chore: recovery checkpoint - v3.0 API successfully recovered
CRITICAL CHECKPOINT - DO NOT PUSH TO GITHUB Recovery Status: - Successfully recovered brainy.ts from compiled JavaScript - All core v3.0 API methods functional (add, get, update, delete, relate, find, etc.) - Neural subsystem intact (562KB embedded patterns, NLP working) - Augmentation pipeline operational (20+ augmentations) - HNSW clustering system complete - Triple Intelligence compiled (needs constructor fix) - Test suite validates functionality Changes preserved: - 898 files with changes from last 3 days - 144,475 insertions - All augmentation improvements - All test coverage enhancements - Complete v3.0 feature set This is a LOCAL checkpoint only - contains recovered work after corruption incident. Created backup in .backups/brainy-full-20250910-151314.tar.gz Branch: recovery-checkpoint-20250910-151433 Date: Wed Sep 10 03:18:04 PM PDT 2025
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.recovery-workspace/dist-backup-20250910-141917/hnsw/optimizedHNSWIndex.d.ts
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.recovery-workspace/dist-backup-20250910-141917/hnsw/optimizedHNSWIndex.d.ts
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/**
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* Optimized HNSW Index for Large-Scale Vector Search
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* Implements dynamic parameter tuning and performance optimizations
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*/
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import { DistanceFunction, HNSWConfig, Vector, VectorDocument } from '../coreTypes.js';
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import { HNSWIndex } from './hnswIndex.js';
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export interface OptimizedHNSWConfig extends HNSWConfig {
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dynamicParameterTuning?: boolean;
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targetSearchLatency?: number;
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targetRecall?: number;
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maxNodes?: number;
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memoryBudget?: number;
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diskCacheEnabled?: boolean;
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compressionEnabled?: boolean;
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performanceTracking?: boolean;
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adaptiveEfSearch?: boolean;
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levelMultiplier?: number;
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seedConnections?: number;
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pruningStrategy?: 'simple' | 'diverse' | 'hybrid';
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}
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interface PerformanceMetrics {
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averageSearchTime: number;
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averageRecall: number;
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memoryUsage: number;
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indexSize: number;
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apiCalls: number;
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cacheHitRate: number;
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}
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interface DynamicParameters {
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efSearch: number;
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efConstruction: number;
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M: number;
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ml: number;
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}
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/**
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* Optimized HNSW Index with dynamic parameter tuning for large datasets
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*/
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export declare class OptimizedHNSWIndex extends HNSWIndex {
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private optimizedConfig;
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private performanceMetrics;
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private dynamicParams;
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private searchHistory;
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private parameterTuningInterval?;
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constructor(config?: Partial<OptimizedHNSWConfig>, distanceFunction?: DistanceFunction);
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/**
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* Optimized search with dynamic parameter adjustment
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*/
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search(queryVector: Vector, k?: number, filter?: (id: string) => Promise<boolean>): Promise<Array<[string, number]>>;
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/**
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* Dynamically adjust efSearch based on performance requirements
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*/
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private adjustEfSearch;
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/**
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* Record search performance metrics
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*/
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private recordSearchMetrics;
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/**
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* Check memory usage and trigger optimizations
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*/
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private checkMemoryUsage;
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/**
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* Compress index to reduce memory usage (placeholder)
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*/
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private compressIndex;
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/**
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* Start automatic parameter tuning
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*/
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private startParameterTuning;
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/**
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* Automatic parameter tuning based on performance metrics
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*/
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private tuneParameters;
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/**
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* Get optimized configuration recommendations for current dataset size
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*/
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getOptimizedConfig(): OptimizedHNSWConfig;
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/**
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* Get current performance metrics
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*/
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getPerformanceMetrics(): PerformanceMetrics & {
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currentParams: DynamicParameters;
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searchHistorySize: number;
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};
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/**
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* Apply optimized bulk insertion strategy
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*/
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bulkInsert(items: VectorDocument[]): Promise<string[]>;
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/**
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* Optimize insertion order to improve index quality
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*/
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private optimizeInsertionOrder;
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/**
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* Cleanup resources
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*/
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destroy(): void;
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}
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export {};
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