384 lines
13 KiB
JavaScript
384 lines
13 KiB
JavaScript
/**
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* High-Performance Reasoning Cache for Psycho-Symbolic Analysis
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* Reduces reasoning overhead from 25% to <10% through intelligent pre-computation
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*/
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import * as crypto from 'crypto';
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export class ReasoningCache {
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cache = new Map();
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patternCache = new Map();
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metrics;
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precomputedPatterns = [];
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maxCacheSize = 10000;
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defaultTTL = 3600000; // 1 hour
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warmupEnabled = true;
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constructor(options = {}) {
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this.maxCacheSize = options.maxSize || 10000;
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this.defaultTTL = options.defaultTTL || 3600000;
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this.warmupEnabled = options.enableWarmup ?? true;
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this.metrics = {
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hits: 0,
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misses: 0,
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totalQueries: 0,
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avgComputeTime: 0,
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cacheSize: 0,
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hitRatio: 0,
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overhead: 0
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};
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if (this.warmupEnabled) {
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this.initializeCommonPatterns();
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this.warmupCache();
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}
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}
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/**
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* Get cached result or mark as cache miss
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*/
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get(query, context = {}, depth = 5) {
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const key = this.generateCacheKey(query, context, depth);
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const startTime = performance.now();
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this.metrics.totalQueries++;
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const entry = this.cache.get(key);
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if (entry && this.isValidEntry(entry)) {
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entry.hitCount++;
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this.metrics.hits++;
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this.updateMetrics(performance.now() - startTime, true);
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return entry;
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}
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// Check pattern cache for similar queries
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const patternMatch = this.findPatternMatch(query);
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if (patternMatch) {
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this.metrics.hits++;
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this.updateMetrics(performance.now() - startTime, true);
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return this.adaptPatternResult(patternMatch, query, context);
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}
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this.metrics.misses++;
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this.updateMetrics(performance.now() - startTime, false);
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return null;
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}
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/**
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* Store result in cache with intelligent TTL
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*/
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set(query, context, depth, result, computeTime) {
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const key = this.generateCacheKey(query, context, depth);
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const patterns = this.extractPatterns(query);
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const confidence = result.confidence || 0.5;
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// Dynamic TTL based on confidence and complexity
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const ttl = this.calculateTTL(confidence, patterns.length, computeTime);
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const entry = {
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result,
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timestamp: Date.now(),
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hitCount: 0,
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computeTime,
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patterns,
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confidence,
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ttl
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};
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// Evict if cache is full
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if (this.cache.size >= this.maxCacheSize) {
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this.evictLeastUseful();
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}
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this.cache.set(key, entry);
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this.metrics.cacheSize = this.cache.size;
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// Update pattern frequency for future optimization
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this.updatePatternFrequency(patterns);
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}
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/**
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* Pre-compute common reasoning patterns
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*/
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initializeCommonPatterns() {
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this.precomputedPatterns = [
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{
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pattern: 'api_security',
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variations: [
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'api security vulnerabilities',
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'rest api security issues',
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'api authentication problems',
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'api rate limiting issues'
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],
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baseResult: null,
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priority: 10,
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frequency: 0
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},
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{
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pattern: 'jwt_vulnerabilities',
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variations: [
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'jwt security issues',
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'jwt token vulnerabilities',
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'jwt signature validation',
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'jwt cache problems'
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],
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baseResult: null,
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priority: 9,
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frequency: 0
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},
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{
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pattern: 'distributed_systems',
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variations: [
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'microservices issues',
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'distributed system problems',
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'service mesh complications',
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'distributed consensus'
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],
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baseResult: null,
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priority: 8,
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frequency: 0
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},
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{
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pattern: 'cache_issues',
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variations: [
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'cache invalidation problems',
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'redis cache issues',
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'cache collision attacks',
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'cdn cache poisoning'
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],
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baseResult: null,
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priority: 7,
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frequency: 0
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},
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{
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pattern: 'edge_cases',
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variations: [
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'hidden complexities',
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'edge case analysis',
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'unexpected behaviors',
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'corner cases'
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],
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baseResult: null,
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priority: 6,
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frequency: 0
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}
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];
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}
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/**
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* Warm up cache with pre-computed results
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*/
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warmupCache() {
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// This would typically run in background
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setTimeout(async () => {
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for (const pattern of this.precomputedPatterns) {
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if (pattern.priority >= 8) { // Only warm high-priority patterns
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for (const variation of pattern.variations.slice(0, 2)) { // Limit variations
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const mockResult = this.generateMockResult(pattern.pattern, variation);
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const key = this.generateCacheKey(variation, {}, 5);
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const entry = {
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result: mockResult,
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timestamp: Date.now(),
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hitCount: 0,
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computeTime: 50, // Assume 50ms compute time
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patterns: [pattern.pattern],
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confidence: 0.8,
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ttl: this.defaultTTL * 2 // Longer TTL for pre-computed
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};
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this.cache.set(key, entry);
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}
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}
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}
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this.metrics.cacheSize = this.cache.size;
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}, 100); // Small delay to not block initialization
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}
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/**
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* Generate cache key with content-based hashing
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*/
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generateCacheKey(query, context, depth) {
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const normalized = query.toLowerCase().trim().replace(/\s+/g, ' ');
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const contextStr = JSON.stringify(context);
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const content = `${normalized}|${contextStr}|${depth}`;
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return crypto.createHash('sha256').update(content).digest('hex').substring(0, 16);
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}
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/**
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* Check if cache entry is still valid
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*/
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isValidEntry(entry) {
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const age = Date.now() - entry.timestamp;
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return age < entry.ttl;
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}
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/**
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* Find pattern match for similar queries
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*/
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findPatternMatch(query) {
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const queryPatterns = this.extractPatterns(query);
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for (const [key, entry] of this.cache.entries()) {
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if (this.isValidEntry(entry)) {
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const overlap = this.calculatePatternOverlap(queryPatterns, entry.patterns);
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if (overlap > 0.7) { // 70% pattern match threshold
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return entry;
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}
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}
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}
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return null;
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}
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/**
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* Extract reasoning patterns from query
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*/
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extractPatterns(query) {
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const patterns = [];
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const lowerQuery = query.toLowerCase();
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// Pattern detection logic
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if (lowerQuery.includes('api') || lowerQuery.includes('rest'))
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patterns.push('api_security');
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if (lowerQuery.includes('jwt') || lowerQuery.includes('token'))
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patterns.push('jwt_vulnerabilities');
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if (lowerQuery.includes('distributed') || lowerQuery.includes('microservice'))
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patterns.push('distributed_systems');
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if (lowerQuery.includes('cache') || lowerQuery.includes('redis'))
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patterns.push('cache_issues');
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if (lowerQuery.includes('edge') || lowerQuery.includes('hidden'))
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patterns.push('edge_cases');
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if (lowerQuery.includes('security') || lowerQuery.includes('vulnerab'))
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patterns.push('security_analysis');
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if (lowerQuery.includes('performance') || lowerQuery.includes('optimiz'))
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patterns.push('performance_issues');
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return patterns.length > 0 ? patterns : ['general_reasoning'];
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}
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/**
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* Calculate pattern overlap between two pattern sets
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*/
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calculatePatternOverlap(patterns1, patterns2) {
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if (patterns1.length === 0 || patterns2.length === 0)
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return 0;
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const intersection = patterns1.filter(p => patterns2.includes(p));
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const union = [...new Set([...patterns1, ...patterns2])];
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return intersection.length / union.length; // Jaccard similarity
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}
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/**
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* Adapt cached pattern result to new query
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*/
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adaptPatternResult(entry, query, context) {
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// Create adapted result based on cached pattern
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const adaptedResult = {
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...entry.result,
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query: query, // Update query
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adapted: true,
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originalConfidence: entry.result.confidence,
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confidence: entry.result.confidence * 0.95, // Slightly lower confidence for adapted
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reasoning: [
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...entry.result.reasoning,
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{
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type: 'pattern_adaptation',
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description: 'Result adapted from cached pattern',
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confidence: 0.9
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}
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]
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};
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return {
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...entry,
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result: adaptedResult,
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hitCount: entry.hitCount + 1
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};
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}
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/**
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* Calculate dynamic TTL based on result quality
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*/
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calculateTTL(confidence, patternCount, computeTime) {
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// Higher confidence = longer TTL
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// More patterns = longer TTL
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// Longer compute time = longer TTL (expensive to recompute)
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const confidenceFactor = confidence; // 0.5-1.0
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const complexityFactor = Math.min(patternCount / 5, 1); // 0-1.0
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const computeFactor = Math.min(computeTime / 1000, 1); // 0-1.0
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const multiplier = (confidenceFactor + complexityFactor + computeFactor) / 3;
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return Math.floor(this.defaultTTL * (0.5 + multiplier * 1.5)); // 0.5x to 2x TTL
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}
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/**
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* Evict least useful cache entries
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*/
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evictLeastUseful() {
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let leastUseful = null;
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let minScore = Infinity;
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for (const [key, entry] of this.cache.entries()) {
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// Score based on: hit count, age, confidence
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const age = Date.now() - entry.timestamp;
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const ageScore = age / entry.ttl; // Higher = older
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const hitScore = 1 / (entry.hitCount + 1); // Higher = fewer hits
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const confidenceScore = 1 - entry.confidence; // Higher = lower confidence
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const totalScore = ageScore + hitScore + confidenceScore;
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if (totalScore < minScore) {
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minScore = totalScore;
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leastUseful = key;
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}
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}
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if (leastUseful) {
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this.cache.delete(leastUseful);
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}
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}
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/**
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* Update pattern frequency for optimization
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*/
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updatePatternFrequency(patterns) {
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for (const pattern of patterns) {
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const existing = this.precomputedPatterns.find(p => p.pattern === pattern);
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if (existing) {
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existing.frequency++;
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}
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}
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}
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/**
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* Generate mock result for cache warming
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*/
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generateMockResult(pattern, query) {
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return {
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query,
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answer: `Pre-computed analysis for ${pattern} patterns.`,
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confidence: 0.8,
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reasoning: [
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{
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type: 'pre_computed',
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description: `Pre-computed result for ${pattern}`,
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confidence: 0.8
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}
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],
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insights: [`Cached insight for ${pattern}`],
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patterns: [pattern],
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cached: true,
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precomputed: true
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};
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}
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/**
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* Update performance metrics
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*/
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updateMetrics(queryTime, hit) {
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this.metrics.hitRatio = this.metrics.hits / this.metrics.totalQueries;
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this.metrics.avgComputeTime = (this.metrics.avgComputeTime + queryTime) / 2;
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this.metrics.overhead = queryTime; // Last query overhead
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}
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/**
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* Get current cache metrics
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*/
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getMetrics() {
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return {
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...this.metrics,
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cacheSize: this.cache.size
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};
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}
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/**
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* Clear cache (for testing/maintenance)
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*/
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clear() {
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this.cache.clear();
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this.patternCache.clear();
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this.metrics = {
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hits: 0,
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misses: 0,
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totalQueries: 0,
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avgComputeTime: 0,
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cacheSize: 0,
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hitRatio: 0,
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overhead: 0
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};
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}
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/**
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* Get cache status for debugging
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*/
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getStatus() {
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return {
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size: this.cache.size,
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maxSize: this.maxCacheSize,
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metrics: this.getMetrics(),
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patterns: this.precomputedPatterns.map(p => ({
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pattern: p.pattern,
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frequency: p.frequency,
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priority: p.priority
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}))
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};
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}
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}
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