Initial commit: Brainy - Multi-Dimensional AI Database

Open source vector database with HNSW indexing, graph relationships,
and metadata facets. Features CLI with professional augmentation registry
integration for discovering extensions and capabilities.

dist/hnsw/optimizedHNSWIndex.d.ts

@@ -0,0 +1,97 @@
+/**
+ * Optimized HNSW Index for Large-Scale Vector Search
+ * Implements dynamic parameter tuning and performance optimizations
+ */
+import { DistanceFunction, HNSWConfig, Vector, VectorDocument } from '../coreTypes.js';
+import { HNSWIndex } from './hnswIndex.js';
+export interface OptimizedHNSWConfig extends HNSWConfig {
+    dynamicParameterTuning?: boolean;
+    targetSearchLatency?: number;
+    targetRecall?: number;
+    maxNodes?: number;
+    memoryBudget?: number;
+    diskCacheEnabled?: boolean;
+    compressionEnabled?: boolean;
+    performanceTracking?: boolean;
+    adaptiveEfSearch?: boolean;
+    levelMultiplier?: number;
+    seedConnections?: number;
+    pruningStrategy?: 'simple' | 'diverse' | 'hybrid';
+}
+interface PerformanceMetrics {
+    averageSearchTime: number;
+    averageRecall: number;
+    memoryUsage: number;
+    indexSize: number;
+    apiCalls: number;
+    cacheHitRate: number;
+}
+interface DynamicParameters {
+    efSearch: number;
+    efConstruction: number;
+    M: number;
+    ml: number;
+}
+/**
+ * Optimized HNSW Index with dynamic parameter tuning for large datasets
+ */
+export declare class OptimizedHNSWIndex extends HNSWIndex {
+    private optimizedConfig;
+    private performanceMetrics;
+    private dynamicParams;
+    private searchHistory;
+    private parameterTuningInterval?;
+    constructor(config?: Partial<OptimizedHNSWConfig>, distanceFunction?: DistanceFunction);
+    /**
+     * Optimized search with dynamic parameter adjustment
+     */
+    search(queryVector: Vector, k?: number, filter?: (id: string) => Promise<boolean>): Promise<Array<[string, number]>>;
+    /**
+     * Dynamically adjust efSearch based on performance requirements
+     */
+    private adjustEfSearch;
+    /**
+     * Record search performance metrics
+     */
+    private recordSearchMetrics;
+    /**
+     * Check memory usage and trigger optimizations
+     */
+    private checkMemoryUsage;
+    /**
+     * Compress index to reduce memory usage (placeholder)
+     */
+    private compressIndex;
+    /**
+     * Start automatic parameter tuning
+     */
+    private startParameterTuning;
+    /**
+     * Automatic parameter tuning based on performance metrics
+     */
+    private tuneParameters;
+    /**
+     * Get optimized configuration recommendations for current dataset size
+     */
+    getOptimizedConfig(): OptimizedHNSWConfig;
+    /**
+     * Get current performance metrics
+     */
+    getPerformanceMetrics(): PerformanceMetrics & {
+        currentParams: DynamicParameters;
+        searchHistorySize: number;
+    };
+    /**
+     * Apply optimized bulk insertion strategy
+     */
+    bulkInsert(items: VectorDocument[]): Promise<string[]>;
+    /**
+     * Optimize insertion order to improve index quality
+     */
+    private optimizeInsertionOrder;
+    /**
+     * Cleanup resources
+     */
+    destroy(): void;
+}
+export {};