: string, - params: any, - next: () => Promise - ): Promise { - // Acquire distributed lock - const lockId = await this.acquireLock(operation, params) - - try { - // Check shared memory for related work - const relatedWork = await this.findRelatedWork(params) - if (relatedWork) { - params.metadata._relatedWork = relatedWork - } - - // Execute with team context - const result = await next() - - // Update shared memory - await this.updateSharedMemory(agentId, operation, params, result) - - // Notify other agents - await this.notifyTeam(agentId, operation, result) - - return result - } finally { - await this.releaseLock(lockId) - } - } -} -``` - -## ๐ŸŽฏ Key Patterns - -All these augmentations follow the same pattern: - -1. **Extend BaseAugmentation** -2. **Define timing & operations** -3. **Initialize resources** in `onInitialize()` -4. **Intercept operations** in `execute()` -5. **Clean up** in `onShutdown()` - -They can: -- **Add APIs** (REST, WebSocket, MCP) -- **Transform data** (chat queries โ†’ operations) -- **Coordinate agents** (distributed locking, shared memory) -- **Visualize in real-time** (WebSocket broadcasts) -- **Integrate any service** (LLMs, databases, APIs) - -The beauty is they all use the **same simple interface** but achieve vastly different goals! \ No newline at end of file diff --git a/docs/augmentations-archive/AUGMENTATION-PIPELINE-ARCHITECTURE.md b/docs/augmentations-archive/AUGMENTATION-PIPELINE-ARCHITECTURE.md deleted file mode 100644 index e97f8448..00000000 --- a/docs/augmentations-archive/AUGMENTATION-PIPELINE-ARCHITECTURE.md +++ /dev/null @@ -1,306 +0,0 @@ -# ๐Ÿ”„ How Augmentations Hook Into Brainy - -## The Complete Pipeline Architecture - -``` -User Code โ†’ BrainyData Method โ†’ Augmentation Pipeline โ†’ Storage/Operations - โ†‘ โ†“ - โ””โ”€โ”€โ”€โ”€โ”€โ”€ Augmentations Execute Here โ”€โ”€โ”˜ -``` - -## ๐ŸŽฏ How Augmentations Register & Execute - -### 1. **Registration During Initialization** - -```typescript -// In BrainyData constructor/init -class BrainyData { - private augmentations = new AugmentationRegistry() - - async init() { - // Register built-in augmentations in priority order - this.augmentations.register(new WALAugmentation()) // Priority: 100 - this.augmentations.register(new EntityRegistryAugmentation()) // Priority: 90 - this.augmentations.register(new NeuralImportAugmentation()) // Priority: 80 - this.augmentations.register(new BatchProcessingAugmentation()) // Priority: 50 - - // Initialize all with context - const context: AugmentationContext = { - brain: this, - storage: this.storage, - config: this.config, - log: (msg, level) => console.log(msg) - } - - await this.augmentations.initialize(context) - } -} -``` - -### 2. **Execution Through Method Interception** - -Every BrainyData operation wraps its core logic with augmentation execution: - -```typescript -// Example: The add() method -async add(content: string, metadata?: any): Promise { - // Augmentations wrap the core operation - return this.augmentations.execute( - 'add', // Operation name - { content, metadata }, // Parameters - async () => { // Core operation - // Actual add logic here - const id = generateId() - await this.storage.set(id, { content, metadata }) - return id - } - ) -} -``` - -### 3. **The Execution Chain** - -```typescript -// In AugmentationRegistry -async execute(operation: string, params: any, mainOperation: () => Promise): Promise { - // 1. Filter augmentations that should run for this operation - const applicable = this.augmentations.filter(aug => - aug.shouldExecute(operation, params) - ) - - // 2. Sort by priority (already sorted during registration) - // Priority 100 runs first, then 90, 80, etc. - - // 3. Create middleware chain - let index = 0 - const executeNext = async (): Promise => { - if (index >= applicable.length) { - // All augmentations processed, run main operation - return mainOperation() - } - - const augmentation = applicable[index++] - // Each augmentation decides what to do with the operation - return augmentation.execute(operation, params, executeNext) - } - - return executeNext() -} -``` - -## ๐ŸŽญ The Four Timing Modes in Action - -### **`timing: 'before'`** - Pre-processing -```typescript -class NeuralImportAugmentation { - timing = 'before' - - async execute(op, params, next) { - // Analyze data BEFORE storage - const analysis = await this.analyzeWithAI(params.content) - params.metadata._neural = analysis - - // Continue with enhanced params - return next() - } -} -``` - -### **`timing: 'after'`** - Post-processing -```typescript -class NotionSynapse { - timing = 'after' - - async execute(op, params, next) { - // Let operation complete first - const result = await next() - - // Then sync to Notion - await this.syncToNotion(op, params, result) - - return result - } -} -``` - -### **`timing: 'around'`** - Wrapping -```typescript -class WALAugmentation { - timing = 'around' - - async execute(op, params, next) { - // Write to WAL before - await this.wal.write({ op, params, timestamp: Date.now() }) - - try { - // Execute operation - const result = await next() - - // Mark as committed - await this.wal.commit() - - return result - } catch (error) { - // Rollback on failure - await this.wal.rollback() - throw error - } - } -} -``` - -### **`timing: 'replace'`** - Complete replacement -```typescript -class S3StorageAugmentation { - timing = 'replace' - - async execute(op, params, next) { - if (op === 'storage.get') { - // Don't call next() - completely replace - return await this.s3.getObject(params.key) - } - // For other operations, pass through - return next() - } -} -``` - -## ๐Ÿ“Š Real Example: How `brain.add()` Works - -```typescript -// User calls: -await brain.add("John is a developer", { type: "person" }) - -// This triggers the chain: - -1. BrainyData.add() calls augmentations.execute('add', params, coreLogic) - -2. AugmentationRegistry filters applicable augmentations: - - WALAugmentation (priority: 100, operations: ['all']) - - EntityRegistryAugmentation (priority: 90, operations: ['add']) - - NeuralImportAugmentation (priority: 80, operations: ['add']) - - BatchProcessingAugmentation (priority: 50, operations: ['add']) - -3. Execution chain (highest priority first): - - WALAugmentation.execute() { - await wal.write(operation) // Log to WAL - const result = await next() // Call next in chain - await wal.commit() // Commit WAL - return result - } - โ†“ - EntityRegistryAugmentation.execute() { - const hash = computeHash(params.content) - if (registry.has(hash)) { - return registry.get(hash) // Return existing ID - } - const result = await next() // Continue chain - registry.set(hash, result) // Register new entity - return result - } - โ†“ - NeuralImportAugmentation.execute() { - const analysis = await analyzeWithAI(params) - params.metadata._neural = analysis // Add AI insights - return next() // Continue with enhanced data - } - โ†“ - BatchProcessingAugmentation.execute() { - batch.add(params) // Add to batch - if (batch.isFull()) { - await batch.flush() // Process batch if full - } - return next() // Continue - } - โ†“ - Core add() logic { - // Finally, the actual storage operation - const id = generateId() - await storage.set(id, params) - await index.add(id, vector) - return id - } -``` - -## ๐Ÿ”Œ Dynamic Registration - -Augmentations can be registered at any time: - -```typescript -// During initialization -brain.augmentations.register(new CustomAugmentation()) - -// Or later, dynamically -const synapse = new NotionSynapse({ apiKey: 'xxx' }) -brain.augmentations.register(synapse) - -// From Brain Cloud marketplace -import { EmotionalIntelligence } from '@brain-cloud/empathy' -brain.augmentations.register(new EmotionalIntelligence()) -``` - -## ๐ŸŽฏ Operation Targeting - -Augmentations declare which operations they care about: - -```typescript -class SearchOptimizer { - operations = ['search', 'searchText', 'findSimilar'] // Only search ops -} - -class GlobalLogger { - operations = ['all'] // Every operation -} - -class StorageReplacer { - operations = ['storage'] // Storage operations only -} -``` - -## ๐Ÿ” On-Demand Execution - -Some augmentations can be triggered manually: - -```typescript -// Get specific augmentation -const neuralImport = brain.augmentations.get('neural-import') - -// Use its public API directly -const analysis = await neuralImport.getNeuralAnalysis(data, 'json') - -// Or trigger through operations -await brain.add(data) // Automatically uses neural import if registered -``` - -## ๐Ÿ“ˆ Priority System - -``` -100: Critical Infrastructure (WAL, Transactions) - 90: Data Integrity (Entity Registry, Deduplication) - 80: Data Processing (Neural Import, Transformation) - 50: Performance (Batching, Caching) - 10: Features (Scoring, Analytics) - 1: Monitoring (Logging, Metrics) -``` - -## ๐ŸŒŠ The Flow - -1. **User Action** โ†’ `brain.add()`, `brain.search()`, etc. -2. **Method Wraps** โ†’ Core logic wrapped with `augmentations.execute()` -3. **Filter** โ†’ Find augmentations for this operation -4. **Sort** โ†’ Order by priority -5. **Chain** โ†’ Each augmentation calls next() or not -6. **Core** โ†’ Eventually hits actual implementation -7. **Unwind** โ†’ Results flow back through chain -8. **Return** โ†’ Enhanced result to user - -## ๐Ÿ’ก Key Insights - -1. **Everything is interceptable** - All operations go through the pipeline -2. **Augmentations compose** - They stack like middleware -3. **Priority matters** - Higher priority runs first -4. **Timing is flexible** - before/after/around/replace covers all needs -5. **Simple but powerful** - One interface, infinite possibilities - -This is why the single `BrainyAugmentation` interface works for EVERYTHING - it's just middleware with superpowers! ๐Ÿš€ \ No newline at end of file diff --git a/docs/augmentations-archive/AUGMENTATION-TYPES-SIMPLE-GUIDE.md b/docs/augmentations-archive/AUGMENTATION-TYPES-SIMPLE-GUIDE.md deleted file mode 100644 index b6282f9d..00000000 --- a/docs/augmentations-archive/AUGMENTATION-TYPES-SIMPLE-GUIDE.md +++ /dev/null @@ -1,288 +0,0 @@ -# Simple Guide: Creating Augmentations - -## The One Interface That Rules Them All - -**EVERY augmentation is a `BrainyAugmentation`:** - -```typescript -interface BrainyAugmentation { - name: string // Unique name - timing: 'before' | 'after' | 'around' | 'replace' // When to run - operations: string[] // What to intercept - priority: number // Order (higher = first) - - initialize(context): Promise // Setup - execute(op, params, next): Promise // Do work - shutdown?(): Promise // Cleanup (optional) -} -``` - -That's it! Every augmentation implements this interface. - -## Creating Different Types of Augmentations - -### 1. Basic Feature Augmentation - -**Use Case:** Add logging, caching, validation, etc. - -```typescript -import { BaseAugmentation } from 'brainy' - -export class LoggingAugmentation extends BaseAugmentation { - name = 'logging' - timing = 'around' // Wrap operations - operations = ['add', 'delete'] // What to log - priority = 10 // Low priority - - async execute(op, params, next) { - console.log(`Starting ${op}`) - const result = await next() - console.log(`Completed ${op}`) - return result - } -} - -// Usage -brain.augmentations.register(new LoggingAugmentation()) -``` - -### 2. Storage Augmentation - -**Use Case:** Provide a storage backend (special: has `provideStorage()` method) - -```typescript -import { StorageAugmentation } from 'brainy' - -export class RedisStorageAugmentation extends StorageAugmentation { - constructor(config) { - super('redis-storage') // Pass name to parent - this.config = config - } - - // Special method for storage only! - async provideStorage() { - return new RedisAdapter(this.config) - } -} - -// Usage (BEFORE init!) -brain.augmentations.register(new RedisStorageAugmentation({ - host: 'localhost', - port: 6379 -})) -await brain.init() // Will use Redis! -``` - -### 3. Data Processing Augmentation - -**Use Case:** Transform or validate data before storage - -```typescript -export class ValidationAugmentation extends BaseAugmentation { - name = 'validator' - timing = 'before' // Run before operation - operations = ['add'] // Validate on add - priority = 50 - - async execute(op, params, next) { - // Validate data - if (!params.data || !params.data.title) { - throw new Error('Title is required') - } - - // Add timestamp - params.data.createdAt = new Date() - - // Continue with modified params - return next() - } -} -``` - -### 4. External System Augmentation (Synapse) - -**Use Case:** Sync with external systems like Notion, Slack, etc. - -```typescript -export class NotionSyncAugmentation extends BaseAugmentation { - name = 'notion-sync' - timing = 'after' // Sync after local operation - operations = ['add', 'update', 'delete'] - priority = 30 - - private notion: NotionClient - - async initialize(context) { - await super.initialize(context) - this.notion = new NotionClient(this.apiKey) - } - - async execute(op, params, next) { - // Do local operation first - const result = await next() - - // Then sync to Notion - if (op === 'add') { - await this.notion.createPage({ - title: params.data.title, - content: params.data.content - }) - } - - return result - } -} -``` - -### 5. Performance Optimization Augmentation - -**Use Case:** Add caching, batching, deduplication - -```typescript -export class CacheAugmentation extends BaseAugmentation { - name = 'smart-cache' - timing = 'around' // Wrap to check cache - operations = ['search'] // Cache searches only - priority = 60 - - private cache = new Map() - - async execute(op, params, next) { - const key = JSON.stringify(params) - - // Check cache - if (this.cache.has(key)) { - this.log('Cache hit!') - return this.cache.get(key) - } - - // Miss - execute and cache - const result = await next() - this.cache.set(key, result) - - // Clear old entries if too many - if (this.cache.size > 1000) { - const firstKey = this.cache.keys().next().value - this.cache.delete(firstKey) - } - - return result - } -} -``` - -## Quick Reference: When to Use Each Timing - -| Timing | Use For | Example | -|--------|---------|---------| -| `before` | Validation, transformation | Check required fields | -| `after` | Logging, syncing, analytics | Send to external API | -| `around` | Caching, error handling, timing | Wrap with try/catch | -| `replace` | Complete replacement | Storage backends | - -## Quick Reference: Common Operations - -| Operation | Description | -|-----------|-------------| -| `'add'` | Adding data to brain | -| `'search'` | Searching/querying | -| `'update'` | Updating existing data | -| `'delete'` | Removing data | -| `'storage'` | Storage resolution (special) | -| `'all'` | Intercept everything | - -## The Context Object - -Every augmentation gets this during `initialize()`: - -```typescript -{ - brain: BrainyData, // The brain instance - storage: StorageAdapter, // Storage backend - config: BrainyDataConfig, // Configuration - log: (msg, level) => void // Logger -} -``` - -## Priority Guidelines - -| Priority | Use For | -|----------|---------| -| 100 | Storage (critical infrastructure) | -| 80-99 | System operations (WAL, connections) | -| 50-79 | Performance (caching, batching) | -| 20-49 | Features (validation, transformation) | -| 1-19 | Logging, analytics | - -## Complete Working Example - -Here's a full augmentation that adds word count to all documents: - -```typescript -import { BaseAugmentation } from 'brainy' - -export class WordCountAugmentation extends BaseAugmentation { - name = 'word-counter' - timing = 'before' - operations = ['add', 'update'] - priority = 40 - - async execute(operation, params, next) { - // Add word count to metadata - if (params.data && params.data.content) { - const wordCount = params.data.content.split(/\s+/).length - params.metadata = params.metadata || {} - params.metadata.wordCount = wordCount - - this.log(`Added word count: ${wordCount}`) - } - - // Continue with enhanced params - return next() - } - - async initialize(context) { - await super.initialize(context) - this.log('Word counter ready!') - } -} - -// Usage -const brain = new BrainyData() -brain.augmentations.register(new WordCountAugmentation()) -await brain.init() - -// Now all adds include word count -await brain.add('Hello world', { - content: 'This is a test document with nine words here' -}) -// Automatically adds: metadata.wordCount = 9 -``` - -## Key Points to Remember - -1. **All augmentations are `BrainyAugmentation`** - One interface -2. **Storage augmentations** add `provideStorage()` method -3. **Register before `init()`** for storage, anytime for others -4. **Use `BaseAugmentation`** for convenience (has helpers) -5. **`next()` is crucial** - Always call it (unless `replace`) -6. **Order matters** - Use priority to control execution order - -## Testing Your Augmentation - -```typescript -describe('MyAugmentation', () => { - it('should enhance data', async () => { - const brain = new BrainyData() - brain.augmentations.register(new MyAugmentation()) - await brain.init() - - await brain.add('test', { data: 'test' }) - const result = await brain.search('test') - - expect(result[0].metadata.enhanced).toBe(true) - }) -}) -``` - -That's it! Augmentations are simple middleware that intercept operations. Pick your timing, operations, and priority, then implement `execute()`! \ No newline at end of file diff --git a/docs/augmentations-archive/COMPLETE-ARCHITECTURE-VISION.md b/docs/augmentations-archive/COMPLETE-ARCHITECTURE-VISION.md deleted file mode 100644 index d4270122..00000000 --- a/docs/augmentations-archive/COMPLETE-ARCHITECTURE-VISION.md +++ /dev/null @@ -1,292 +0,0 @@ -# ๐Ÿง  The Complete Brainy Architecture Vision - -## ๐ŸŽฏ The Genius: Everything is an Augmentation - -``` - ๐Ÿง  BRAINY CORE - โ”‚ - โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” - โ”‚ Augmentations โ”‚ - โ”‚ Pipeline โ”‚ - โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ - โ”‚ - โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ผโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” - โ”‚ โ”‚ โ”‚ - Data Processing External API Exposure - Augmentations Connections Augmentations - โ”‚ โ”‚ โ”‚ - NeuralImport Synapses APIServer - EntityRegistry (Notion,etc) (REST/WS) - BatchProcessing โ”‚ MCPServer - IntelligentScoring โ”‚ GraphQLServer - โ”‚ โ”‚ โ”‚ - โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ - โ”‚ - Storage Layer - (FS, S3, OPFS, Memory) -``` - -## ๐Ÿ”„ How It All Works Together - -### 1. **Core Pipeline** -Every operation flows through the augmentation pipeline: - -```typescript -User Action โ†’ BrainyData Method โ†’ Augmentation Pipeline โ†’ Storage - โ†‘ - All Augmentations Execute Here -``` - -### 2. **Augmentation Categories (All Using Same Interface!)** - -#### ๐Ÿงฌ **Data Processing** (timing: 'before') -- **NeuralImport** - AI understands data before storage -- **EntityRegistry** - Deduplicates entities -- **BatchProcessing** - Optimizes bulk operations - -#### ๐ŸŒ **External Connections** (timing: 'after') -- **Synapses** - Sync with Notion, Salesforce, etc. -- **WebSocketBroadcast** - Real-time updates to clients -- **TeamCoordination** - Multi-agent synchronization - -#### ๐Ÿ“ก **API Exposure** (timing: 'after' or separate process) -- **APIServerAugmentation** - REST/WebSocket/MCP server -- **GraphQLAugmentation** - GraphQL endpoint -- **ServiceWorkerAugmentation** - Browser local API - -#### ๐Ÿ’พ **Storage Backends** (timing: 'replace') -- **S3StorageAugmentation** - Use S3 instead of local -- **RedisAugmentation** - Use Redis for caching -- **PostgresAugmentation** - Use Postgres for persistence - -#### ๐Ÿ›ก๏ธ **Infrastructure** (timing: 'around') -- **WALAugmentation** - Write-ahead logging -- **TransactionAugmentation** - ACID transactions -- **CacheAugmentation** - Multi-level caching - -## ๐ŸŒŸ The Beautiful Simplicity - -### One Interface Rules All - -```typescript -interface BrainyAugmentation { - name: string - timing: 'before' | 'after' | 'around' | 'replace' - operations: string[] - priority: number - initialize(context): Promise - execute(operation, params, next): Promise - shutdown?(): Promise -} -``` - -This single interface can: -- **Process data** with AI -- **Connect** to any external service -- **Expose** APIs (REST, WebSocket, MCP, GraphQL) -- **Replace** storage backends -- **Add** infrastructure (WAL, transactions, caching) -- **Coordinate** distributed systems -- **Visualize** data in real-time -- Literally **ANYTHING** - -## ๐Ÿ—๏ธ Real-World Deployment Architecture - -### Scenario 1: Local Development -```typescript -const brain = new BrainyData({ - augmentations: [ - new NeuralImportAugmentation(), // AI processing - new EntityRegistryAugmentation(), // Deduplication - new WALAugmentation() // Durability - ] -}) -``` - -### Scenario 2: Production Server -```typescript -const brain = new BrainyData({ - augmentations: [ - // Infrastructure - new WALAugmentation(), - new ConnectionPoolAugmentation(), - new RequestDeduplicatorAugmentation(), - - // Data Processing - new NeuralImportAugmentation(), - new EntityRegistryAugmentation(), - new BatchProcessingAugmentation(), - - // External Connections - new NotionSynapse({ apiKey: 'xxx' }), - new SlackSynapse({ token: 'xxx' }), - - // API Exposure - new APIServerAugmentation({ port: 3000 }), - new MCPServerAugmentation({ port: 3001 }), - - // Monitoring - new MetricsAugmentation(), - new LoggingAugmentation() - ] -}) -``` - -### Scenario 3: Distributed AI Agent System -```typescript -const brain = new BrainyData({ - augmentations: [ - // Agent Coordination - new TeamCoordinationAugmentation(), - new DistributedLockAugmentation(), - new SharedMemoryAugmentation(), - - // Agent Memory - new MCPAgentMemoryAugmentation(), - new ConversationHistoryAugmentation(), - - // Real-time Communication - new WebSocketBroadcastAugmentation(), - new PubSubAugmentation(), - - // Visualization - new GraphVisualizationAugmentation() - ] -}) -``` - -## ๐Ÿ”Œ How API Exposure Works - -The **APIServerAugmentation** is special - it can run in two modes: - -### Mode 1: Embedded (Same Process) -```typescript -brain.augmentations.register(new APIServerAugmentation()) -// API server runs in same process, hooks into pipeline -``` - -### Mode 2: Standalone (Separate Process) -```typescript -// server.js - separate file -import { BrainyData } from 'brainy' -import { APIServerAugmentation } from 'brainy/augmentations' - -const brain = new BrainyData() -const apiServer = new APIServerAugmentation() - -// Can also run as standalone server connecting to remote Brainy -apiServer.connectToRemoteBrainy('ws://brainy-host:8080') -apiServer.listen(3000) -``` - -## ๐ŸŽญ The Four Timing Modes in Practice - -### System Startup Sequence -``` -1. INITIALIZE Phase - โ””โ”€> All augmentations initialize (storage, connections, servers) - -2. OPERATION Phase (for each operation) - โ”œโ”€> 'before' augmentations (NeuralImport, Validation) - โ”œโ”€> 'around' augmentations start (WAL, Transactions) - โ”œโ”€> 'replace' augmentations (if any, skip core) - โ”œโ”€> Core operation (or replaced operation) - โ”œโ”€> 'around' augmentations complete (Commit/Rollback) - โ””โ”€> 'after' augmentations (Sync, Broadcast, Log) - -3. SHUTDOWN Phase - โ””โ”€> All augmentations cleanup (close connections, flush buffers) -``` - -## ๐ŸŒ Deployment Patterns - -### Pattern 1: Monolithic -Everything in one process: -``` -โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” -โ”‚ Single Node.js Process โ”‚ -โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ -โ”‚ โ”‚ BrainyData Core โ”‚ โ”‚ -โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚ -โ”‚ โ”‚ All Augmentations โ”‚ โ”‚ -โ”‚ โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค โ”‚ -โ”‚ โ”‚ API Server โ”‚ โ”‚ -โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ -โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ -``` - -### Pattern 2: Microservices -Distributed across services: -``` -โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” -โ”‚ Brainy Core โ”‚โ”€โ”€โ”€โ”€โ–ถโ”‚ API Gateway โ”‚โ”€โ”€โ”€โ”€โ–ถโ”‚ Clients โ”‚ -โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ - โ”‚ - โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” - โ–ผ โ–ผ -โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” -โ”‚ Synapses โ”‚ โ”‚ AI Agents โ”‚ -โ”‚ Service โ”‚ โ”‚ Service โ”‚ -โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ -``` - -### Pattern 3: Edge Computing -Brainy at the edge: -``` -โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” -โ”‚ CloudFlare Worker โ”‚ -โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ -โ”‚ โ”‚ Brainy (Memory Storage) โ”‚ โ”‚ -โ”‚ โ”‚ + API Server Augmentation โ”‚ โ”‚ -โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ -โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ - โ”‚ - โ–ผ - โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” - โ”‚ S3 Storage โ”‚ - โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ -``` - -## ๐Ÿš€ The Power of Composition - -Any combination works because everything uses the same interface: - -```typescript -// Local AI Assistant -[NeuralImport, ChatInterface, LocalStorage] - -// Production API -[WAL, S3Storage, APIServer, RateLimiting] - -// Multi-Agent System -[TeamCoordination, MCPServer, GraphVisualization] - -// Data Pipeline -[KafkaConsumer, NeuralImport, PostgresStorage] - -// Real-time Analytics -[StreamProcessing, Clustering, WebSocketBroadcast] -``` - -## ๐ŸŽฏ Key Insights - -1. **No Special Cases** - Everything is an augmentation -2. **Complete Flexibility** - Mix and match any combination -3. **Environment Agnostic** - Works in browser, Node, Deno, edge -4. **Protocol Agnostic** - REST, WebSocket, MCP, GraphQL, gRPC -5. **Storage Agnostic** - Local, S3, Redis, Postgres, anything -6. **Infinitely Extensible** - Just add more augmentations - -## ๐Ÿง  The Philosophy - -> "Make everything an augmentation, and the system becomes infinitely flexible while remaining dead simple." - -This is why Brainy can be: -- A local embedded database -- A distributed knowledge graph -- An AI agent memory system -- A real-time collaboration platform -- A data pipeline processor -- All of the above simultaneously - -**One interface. Infinite possibilities. That's the Brainy way.** ๐Ÿš€ \ No newline at end of file diff --git a/docs/augmentations-archive/README.md b/docs/augmentations-archive/README.md deleted file mode 100644 index cd05fb63..00000000 --- a/docs/augmentations-archive/README.md +++ /dev/null @@ -1,18 +0,0 @@ -# Augmentations Documentation Archive - -This directory contains historical augmentation documentation from the Brainy 2.0 development process. - -## Current Documentation -The definitive augmentation documentation is now located at: -- **`/docs/augmentations/README.md`** - Main augmentation guide -- **`/docs/architecture/augmentations.md`** - Architecture details - -## Archived Documents -These documents represent the evolution of the augmentation system design: -- Various implementation approaches -- Pipeline architecture exploration -- Storage augmentation patterns -- Example implementations - -## Note -These documents are archived to preserve development history while maintaining a clean documentation structure. \ No newline at end of file diff --git a/docs/augmentations-archive/STORAGE-AUGMENTATIONS-GUIDE.md b/docs/augmentations-archive/STORAGE-AUGMENTATIONS-GUIDE.md deleted file mode 100644 index f1de0657..00000000 --- a/docs/augmentations-archive/STORAGE-AUGMENTATIONS-GUIDE.md +++ /dev/null @@ -1,276 +0,0 @@ -# Storage Augmentations Guide - -## Overview - -Brainy uses a unified augmentation system for storage backends. This guide explains the difference between built-in storage augmentations and how to create custom ones. - -## Built-in Storage Augmentations - -These wrap existing, battle-tested storage adapters from `/storage/adapters/`: - -| Augmentation | Underlying Adapter | Environment | Description | -|--------------|-------------------|-------------|-------------| -| `MemoryStorageAugmentation` | `MemoryStorage` | Universal | Fast in-memory storage (not persistent) | -| `FileSystemStorageAugmentation` | `FileSystemStorage` | Node.js | Persistent file-based storage | -| `OPFSStorageAugmentation` | `OPFSStorage` | Browser | Browser persistent storage | -| `S3StorageAugmentation` | `S3CompatibleStorage` | Universal | Amazon S3 with throttling & caching | -| `R2StorageAugmentation` | `R2Storage` | Universal | Cloudflare R2 storage | -| `GCSStorageAugmentation` | `S3CompatibleStorage` | Universal | Google Cloud Storage | - -### Architecture of Built-in Storage - -``` -BrainyData - โ†“ -StorageAugmentation (thin wrapper) - โ†“ -StorageAdapter (actual implementation in /storage/adapters/) - โ†“ -Actual Storage (filesystem, S3, memory, etc.) -``` - -### Why This Design? - -1. **Preserve existing code** - Storage adapters have years of bug fixes -2. **Complex features intact** - S3 throttling, caching, retry logic preserved -3. **Minimal wrapper** - Augmentations are just 20-30 lines -4. **Zero feature loss** - All 30+ StorageAdapter methods work unchanged - -## Using Built-in Storage - -### 1. Zero-Config (Auto-Selection) -```typescript -const brain = new BrainyData() -await brain.init() -// Automatically selects: -// - Node.js โ†’ FileSystemStorage -// - Browser โ†’ OPFSStorage (or Memory fallback) -``` - -### 2. Configuration-Based -```typescript -const brain = new BrainyData({ - storage: { - s3Storage: { - bucketName: 'my-bucket', - accessKeyId: 'xxx', - secretAccessKey: 'yyy' - } - } -}) -``` - -### 3. Augmentation Override -```typescript -const brain = new BrainyData() -brain.augmentations.register(new S3StorageAugmentation({ - bucketName: 'my-bucket', - region: 'us-east-1', - accessKeyId: 'xxx', - secretAccessKey: 'yyy' -})) -await brain.init() -``` - -## Creating Custom Storage Augmentations - -Custom storage augmentations can either: -1. Wrap an existing adapter (like built-ins do) -2. Implement the StorageAdapter interface directly - -### Option 1: Wrapping an Existing Adapter - -```typescript -import { StorageAugmentation } from 'brainy' -import { CustomAdapter } from './my-custom-adapter' - -export class CustomStorageAugmentation extends StorageAugmentation { - private config: CustomConfig - - constructor(config: CustomConfig) { - super('custom-storage') - this.config = config - } - - async provideStorage(): Promise { - // Create and return your adapter - const adapter = new CustomAdapter(this.config) - return adapter - } -} -``` - -### Option 2: Self-Contained Implementation - -```typescript -import { StorageAugmentation, StorageAdapter } from 'brainy' -import Redis from 'ioredis' - -export class RedisStorageAugmentation extends StorageAugmentation { - private redis: Redis - - constructor(config: RedisConfig) { - super('redis-storage') - this.redis = new Redis(config) - } - - async provideStorage(): Promise { - // Return an object implementing StorageAdapter - return { - async init() { - await this.redis.ping() - }, - - async saveNoun(noun) { - await this.redis.set( - `noun:${noun.id}`, - JSON.stringify(noun) - ) - }, - - async getNoun(id) { - const data = await this.redis.get(`noun:${id}`) - return data ? JSON.parse(data) : null - }, - - async deleteNoun(id) { - await this.redis.del(`noun:${id}`) - }, - - // ... implement all 30+ required methods - // See StorageAdapter interface in coreTypes.ts - } - } -} -``` - -## StorageAdapter Interface Requirements - -Your custom storage must implement these core methods: - -```typescript -interface StorageAdapter { - // Initialization - init(): Promise - - // Noun operations - saveNoun(noun: HNSWNoun): Promise - getNoun(id: string): Promise - deleteNoun(id: string): Promise - getNounsByNounType(type: string): Promise - - // Verb operations - saveVerb(verb: HNSWVerb): Promise - getVerb(id: string): Promise - deleteVerb(id: string): Promise - getVerbsBySource(sourceId: string): Promise - getVerbsByTarget(targetId: string): Promise - - // Metadata operations - saveMetadata(id: string, metadata: any): Promise - getMetadata(id: string): Promise - saveVerbMetadata(id: string, metadata: any): Promise - getVerbMetadata(id: string): Promise - - // Pagination - getNouns(options?: PaginationOptions): Promise - getVerbs(options?: PaginationOptions): Promise - - // Statistics - getStatistics(): Promise - saveStatistics(stats: StatisticsData): Promise - incrementStatistic(type: string, service: string): Promise - - // Utility - clear(): Promise - getStorageStatus(): Promise - - // ... plus ~10 more methods -} -``` - -## Publishing to Brain Cloud (Future) - -Custom storage augmentations can be published to the Brain Cloud marketplace: - -```json -// package.json -{ - "name": "@brain-cloud/redis-storage", - "version": "1.0.0", - "brainy": { - "type": "augmentation", - "category": "storage", - "implements": "StorageAdapter" - } -} -``` - -Users will be able to install via: -```bash -brainy augment install redis-storage -``` - -## Best Practices - -1. **Use existing adapters when possible** - They're well-tested -2. **Implement all methods** - StorageAdapter has 30+ required methods -3. **Handle errors gracefully** - Storage is critical infrastructure -4. **Include connection pooling** - For network-based storage -5. **Add retry logic** - Network operations can fail -6. **Implement caching** - Reduce latency for hot data -7. **Track statistics** - Use BaseStorageAdapter if possible -8. **Document configuration** - Make it easy for users - -## Examples in the Wild - -### MongoDB Storage (Community) -```typescript -class MongoStorageAugmentation extends StorageAugmentation { - async provideStorage() { - const client = new MongoClient(this.uri) - const db = client.db('brainy') - - return { - async saveNoun(noun) { - await db.collection('nouns').replaceOne( - { _id: noun.id }, - noun, - { upsert: true } - ) - }, - // ... full implementation - } - } -} -``` - -### PostgreSQL Storage (Premium) -```typescript -class PostgreSQLStorageAugmentation extends StorageAugmentation { - async provideStorage() { - const pool = new Pool(this.config) - - return { - async saveNoun(noun) { - await pool.query( - 'INSERT INTO nouns (id, data) VALUES ($1, $2) ON CONFLICT (id) DO UPDATE SET data = $2', - [noun.id, JSON.stringify(noun)] - ) - }, - // ... full implementation - } - } -} -``` - -## Summary - -- **Built-in augmentations** wrap existing adapters (thin layer) -- **Custom augmentations** can wrap OR implement directly -- **Storage adapters** in `/storage/adapters/` are for core only -- **Premium storage** comes as self-contained augmentations -- **Everything uses** the same StorageAdapter interface -- **Zero-config** still works perfectly - -This design provides maximum flexibility while preserving all existing functionality! \ No newline at end of file diff --git a/docs/augmentations-archive/UNIFIED-AUGMENTATION-SYSTEM.md b/docs/augmentations-archive/UNIFIED-AUGMENTATION-SYSTEM.md deleted file mode 100644 index b0930e85..00000000 --- a/docs/augmentations-archive/UNIFIED-AUGMENTATION-SYSTEM.md +++ /dev/null @@ -1,239 +0,0 @@ -# ๐Ÿง  Unified Augmentation System - -## The Single Interface That Rules Them All - -Brainy uses ONE elegant interface for ALL augmentations: - -```typescript -interface BrainyAugmentation { - name: string - timing: 'before' | 'after' | 'around' | 'replace' - operations: string[] - priority: number - initialize(context): Promise - execute(operation, params, next): Promise - shutdown?(): Promise -} -``` - -## Why This Works for EVERYTHING - -### ๐ŸŽญ The Four Timing Modes - -1. **`before`**: Pre-process data - - Data validation - - Authentication checks - - Input transformation - -2. **`after`**: Post-process results - - Logging - - Analytics - - Cache updates - -3. **`around`**: Wrap operations (middleware) - - Error handling - - Performance monitoring - - Transaction management - -4. **`replace`**: Complete replacement - - Alternative storage backends - - Mock implementations - - Custom algorithms - -### ๐ŸŽฏ Operation Targeting - -Augmentations can target: -- Specific operations: `['add', 'search']` -- All operations: `['all']` -- Pattern matching: Operations containing certain strings - -### ๐Ÿ”„ The Execute Chain - -```typescript -async execute(operation, params, next): Promise { - // Before logic - console.log(`Starting ${operation}`) - - // Call next (or don't!) - const result = await next() - - // After logic - console.log(`Completed ${operation}`) - - return result -} -``` - -## ๐Ÿ“ฆ Categories of Augmentations - -While using the same interface, augmentations naturally fall into categories: - -### 1. **Data Processing** -```typescript -class NeuralImportAugmentation { - timing = 'before' - operations = ['add', 'addNoun'] - - async execute(op, params, next) { - // Analyze data with AI - const enhanced = await this.processWithAI(params) - // Continue with enhanced data - return next(enhanced) - } -} -``` - -### 2. **External Connections (Synapses)** -```typescript -class NotionSynapse { - timing = 'after' - operations = ['add', 'update', 'delete'] - - async initialize(context) { - await this.connectToNotion() - } - - async execute(op, params, next) { - const result = await next() - // Sync to Notion after local operation - await this.syncToNotion(op, params) - return result - } -} -``` - -### 3. **Storage Backends** -```typescript -class S3StorageAugmentation { - timing = 'replace' - operations = ['storage'] - - async execute(op, params, next) { - // Don't call next() - replace entirely - return await this.s3Client.store(params) - } -} -``` - -### 4. **Real-time Communication** -```typescript -class WebSocketBroadcast { - timing = 'after' - operations = ['all'] - - async initialize(context) { - this.ws = new WebSocket(url) - } - - async execute(op, params, next) { - const result = await next() - // Broadcast changes - this.ws.send({ op, params, result }) - return result - } -} -``` - -### 5. **AI Agent Coordination** -```typescript -class TeamMemoryAugmentation { - timing = 'around' - operations = ['add', 'search'] - - async execute(op, params, next) { - // Acquire distributed lock - await this.acquireLock(op) - try { - // Synchronize with team - const teamData = await this.syncWithTeam(params) - const result = await next(teamData) - // Broadcast result to team - await this.broadcastToTeam(result) - return result - } finally { - await this.releaseLock(op) - } - } -} -``` - -### 6. **Analytics & Prediction** -```typescript -class PredictiveAnalytics { - timing = 'after' - operations = ['search'] - - async execute(op, params, next) { - const results = await next() - // Analyze search patterns - this.recordPattern(params, results) - // Add predictions - results.predictions = await this.predict(params) - return results - } -} -``` - -## ๐Ÿ”Œ How Augmentations Connect - -```typescript -// In BrainyData initialization -const brain = new BrainyData({ - augmentations: [ - new NeuralImportAugmentation(), - new NotionSynapse({ apiKey: 'xxx' }), - new TeamMemoryAugmentation(), - new PredictiveAnalytics() - ] -}) - -// Or dynamically -brain.augmentations.register(new CustomAugmentation()) -``` - -## ๐ŸŽฏ Priority System - -```typescript -// Execution order (highest first) -100: Critical (WAL, Storage) -50: Performance (Cache, Dedup) -10: Features (Scoring, Analytics) -1: Optional (Logging) -``` - -## ๐ŸŒ Brain Cloud Integration - -All augmentations (free, community, premium) use this SAME interface: - -```typescript -// From Brain Cloud marketplace -import { EmotionalIntelligence } from '@brainy-cloud/empathy' - -const empathy = new EmotionalIntelligence() -// It's just a BrainyAugmentation! -brain.augmentations.register(empathy) -``` - -## ๐Ÿ’ก Why This Design Wins - -1. **Simplicity**: One interface to learn -2. **Flexibility**: Can do literally anything -3. **Composability**: Stack augmentations like middleware -4. **Extensibility**: Easy to add new augmentations -5. **Marketplace Ready**: All augmentations compatible - -## ๐Ÿš€ The Future is Unified - -No more complex type hierarchies. No more ISenseAugmentation, IConduitAugmentation, etc. - -Just one beautiful, simple interface that can: -- Process data with AI -- Connect to any platform -- Coordinate AI teams -- Provide predictive analytics -- Add empathy to AI -- Store anywhere -- Communicate in real-time -- And literally anything else you can imagine - -**One interface. Infinite possibilities. That's the Brainy way.** ๐Ÿง โœจ \ No newline at end of file diff --git a/docs/planning/FINAL_RELEASE_ASSESSMENT.md b/docs/planning/FINAL_RELEASE_ASSESSMENT.md deleted file mode 100644 index e34c0861..00000000 --- a/docs/planning/FINAL_RELEASE_ASSESSMENT.md +++ /dev/null @@ -1,167 +0,0 @@ -# ๐Ÿš€ Brainy 2.0 - FINAL RELEASE ASSESSMENT - -## ๐Ÿ“… Final Review: 2025-08-22 15:25 UTC - -## โœ… 100% RELEASE CONFIDENCE ACHIEVED - -### Core Functionality: BULLETPROOF โœ… - -#### 1. **Intelligent Verb Scoring** - 18/18 Tests Passing โœ… -- โœ… Smart by default (enabled=true) -- โœ… Proper augmentation interception working -- โœ… Semantic similarity computation -- โœ… Temporal decay reasoning -- โœ… Learning statistics -- โœ… Export/Import functionality -- โœ… Standalone augmentation API -- **Status: PRODUCTION READY** - -#### 2. **Triple Intelligence (find())** - Comprehensive Coverage โœ… -- โœ… Natural language queries ("find developers") -- โœ… Vector similarity search (`similar: 'text'`) -- โœ… Graph traversal (`connected: { to: 'node' }`) -- โœ… Metadata filtering (`where: { field: 'value' }`) -- โœ… Combined intelligence with fusion scoring -- โœ… Performance optimized for complex queries -- **Status: PRODUCTION READY** - -#### 3. **Neural APIs** - External Library Ready โœ… -- โœ… Similarity calculation API -- โœ… Clustering algorithms (hierarchical, k-means) -- โœ… Visualization data generation (nodes/edges with coordinates) -- โœ… Semantic neighbors -- โœ… Performance caching -- **Status: READY FOR EXTERNAL LIBRARIES** - -#### 4. **Zero Configuration** - Perfect โœ… -- โœ… `new BrainyData()` works immediately -- โœ… Model loading cascade: Local โ†’ CDN โ†’ GitHub โ†’ HuggingFace -- โœ… 384 dimensions enforced automatically -- โœ… All augmentations enabled by default -- **Status: ZERO-CONFIG VERIFIED** - -### Test Coverage: EXTENSIVE โœ… - -#### Created Comprehensive Test Suites -1. **Intelligent Verb Scoring**: 18 tests covering all functionality -2. **Neural Import**: Complete test coverage for file processing -3. **Neural Clustering**: Full API test coverage for external use -4. **Find() Method**: Extensive Triple Intelligence tests -5. **Augmentations**: WAL, Entity Registry, Batch Processing, Request Deduplicator -6. **Release Critical**: Core functionality validation - -#### Test Infrastructure -- โœ… Memory-safe test runner created -- โœ… Test isolation strategies documented -- โœ… Proper cleanup in all test files -- โœ… Performance benchmarks included - -### Architecture: SOLID โœ… - -#### Fixed All Critical Issues -- โœ… Consolidated duplicate intelligent verb scoring implementations -- โœ… Proper BaseAugmentation system throughout -- โœ… Correct 2.0 API usage (addNoun/addVerb) everywhere -- โœ… Smart defaults (features enabled by default) -- โœ… No old interfaces or legacy code paths - -#### Performance Optimizations -- โœ… HNSW indexing for O(log n) vector search -- โœ… Request deduplication for 3x performance boost -- โœ… Batch processing with adaptive batching -- โœ… Entity registry for O(1) lookups -- โœ… Multi-level caching systems - -## ๐ŸŽฏ RELEASE READINESS: 100% - -### What We Ship -```typescript -// The complete Brainy 2.0 experience -const brain = new BrainyData() -await brain.init() - -// Revolutionary noun-verb data model -await brain.addNoun(vector, metadata) -await brain.addVerb(source, target, type) - -// Triple Intelligence in one method -const results = await brain.find('find developers who use JavaScript') - -// Neural APIs for external libraries -const neural = new NeuralAPI(brain) -const clusters = await neural.clusters() -const viz = await neural.visualize() -``` - -### Core Innovation Validated -- โœ… **Triple Intelligence**: Vector + Graph + Metadata search unified -- โœ… **Intelligent Verb Scoring**: Smart relationship weights -- โœ… **Neural APIs**: Ready for external visualization libraries -- โœ… **Zero Config**: Works perfectly out of the box -- โœ… **384 Dimensions**: All-MiniLM-L6-v2 model enforced - -### Enterprise Features Included -- โœ… WAL (Write-Ahead Logging) for durability -- โœ… Entity Registry for high-throughput deduplication -- โœ… Batch Processing with adaptive optimization -- โœ… Request Deduplicator for 3x performance -- โœ… Connection Pooling for resource management -- โœ… All storage adapters (Filesystem, S3, OPFS, Memory) - -## ๐Ÿ”ฅ CONFIDENCE FACTORS - -### Technical Excellence โœ… -- **Core API**: Rock solid, 18/18 tests passing for key features -- **Performance**: Sub-100ms search for 100 items -- **Memory**: Efficient cleanup, no significant leaks -- **Error Handling**: Graceful failure recovery -- **Scalability**: Tested with complex datasets - -### Innovation Leadership โœ… -- **First True Triple Intelligence**: Vector + Graph + Metadata unified -- **Smart by Default**: No configuration required -- **Revolutionary Data Model**: Noun-verb taxonomy -- **Neural API**: Ready for external clustering/visualization libraries - -### Production Readiness โœ… -- **Zero Breaking Changes**: For existing users -- **MIT Licensed**: No premium features, everything included -- **Comprehensive Documentation**: All APIs documented -- **Backward Compatible**: Existing code continues to work - -## ๐Ÿš€ FINAL RECOMMENDATION: **SHIP IT!** - -Brainy 2.0 represents a fundamental leap forward in vector database technology: - -1. **Triple Intelligence** solves the problem of having to choose between vector, graph, or metadata search -2. **Intelligent Verb Scoring** automatically computes optimal relationship weights -3. **Neural APIs** enable external libraries to build advanced visualizations -4. **Zero Configuration** makes it accessible to all developers - -The core innovation is **validated**, **tested**, and **ready for production**. - -## โœ… Pre-Release Checklist Complete - -- [x] All critical features tested and working -- [x] Performance benchmarks passed -- [x] Memory management verified -- [x] Error handling robust -- [x] Zero-config validated -- [x] Documentation complete -- [x] API surface stable -- [x] No breaking changes -- [x] License verified (MIT) -- [x] Dependencies audited - -## ๐ŸŽ‰ SHIP BRAINY 2.0! - -**Release Confidence: 100%** -**Ready for npm publish: YES** -**Ready for production use: YES** - -*The future of intelligent data is here.* - ---- -*Final Assessment: 2025-08-22 15:25 UTC* -*Assessor: Claude Code Assistant* -*Status: โœ… APPROVED FOR RELEASE* \ No newline at end of file diff --git a/docs/planning/IMPLEMENTATION_STATUS.md b/docs/planning/IMPLEMENTATION_STATUS.md deleted file mode 100644 index 4d04ccc5..00000000 --- a/docs/planning/IMPLEMENTATION_STATUS.md +++ /dev/null @@ -1,177 +0,0 @@ -# Brainy 2.0.0 Implementation Status - -## โœ… Fully Implemented & Working - -### Core Features -- โœ… **Noun-Verb Taxonomy** - Complete implementation with addNoun() and addVerb() -- โœ… **Triple Intelligence Engine** - Vector + Graph + Metadata unified queries -- โœ… **Natural Language find()** - Basic NLP with 220+ embedded patterns -- โœ… **HNSW Vector Search** - O(log n) similarity search -- โœ… **Field Indexing** - O(1) metadata lookups via FieldIndex class -- โœ… **Graph Pathfinding** - Relationship traversal system - -### Storage Adapters -- โœ… **Memory Storage** - Full implementation -- โœ… **FileSystem Storage** - Production ready -- โœ… **OPFS Storage** - Browser persistent storage -- โœ… **S3-Compatible Storage** - AWS S3, MinIO, etc. - -### Augmentations -- โœ… **WAL Augmentation** - Write-ahead logging for durability -- โœ… **Entity Registry** - High-performance deduplication -- โœ… **Intelligent Verb Scoring** - Relationship strength calculation -- โœ… **Auto-Register Entities** - Basic entity extraction -- โœ… **Batch Processing** - Bulk operation optimization -- โœ… **Connection Pool** - Connection management -- โœ… **WebSocket Conduit** - Real-time communication -- โœ… **Memory Augmentations** - Storage-specific optimizations - -### Performance -- โœ… **Multi-level Caching** - EnhancedCacheManager implemented -- โœ… **Read-only Optimizations** - Special optimizations for read-only mode -- โœ… **Batch Operations** - Efficient bulk processing -- โœ… **Lazy Loading** - On-demand resource loading - -## โš ๏ธ Partially Implemented - -### Natural Language Processing -- โœ… Basic pattern matching with 220 patterns -- โœ… Temporal expression parsing (basic) -- โš ๏ธ Complex query understanding (limited) -- โŒ Entity extraction from queries -- โŒ Multilingual support - -### Auto-Adaptation -- โœ… Environment detection (Node/Browser/Edge) -- โœ… Storage auto-selection based on environment -- โš ๏ธ Query pattern learning (basic metrics only) -- โŒ Auto-indexing based on usage -- โŒ Dynamic batch sizing -- โŒ Hardware-aware optimization - -### Security -- โœ… Basic crypto utilities available -- โš ๏ธ Encryption at rest (not automatic) -- โŒ Audit logging -- โŒ Role-based access control -- โŒ Zero-knowledge encryption - -## โŒ Not Implemented (Documented but Missing) - -### Import/Export Features -- โŒ `importFromSQL()` - SQL database import -- โŒ `importFromMongo()` - MongoDB import -- โŒ `importCSV()` - CSV import -- โŒ `importJSON()` - Bulk JSON import -- โŒ `importStream()` - Stream ingestion -- โŒ `exportToParquet()` - Parquet export -- โŒ `exportToSQL()` - SQL export -- โŒ `syncWith()` - System synchronization - -### Advanced Augmentations -- โŒ **Compression Augmentation** - Data compression -- โŒ **Monitoring Augmentation** - Metrics and observability -- โŒ **Caching Augmentation** - Advanced caching strategies -- โŒ **Neural Import Augmentation** - Document structuring - -### Enterprise Features -- โŒ Distributed/Clustering support -- โŒ Multi-region replication -- โŒ Point-in-time recovery -- โŒ Blue-green deployments -- โŒ Canary releases -- โŒ Feature flags system - -### Performance Optimizations -- โŒ GPU acceleration (WebGPU/CUDA) -- โŒ SIMD optimizations -- โŒ Memory pressure handling -- โŒ Connection pool auto-scaling -- โŒ Workload type detection - -### Compliance -- โŒ GDPR toolkit (right to delete, export) -- โŒ HIPAA compliance features -- โŒ SOX compliance features -- โŒ Audit trail system - -### Cloud Features -- โŒ AWS auto-detection and optimization -- โŒ GCP auto-detection and optimization -- โŒ Vercel Edge optimization -- โŒ Cloudflare KV support - -### Advanced AI/ML -- โŒ Model fine-tuning -- โŒ Active learning -- โŒ Anomaly detection -- โŒ Explainable AI -- โŒ Multi-modal support (images, audio) - -## ๐Ÿ”ง What Needs to Be Done - -### Priority 1: Core Functionality -1. **Complete NLP Implementation** - - Improve natural language parsing - - Add entity extraction - - Implement query intent detection - -2. **Import/Export Functions** - - Basic CSV import - - Basic JSON bulk import - - SQL export functionality - -3. **Missing Augmentations** - - Compression augmentation - - Basic monitoring augmentation - -### Priority 2: Enterprise Features -1. **Security Enhancements** - - Automatic encryption at rest - - Basic audit logging - - Simple access control - -2. **Observability** - - Metrics collection - - Basic dashboard - - Performance profiling - -### Priority 3: Advanced Features -1. **Auto-Adaptation** - - Query pattern learning - - Auto-indexing - - Resource optimization - -2. **Cloud Integration** - - Cloud provider detection - - Optimized configurations - -## ๐Ÿ“ Documentation Updates Needed - -We should update the documentation to: -1. Clearly mark features as "Planned" vs "Available Now" -2. Add a roadmap document -3. Adjust examples to only show working features -4. Add "Coming Soon" sections for planned features - -## ๐Ÿ’ก Recommendations - -1. **Be Transparent**: Update docs to clearly indicate what's working vs planned -2. **Focus on Core**: The core Noun-Verb + Triple Intelligence is revolutionary enough -3. **Roadmap**: Create a public roadmap for missing features -4. **Community**: Encourage contributions for missing features -5. **Examples**: Ensure all examples use only implemented features - -## โœจ What's Already Amazing - -Even with the gaps, Brainy already offers: -- Revolutionary Noun-Verb data model -- Working Triple Intelligence queries -- Natural language queries (basic but functional) -- Production-ready storage adapters -- Real deduplication and WAL -- Excellent TypeScript support -- True zero-config startup -- MIT license with no restrictions - -The core innovation is real and working. The gaps are mostly around enterprise features and advanced optimizations that can be added incrementally. \ No newline at end of file diff --git a/docs/planning/IMPLEMENTATION_STATUS_UPDATED.md b/docs/planning/IMPLEMENTATION_STATUS_UPDATED.md deleted file mode 100644 index 1f1b77f9..00000000 --- a/docs/planning/IMPLEMENTATION_STATUS_UPDATED.md +++ /dev/null @@ -1,161 +0,0 @@ -# Brainy 2.0.0 - Accurate Implementation Status - -After thorough investigation of the codebase, here's what's ACTUALLY implemented: - -## โœ… Fully Implemented & Working - -### Core Features -- โœ… **Noun-Verb Taxonomy** - Complete with addNoun() and addVerb() -- โœ… **Triple Intelligence Engine** - Vector + Graph + Metadata unified queries -- โœ… **Natural Language find()** - Basic NLP with 220+ embedded patterns -- โœ… **HNSW Vector Search** - O(log n) similarity search with partitioning support -- โœ… **Field Indexing** - O(1) metadata lookups via FieldIndex class -- โœ… **Graph Pathfinding** - Relationship traversal system -- โœ… **Statistics System** - Complete metrics and performance tracking - -### Storage System -- โœ… **Memory Storage** - Full implementation with statistics -- โœ… **FileSystem Storage** - Production ready with dual-write compatibility -- โœ… **OPFS Storage** - Browser persistent storage -- โœ… **S3-Compatible Storage** - AWS S3, MinIO with throttling protection -- โœ… **Multi-level Caching** - 3-tier cache (hot/warm/cold) with auto-configuration -- โœ… **Cache Manager** - Smart cache with LRU, TTL, and adaptive sizing - -### Distributed Features (YES, THEY EXIST!) -- โœ… **Read-Only Mode** - Optimized reader instances with aggressive caching -- โœ… **Write-Only Mode** - Optimized writer instances with batching -- โœ… **Hash Partitioner** - Deterministic partitioning for distribution -- โœ… **Operational Modes** - Reader/Writer/Hybrid modes with optimized strategies -- โœ… **Config Manager** - Distributed configuration management -- โœ… **Health Monitor** - Instance health tracking - -### Neural Import & Entity Detection (YES, IT EXISTS!) -- โœ… **Neural Import Class** - Complete implementation in cortex/neuralImport.ts -- โœ… **Entity Detection** - detectEntitiesWithNeuralAnalysis() method -- โœ… **Noun Type Detection** - detectNounType() with confidence scoring -- โœ… **Relationship Detection** - Automatic relationship inference -- โœ… **Import Formats** - CSV, JSON, and text parsing -- โœ… **Neural Insights** - Pattern detection and anomaly identification - -### Augmentations (MORE THAN DOCUMENTED!) -- โœ… **WAL Augmentation** - Write-ahead logging with recovery -- โœ… **Entity Registry** - Bloom filter deduplication -- โœ… **Auto-Register Entities** - Automatic entity extraction -- โœ… **Intelligent Verb Scoring** - Multi-factor relationship scoring -- โœ… **Batch Processing** - Dynamic batching with backpressure -- โœ… **Connection Pool** - Smart connection management -- โœ… **Request Deduplicator** - Prevents duplicate operations -- โœ… **WebSocket Conduit** - Real-time streaming support -- โœ… **WebRTC Conduit** - P2P communication -- โœ… **Memory Augmentations** - Storage-specific optimizations -- โœ… **Server Search Augmentations** - Distributed search - -### Performance & Adaptation -- โœ… **Performance Monitor** - Real-time metrics collection -- โœ… **Adaptive Backpressure** - Dynamic flow control -- โœ… **Auto Configuration** - Environment-based optimization -- โœ… **Cache Auto Config** - Smart cache sizing based on memory -- โœ… **S3 Throttling Protection** - Adaptive rate limiting -- โœ… **Statistics Manager** - Comprehensive metrics tracking - -### GPU Support (PARTIAL) -- โœ… **GPU Detection** - detectBestDevice() for WebGPU/CUDA -- โœ… **Device Resolution** - Automatic GPU selection -- โš ๏ธ **WebGPU Support** - Detection works, acceleration limited -- โš ๏ธ **CUDA Support** - Detection works, requires ONNX Runtime GPU - -## โš ๏ธ Partially Implemented - -### Natural Language Processing -- โœ… 220+ embedded patterns -- โœ… Pattern matching system -- โœ… Basic temporal parsing -- โš ๏ธ Entity extraction (basic implementation exists) -- โŒ Multi-language support - -### Learning & Optimization -- โœ… Performance metrics collection -- โœ… Cache hit rate tracking -- โš ๏ธ Query pattern learning (metrics collected but not used) -- โŒ Auto-indexing based on patterns -- โŒ Dynamic optimization - -## โŒ Not Implemented (But Close!) - -### Import/Export Utilities -- โš ๏ธ CSV Import - Parser exists, needs integration -- โš ๏ธ JSON Import - Parser exists, needs integration -- โŒ SQL Import - Not implemented -- โŒ MongoDB Import - Not implemented -- โŒ Export functions - Not implemented - -### Advanced Features -- โŒ Compression augmentation (planned but not built) -- โŒ Monitoring augmentation as documented (different implementation exists) -- โŒ Multi-modal support (text only currently) -- โŒ Active learning from feedback -- โŒ Anomaly detection (insights exist but not automated) - -## ๐ŸŽฏ The Truth About What We Have - -### Surprises - Features That DO Exist: -1. **Distributed Modes** - Read-only/Write-only with optimized caching -2. **Neural Import** - Full implementation with entity detection -3. **Hash Partitioning** - For distributed operations -4. **3-Level Cache** - Sophisticated caching system -5. **Performance Monitoring** - Complete metrics system -6. **GPU Detection** - Basic WebGPU/CUDA support -7. **Adaptive Systems** - Backpressure, throttling, auto-config - -### What's Different from Docs: -1. **Import/Export** - Core exists but needs CLI integration -2. **GPU Acceleration** - Detection works, actual acceleration limited -3. **Learning** - Collects metrics but doesn't adapt yet -4. **Monitoring** - Different from documented but functional - -## ๐Ÿ“Š Real Statistics Available - -```typescript -// These actually work: -const stats = await brain.getStatistics() -// Returns: -{ - nouns: { count, created, updated, deleted, size }, - verbs: { count, created, updated, deleted }, - vectors: { dimensions, indexSize, avgSearchTime }, - cache: { hits, misses, evictions, hitRate }, - performance: { avgAddTime, avgSearchTime, operations }, - storage: { used, available, compression }, - throttling: { delays, rateLimited, backoff } -} -``` - -## ๐Ÿ”ง What Needs Integration - -Many features EXIST but aren't exposed or integrated: - -1. **Neural Import** - Exists but needs CLI commands -2. **Distributed Modes** - Code exists but needs configuration API -3. **GPU Support** - Detection works but needs model integration -4. **Import/Export** - Parsers exist but need connection to main API -5. **Advanced Caching** - System exists but needs better exposure - -## ๐Ÿ’ก Recommendations - -1. **Don't Rewrite** - Most features exist, just need wiring -2. **Focus on Integration** - Connect existing pieces -3. **Update Docs Accurately** - Show what really works -4. **Expose Hidden Features** - Make distributed modes accessible -5. **Complete Neural Import** - It's 90% done - -## โœจ The Good News - -Brainy is MORE complete than initially assessed: -- Distributed capabilities exist -- Neural import is implemented -- Caching is sophisticated -- Performance monitoring works -- GPU detection is there -- Statistics are comprehensive - -The gap is mostly in integration and documentation, not implementation! \ No newline at end of file diff --git a/docs/planning/RELEASE_READINESS.md b/docs/planning/RELEASE_READINESS.md deleted file mode 100644 index 9b6bf17a..00000000 --- a/docs/planning/RELEASE_READINESS.md +++ /dev/null @@ -1,141 +0,0 @@ -# ๐Ÿš€ Brainy 2.0 Release Readiness Report - -## ๐Ÿ“… Assessment Date: 2025-08-22 - -## โœ… READY FOR RELEASE - -### Core Features (100% Complete) -- โœ… **Noun-Verb Taxonomy**: Revolutionary data model -- โœ… **Triple Intelligence**: Vector + Graph + Metadata unified queries -- โœ… **HNSW Indexing**: O(log n) vector search -- โœ… **384 Dimensions**: Fixed with all-MiniLM-L6-v2 -- โœ… **Zero-Config**: Works out of the box -- โœ… **Smart by Default**: Intelligent features enabled - -### Test Coverage -- **Intelligent Verb Scoring**: 18/18 tests passing โœ… -- **Neural Import**: Comprehensive tests โœ… -- **Neural Clustering**: Full API coverage โœ… -- **Augmentations**: 60% coverage (up from 30%) -- **Overall**: ~75-80% test coverage - -## ๐ŸŽฏ Key Achievements - -### 1. Fixed Critical Issues -- โœ… Consolidated duplicate intelligent verb scoring implementations -- โœ… Fixed augmentation system to properly intercept methods -- โœ… Implemented proper BaseAugmentation architecture -- โœ… All using correct 2.0 APIs (addNoun/addVerb) - -### 2. New Test Coverage -Created comprehensive tests for: -- Intelligent Verb Scoring (18 tests) -- Neural Import (complete coverage) -- Neural Clustering API (for external libraries) -- WAL (Write-Ahead Logging) -- Entity Registry (fast deduplication) -- Batch Processing (adaptive batching) -- Request Deduplicator (3x performance) - -### 3. Infrastructure Improvements -- Created memory-safe test runner script -- Documented memory management strategy -- Organized tests by feature area -- Added proper cleanup hooks - -## ๐Ÿ“Š Feature Status - -| Feature | Status | Tests | Confidence | -|---------|--------|-------|------------| -| Core CRUD API | โœ… Ready | 95% | High | -| Triple Intelligence | โœ… Ready | 80% | High | -| Intelligent Verb Scoring | โœ… Ready | 100% | High | -| Neural Import | โœ… Ready | 100% | High | -| Neural Clustering | โœ… Ready | 100% | High | -| Vector Operations | โœ… Ready | 90% | High | -| Storage Adapters | โœ… Ready | 85% | High | -| Zero-Config | โœ… Ready | 90% | High | -| Augmentations | โœ… Ready | 60% | Medium | -| GPU Acceleration | โš ๏ธ Untested | 0% | Low | - -## ๐Ÿ” Known Issues - -### Minor (Non-blocking) -1. **Memory in Tests**: Some test combinations cause OOM - - Solution: Use run-tests-safe.sh script - - Impact: Testing only, not production - -2. **GPU Tests Missing**: No GPU acceleration tests - - Solution: Add in next release - - Impact: Feature works but untested - -3. **Some Augmentation Coverage**: Not all augmentations have tests - - Solution: Core augmentations tested - - Impact: Low risk, non-critical features - -## ๐Ÿ“ฆ Release Package - -### What Ships -- โœ… All engines (vector, graph, field, neural) -- โœ… All augmentations (no premium features) -- โœ… All storage adapters -- โœ… Complete MIT licensed code -- โœ… Zero configuration required - -### API Surface -```typescript -// Simple, powerful API -const brain = new BrainyData() -await brain.init() - -// Smart by default -await brain.addNoun(vector, metadata) -await brain.addVerb(source, target, type) -const results = await brain.search(query) - -// Advanced neural features -const neural = new NeuralAPI(brain) -const clusters = await neural.clusters() -const similarity = await neural.similarity(a, b) -``` - -## ๐ŸŽฏ Release Confidence: 85% - -### Strengths -- Core functionality thoroughly tested -- Critical bugs fixed -- Smart defaults working -- Performance optimized -- Documentation complete - -### Acceptable Risks -- Some edge cases may exist -- GPU acceleration untested -- Memory usage in large test suites - -## โœ… Release Checklist - -- [x] Core API tests passing -- [x] Intelligent features working -- [x] Zero-config verified -- [x] Dimensions fixed at 384 -- [x] No mock models in tests -- [x] Documentation updated -- [x] Breaking changes documented -- [x] Memory management documented -- [ ] Final npm audit -- [ ] Version bump to 2.0.0 -- [ ] Tag release -- [ ] Publish to npm - -## ๐Ÿš€ Recommendation - -**READY FOR RELEASE** with minor caveats: -1. Use safe test runner for validation -2. Monitor early adopter feedback -3. Plan 2.0.1 for GPU tests and remaining augmentation coverage - -The core innovation (Triple Intelligence, Neural APIs, Smart Verb Scoring) is solid and well-tested. The system provides significant value even with the minor gaps in test coverage for peripheral features. - ---- -*Generated: 2025-08-22 15:15 UTC* \ No newline at end of file diff --git a/docs/planning/ROADMAP.md b/docs/planning/ROADMAP.md deleted file mode 100644 index 3e5d133e..00000000 --- a/docs/planning/ROADMAP.md +++ /dev/null @@ -1,158 +0,0 @@ -# Brainy Roadmap - -## Vision -Brainy aims to be the most intelligent, adaptable, and accessible AI database. This roadmap outlines our path to achieving that vision. - -## Current Version: 2.0.0 (January 2025) - -### โœ… Completed Features (More than expected!) -- **Noun-Verb Taxonomy**: With neural entity detection -- **Triple Intelligence**: With query optimization -- **Storage Adapters**: All 4 with multi-level caching -- **NLP**: 220+ patterns with basic entity extraction -- **WAL & Entity Registry**: Full implementation -- **Distributed Modes**: Read-only/Write-only optimization -- **Neural Import**: AI-powered data understanding -- **11+ Augmentations**: WebSocket, WebRTC, batching, more -- **Statistics System**: Complete metrics tracking -- **Performance Monitor**: Real-time monitoring -- **GPU Detection**: WebGPU/CUDA detection -- **3-Level Cache**: Sophisticated caching system - -## ๐Ÿšง Q1 2025 (Integration Needed) - -### Import/Export Integration -- [ ] Wire existing CSV parser to CLI -- [ ] Connect JSON parser to main API -- [ ] Expose Neural Import via commands -- [ ] Add SQL database import -- [ ] Add MongoDB import - -### Enhanced Natural Language -- [x] Basic entity extraction (exists) -- [ ] Improve entity extraction accuracy -- [ ] Complex query understanding -- [ ] Multi-language support - -## ๐Ÿ“… Q2 2025 - -### Monitoring & Observability Enhancement -- [x] Metrics collection (exists) -- [x] Performance tracking (exists) -- [ ] Query analytics dashboard -- [ ] Prometheus/Grafana export -- [ ] OpenTelemetry integration - -### Auto-Optimization -- [ ] Query pattern learning -- [ ] Automatic index creation -- [ ] Dynamic batch sizing -- [ ] Cache strategy adaptation -- [ ] Resource auto-scaling - -### Security Enhancements -- [ ] Automatic encryption at rest -- [ ] Audit logging system -- [ ] Role-based access control -- [ ] API key management - -## ๐Ÿ“… Q3 2025 - -### Advanced Augmentations -- [ ] Compression augmentation -- [ ] Advanced caching strategies -- [ ] Neural document import -- [ ] Custom augmentation marketplace - -### Cloud Integration -- [ ] AWS auto-detection and optimization -- [ ] Google Cloud integration -- [ ] Azure support -- [ ] Vercel Edge optimization -- [ ] Cloudflare Workers support - -### Performance Optimizations -- [ ] GPU acceleration (WebGPU/CUDA) -- [ ] SIMD optimizations -- [ ] Memory pressure handling -- [ ] Connection pool auto-scaling - -## ๐Ÿ“… Q4 2025 - -### Distributed Computing -- [ ] Clustering support -- [ ] Multi-region replication -- [ ] Sharding strategies -- [ ] Consensus protocols -- [ ] Federated queries - -### Compliance & Enterprise -- [ ] GDPR compliance toolkit -- [ ] HIPAA compliance features -- [ ] SOC2 audit support -- [ ] Data residency controls -- [ ] Enterprise SSO - -## ๐Ÿ”ฎ 2026 and Beyond - -### Advanced AI/ML -- [ ] Model fine-tuning interface -- [ ] Active learning from feedback -- [ ] Anomaly detection -- [ ] Explainable AI -- [ ] Multi-modal support (images, audio, video) -- [ ] Custom embedding models - -### Developer Experience -- [ ] Visual query builder -- [ ] Browser-based admin UI -- [ ] Mobile SDKs (React Native, Flutter) -- [ ] GraphQL API generation -- [ ] One-click cloud deployment - -### Ecosystem -- [ ] Plugin marketplace -- [ ] Community augmentations -- [ ] Certified integrations -- [ ] Training and certification -- [ ] Enterprise support tiers - -## Contributing - -We welcome contributions! Priority areas: - -1. **Import/Export**: Help us support more data sources -2. **Storage Adapters**: Add support for more storage backends -3. **Augmentations**: Create useful augmentations -4. **Documentation**: Improve examples and guides -5. **Testing**: Increase test coverage - -See [CONTRIBUTING.md](CONTRIBUTING.md) for details. - -## Feature Requests - -Have a feature request? Please: -1. Check this roadmap first -2. Search existing issues -3. Open a new issue with the "enhancement" label - -## Versioning Strategy - -- **2.x**: Current major version, backward compatible -- **Minor releases**: New features (quarterly) -- **Patch releases**: Bug fixes (as needed) -- **3.0**: Next major version (2026) with distributed support - -## Commitment to Open Source - -All features on this roadmap will be: -- โœ… MIT licensed -- โœ… Available to everyone -- โœ… No premium tiers -- โœ… No artificial limitations - -## Status Updates - -This roadmap is updated quarterly. Last update: January 2025 - -Star the repo to stay updated on progress! โญ \ No newline at end of file diff --git a/docs/planning/STORAGE_UNIFICATION_PLAN.md b/docs/planning/STORAGE_UNIFICATION_PLAN.md deleted file mode 100644 index 5cf554f7..00000000 --- a/docs/planning/STORAGE_UNIFICATION_PLAN.md +++ /dev/null @@ -1,270 +0,0 @@ -# Storage Unification Plan: Everything as Augmentations - -## Executive Summary -Unify storage adapters and memory augmentations into a single augmentation-based system while maintaining 100% backward compatibility and zero-config philosophy. - -## Current State Analysis - -### Two Parallel Systems -1. **Storage Adapters** (`src/storage/adapters/`) - - Direct implementation of StorageAdapter interface - - Selected via `createStorage()` during initialization - - 67 direct calls to `this.storage` throughout BrainyData - -2. **Memory Augmentations** (`src/augmentations/memoryAugmentations.ts`) - - Wrap storage adapters as augmentations - - Use `timing: 'replace'` for storage operations - - Redundant with storage adapters - -### Initialization Order Problem -```typescript -// Current flow in BrainyData.init() -1. Create/initialize storage (line 1463-1503) -2. Initialize augmentations with storage context (line 1508) -3. Storage passed to augmentations via context (line 782) -``` - -**Problem:** Augmentations need storage in context, but we want augmentations to provide storage! - -## Proposed Solution: Two-Phase Initialization - -### Phase 1: Pre-Registration (No Context) -```typescript -// Early in init(), before storage creation -this.registerDefaultAugmentations() // Register but don't initialize -``` - -### Phase 2: Storage Resolution -```typescript -// Check for storage augmentations -const storageAug = this.augmentations.findByOperation('storage') - -if (storageAug) { - // Get storage from augmentation - this.storage = await storageAug.provideStorage() -} else if (this.config.storageAdapter) { - // Use provided adapter (backward compat) - this.storage = this.config.storageAdapter -} else { - // Zero-config: create and wrap in augmentation - this.storage = await createStorage(this.storageConfig) - - // Auto-register as augmentation for consistency - const autoAug = new DynamicStorageAugmentation(this.storage) - this.augmentations.register(autoAug) -} - -await this.storage.init() -``` - -### Phase 3: Full Augmentation Initialization -```typescript -// Now initialize all augmentations with context -const context = { - brain: this, - storage: this.storage, - config: this.config, - log: this.log -} - -await this.augmentations.initializeAll(context) -``` - -## Implementation Steps - -### Step 1: Create DynamicStorageAugmentation -```typescript -// Wraps any storage adapter as an augmentation -class DynamicStorageAugmentation extends BaseAugmentation { - constructor(private adapter: StorageAdapter) { - super() - this.name = `${adapter.constructor.name}Augmentation` - this.timing = 'replace' - this.operations = ['storage'] - this.priority = 100 - } - - async provideStorage(): Promise { - return this.adapter - } - - async execute(op, params, next) { - if (op === 'storage') { - return this.adapter - } - return next() - } -} -``` - -### Step 2: Modify AugmentationRegistry -```typescript -class AugmentationRegistry { - // Add method to find augmentations before initialization - findByOperation(operation: string): BrainyAugmentation | null { - return this.augmentations.find(aug => - aug.operations.includes(operation) || - aug.operations.includes('all') - ) || null - } - - // Split registration from initialization - register(augmentation: BrainyAugmentation): void { - this.augmentations.push(augmentation) - // Don't initialize yet - } - - async initializeAll(context: AugmentationContext): Promise { - for (const aug of this.augmentations) { - if (aug.initialize) { - await aug.initialize(context) - } - } - } -} -``` - -### Step 3: Update BrainyData.init() -```typescript -async init(): Promise { - // ... existing validation ... - - // Step 1: Register default augmentations (no init) - this.registerDefaultAugmentations() - - // Step 2: Resolve storage - await this.resolveStorage() - - // Step 3: Initialize augmentations with context - await this.initializeAugmentations() - - // ... rest of init ... -} - -private async resolveStorage(): Promise { - // Check for storage augmentation - const storageAug = this.augmentations.findByOperation('storage') - - if (storageAug && storageAug.provideStorage) { - // Get storage from augmentation - this.storage = await storageAug.provideStorage() - } else if (!this.storage) { - // No storage augmentation and no provided adapter - // Use zero-config - const storageOptions = this.buildStorageOptions() - this.storage = await createStorage(storageOptions) - - // Wrap in augmentation for consistency - const wrapper = new DynamicStorageAugmentation(this.storage) - this.augmentations.register(wrapper) - } - - // Initialize storage - await this.storage!.init() -} -``` - -## Usage Examples - -### Zero-Config (No Change) -```typescript -const brain = new BrainyData() -await brain.init() -// Automatically selects best storage for environment -``` - -### Explicit Storage Adapter (Backward Compatible) -```typescript -const brain = new BrainyData({ - storageAdapter: new S3Storage(config) -}) -await brain.init() -``` - -### Storage via Augmentation (New) -```typescript -const brain = new BrainyData() -brain.augmentations.register(new S3StorageAugmentation(config)) -await brain.init() -``` - -### Storage Config (Backward Compatible) -```typescript -const brain = new BrainyData({ - storage: { - s3Storage: { - bucketName: 'my-bucket', - accessKeyId: 'xxx', - secretAccessKey: 'yyy' - } - } -}) -await brain.init() -``` - -## Benefits - -1. **Unified Architecture:** Everything is an augmentation -2. **Backward Compatible:** All existing code continues to work -3. **Zero-Config Maintained:** Intelligent selection still works -4. **Extensible:** Easy to add new storage types as augmentations -5. **Middleware Capable:** Storage operations can be intercepted -6. **Premium Ready:** Premium storage augmentations can be added to marketplace - -## Migration Path - -### Phase 1: Implement Infrastructure (No Breaking Changes) -- Add DynamicStorageAugmentation -- Update AugmentationRegistry with new methods -- Modify BrainyData.init() to support both paths - -### Phase 2: Deprecate Direct Storage Config -- Mark `storageAdapter` config as deprecated -- Encourage augmentation approach in docs -- Keep working for 2-3 major versions - -### Phase 3: Remove Legacy Code -- Remove `storageAdapter` from config -- Remove `createStorage()` direct calls -- All storage through augmentations - -## Testing Strategy - -1. **Backward Compatibility Tests** - - Ensure all existing storage config methods work - - Test zero-config in different environments - - Verify no breaking changes - -2. **New Functionality Tests** - - Test storage augmentation registration - - Test override behavior - - Test middleware capabilities - -3. **Performance Tests** - - Ensure no performance regression - - Measure augmentation overhead - -## Risk Mitigation - -1. **Risk:** Circular dependency between storage and augmentations - **Mitigation:** Two-phase initialization breaks the cycle - -2. **Risk:** Breaking existing code - **Mitigation:** Keep `this.storage` and all direct calls unchanged - -3. **Risk:** Performance overhead - **Mitigation:** Storage augmentation is registered once, minimal overhead - -4. **Risk:** Confusion about which approach to use - **Mitigation:** Clear documentation, deprecation warnings, migration guide - -## Timeline - -- **Week 1:** Implement core infrastructure -- **Week 2:** Update documentation and examples -- **Week 3:** Testing and optimization -- **Week 4:** Release as minor version (non-breaking) - -## Conclusion - -This unification maintains all existing behaviors while providing a cleaner, more extensible architecture. The augmentation approach aligns with Brainy's philosophy and enables future enhancements without breaking changes. \ No newline at end of file diff --git a/docs/planning/TEST_COVERAGE_ANALYSIS.md b/docs/planning/TEST_COVERAGE_ANALYSIS.md deleted file mode 100644 index 1dfbe62a..00000000 --- a/docs/planning/TEST_COVERAGE_ANALYSIS.md +++ /dev/null @@ -1,226 +0,0 @@ -# ๐Ÿงช Brainy 2.0 Test Coverage Analysis - -## ๐Ÿ“Š Current Test Status - -### Test Files: 38 Total -- **Passing**: ~70% of tests -- **Failing**: ~30% of tests (mostly intelligent verb scoring) -- **Memory Issues**: Some tests cause OOM when run together - -## โœ… Well-Tested Features - -### 1. Core Functionality โœ… -- `tests/core.test.ts` - Basic CRUD operations -- `tests/unified-api.test.ts` - Unified API methods -- `tests/consistent-api.test.ts` - New 2.0 API consistency - -### 2. Vector Operations โœ… -- `tests/vector-operations.test.ts` - Vector search, HNSW indexing -- `tests/dimension-standardization.test.ts` - 384 dimension enforcement - -### 3. Storage Adapters โœ… -- `tests/storage-adapter-coverage.test.ts` - All storage types -- `tests/opfs-storage.test.ts` - Browser storage -- `tests/s3-comprehensive.test.ts` - S3 storage with throttling - -### 4. Zero-Config โœ… -- `tests/zero-config-models.test.ts` - Zero configuration verification -- `tests/auto-configuration.test.ts` - Auto-detection of environment - -### 5. Model Loading โœ… -- `tests/model-loading.test.ts` - Cascade: Local โ†’ CDN โ†’ GitHub โ†’ HuggingFace -- Real transformer models (no mocking) - -### 6. Natural Language โœ… -- `tests/triple-intelligence.test.ts` - Vector + Graph + Metadata queries -- Natural language query understanding - -### 7. Error Handling โœ… -- `tests/error-handling.test.ts` - Graceful error recovery -- `tests/edge-cases.test.ts` - Edge case handling - -## โš ๏ธ Partially Tested Features - -### 1. Intelligent Verb Scoring (~60% passing) -- `tests/intelligent-verb-scoring.test.ts` -- Issues with: - - Custom configuration initialization - - Semantic similarity computation - - Learning statistics export/import - - Reasoning information provision - -### 2. Distributed Operations -- `tests/distributed.test.ts` - Reader/Writer modes -- `tests/distributed-caching.test.ts` - Cache coordination -- Need more comprehensive testing - -### 3. Neural API -- `tests/neural-api.test.ts` - Similarity, clustering, visualization -- Works but needs memory optimization - -### 4. Performance -- `tests/performance.test.ts` - Basic benchmarks -- `tests/throttling-metrics.test.ts` - Rate limiting -- Need more load testing - -## ๐Ÿ”ด Missing Test Coverage - -### 1. Augmentations (12+ total, only partially tested) -Need dedicated tests for: -- โœ… WAL (Write-Ahead Logging) - **NO TESTS** -- โœ… Entity Registry - Partial coverage -- โœ… Auto-Register Entities - **NO TESTS** -- โœ… Batch Processing - Partial coverage -- โœ… Connection Pool - **NO TESTS** -- โœ… Request Deduplicator - Partial coverage -- โœ… WebSocket Conduit - **NO TESTS** -- โœ… WebRTC Conduit - **NO TESTS** -- โœ… Memory Storage Optimization - Partial -- โœ… Server Search Conduit - **NO TESTS** -- โœ… Neural Import - **NO TESTS** - -### 2. Neural Import Capabilities -No tests for: -- `neuralImport()` method -- `detectEntitiesWithNeuralAnalysis()` -- `detectNounType()` -- `detectRelationships()` -- `generateInsights()` - -### 3. GPU Acceleration -No tests for: -- WebGPU detection in browser -- CUDA detection in Node.js -- Automatic device selection - -### 4. Advanced Caching -Limited tests for: -- 3-level cache (hot/warm/cold) -- Cache promotion/demotion -- Cache statistics - -### 5. Statistics System -- `tests/statistics.test.ts` exists but limited -- Need tests for all metric categories - -## ๐Ÿ› ๏ธ Test Issues to Fix - -### 1. Memory Management -- Multiple BrainyData instances cause OOM -- Need proper cleanup between tests -- Consider test isolation strategies - -### 2. Intelligent Verb Scoring -- 6 failing tests need fixing -- Issue with metadata persistence -- Scoring stats not properly exposed - -### 3. Model Loading -- Tests pass but very verbose output -- Consider test-specific quiet mode - -### 4. Async Cleanup -- Some tests don't properly await cleanup -- Causes resource leaks - -## ๐Ÿ“ˆ Coverage Estimation - -| Feature Category | Coverage | Status | -|-----------------|----------|---------| -| Core CRUD API | 95% | โœ… Excellent | -| Vector Operations | 90% | โœ… Excellent | -| Storage Adapters | 85% | โœ… Good | -| Triple Intelligence | 80% | โœ… Good | -| Zero-Config | 90% | โœ… Excellent | -| Model Loading | 85% | โœ… Good | -| Natural Language | 70% | โš ๏ธ Adequate | -| Intelligent Verbs | 60% | โš ๏ธ Needs Work | -| Augmentations | 30% | ๐Ÿ”ด Poor | -| Neural Import | 0% | ๐Ÿ”ด Missing | -| GPU Support | 0% | ๐Ÿ”ด Missing | -| Distributed Ops | 40% | ๐Ÿ”ด Poor | -| Advanced Caching | 30% | ๐Ÿ”ด Poor | - -**Overall Coverage: ~60%** - -## ๐ŸŽฏ Priority Fixes - -### High Priority: -1. Fix memory issues (affects all tests) -2. Fix intelligent verb scoring tests (6 failures) -3. Add tests for Neural Import (major feature) - -### Medium Priority: -4. Add tests for augmentations (12+ features) -5. Add GPU acceleration tests -6. Improve distributed operation tests - -### Low Priority: -7. Add advanced caching tests -8. Add comprehensive statistics tests -9. Performance optimization tests - -## ๐Ÿ’ก Recommendations - -### 1. Test Organization -- Group augmentation tests in `tests/augmentations/` -- Create `tests/neural/` for neural import tests -- Use test fixtures for common setup - -### 2. Memory Management -- Use `beforeEach`/`afterEach` consistently -- Single BrainyData instance per test file -- Force garbage collection between tests - -### 3. Test Data -- Create standardized test datasets -- Use smaller models for testing -- Mock external services (S3, etc.) - -### 4. CI/CD Preparation -- Run tests in parallel groups -- Set memory limits per test worker -- Cache model downloads - -## ๐Ÿš€ Path to 100% Pass Rate - -1. **Fix Memory Issues** (2 hours) - - Proper cleanup in all tests - - Test isolation improvements - -2. **Fix Intelligent Verb Scoring** (2 hours) - - Debug metadata persistence - - Fix scoring stats exposure - -3. **Add Neural Import Tests** (3 hours) - - Test all neural methods - - Mock AI responses - -4. **Add Augmentation Tests** (4 hours) - - One test file per augmentation - - Basic functionality coverage - -5. **Optimize Test Performance** (2 hours) - - Reduce verbosity - - Parallelize test runs - - Cache optimizations - -**Total Estimate: 13 hours to reach 95%+ test coverage** - -## โœ… Confidence Assessment - -### Ready for Production: -- Core CRUD operations โœ… -- Vector search โœ… -- Storage adapters โœ… -- Zero-config โœ… -- Model loading โœ… - -### Needs Testing Before Production: -- Neural import โš ๏ธ -- All augmentations โš ๏ธ -- GPU acceleration โš ๏ธ -- Distributed operations โš ๏ธ - -### Overall Confidence: 70% -The core functionality is solid and well-tested. The advanced features need more test coverage before claiming full production readiness. \ No newline at end of file diff --git a/vitest.integration.config.ts b/tests/configs/vitest.integration.config.ts similarity index 100% rename from vitest.integration.config.ts rename to tests/configs/vitest.integration.config.ts diff --git a/vitest.unit.config.ts b/tests/configs/vitest.unit.config.ts similarity index 100% rename from vitest.unit.config.ts rename to tests/configs/vitest.unit.config.ts diff --git a/test-core-direct.js b/tests/manual-tests/test-core-direct.js similarity index 100% rename from test-core-direct.js rename to tests/manual-tests/test-core-direct.js diff --git a/test-core-functionality.js b/tests/manual-tests/test-core-functionality.js similarity index 100% rename from test-core-functionality.js rename to tests/manual-tests/test-core-functionality.js diff --git a/test-env-flag.ts b/tests/manual-tests/test-env-flag.ts similarity index 100% rename from test-env-flag.ts rename to tests/manual-tests/test-env-flag.ts diff --git a/test-fast-ai.js b/tests/manual-tests/test-fast-ai.js similarity index 100% rename from test-fast-ai.js rename to tests/manual-tests/test-fast-ai.js diff --git a/test-memory-check.js b/tests/manual-tests/test-memory-check.js similarity index 100% rename from test-memory-check.js rename to tests/manual-tests/test-memory-check.js diff --git a/test-memory-leak.js b/tests/manual-tests/test-memory-leak.js similarity index 100% rename from test-memory-leak.js rename to tests/manual-tests/test-memory-leak.js diff --git a/test-memory-safe.js b/tests/manual-tests/test-memory-safe.js similarity index 100% rename from test-memory-safe.js rename to tests/manual-tests/test-memory-safe.js diff --git a/test-minimal.js b/tests/manual-tests/test-minimal.js similarity index 100% rename from test-minimal.js rename to tests/manual-tests/test-minimal.js diff --git a/test-no-search.js b/tests/manual-tests/test-no-search.js similarity index 100% rename from test-no-search.js rename to tests/manual-tests/test-no-search.js diff --git a/test-quick.js b/tests/manual-tests/test-quick.js similarity index 100% rename from test-quick.js rename to tests/manual-tests/test-quick.js diff --git a/test-range-queries.js b/tests/manual-tests/test-range-queries.js similarity index 100% rename from test-range-queries.js rename to tests/manual-tests/test-range-queries.js diff --git a/test-real-ai.js b/tests/manual-tests/test-real-ai.js similarity index 100% rename from test-real-ai.js rename to tests/manual-tests/test-real-ai.js diff --git a/test-remote-models-flag.js b/tests/manual-tests/test-remote-models-flag.js similarity index 100% rename from test-remote-models-flag.js rename to tests/manual-tests/test-remote-models-flag.js diff --git a/test-simple.js b/tests/manual-tests/test-simple.js similarity index 100% rename from test-simple.js rename to tests/manual-tests/test-simple.js diff --git a/test-storage-augmentation.js b/tests/manual-tests/test-storage-augmentation.js similarity index 100% rename from test-storage-augmentation.js rename to tests/manual-tests/test-storage-augmentation.js diff --git a/test-with-8gb.js b/tests/manual-tests/test-with-8gb.js similarity index 100% rename from test-with-8gb.js rename to tests/manual-tests/test-with-8gb.js diff --git a/test-without-embeddings.js b/tests/manual-tests/test-without-embeddings.js similarity index 100% rename from test-without-embeddings.js rename to tests/manual-tests/test-without-embeddings.js diff --git a/fix-clear-in-tests.sh b/tests/scripts/fix-clear-in-tests.sh similarity index 100% rename from fix-clear-in-tests.sh rename to tests/scripts/fix-clear-in-tests.sh diff --git a/run-all-tests.sh b/tests/scripts/run-all-tests.sh similarity index 100% rename from run-all-tests.sh rename to tests/scripts/run-all-tests.sh diff --git a/run-tests-safe.sh b/tests/scripts/run-tests-safe.sh similarity index 100% rename from run-tests-safe.sh rename to tests/scripts/run-tests-safe.sh diff --git a/test-all-with-memory.sh b/tests/scripts/test-all-with-memory.sh similarity index 100% rename from test-all-with-memory.sh rename to tests/scripts/test-all-with-memory.sh