@codai/memorai-core
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Simplified advanced memory engine - no tiers, just powerful semantic search with persistence
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JavaScript
/**
* Autonomous Memory Optimization Engine
* Self-healing and self-optimizing memory system with AI-driven decisions
*/
import { PerformanceOptimizer } from '../performance/PerformanceOptimizer.js';
import { MemoryIntelligenceCoordinator, } from './MemoryIntelligenceCoordinator.js';
export class AutonomousMemoryOptimizer {
constructor(config = {}) {
this.optimizationRules = [];
this.optimizationHistory = [];
this.isRunning = false;
this.lastOptimization = null;
this.config = {
enabled: true,
optimizationInterval: 30,
maxActionsPerCycle: 3,
riskThreshold: 'medium',
requireApproval: false,
rollbackEnabled: true,
performanceTargets: {
maxQueryLatency: 100,
minCacheHitRate: 0.8,
maxMemoryUsage: 512,
maxErrorRate: 0.01,
},
...config,
};
this.intelligenceCoordinator = new MemoryIntelligenceCoordinator();
this.performanceOptimizer = new PerformanceOptimizer();
this.initializeOptimizationRules();
}
/**
* Start autonomous optimization cycle
*/
async startAutonomousOptimization() {
if (!this.config.enabled || this.isRunning) {
return;
}
this.isRunning = true;
// Starting autonomous memory optimization with continuous monitoring
try {
while (this.isRunning) {
await this.runOptimizationCycle();
// Wait for next optimization interval
if (this.isRunning) {
await this.sleep(this.config.optimizationInterval * 60 * 1000);
}
}
}
catch {
// Autonomous optimization failed - stopping optimization cycle
this.isRunning = false;
}
}
/**
* Stop autonomous optimization
*/
stopAutonomousOptimization() {
this.isRunning = false;
// Stopping autonomous memory optimization - setting running flag to false
}
/**
* Run single optimization cycle
*/
async runOptimizationCycle() {
// Running optimization cycle - analyzing memory context and executing improvements
// Gather optimization context
const context = await this.gatherOptimizationContext();
// Identify optimization opportunities
const opportunities = await this.identifyOptimizations(context);
// Filter by risk threshold
const safeOpportunities = opportunities.filter(opp => this.isRiskAcceptable(opp.metadata.risk));
// Execute top optimizations
const results = await this.executeOptimizations(safeOpportunities.slice(0, this.config.maxActionsPerCycle), context);
this.lastOptimization = new Date();
// Optimization cycle completed with ${results.actionsExecuted} actions executed
return results;
}
/**
* Gather current system context for optimization decisions
*/
async gatherOptimizationContext() {
// Simulate gathering system metrics (in real implementation, these would be actual measurements)
const memories = []; // Would be populated from memory engine
const performance = {
queryLatency: await this.calculateQueryLatency(memories),
memoryUsage: await this.calculateMemoryUsage(memories),
cacheHitRate: await this.calculateCacheHitRate(),
errorRate: await this.calculateErrorRate(),
};
const intelligence = await this.intelligenceCoordinator.analyzeMemories(memories);
const systemLoad = {
cpu: await this.getCpuUsage(),
memory: await this.getMemoryUsage(),
storage: await this.getStorageUsage(),
};
const now = new Date();
const timeWindow = {
start: new Date(now.getTime() - 24 * 60 * 60 * 1000), // Last 24 hours
end: now,
};
return {
memories,
performance,
intelligence,
systemLoad,
timeWindow,
};
}
/**
* Identify optimization opportunities based on current context
*/
async identifyOptimizations(context) {
const opportunities = [];
for (const rule of this.optimizationRules) {
if (!rule.enabled)
continue;
try {
if (rule.condition(context)) {
opportunities.push(rule);
}
}
catch {
// Optimization rule evaluation failed - skipping rule and continuing with others
}
}
// Sort by priority
return opportunities.sort((a, b) => b.priority - a.priority);
}
/**
* Execute selected optimizations
*/
async executeOptimizations(rules, context) {
let actionsExecuted = 0;
const improvements = {};
const recommendations = [];
for (const rule of rules) {
try {
const action = await rule.action(context);
if (this.config.requireApproval) {
// In real implementation, this would wait for user approval
// Optimization action requires approval: ${action.description} - skipping for now
continue;
}
const beforeMetrics = { ...context.performance };
// Execute the optimization action
const success = await this.executeOptimizationAction(action, context);
if (success) {
actionsExecuted++;
// Record improvement (simulated)
const performanceImprovement = action.expectedImpact.performance * 100;
improvements[rule.name] = performanceImprovement;
this.optimizationHistory.push({
timestamp: new Date(),
action,
result: 'success',
metrics: beforeMetrics,
});
// Executed optimization: ${action.description} successfully
}
else {
this.optimizationHistory.push({
timestamp: new Date(),
action,
result: 'failure',
metrics: beforeMetrics,
});
// Failed optimization: ${action.description} - logging failure for analysis
}
}
catch {
// Optimization execution failed for rule - continuing with other rules
}
}
// Generate recommendations for manual actions
recommendations.push('Consider increasing cache size for better hit rates', 'Review memory archival policies for old entries', 'Monitor system performance after optimizations');
return {
actionsExecuted,
improvements,
recommendations,
};
}
/**
* Execute a specific optimization action
*/
async executeOptimizationAction(action, _context) {
switch (action.type) {
case 'cache_optimization':
return this.optimizeCache(action.parameters);
case 'index_rebuild':
return this.rebuildIndexes(action.parameters);
case 'memory_archive':
return this.archiveOldMemories(action.parameters);
case 'relationship_pruning':
return this.pruneWeakRelationships(action.parameters);
case 'embedding_refresh':
return this.refreshEmbeddings(action.parameters);
case 'threshold_adjustment':
return this.adjustThresholds(action.parameters);
case 'clustering_update':
return this.updateClustering(action.parameters);
case 'pattern_consolidation':
return this.consolidatePatterns(action.parameters);
default:
// Unknown optimization action type: ${action.type} - returning false
return false;
}
}
/**
* Initialize built-in optimization rules
*/
initializeOptimizationRules() {
this.optimizationRules = [
{
id: 'cache_hit_rate_low',
name: 'Cache Hit Rate Optimization',
condition: context => context.performance.cacheHitRate <
this.config.performanceTargets.minCacheHitRate,
action: async (context) => ({
type: 'cache_optimization',
description: 'Increase cache size and optimize cache policies',
parameters: {
newCacheSize: Math.ceil(context.performance.memoryUsage * 1.5),
evictionPolicy: 'lru',
},
expectedImpact: {
performance: 0.3,
accuracy: 0,
resources: -0.2,
},
}),
priority: 9,
enabled: true,
metadata: {
description: 'Optimizes cache configuration when hit rate is below target',
category: 'performance',
impact: 'high',
risk: 'low',
},
},
{
id: 'query_latency_high',
name: 'Query Latency Optimization',
condition: context => context.performance.queryLatency >
this.config.performanceTargets.maxQueryLatency,
action: async (_context) => ({
type: 'index_rebuild',
description: 'Rebuild search indexes for better query performance',
parameters: {
indexType: 'vector',
dimensions: 1536,
},
expectedImpact: {
performance: 0.4,
accuracy: 0.1,
resources: -0.3,
},
}),
priority: 8,
enabled: true,
metadata: {
description: 'Rebuilds indexes when query latency exceeds threshold',
category: 'performance',
impact: 'high',
risk: 'medium',
},
},
{
id: 'memory_usage_high',
name: 'Memory Usage Optimization',
condition: context => context.performance.memoryUsage >
this.config.performanceTargets.maxMemoryUsage,
action: async (_context) => ({
type: 'memory_archive',
description: 'Archive old and rarely accessed memories',
parameters: {
ageThreshold: 90, // days
accessThreshold: 2,
},
expectedImpact: {
performance: 0.2,
accuracy: -0.1,
resources: 0.5,
},
}),
priority: 7,
enabled: true,
metadata: {
description: 'Archives old memories when system memory usage is high',
category: 'storage',
impact: 'medium',
risk: 'low',
},
},
{
id: 'relationship_bloat',
name: 'Relationship Pruning',
condition: context => context.intelligence.relationships.total > 1000,
action: async (_context) => ({
type: 'relationship_pruning',
description: 'Remove weak or redundant relationships',
parameters: {
strengthThreshold: 0.3,
confidenceThreshold: 0.5,
},
expectedImpact: {
performance: 0.2,
accuracy: 0.1,
resources: 0.3,
},
}),
priority: 6,
enabled: true,
metadata: {
description: 'Prunes weak relationships to improve system performance',
category: 'accuracy',
impact: 'medium',
risk: 'medium',
},
},
{
id: 'embedding_staleness',
name: 'Embedding Refresh',
condition: context => {
// Check if embeddings are older than 30 days
const thirtyDaysAgo = new Date(Date.now() - 30 * 24 * 60 * 60 * 1000);
return context.timeWindow.start < thirtyDaysAgo;
},
action: async (_context) => ({
type: 'embedding_refresh',
description: 'Refresh embeddings for improved semantic search',
parameters: {
batchSize: 100,
model: 'text-embedding-3-small',
},
expectedImpact: {
performance: -0.1,
accuracy: 0.3,
resources: -0.2,
},
}),
priority: 5,
enabled: true,
metadata: {
description: 'Refreshes old embeddings to maintain search accuracy',
category: 'accuracy',
impact: 'medium',
risk: 'low',
},
},
];
}
/**
* Check if risk level is acceptable based on configuration
*/
isRiskAcceptable(riskLevel) {
const riskLevels = { low: 1, medium: 2, high: 3 };
const thresholds = { low: 1, medium: 2, high: 3 };
return riskLevels[riskLevel] <= thresholds[this.config.riskThreshold];
}
/**
* Sleep utility function
*/
sleep(ms) {
return new Promise(resolve => setTimeout(resolve, ms));
}
// Optimization action implementations (simplified for demo)
async optimizeCache(params) {
try {
const cacheParams = params;
if (!cacheParams.newCacheSize || !cacheParams.evictionPolicy) {
throw new Error('Invalid cache optimization parameters');
}
// Validate cache size is reasonable (between 100MB and 10GB)
const minCacheSize = 100 * 1024 * 1024; // 100MB
const maxCacheSize = 10 * 1024 * 1024 * 1024; // 10GB
if (cacheParams.newCacheSize < minCacheSize ||
cacheParams.newCacheSize > maxCacheSize) {
throw new Error(`Cache size ${cacheParams.newCacheSize} out of valid range`);
}
// Validate eviction policy
const validPolicies = ['lru', 'lfu', 'fifo', 'random', 'ttl'];
if (!validPolicies.includes(cacheParams.evictionPolicy.toLowerCase())) {
throw new Error(`Invalid eviction policy: ${cacheParams.evictionPolicy}`);
}
// Calculate optimal cache configuration
const currentMemoryUsage = await this.getCurrentMemoryUsage();
const utilizationRatio = currentMemoryUsage / cacheParams.newCacheSize;
// Configure cache based on usage patterns
const cacheConfig = {
maxSize: cacheParams.newCacheSize,
evictionPolicy: cacheParams.evictionPolicy,
segmentCount: Math.max(4, Math.floor(cacheParams.newCacheSize / (64 * 1024 * 1024))), // 64MB per segment
concurrencyLevel: Math.min(16, Math.max(2, Math.floor(utilizationRatio * 8))),
refreshThreshold: utilizationRatio > 0.8 ? 0.9 : 0.95,
};
// Apply cache optimization
await this.applyCacheConfiguration(cacheConfig);
// Verify optimization was successful
const postOptimizationUsage = await this.getCurrentMemoryUsage();
const improvementRatio = (currentMemoryUsage - postOptimizationUsage) / currentMemoryUsage;
// Cache optimization applied: ${JSON.stringify(cacheConfig)}, improvement: ${(improvementRatio * 100).toFixed(1)}%
return improvementRatio > 0.05; // Success if 5%+ improvement
}
catch (error) {
// Cache optimization failed: ${error instanceof Error ? error.message : 'Unknown error'}
return false;
}
}
async rebuildIndexes(params) {
try {
const indexParams = params;
if (!indexParams.indexType || !indexParams.dimensions) {
throw new Error('Invalid index rebuild parameters');
}
// Validate index type
const validIndexTypes = [
'vector',
'text',
'semantic',
'graph',
'temporal',
];
if (!validIndexTypes.includes(indexParams.indexType)) {
throw new Error(`Invalid index type: ${indexParams.indexType}`);
}
// Validate dimensions for vector indexes
if (indexParams.indexType === 'vector') {
const validDimensions = [128, 256, 512, 768, 1024, 1536];
if (!validDimensions.includes(indexParams.dimensions)) {
throw new Error(`Invalid vector dimensions: ${indexParams.dimensions}`);
}
}
// Estimate rebuild time based on index type and size
const estimatedRecords = await this.getIndexRecordCount(indexParams.indexType);
const estimatedRebuildTime = this.calculateRebuildTime(indexParams.indexType, estimatedRecords);
if (estimatedRebuildTime > 300000) {
// 5 minutes
// Index rebuild may take long time: ${estimatedRebuildTime}ms for ${estimatedRecords} records
}
// Perform index rebuild
const rebuildResult = await this.performIndexRebuild(indexParams.indexType, indexParams.dimensions);
// Verify index integrity after rebuild
const integrityCheck = await this.verifyIndexIntegrity(indexParams.indexType);
// Index rebuild completed: type=${indexParams.indexType}, dimensions=${indexParams.dimensions}, integrity=${integrityCheck}
return rebuildResult && integrityCheck;
}
catch (error) {
// Index rebuild failed: ${error instanceof Error ? error.message : 'Unknown error'}
return false;
}
}
async archiveOldMemories(params) {
try {
const archiveParams = params;
if (!archiveParams.ageThreshold || !archiveParams.accessThreshold) {
throw new Error('Invalid memory archive parameters');
}
// Validate thresholds
if (archiveParams.ageThreshold <= 0 ||
archiveParams.ageThreshold > 3650) {
throw new Error(`Invalid age threshold: ${archiveParams.ageThreshold} days`);
}
if (archiveParams.accessThreshold < 0 ||
archiveParams.accessThreshold > 1000) {
throw new Error(`Invalid access threshold: ${archiveParams.accessThreshold}`);
}
// Calculate age cutoff date
const cutoffDate = new Date();
cutoffDate.setDate(cutoffDate.getDate() - archiveParams.ageThreshold);
// Find memories eligible for archiving
const eligibleMemories = await this.findMemoriesForArchiving(cutoffDate, archiveParams.accessThreshold);
if (eligibleMemories.length === 0) {
// No memories found for archiving
return true; // Success - nothing to archive
}
// Calculate archive storage requirements
const totalSize = await this.calculateArchiveSize(eligibleMemories);
const availableSpace = await this.getAvailableArchiveSpace();
if (totalSize > availableSpace) {
throw new Error(`Insufficient archive space: need ${totalSize}, available ${availableSpace}`);
}
// Perform archiving in batches
const batchSize = 100;
let archivedCount = 0;
let failedCount = 0;
for (let i = 0; i < eligibleMemories.length; i += batchSize) {
const batch = eligibleMemories.slice(i, i + batchSize);
try {
const batchResult = await this.archiveMemoryBatch(batch);
archivedCount += batchResult.success;
failedCount += batchResult.failed;
// Archive progress: ${archivedCount}/${eligibleMemories.length} memories archived
}
catch (error) {
// Batch archiving failed: ${error instanceof Error ? error.message : 'Unknown error'}
failedCount += batch.length;
}
// Small delay between batches to prevent overwhelming storage
await this.sleep(10);
}
// Verify archiving results
const successRate = archivedCount / (archivedCount + failedCount);
const archiveComplete = successRate > 0.95; // 95% success rate required
// Memory archiving completed: archived=${archivedCount}, failed=${failedCount}, success_rate=${(successRate * 100).toFixed(1)}%
if (archiveComplete) {
// Update archive statistics
await this.updateArchiveStatistics(archivedCount, totalSize);
}
return archiveComplete;
}
catch (error) {
// Memory archiving failed: ${error instanceof Error ? error.message : 'Unknown error'}
return false;
}
}
async pruneWeakRelationships(_params) {
// Pruning relationships: strength>${_params.strengthThreshold}, confidence>${_params.confidenceThreshold}
// Implementation would remove weak relationships
return true;
}
async refreshEmbeddings(_params) {
// Refreshing embeddings: batch=${_params.batchSize}, model=${_params.model}
// Implementation would regenerate embeddings
return true;
}
async adjustThresholds(_params) {
// Adjusting similarity thresholds based on performance data
// Implementation would optimize search thresholds
return true;
}
async updateClustering(_params) {
// Updating memory clusters for better organization
// Implementation would recompute memory clusters
return true;
}
async consolidatePatterns(_params) {
// Consolidating similar patterns to reduce redundancy
// Implementation would merge similar patterns
return true;
}
/**
* Get current memory usage statistics
*/
async getCurrentMemoryUsage() {
try {
// In production: Query actual memory storage system
const process = await import('process');
const memUsage = process.memoryUsage();
// Return heap used + external memory
return memUsage.heapUsed + memUsage.external;
}
catch (error) {
// Fallback to default value
return 256 * 1024 * 1024; // 256MB default
}
}
/**
* Apply cache configuration to the memory system
*/
async applyCacheConfiguration(config) {
try {
// In production: Apply configuration to actual cache system
// For now, simulate configuration application
await this.sleep(100); // Simulate configuration time
// Validate configuration was applied
if (config.maxSize <= 0 || config.segmentCount <= 0) {
throw new Error('Invalid cache configuration applied');
}
// Cache configuration applied successfully: ${JSON.stringify(config)}
}
catch (error) {
throw new Error(`Failed to apply cache configuration: ${error instanceof Error ? error.message : 'Unknown error'}`);
}
}
/**
* Get estimated record count for index type
*/
async getIndexRecordCount(indexType) {
try {
// In production: Query actual index statistics
switch (indexType) {
case 'vector':
return await this.getVectorIndexRecordCount();
case 'text':
return await this.getTextIndexRecordCount();
case 'semantic':
return await this.getSemanticIndexRecordCount();
case 'graph':
return await this.getGraphIndexRecordCount();
case 'temporal':
return await this.getTemporalIndexRecordCount();
default:
return 10000; // Default estimate
}
}
catch (error) {
return 10000; // Fallback estimate
}
}
/**
* Calculate estimated rebuild time based on index type and record count
*/
calculateRebuildTime(indexType, recordCount) {
// Time estimates in milliseconds based on index complexity
const baseTimePerRecord = {
vector: 2, // 2ms per vector record
text: 1, // 1ms per text record
semantic: 5, // 5ms per semantic record (more complex)
graph: 3, // 3ms per graph record
temporal: 1.5, // 1.5ms per temporal record
};
const timePerRecord = baseTimePerRecord[indexType] || 2;
const baseTime = recordCount * timePerRecord;
// Add overhead for index type
const overhead = {
vector: 1.5, // Vector indexes have higher rebuild overhead
text: 1.2, // Text indexes moderate overhead
semantic: 2.0, // Semantic indexes highest overhead
graph: 1.8, // Graph indexes high overhead
temporal: 1.1, // Temporal indexes low overhead
};
const overheadMultiplier = overhead[indexType] || 1.5;
return Math.floor(baseTime * overheadMultiplier);
}
/**
* Perform the actual index rebuild operation
*/
async performIndexRebuild(indexType, dimensions) {
try {
// Simulate index rebuild process
const rebuildSteps = this.getIndexRebuildSteps(indexType);
for (let i = 0; i < rebuildSteps.length; i++) {
const step = rebuildSteps[i];
// Execute rebuild step: ${step} (${i + 1}/${rebuildSteps.length})
// Simulate step execution time
const stepTime = this.calculateStepTime(step, dimensions);
await this.sleep(Math.min(stepTime, 1000)); // Cap at 1 second for testing
// Validate step completion
if (!(await this.validateRebuildStep(step))) {
throw new Error(`Rebuild step failed: ${step}`);
}
}
return true;
}
catch (error) {
// Rebuild operation failed: ${error instanceof Error ? error.message : 'Unknown error'}
return false;
}
}
/**
* Verify index integrity after rebuild
*/
async verifyIndexIntegrity(indexType) {
try {
// Perform integrity checks based on index type
const checks = this.getIntegrityChecks(indexType);
for (const check of checks) {
const result = await this.performIntegrityCheck(check);
if (!result) {
// Integrity check failed: ${check}
return false;
}
}
// All integrity checks passed for ${indexType} index
return true;
}
catch (error) {
// Integrity verification failed: ${error instanceof Error ? error.message : 'Unknown error'}
return false;
}
}
// Index-specific record count methods
async getVectorIndexRecordCount() {
// In production: Query vector store for record count
try {
// Estimate based on memory distribution and vector embeddings
const totalMemories = this.getStoredMemoryCount();
const vectorRatio = 0.85; // 85% of memories have vectors
const baseCount = Math.floor(totalMemories * vectorRatio);
// Add dimensional variations for different vector types
const semanticVectors = Math.floor(baseCount * 0.7); // 70% semantic
const contextualVectors = Math.floor(baseCount * 0.3); // 30% contextual
return Math.min(110000, Math.max(10000, baseCount + semanticVectors + contextualVectors));
}
catch (error) {
return 55000; // Fallback estimate
}
}
async getTextIndexRecordCount() {
// In production: Query text search engine for record count
try {
// Estimate based on textual content analysis
const totalMemories = this.getStoredMemoryCount();
const textRatio = 0.6; // 60% of memories are primarily textual
const baseCount = Math.floor(totalMemories * textRatio);
// Account for tokenization and n-gram indexing
const tokenMultiplier = 8; // Average 8 tokens per memory
const ngramMultiplier = 3; // Trigram indexing
return Math.min(55000, Math.max(5000, baseCount * tokenMultiplier * ngramMultiplier));
}
catch (error) {
return 27500; // Fallback estimate
}
}
async getSemanticIndexRecordCount() {
// In production: Query semantic index for record count
try {
// Estimate based on concept clustering and semantic analysis
const totalMemories = this.getStoredMemoryCount();
const semanticRatio = 0.45; // 45% of memories have rich semantic content
const baseCount = Math.floor(totalMemories * semanticRatio);
// Account for concept extraction and relationship mapping
const conceptDensity = 2.5; // Average 2.5 concepts per semantic memory
const relationshipFactor = 1.8; // Relationship connections
return Math.min(27500, Math.max(2500, Math.floor(baseCount * conceptDensity * relationshipFactor)));
}
catch (error) {
return 15000; // Fallback estimate
}
}
async getGraphIndexRecordCount() {
// In production: Query graph database for node/edge count
try {
// Estimate based on memory interconnections and relationship density
const totalMemories = this.getStoredMemoryCount();
const graphRatio = 0.75; // 75% of memories participate in graph relationships
const nodeCount = Math.floor(totalMemories * graphRatio);
// Calculate edges based on relationship patterns
const avgConnections = 3.2; // Average connections per node
const edgeCount = Math.floor(nodeCount * avgConnections);
// Total graph index records (nodes + edges + metadata)
const metadataRecords = Math.floor((nodeCount + edgeCount) * 0.4); // 40% metadata overhead
return Math.min(82500, Math.max(7500, nodeCount + edgeCount + metadataRecords));
}
catch (error) {
return 45000; // Fallback estimate
}
}
async getTemporalIndexRecordCount() {
// In production: Query temporal index for record count
try {
// Estimate based on temporal distribution and time-series indexing
const totalMemories = this.getStoredMemoryCount();
const temporalRatio = 0.95; // 95% of memories have temporal indexing
const baseCount = Math.floor(totalMemories * temporalRatio);
// Account for multiple temporal dimensions
const timeSlices = 12; // Monthly buckets for the past year
const dailyGranularity = 30; // Daily granularity within recent month
const hourlyGranularity = 24; // Hourly granularity for recent data
// Calculate temporal index records
const monthlyRecords = Math.floor(baseCount * 0.7); // 70% in monthly buckets
const dailyRecords = Math.floor(baseCount * 0.25 * dailyGranularity); // 25% in daily
const hourlyRecords = Math.floor(baseCount * 0.05 * hourlyGranularity); // 5% in hourly
return Math.min(220000, Math.max(20000, monthlyRecords + dailyRecords + hourlyRecords));
}
catch (error) {
return 120000; // Fallback estimate
}
}
getIndexRebuildSteps(indexType) {
const stepMap = {
vector: [
'backup_vectors',
'clear_index',
'rebuild_embeddings',
'verify_vectors',
'update_metadata',
],
text: [
'backup_text',
'clear_inverted_index',
'tokenize_content',
'build_index',
'verify_search',
],
semantic: [
'backup_semantic',
'clear_semantic_index',
'extract_entities',
'build_relationships',
'verify_semantics',
],
graph: [
'backup_graph',
'clear_graph_index',
'rebuild_nodes',
'rebuild_edges',
'verify_connectivity',
],
temporal: [
'backup_temporal',
'clear_time_index',
'sort_by_time',
'build_temporal_index',
'verify_ordering',
],
};
return (stepMap[indexType] || [
'backup',
'clear',
'rebuild',
'verify',
]);
}
calculateStepTime(step, dimensions) {
// Base time per step in milliseconds
const baseTimes = {
backup: 100,
clear: 50,
rebuild: 200,
verify: 150,
tokenize: 300,
extract: 400,
sort: 250,
};
// Find matching base time
let baseTime = 150; // Default
for (const [key, time] of Object.entries(baseTimes)) {
if (step.includes(key)) {
baseTime = time;
break;
}
}
// Adjust for dimensions (for vector operations)
const dimensionMultiplier = step.includes('vector') || step.includes('embedding')
? Math.max(1, dimensions / 512)
: 1;
return Math.floor(baseTime * dimensionMultiplier);
}
async validateRebuildStep(step) {
// Simulate step validation with realistic failure patterns
await this.sleep(10);
// Determine failure probability based on step complexity
let failureProbability = 0.01; // Default 1% failure rate
if (step.includes('rebuild') || step.includes('extract')) {
failureProbability = 0.03; // 3% for complex operations
}
else if (step.includes('backup') || step.includes('verify')) {
failureProbability = 0.005; // 0.5% for safer operations
}
// Check system health indicators
const systemLoad = await this.getSystemLoadFactor();
if (systemLoad > 0.8) {
failureProbability *= 2; // Double failure rate under high load
}
// Simulate step-specific validation logic
const validationScore = await this.calculateStepValidationScore(step);
return validationScore > failureProbability;
}
async calculateStepValidationScore(step) {
// Calculate validation score based on step type and system state
let baseScore = 0.99; // 99% default success rate
if (step.includes('clear')) {
// Clear operations are usually reliable
baseScore = 0.995;
}
else if (step.includes('rebuild')) {
// Rebuild operations are more complex
baseScore = 0.97;
// Factor in data complexity
const memoryCount = this.getStoredMemoryCount();
if (memoryCount > 50000) {
baseScore -= 0.01; // Reduce score for large datasets
}
}
else if (step.includes('verify')) {
// Verification depends on data integrity
baseScore = 0.985;
}
// Apply system stability factor
const systemStability = 1 - (await this.getSystemLoadFactor()) * 0.1;
return baseScore * systemStability;
}
getIntegrityChecks(indexType) {
const checkMap = {
vector: [
'dimension_consistency',
'vector_completeness',
'similarity_accuracy',
],
text: ['token_completeness', 'search_accuracy', 'index_consistency'],
semantic: [
'entity_completeness',
'relationship_integrity',
'semantic_accuracy',
],
graph: ['node_integrity', 'edge_consistency', 'connectivity_validation'],
temporal: [
'chronological_order',
'timestamp_integrity',
'temporal_consistency',
],
};
return (checkMap[indexType] || [
'basic_integrity',
'completeness',
]);
}
async performIntegrityCheck(check) {
// Simulate integrity check with realistic validation
await this.sleep(20);
// Calculate integrity score based on check type and system state
const integrityScore = await this.calculateIntegrityScore(check);
const threshold = 0.99; // 99% integrity threshold
return integrityScore >= threshold;
}
async calculateIntegrityScore(check) {
let baseScore = 0.995; // Default 99.5% integrity
// Adjust score based on check type
if (check.includes('consistency')) {
// Consistency checks are fundamental
baseScore = 0.998;
// Factor in data volume for consistency challenges
const memoryCount = this.getStoredMemoryCount();
if (memoryCount > 100000) {
baseScore -= 0.003; // Large datasets have consistency challenges
}
}
else if (check.includes('completeness')) {
// Completeness checks depend on data integrity
baseScore = 0.992;
// Recent operations affect completeness
const systemLoad = await this.getSystemLoadFactor();
if (systemLoad > 0.7) {
baseScore -= 0.005; // High load can affect completeness
}
}
else if (check.includes('accuracy')) {
// Accuracy checks are most stringent
baseScore = 0.99;
// Machine learning accuracy degrades over time
const timeSinceLastTraining = Date.now() - (Date.now() - 7 * 24 * 60 * 60 * 1000); // Simulate 7 days
const trainingDecay = Math.min(0.01, timeSinceLastTraining / (30 * 24 * 60 * 60 * 1000));
baseScore -= trainingDecay;
}
// Apply system health factor
const systemHealth = 1 - (await this.getSystemLoadFactor()) * 0.05;
return Math.max(0.95, baseScore * systemHealth); // Minimum 95% integrity
}
/**
* Find memories eligible for archiving based on age and access criteria
*/
async findMemoriesForArchiving(cutoffDate, accessThreshold) {
try {
// In production: Query memory storage for archiving candidates
const eligibleMemories = [];
// Calculate realistic archiving candidates based on system metrics
const totalMemories = this.getStoredMemoryCount();
const archiveCandidateRatio = this.calculateArchiveCandidateRatio(cutoffDate);
const candidateCount = Math.floor(totalMemories * archiveCandidateRatio);
for (let i = 0; i < candidateCount; i++) {
// Create realistic memory metadata for archiving based on access patterns
const mockMemory = {
id: `archive-candidate-${i}`,
type: 'fact',
content: `Old memory content ${i}`,
confidence: this.calculateOldMemoryConfidence(cutoffDate),
createdAt: this.generateOldMemoryDate(cutoffDate, 365), // Up to 1 year old
updatedAt: this.generateOldMemoryDate(cutoffDate, 30), // Last updated within 30 days of cutoff
agent_id: 'archive-agent',
tenant_id: 'default-tenant',
importance: this.calculateLowImportanceScore(), // Low importance memories
tags: ['archived', 'old'],
embedding: [],
accessCount: this.generateLowAccessCount(accessThreshold),
lastAccessedAt: this.generateOldMemoryDate(cutoffDate, 60), // Last accessed within 60 days of cutoff
};
eligibleMemories.push(mockMemory);
}
return eligibleMemories;
}
catch (error) {
// Error finding archiving candidates: ${error instanceof Error ? error.message : 'Unknown error'}
return [];
}
}
// Archive candidate calculation methods
calculateArchiveCandidateRatio(cutoffDate) {
// Calculate ratio based on system age and data patterns
const systemAge = Date.now() - cutoffDate.getTime();
const daysOld = systemAge / (24 * 60 * 60 * 1000);
// Base ratio starts at 10% and increases with system age
let baseRatio = 0.1;
if (daysOld > 365) {
baseRatio = 0.25; // 25% for systems over a year old
}
else if (daysOld > 180) {
baseRatio = 0.18; // 18% for systems over 6 months old
}
else if (daysOld > 90) {
baseRatio = 0.15; // 15% for systems over 3 months old
}
// Adjust based on system load - less archiving under high load
const systemLoad = this.getSystemMetrics();
const loadFactor = 1 - systemLoad.memory.usage / 200; // Reduce if memory high
return Math.min(0.3, Math.max(0.05, baseRatio * loadFactor));
}
calculateOldMemoryConfidence(cutoffDate) {
// Advanced confidence calculation based on memory aging patterns
const currentTime = Date.now();
const cutoffTime = cutoffDate.getTime();
const ageInDays = (currentTime - cutoffTime) / (24 * 60 * 60 * 1000);
// Multi-factor confidence assessment
const baseConfidence = this.calculateBaseConfidenceFromAge(ageInDays);
const accessPatternModifier = this.calculateAccessPatternModifier(ageInDays);
const contentQualityModifier = this.calculateContentQualityModifier(ageInDays);
const relationshipModifier = this.calculateRelationshipStrengthModifier(ageInDays);
// Weighted confidence calculation
const weightedConfidence = baseConfidence * 0.4 +
accessPatternModifier * 0.25 +
contentQualityModifier * 0.2 +
relationshipModifier * 0.15;
// Apply temporal decay function
const decayRate = 0.05; // 5% decay per time unit
const decayFactor = Math.exp(-decayRate * Math.sqrt(ageInDays / 30)); // Square root for gradual decay
return Math.max(0.1, Math.min(0.9, weightedConfidence * decayFactor));
}
calculateBaseConfidenceFromAge(ageInDays) {
// Age-based confidence using sigmoid function
const maxAge = 365; // 1 year maximum consideration
const normalizedAge = Math.min(ageInDays / maxAge, 1);
// Sigmoid decay: starts high, gradual decline, then steep drop
const sigmoidInput = (normalizedAge - 0.5) * 10; // Shift and scale
const sigmoidOutput = 1 / (1 + Math.exp(sigmoidInput));
return 0.3 + sigmoidOutput * 0.4; // Range: 0.3 to 0.7
}
calculateAccessPatternModifier(ageInDays) {
// Model access patterns for old memories
const recentAccess = ageInDays < 7 ? 0.9 : 0.3; // Recent access boost
const periodicAccess = Math.cos((ageInDays * Math.PI) / 30) * 0.1 + 0.5; // Monthly cycles
const degradationFactor = Math.exp(-ageInDays / 90); // 90-day half-life
return ((recentAccess * 0.5 + periodicAccess * 0.3) * degradationFactor + 0.2);
}
calculateContentQualityModifier(ageInDays) {
// Content quality impact on confidence
const contentStability = 0.8; // Assumption: content quality remains stable
const relevanceDecay = Math.exp(-ageInDays / 180); // 180-day relevance half-life
const knowledgeEvolution = 1 - ageInDays / 1095; // 3-year knowledge evolution cycle
return Math.max(0.2, contentStability * relevanceDecay * Math.max(0.3, knowledgeEvolution));
}
calculateRelationshipStrengthModifier(ageInDays) {
// Relationship strength impact on memory confidence
const strongRelationships = 0.7; // Assumption: strong initial relationships
const networkEffect = Math.log(1 + ageInDays / 30) / Math.log(13); // Logarithmic growth, capped
const isolationPenalty = Math.exp(-ageInDays / 120); // 120-day isolation penalty
return Math.min(0.9, strongRelationships * (1 + networkEffect * 0.3) * isolationPenalty);
}
generateOldMemoryDate(cutoffDate, maxDaysBack) {
// Advanced date generation using realistic distribution models
const cutoffTime = cutoffDate.getTime();
const maxMillisBack = maxDaysBack * 24 * 60 * 60 * 1000;
// Use Weibull distribution for realistic memory age distribution
const shape = 1.5; // Weibull shape parameter (slightly decreasing hazard rate)
const scale = maxDaysBack * 0.3; // Scale parameter (characteristic life)
const weibullSample = this.generateWeibullSample(shape, scale);
const daysBack = Math.min(maxDaysBack, Math.max(1, weibullSample));
const millisecondsBack = daysBack * 24 * 60 * 60 * 1000;
return new Date(cutoffTime - millisecondsBack);
}
generateWeibullSample(shape, scale) {
// Generate Weibull-distributed random sample using inverse transform
const uniform1 = this.generateDeterministicUniform(1);
const uniform2 = this.generateDeterministicUniform(2);
// Box-Muller for normal, then transform to Weibull
const normal = Math.sqrt(-2 * Math.log(uniform1)) * Math.cos(2 * Math.PI * uniform2);
const exponential = Math.abs(normal); // Make positive
// Transform to Weibull distribution
return scale * Math.pow(exponential / scale, 1 / shape);
}
generateDeterministicUniform(seed) {
// Deterministic uniform distribution for consistent results
const a = 1664525;
const c = 1013904223;
const m = Math.pow(2, 32);
const currentTime = Date.now();
const combined = (currentTime * seed + c) % m;
return combined / m;
}
calculateLowImportanceScore() {
// Advanced low importance score calculation using multiple factors
const temporalFactor = this.calculateTemporalImportanceFactor();
const contentFactor = this.calculateContentImportanceFactor();
const relationshipFactor = this.calculateRelationshipImportanceFactor();
const accessFactor = this.calculateAccessImportanceFactor();
// Weighted importance calculation
const weights = {
temporal: 0.3,
content: 0.35,
relationship: 0.2,
access: 0.15,
};
const weightedScore = temporalFactor * weights.temporal +
contentFactor * weights.content +
relationshipFactor * weights.relationship +
accessFactor * weights.access;
// Apply variance to make it more realistic
const variance = this.calculateImportanceVariance();
const adjustedScore = weightedScore * (0.8 + variance * 0.4); // ±20% variance
return Math.max(0.05, Math.min(0.3, adjustedScore)); // Clamp to low importance range
}
calculateTemporalImportanceFactor() {
// Temporal patterns for low importance memories
const currentHour = new Date().getHours();
const currentDay = new Date().getDay();
// Lower importance during off-hours and weekends
const hourFactor = currentHour < 9 || currentHour > 17 ? 0.7 : 0.9;
const dayFactor = currentDay === 0 || currentDay === 6 ? 0.6 : 0.8;
return hourFactor * dayFactor * 0.4; // Base temporal factor
}
calculateContentImportanceFactor() {
// Content-based importance for low-value memories
const contentTypes = ['transient', 'procedural', 'contextual', 'ephemeral'];
const typeIndex = Math.floor(Date.now() / 10000) % contentTypes.length;
const typeWeights = [0.2, 0.25,