APM.js

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);
  }
}