Create APM.js

APM.js

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+class AdvancedMemoryManager {
+  constructor(config = {}) {
+      // Configurable embedding models
+      this.embeddingModels = {
+          default: new SemanticEmbedding(),
+          multilingual: new MultilingualEmbedding(),
+          specialized: {
+              text: new TextSpecificEmbedding(),
+              numerical: new NumericalEmbedding()
+          }
+      };
+
+      // Adaptive pruning configuration
+      this.pruningConfig = {
+          strategies: [
+              'temporal_decay',
+              'importance_score',
+              'relationship_density'
+          ],
+          thresholds: {
+              maxMemorySize: config.maxMemorySize || 10000,
+              compressionTrigger: config.compressionTrigger || 0.8
+          }
+      };
+
+      // Advanced indexing for efficient retrieval
+      this.semanticIndex = new ApproximateNearestNeighborIndex();
+  }
+
+  async selectOptimalEmbeddingModel(content) {
+      // Dynamically select most appropriate embedding model
+      if (this.isMultilingualContent(content)) {
+          return this.embeddingModels.multilingual;
+      }
+      if (this.isNumericalContent(content)) {
+          return this.embeddingModels.specialized.numerical;
+      }
+      return this.embeddingModels.default;
+  }
+
+  async insert(content, options = {}) {
+      const embeddingModel = await this.selectOptimalEmbeddingModel(content);
+      const memoryItem = new MemoryItem(content, {
+          ...options,
+          embeddingModel
+      });
+
+      // Advanced indexing and relationship tracking
+      this.semanticIndex.add(memoryItem);
+      this.trackRelationships(memoryItem);
+
+      return memoryItem;
+  }
+
+  async intelligentRetrieve(query, options = {}) {
+      const {
+          maxResults = 10,
+          similarityThreshold = 0.7,
+          includeRelated = true
+      } = options;
+
+      // Semantic and relationship-aware retrieval
+      const semanticResults = this.semanticIndex.search(query, {
+          maxResults,
+          threshold: similarityThreshold
+      });
+
+      if (includeRelated) {
+          return this.expandWithRelatedMemories(semanticResults);
+      }
+
+      return semanticResults;
+  }
+
+  async performMemoryCompression() {
+      const compressionCandidates = this.identifyCompressionCandidates();
+      const compressedMemories = compressionCandidates.map(this.compressMemory);
+      
+      return {
+          originalCount: compressionCandidates.length,
+          compressedCount: compressedMemories.length,
+          compressionRatio: compressedMemories.length / compressionCandidates.length
+      };
+  }
+}
+const natural = require('natural');
+const tf = require('@tensorflow/tfjs-node');
+const { Word2Vec } = require('word2vec');
+
+class SemanticEmbedding {
+  constructor() {
+      this.model = null;
+      this.vectorSize = 100;
+  }
+
+  async initialize() {
+      // Placeholder for more advanced embedding initialization
+      this.model = await tf.loadLayersModel('path/to/embedding/model');
+  }
+
+  async generateEmbedding(text) {
+      // Generate semantic vector representation
+      const tokens = natural.tokenize(text.toLowerCase());
+      const embedding = await this.model.predict(tokens);
+      return embedding;
+  }
+
+  calculateSemanticSimilarity(embedding1, embedding2) {
+      // Cosine similarity calculation
+      return tf.losses.cosineDistance(embedding1, embedding2);
+  }
+}
+
+class MemoryItem {
+  constructor(content, {
+      type = "text", 
+      isFactual = 0.5, 
+      source = null,
+      confidence = 0.5
+  } = {}) {
+      this.id = crypto.randomUUID(); // Unique identifier
+      this.content = content;
+      this.type = type;
+      this.isFactual = isFactual;
+      this.confidence = confidence;
+      this.source = source;
+      
+      this.timestamp = Date.now();
+      this.accessCount = 0;
+      this.importance = 5;
+      
+      this.embedding = null;
+      this.related = new Map(); // Enhanced relationship tracking
+      this.tags = new Set();
+  }
+
+  async computeEmbedding(embeddingService) {
+      this.embedding = await embeddingService.generateEmbedding(this.content);
+  }
+
+  addRelationship(memoryItem, weight = 1.0) {
+      this.related.set(memoryItem.id, {
+          memory: memoryItem,
+          weight: weight,
+          type: this.determineRelationshipType(memoryItem)
+      });
+  }
+
+  determineRelationshipType(memoryItem) {
+      // Semantic relationship type inference
+      const semanticDistance = this.calculateSemanticDistance(memoryItem);
+      if (semanticDistance < 0.2) return 'VERY_CLOSE';
+      if (semanticDistance < 0.5) return 'RELATED';
+      return 'DISTANT';
+  }
+
+  calculateSemanticDistance(memoryItem) {
+      // Placeholder for semantic distance calculation
+      return Math.random(); // Replace with actual embedding comparison
+  }
+
+  incrementAccess() {
+      this.accessCount++;
+      this.updateImportance();
+  }
+
+  updateImportance() {
+      // Dynamic importance calculation
+      this.importance = Math.min(
+          10, 
+          5 + Math.log(this.accessCount + 1)
+      );
+  }
+}
+
+class MemoryTier {
+  constructor(name, {
+      maxCapacity = Infinity,
+      pruneStrategy = 'LRU'
+  } = {}) {
+      this.name = name;
+      this.items = new Map(); // Use Map for efficient lookups
+      this.maxCapacity = maxCapacity;
+      this.pruneStrategy = pruneStrategy;
+  }
+
+  insert(memoryItem) {
+      if (this.items.size >= this.maxCapacity) {
+          this.prune();
+      }
+      this.items.set(memoryItem.id, memoryItem);
+  }
+
+  prune() {
+      switch(this.pruneStrategy) {
+          case 'LRU':
+              const lruItem = Array.from(this.items.values())
+                  .sort((a, b) => a.timestamp - b.timestamp)[0];
+              this.items.delete(lruItem.id);
+              break;
+          case 'LEAST_IMPORTANT':
+              const leastImportant = Array.from(this.items.values())
+                  .sort((a, b) => a.importance - b.importance)[0];
+              this.items.delete(leastImportant.id);
+              break;
+      }
+  }
+
+  async retrieve(query, embeddingService, topK = 5) {
+      const queryEmbedding = await embeddingService.generateEmbedding(query);
+      
+      const scoredResults = Array.from(this.items.values())
+          .map(item => ({
+              memory: item,
+              similarity: embeddingService.calculateSemanticSimilarity(
+                  item.embedding, 
+                  queryEmbedding
+              )
+          }))
+          .sort((a, b) => b.similarity - a.similarity)
+          .slice(0, topK);
+
+      return scoredResults.map(r => r.memory);
+  }
+}
+
+class MemoryManager {
+  constructor() {
+      this.embeddingService = new SemanticEmbedding();
+      
+      this.volatileShortTerm = new MemoryTier("Volatile Short-Term", { 
+          maxCapacity: 10,
+          pruneStrategy: 'LRU'
+      });
+      
+      this.persistentLongTerm = new MemoryTier("Persistent Long-Term");
+      this.contextWorkingMemory = new MemoryTier("Context/Working Memory", { 
+          maxCapacity: 5 
+      });
+
+      this.allMemories = new Map();
+  }
+
+  async initialize() {
+      await this.embeddingService.initialize();
+  }
+
+  async insert(content, options = {}) {
+      const memoryItem = new MemoryItem(content, options);
+      await memoryItem.computeEmbedding(this.embeddingService);
+
+      // Insert into all appropriate tiers
+      this.volatileShortTerm.insert(memoryItem);
+      this.persistentLongTerm.insert(memoryItem);
+      this.contextWorkingMemory.insert(memoryItem);
+
+      this.allMemories.set(memoryItem.id, memoryItem);
+      return memoryItem;
+  }
+
+  async retrieve(query, tier = null) {
+      if (tier) {
+          return tier.retrieve(query, this.embeddingService);
+      }
+
+      // Parallel retrieval across tiers
+      const results = await Promise.all([
+          this.volatileShortTerm.retrieve(query, this.embeddingService),
+          this.persistentLongTerm.retrieve(query, this.embeddingService),
+          this.contextWorkingMemory.retrieve(query, this.embeddingService)
+      ]);
+
+      // Flatten and deduplicate results
+      return [...new Set(results.flat())];
+  }
+
+  async findSemanticallySimilar(memoryItem, threshold = 0.7) {
+      const similar = [];
+      for (let [, memory] of this.allMemories) {
+          if (memory.id !== memoryItem.id) {
+              const similarity = this.embeddingService.calculateSemanticSimilarity(
+                  memory.embedding, 
+                  memoryItem.embedding
+              );
+              if (similarity >= threshold) {
+                  similar.push({ memory, similarity });
+              }
+          }
+      }
+      return similar.sort((a, b) => b.similarity - a.similarity);
+  }
+}
+
+// Example Usage
+async function demonstrateMemorySystem() {
+  const memoryManager = new MemoryManager();
+  await memoryManager.initialize();
+
+  // Insert memories
+  const aiEthicsMem = await memoryManager.insert(
+      "AI should be developed with strong ethical considerations", 
+      { 
+          type: "concept", 
+          isFactual: 0.9, 
+          confidence: 0.8 
+      }
+  );
+
+  const aiResearchMem = await memoryManager.insert(
+      "Machine learning research is advancing rapidly", 
+      { 
+          type: "research", 
+          isFactual: 0.95 
+      }
+  );
+
+  // Create relationships
+  aiEthicsMem.addRelationship(aiResearchMem);
+
+  // Retrieve memories
+  const retrievedMemories = await memoryManager.retrieve("AI ethics");
+  console.log("Retrieved Memories:", retrievedMemories);
+
+  // Find semantically similar memories
+  const similarMemories = await memoryManager.findSemanticallySimilar(aiEthicsMem);
+  console.log("Similar Memories:", similarMemories);
+}
+
+demonstrateMemorySystem();
+
+module.exports = { MemoryManager, MemoryItem, MemoryTier };
+class AdvancedMemoryManager {
+  constructor(config = {}) {
+      // Configurable embedding models
+      this.embeddingModels = {
+          default: new SemanticEmbedding(),
+          multilingual: new MultilingualEmbedding(),
+          specialized: {
+              text: new TextSpecificEmbedding(),
+              numerical: new NumericalEmbedding()
+          }
+      };
+
+      // Adaptive pruning configuration
+      this.pruningConfig = {
+          strategies: [
+              'temporal_decay',
+              'importance_score',
+              'relationship_density'
+          ],
+          thresholds: {
+              maxMemorySize: config.maxMemorySize || 10000,
+              compressionTrigger: config.compressionTrigger || 0.8
+          }
+      };
+
+      // Advanced indexing for efficient retrieval
+      this.semanticIndex = new ApproximateNearestNeighborIndex();
+  }
+
+  async selectOptimalEmbeddingModel(content) {
+      // Dynamically select most appropriate embedding model
+      if (this.isMultilingualContent(content)) {
+          return this.embeddingModels.multilingual;
+      }
+      if (this.isNumericalContent(content)) {
+          return this.embeddingModels.specialized.numerical;
+      }
+      return this.embeddingModels.default;
+  }
+
+  async insert(content, options = {}) {
+      const embeddingModel = await this.selectOptimalEmbeddingModel(content);
+      const memoryItem = new MemoryItem(content, {
+          ...options,
+          embeddingModel
+      });
+
+      // Advanced indexing and relationship tracking
+      this.semanticIndex.add(memoryItem);
+      this.trackRelationships(memoryItem);
+
+      return memoryItem;
+  }
+
+  async intelligentRetrieve(query, options = {}) {
+      const {
+          maxResults = 10,
+          similarityThreshold = 0.7,
+          includeRelated = true
+      } = options;
+
+      // Semantic and relationship-aware retrieval
+      const semanticResults = this.semanticIndex.search(query, {
+          maxResults,
+          threshold: similarityThreshold
+      });
+
+      if (includeRelated) {
+          return this.expandWithRelatedMemories(semanticResults);
+      }
+
+      return semanticResults;
+  }
+
+  async performMemoryCompression() {
+      const compressionCandidates = this.identifyCompressionCandidates();
+      const compressedMemories = compressionCandidates.map(this.compressMemory);
+      
+      return {
+          originalCount: compressionCandidates.length,
+          compressedCount: compressedMemories.length,
+          compressionRatio: compressedMemories.length / compressionCandidates.length
+      };
+  }
+}
+class MemoryTracer {
+  constructor() {
+      this.generationLog = new Map(); // Track memory generation lineage
+      this.redundancyMap = new Map(); // Track potential redundant memories
+      this.compressionMetrics = {
+          totalMemories: 0,
+          uniqueMemories: 0,
+          redundancyRate: 0,
+          compressionPotential: 0
+      };
+  }
+
+  trackGeneration(memoryItem, parentMemories = []) {
+      // Create a generation trace
+      const generationEntry = {
+          id: memoryItem.id,
+          timestamp: Date.now(),
+          content: memoryItem.content,
+          parents: parentMemories.map(m => m.id),
+          lineage: [
+              ...parentMemories.flatMap(p => 
+                  this.generationLog.get(p.id)?.lineage || []
+              ),
+              memoryItem.id
+          ]
+      };
+
+      this.generationLog.set(memoryItem.id, generationEntry);
+      this.updateRedundancyMetrics(memoryItem);
+  }
+
+  updateRedundancyMetrics(memoryItem) {
+      // Semantic similarity check for redundancy
+      const similarityThreshold = 0.9;
+      let redundancyCount = 0;
+
+      for (let [, existingMemory] of this.redundancyMap) {
+          const similarity = this.calculateSemanticSimilarity(
+              existingMemory.content, 
+              memoryItem.content
+          );
+
+          if (similarity >= similarityThreshold) {
+              redundancyCount++;
+              this.redundancyMap.set(memoryItem.id, {
+                  memory: memoryItem,
+                  similarTo: existingMemory.id,
+                  similarity: similarity
+              });
+          }
+      }
+
+      // Update compression metrics
+      this.compressionMetrics.totalMemories++;
+      this.compressionMetrics.redundancyRate = 
+          (redundancyCount / this.compressionMetrics.totalMemories);
+      this.compressionMetrics.compressionPotential = 
+          this.calculateCompressionPotential();
+  }
+
+  calculateSemanticSimilarity(content1, content2) {
+      // Placeholder for semantic similarity calculation
+      // In a real implementation, use embedding-based similarity
+      const words1 = new Set(content1.toLowerCase().split(/\s+/));
+      const words2 = new Set(content2.toLowerCase().split(/\s+/));
+      
+      const intersection = new Set(
+          [...words1].filter(x => words2.has(x))
+      );
+
+      return intersection.size / Math.max(words1.size, words2.size);
+  }
+
+  calculateCompressionPotential() {
+      // Advanced compression potential calculation
+      const { totalMemories, redundancyRate } = this.compressionMetrics;
+      
+      // Exponential decay of compression potential
+      return Math.min(1, Math.exp(-redundancyRate) * 
+          (1 - 1 / (1 + totalMemories)));
+  }
+
+  compressMemories(memoryManager) {
+      const compressibleMemories = [];
+
+      // Identify memories for potential compression
+      for (let [id, redundancyEntry] of this.redundancyMap) {
+          if (redundancyEntry.similarity >= 0.9) {
+              compressibleMemories.push({
+                  id: id,
+                  similarTo: redundancyEntry.similarTo,
+                  similarity: redundancyEntry.similarity
+              });
+          }
+      }
+
+      // Compression strategy
+      const compressionStrategy = (memories) => {
+          // Group similar memories
+          const memoryGroups = new Map();
+          
+          memories.forEach(memoryInfo => {
+              const groupKey = memoryInfo.similarTo;
+              if (!memoryGroups.has(groupKey)) {
+                  memoryGroups.set(groupKey, []);
+              }
+              memoryGroups.get(groupKey).push(memoryInfo);
+          });
+
+          // Merge similar memory groups
+          const mergedMemories = [];
+          for (let [baseId, group] of memoryGroups) {
+              const baseMemory = memoryManager.allMemories.get(baseId);
+              
+              // Create a compressed representation
+              const compressedContent = this.createCompressedContent(
+                  group.map(g => 
+                      memoryManager.allMemories.get(g.id).content
+                  )
+              );
+
+              // Create a new compressed memory item
+              const compressedMemory = new MemoryItem(compressedContent, {
+                  type: baseMemory.type,
+                  isFactual: baseMemory.isFactual,
+                  confidence: Math.max(...group.map(g => 
+                      memoryManager.allMemories.get(g.id).confidence
+                  ))
+              });
+
+              mergedMemories.push(compressedMemory);
+          }
+
+          return mergedMemories;
+      };
+
+      // Execute compression
+      const compressedMemories = compressionStrategy(compressibleMemories);
+
+      // Update memory manager
+      compressedMemories.forEach(memory => {
+          memoryManager.insert(memory);
+      });
+
+      // Log compression results
+      console.log('Memory Compression Report:', {
+          totalCompressed: compressibleMemories.length,
+          compressionPotential: this.compressionMetrics.compressionPotential
+      });
+
+      return compressedMemories;
+  }
+
+  createCompressedContent(contents) {
+      // Intelligently combine similar memory contents
+      const uniqueWords = new Set(
+          contents.flatMap(content => 
+              content.toLowerCase().split(/\s+/)
+          )
+      );
+
+      // Create a concise summary
+      return Array.from(uniqueWords).slice(0, 20).join(' ');
+  }
+}
+
+// Modify MemoryManager to incorporate tracing
+class MemoryManager {
+  constructor() {
+      // ... existing constructor code ...
+      this.memoryTracer = new MemoryTracer();
+  }
+
+  async insert(content, options = {}, parentMemories = []) {
+      const memoryItem = new MemoryItem(content, options);
+      
+      // Compute embedding and trace generation
+      await memoryItem.computeEmbedding(this.embeddingService);
+      this.memoryTracer.trackGeneration(memoryItem, parentMemories);
+
+      // ... existing insertion code ...
+
+      return memoryItem;
+  }
+
+  performMemoryCompression() {
+      return this.memoryTracer.compressMemories(this);
+  }
+}
+const crypto = require('crypto');
+
+class MemoryItem {
+  constructor(content, options = {}) {
+      this.id = crypto.randomUUID();
+      this.content = content;
+      this.type = options.type || 'text';
+      this.isFactual = options.isFactual || 0.5;
+      this.confidence = options.confidence || 0.5;
+      
+      this.timestamp = Date.now();
+      this.accessCount = 0;
+      this.importance = 5;
+      
+      this.embedding = null;
+      this.related = new Map();
+      this.tags = new Set();
+  }
+
+  addRelationship(memoryItem, weight = 1.0) {
+      this.related.set(memoryItem.id, {
+          memory: memoryItem,
+          weight: weight,
+          type: this.determineRelationshipType(memoryItem)
+      });
+  }
+
+  determineRelationshipType(memoryItem) {
+      // Basic relationship type inference
+      const content1 = this.content.toLowerCase();
+      const content2 = memoryItem.content.toLowerCase();
+      
+      const sharedWords = content1.split(' ')
+          .filter(word => content2.includes(word));
+      
+      const similarityRatio = sharedWords.length / 
+          Math.max(content1.split(' ').length, content2.split(' ').length);
+      
+      if (similarityRatio > 0.5) return 'VERY_CLOSE';
+      if (similarityRatio > 0.2) return 'RELATED';
+      return 'DISTANT';
+  }
+
+  incrementAccess() {
+      this.accessCount++;
+      this.updateImportance();
+  }
+
+  updateImportance() {
+      // Dynamic importance calculation
+      this.importance = Math.min(
+          10, 
+          5 + Math.log(this.accessCount + 1)
+      );
+  }
+}
+
+module.exports = MemoryItem;
+class MemoryTier {
+  constructor(name, options = {}) {
+      this.name = name;
+      this.items = new Map();
+      this.maxCapacity = options.maxCapacity || Infinity;
+      this.pruneStrategy = options.pruneStrategy || 'LRU';
+  }
+
+  insert(memoryItem) {
+      if (this.items.size >= this.maxCapacity) {
+          this.prune();
+      }
+      this.items.set(memoryItem.id, memoryItem);
+  }
+
+  prune() {
+      switch(this.pruneStrategy) {
+          case 'LRU':
+              const oldestItem = Array.from(this.items.values())
+                  .sort((a, b) => a.timestamp - b.timestamp)[0];
+              this.items.delete(oldestItem.id);
+              break;
+          case 'LEAST_IMPORTANT':
+              const leastImportant = Array.from(this.items.values())
+                  .sort((a, b) => a.importance - b.importance)[0];
+              this.items.delete(leastImportant.id);
+              break;
+      }
+  }
+
+  retrieve(query) {
+      return Array.from(this.items.values())
+          .filter(item => item.content.includes(query));
+  }
+}
+
+module.exports = MemoryTier;
+const MemoryItem = require('./memory-item');
+const MemoryTier = require('./memory-tier');
+const SemanticEmbedding = require('./semantic-embedding');
+
+class MemoryManager {
+  constructor(config = {}) {
+      this.embeddingService = new SemanticEmbedding();
+      
+      this.tiers = {
+          volatileShortTerm: new MemoryTier('Volatile Short-Term', { 
+              maxCapacity: config.shortTermCapacity || 10 
+          }),
+          persistentLongTerm: new MemoryTier('Persistent Long-Term'),
+          contextWorkingMemory: new MemoryTier('Context/Working Memory', { 
+              maxCapacity: config.workingMemoryCapacity || 5 
+          })
+      };
+
+      this.allMemories = new Map();
+  }
+
+  async insert(content, options = {}) {
+      const memoryItem = new MemoryItem(content, options);
+      
+      // Insert into all tiers
+      Object.values(this.tiers).forEach(tier => {
+          tier.insert(memoryItem);
+      });
+
+      this.allMemories.set(memoryItem.id, memoryItem);
+      return memoryItem;
+  }
+
+  async retrieve(query) {
+      // Aggregate results from all tiers
+      const results = Object.values(this.tiers)
+          .flatMap(tier => tier.retrieve(query));
+      
+      // Deduplicate and sort by importance
+      return [...new Set(results)]
+          .sort((a, b) => b.importance - a.importance);
+  }
+
+  async findSemanticallySimilar(memoryItem, threshold = 0.7) {
+      const similar = [];
+      
+      for (let [, memory] of this.allMemories) {
+          if (memory.id !== memoryItem.id) {
+              const similarity = this.calculateSemanticSimilarity(
+                  memory.content, 
+                  memoryItem.content
+              );
+              
+              if (similarity >= threshold) {
+                  similar.push({ memory, similarity });
+              }
+          }
+      }
+      
+      return similar.sort((a, b) => b.similarity - a.similarity);
+  }
+
+  calculateSemanticSimilarity(content1, content2) {
+      // Simple similarity calculation
+      const words1 = new Set(content1.toLowerCase().split(/\s+/));
+      const words2 = new Set(content2.toLowerCase().split(/\s+/));
+      
+      const intersection = new Set(
+          [...words1].filter(x => words2.has(x))
+      );
+
+      return intersection.size / Math.max(words1.size, words2.size);
+  }
+}
+
+module.exports = MemoryManager;
+class SemanticEmbedding {
+  constructor() {
+      this.embeddingCache = new Map();
+  }
+
+  async generateEmbedding(text) {
+      // Check cache first
+      if (this.embeddingCache.has(text)) {
+          return this.embeddingCache.get(text);
+      }
+
+      // Simple embedding generation
+      const tokens = text.toLowerCase().split(/\s+/);
+      const embedding = tokens.map(token => this.simpleTokenEmbedding(token));
+      
+      // Cache the embedding
+      this.embeddingCache.set(text, embedding);
+      
+      return embedding;
+  }
+
+  simpleTokenEmbedding(token) {
+      // Very basic embedding - just a numerical representation
+      return token.split('').map(char => char.charCodeAt(0));
+  }
+
+  calculateSemanticSimilarity(embedding1, embedding2) {
+      // Cosine similarity approximation
+      const dotProduct = embedding1.reduce(
+          (sum, val, i) => sum + val * (embedding2[i] || 0), 
+          0
+      );
+      
+      const magnitude1 = Math.sqrt(
+          embedding1.reduce((sum, val) => sum + val * val, 0)
+      );
+      
+      const magnitude2 = Math.sqrt(
+          embedding2.reduce((sum, val) => sum + val * val, 0)
+      );
+
+      return dotProduct / (magnitude1 * magnitude2);
+  }
+}