Memory and State - ElizaOS Documentation

Memory Architecture Overview

In elizaOS, memory and state management are core responsibilities of the AgentRuntime. The system provides a unified API for creating, storing, retrieving, and searching memories, enabling agents to maintain context and learn from interactions. For runtime details, see Runtime and Lifecycle and Runtime Core.

Core Memory Concepts

Memory Interface

Every piece of information an agent processes becomes a Memory:

interface Memory {
  id?: UUID;                    // Unique identifier
  entityId: UUID;               // Who created this memory (user/agent)
  roomId: UUID;                 // Conversation context
  worldId?: UUID;               // Broader context (e.g., server)
  content: Content;             // The actual content
  embedding?: number[];         // Vector representation
  createdAt?: number;          // Timestamp
  metadata?: MemoryMetadata;   // Additional data
}

interface Content {
  text?: string;               // Text content
  actions?: string[];          // Associated actions
  inReplyTo?: UUID;           // Reference to previous memory
  metadata?: any;             // Custom metadata
}

Memory Lifecycle

1. Creation

// Creating a memory through the runtime
async function createMemory(runtime: IAgentRuntime, message: string) {
  const memory: CreateMemory = {
    agentId: runtime.agentId,
    entityId: userId,
    roomId: currentRoom,
    content: { 
      text: message,
      metadata: {
        source: 'chat',
        processed: Date.now()
      }
    }
  };
  
  // Runtime automatically generates embeddings if not provided
  const memoryId = await runtime.createMemory(memory);
  return memoryId;
}

2. Storage

Memories are persisted through the IDatabaseAdapter:

// The runtime handles storage automatically
// Memories are stored with:
// - Full text for retrieval
// - Embeddings for semantic search
// - Metadata for filtering
// - Relationships for context

3. Retrieval

// Recent memories from a conversation
const recentMemories = await runtime.getMemories({
  roomId: roomId,
  count: 10,
  unique: true  // Deduplicate similar memories
});

// Memories from a specific user
const userMemories = await runtime.getMemories({
  entityId: userId,
  count: 20
});

// Time-bounded memories
const todaysMemories = await runtime.getMemories({
  roomId: roomId,
  start: startOfDay,
  end: endOfDay
});

Context Management

Context Window

The context window determines how much information the agent considers:

// Context window configuration
export class AgentRuntime {
  readonly #conversationLength = 32; // Default messages to consider
  
  // Dynamically adjust based on token limits
  async buildContext(roomId: UUID): Promise<State> {
    const memories = await this.getMemories({
      roomId,
      count: this.#conversationLength
    });
    
    // Token counting and pruning
    let tokenCount = 0;
    const maxTokens = 4000; // Leave room for response
    const prunedMemories = [];
    
    for (const memory of memories) {
      const tokens = estimateTokens(memory.content.text);
      if (tokenCount + tokens > maxTokens) break;
      tokenCount += tokens;
      prunedMemories.push(memory);
    }
    
    return this.composeState(prunedMemories);
  }
}

Context Selection Strategies

Recency-Based

Most recent messages are most relevant:

const recentContext = await runtime.getMemories({
  roomId: roomId,
  count: 20,
  orderBy: 'createdAt',
  direction: 'DESC'
});

Importance-Based

Prioritize important memories:

// Importance scoring based on:
// - User reactions
// - Agent actions taken
// - Explicit markers
const importantMemories = await runtime.searchMemories({
  roomId: roomId,
  filter: {
    importance: { $gte: 0.8 }
  },
  count: 10
});

Hybrid Approach

Combine recent and important:

async function getHybridContext(runtime: IAgentRuntime, roomId: UUID) {
  // Get recent messages for immediate context
  const recent = await runtime.getMemories({
    roomId,
    count: 10
  });
  
  // Get important historical context
  const important = await runtime.searchMemories({
    roomId,
    query: "important decisions, key information, user preferences",
    match_threshold: 0.7,
    count: 5
  });
  
  // Combine and deduplicate
  const combined = [...recent, ...important];
  return deduplicateMemories(combined);
}

State Composition

State composition brings together memories and provider data:

// The runtime's state composition pipeline
interface State {
  messages: Memory[];           // Conversation history
  facts: string[];              // Known facts
  providers: ProviderData[];    // Provider contributions
  context: string;              // Formatted context
}

// Provider contribution to state
export const userContextProvider: Provider = {
  name: 'userContext',
  get: async (runtime, message, state) => {
    const userProfile = await runtime.getEntity(message.entityId);
    return {
      text: `User: ${userProfile.name}`,
      data: {
        preferences: userProfile.metadata?.preferences,
        history: userProfile.metadata?.interactionCount
      }
    };
  }
};

Memory Types

Short-term Memory

Working memory for immediate tasks:

// Short-term memory is typically the current conversation
class WorkingMemory {
  private buffer: Memory[] = [];
  private maxSize = 50;
  
  add(memory: Memory) {
    this.buffer.push(memory);
    if (this.buffer.length > this.maxSize) {
      this.buffer.shift(); // Remove oldest
    }
  }
  
  getRecent(count: number): Memory[] {
    return this.buffer.slice(-count);
  }
  
  clear() {
    this.buffer = [];
  }
}

Long-term Memory

Persistent storage of important information:

// Long-term memories are marked and preserved
interface LongTermMemory extends Memory {
  metadata: {
    type: 'long_term';
    importance: number;
    lastAccessed: number;
    accessCount: number;
  };
}

// Consolidation process
async function consolidateToLongTerm(
  runtime: IAgentRuntime,
  memory: Memory
): Promise<void> {
  if (shouldConsolidate(memory)) {
    await runtime.updateMemory({
      ...memory,
      metadata: {
        ...memory.metadata,
        type: 'long_term',
        importance: calculateImportance(memory),
        consolidatedAt: Date.now()
      }
    });
  }
}

Knowledge Memory

Static and dynamic knowledge:

// Knowledge loaded from character configuration
const staticKnowledge = character.knowledge || [];

// Dynamic knowledge learned during interactions
async function learnFact(runtime: IAgentRuntime, fact: string) {
  await runtime.createMemory({
    content: {
      text: fact,
      metadata: {
        type: 'knowledge',
        learned: true,
        confidence: 0.9
      }
    },
    roomId: 'knowledge-base',
    entityId: runtime.agentId
  });
}

// Retrieving knowledge
async function getKnowledge(runtime: IAgentRuntime, topic: string) {
  return await runtime.searchMemories({
    query: topic,
    filter: {
      'metadata.type': 'knowledge'
    },
    match_threshold: 0.7
  });
}

Memory Operations

Creating Memories

Best practices for memory creation:

// Complete memory creation with all metadata
async function createRichMemory(
  runtime: IAgentRuntime,
  content: string,
  context: any
): Promise<UUID> {
  const memory: CreateMemory = {
    agentId: runtime.agentId,
    entityId: context.userId,
    roomId: context.roomId,
    content: {
      text: content,
      actions: context.actions || [],
      inReplyTo: context.replyTo,
      metadata: {
        source: context.source,
        platform: context.platform,
        sentiment: analyzeSentiment(content),
        topics: extractTopics(content),
        entities: extractEntities(content)
      }
    },
    // Pre-compute embedding for better performance
    embedding: await runtime.embed(content)
  };
  
  return await runtime.createMemory(memory);
}

Retrieving Memories

Efficient retrieval patterns:

// Paginated retrieval for large conversations
async function getPaginatedMemories(
  runtime: IAgentRuntime,
  roomId: UUID,
  page: number = 1,
  pageSize: number = 20
) {
  const offset = (page - 1) * pageSize;
  return await runtime.getMemories({
    roomId,
    count: pageSize,
    offset
  });
}

// Filtered retrieval
async function getFilteredMemories(
  runtime: IAgentRuntime,
  filters: MemoryFilters
) {
  return await runtime.getMemories({
    roomId: filters.roomId,
    entityId: filters.entityId,
    start: filters.startDate,
    end: filters.endDate,
    filter: {
      'content.actions': { $contains: filters.action },
      'metadata.sentiment': filters.sentiment
    }
  });
}

Searching Memories

Advanced search capabilities:

// Semantic search with embeddings
async function semanticSearch(
  runtime: IAgentRuntime,
  query: string,
  options: SearchOptions = {}
): Promise<Memory[]> {
  const embedding = await runtime.embed(query);
  
  return await runtime.searchMemoriesByEmbedding(embedding, {
    match_threshold: options.threshold || 0.75,
    count: options.limit || 10,
    roomId: options.roomId,
    filter: options.filter
  });
}

// Hybrid search combining semantic and keyword
async function hybridSearch(
  runtime: IAgentRuntime,
  query: string
): Promise<Memory[]> {
  // Semantic search
  const semantic = await semanticSearch(runtime, query);
  
  // Keyword search
  const keywords = extractKeywords(query);
  const keyword = await runtime.searchMemories({
    text: keywords.join(' OR '),
    count: 10
  });
  
  // Combine and rank
  return rankSearchResults([...semantic, ...keyword]);
}

Embeddings and Vectors

Embedding Generation

How and when embeddings are created:

// Automatic embedding generation
class EmbeddingManager {
  private model: EmbeddingModel;
  private cache = new Map<string, number[]>();
  
  async generateEmbedding(text: string): Promise<number[]> {
    // Check cache first
    const cached = this.cache.get(text);
    if (cached) return cached;
    
    // Generate new embedding
    const embedding = await this.model.embed(text);
    
    // Cache for reuse
    this.cache.set(text, embedding);
    
    return embedding;
  }
  
  // Batch processing for efficiency
  async generateBatch(texts: string[]): Promise<number[][]> {
    const uncached = texts.filter(t => !this.cache.has(t));
    
    if (uncached.length > 0) {
      const embeddings = await this.model.embedBatch(uncached);
      uncached.forEach((text, i) => {
        this.cache.set(text, embeddings[i]);
      });
    }
    
    return texts.map(t => this.cache.get(t)!);
  }
}

Vector Search

Efficient similarity search:

// Vector similarity calculation
function cosineSimilarity(a: number[], b: number[]): number {
  let dotProduct = 0;
  let normA = 0;
  let normB = 0;
  
  for (let i = 0; i < a.length; i++) {
    dotProduct += a[i] * b[i];
    normA += a[i] * a[i];
    normB += b[i] * b[i];
  }
  
  return dotProduct / (Math.sqrt(normA) * Math.sqrt(normB));
}

// Optimized vector search with indexing
class VectorIndex {
  private index: AnnoyIndex;  // Approximate nearest neighbor
  
  async search(
    query: number[],
    k: number = 10
  ): Promise<SearchResult[]> {
    const neighbors = await this.index.getNearestNeighbors(query, k);
    
    return neighbors.map(n => ({
      id: n.id,
      similarity: n.distance,
      memory: this.getMemory(n.id)
    }));
  }
  
  // Periodic index rebuilding for new memories
  async rebuild() {
    const memories = await this.getAllMemories();
    this.index = new AnnoyIndex(memories);
    await this.index.build();
  }
}

State Management

State Structure

The complete state object:

interface State {
  // Core conversation context
  messages: Memory[];
  recentMessages: string;
  
  // Agent knowledge
  facts: string[];
  knowledge: string;
  
  // Provider contributions
  providers: {
    [key: string]: {
      text: string;
      data: any;
    };
  };
  
  // Composed context
  context: string;
  
  // Metadata
  metadata: {
    roomId: UUID;
    entityId: UUID;
    timestamp: number;
    tokenCount: number;
  };
}

State Updates

Managing state changes:

class StateManager {
  private currentState: State;
  private stateHistory: State[] = [];
  private maxHistory = 10;
  
  async updateState(runtime: IAgentRuntime, trigger: Memory) {
    // Save current state to history
    this.stateHistory.push(this.currentState);
    if (this.stateHistory.length > this.maxHistory) {
      this.stateHistory.shift();
    }
    
    // Build new state
    this.currentState = await this.buildState(runtime, trigger);
    
    // Notify listeners
    this.emitStateChange(this.currentState);
    
    return this.currentState;
  }
  
  private async buildState(
    runtime: IAgentRuntime,
    trigger: Memory
  ): Promise<State> {
    // Get relevant memories
    const memories = await runtime.getMemories({
      roomId: trigger.roomId,
      count: 20
    });
    
    // Get provider data
    const providers = await this.gatherProviderData(runtime, trigger);
    
    // Compose final state
    return runtime.composeState({
      messages: memories,
      providers,
      trigger
    });
  }
}

Performance Optimization

Memory Pruning

Strategies for managing memory size:

// Time-based pruning
async function pruneOldMemories(
  runtime: IAgentRuntime,
  maxAge: number = 30 * 24 * 60 * 60 * 1000 // 30 days
) {
  const cutoff = Date.now() - maxAge;
  
  await runtime.deleteMemories({
    filter: {
      createdAt: { $lt: cutoff },
      'metadata.type': { $ne: 'long_term' }  // Preserve long-term
    }
  });
}

// Importance-based pruning
async function pruneByImportance(
  runtime: IAgentRuntime,
  maxMemories: number = 10000
) {
  const memories = await runtime.getAllMemories();
  
  if (memories.length <= maxMemories) return;
  
  // Score and sort memories
  const scored = memories.map(m => ({
    memory: m,
    score: calculateImportanceScore(m)
  }));
  
  scored.sort((a, b) => b.score - a.score);
  
  // Keep top memories, delete rest
  const toDelete = scored.slice(maxMemories);
  for (const item of toDelete) {
    await runtime.deleteMemory(item.memory.id);
  }
}

Caching Strategies

Multi-level caching for performance:

class MemoryCache {
  private l1Cache = new Map<UUID, Memory>();    // Hot cache (in-memory)
  private l2Cache = new LRUCache<UUID, Memory>({  // Warm cache
    max: 1000,
    ttl: 5 * 60 * 1000  // 5 minutes
  });
  
  async get(id: UUID): Promise<Memory | null> {
    // Check L1
    if (this.l1Cache.has(id)) {
      return this.l1Cache.get(id);
    }
    
    // Check L2
    const l2Result = this.l2Cache.get(id);
    if (l2Result) {
      this.l1Cache.set(id, l2Result);  // Promote to L1
      return l2Result;
    }
    
    // Fetch from database
    const memory = await this.fetchFromDB(id);
    if (memory) {
      this.cache(memory);
    }
    
    return memory;
  }
  
  private cache(memory: Memory) {
    this.l1Cache.set(memory.id, memory);
    this.l2Cache.set(memory.id, memory);
    
    // Manage L1 size
    if (this.l1Cache.size > 100) {
      const oldest = this.l1Cache.keys().next().value;
      this.l1Cache.delete(oldest);
    }
  }
}

Database Optimization

Query optimization techniques:

// Indexed queries
interface MemoryIndexes {
  roomId: BTreeIndex;
  entityId: BTreeIndex;
  createdAt: BTreeIndex;
  embedding: IVFIndex;  // Inverted file index for vectors
}

// Batch operations
async function batchCreateMemories(
  runtime: IAgentRuntime,
  memories: CreateMemory[]
): Promise<UUID[]> {
  // Generate embeddings in batch
  const texts = memories.map(m => m.content.text);
  const embeddings = await runtime.embedBatch(texts);
  
  // Prepare batch insert
  const enriched = memories.map((m, i) => ({
    ...m,
    embedding: embeddings[i]
  }));
  
  // Single database transaction
  return await runtime.batchCreateMemories(enriched);
}

Advanced Patterns

Memory Networks

Building relationships between memories:

// Memory graph structure
interface MemoryNode {
  memory: Memory;
  connections: {
    causes: UUID[];      // Memories that led to this
    effects: UUID[];     // Memories caused by this
    related: UUID[];     // Thematically related
    references: UUID[];  // Explicit references
  };
}

// Building memory graphs
async function buildMemoryGraph(
  runtime: IAgentRuntime,
  rootMemoryId: UUID
): Promise<MemoryGraph> {
  const visited = new Set<UUID>();
  const graph = new Map<UUID, MemoryNode>();
  
  async function traverse(memoryId: UUID, depth: number = 0) {
    if (visited.has(memoryId) || depth > 3) return;
    visited.add(memoryId);
    
    const memory = await runtime.getMemory(memoryId);
    const connections = await findConnections(runtime, memory);
    
    graph.set(memoryId, {
      memory,
      connections
    });
    
    // Recursively traverse connections
    for (const connectedId of Object.values(connections).flat()) {
      await traverse(connectedId, depth + 1);
    }
  }
  
  await traverse(rootMemoryId);
  return graph;
}

Temporal Patterns

Time-aware memory retrieval:

// Temporal memory windows
async function getTemporalContext(
  runtime: IAgentRuntime,
  timestamp: number,
  windowSize: number = 60 * 60 * 1000  // 1 hour
) {
  return await runtime.getMemories({
    start: timestamp - windowSize / 2,
    end: timestamp + windowSize / 2,
    orderBy: 'createdAt'
  });
}

// Memory decay modeling
function calculateMemoryRelevance(
  memory: Memory,
  currentTime: number
): number {
  const age = currentTime - memory.createdAt;
  const halfLife = 7 * 24 * 60 * 60 * 1000;  // 1 week
  
  // Exponential decay with importance modifier
  const decay = Math.exp(-age / halfLife);
  const importance = memory.metadata?.importance || 0.5;
  
  return decay * importance;
}

Multi-agent Memory

Shared memory spaces between agents:

// Shared memory pool
interface SharedMemorySpace {
  id: UUID;
  agents: UUID[];
  visibility: 'public' | 'private' | 'selective';
  permissions: {
    [agentId: string]: {
      read: boolean;
      write: boolean;
      delete: boolean;
    };
  };
}

// Accessing shared memories
async function getSharedMemories(
  runtime: IAgentRuntime,
  spaceId: UUID
): Promise<Memory[]> {
  // Check permissions
  const space = await runtime.getSharedSpace(spaceId);
  const permissions = space.permissions[runtime.agentId];
  
  if (!permissions?.read) {
    throw new Error('No read access to shared space');
  }
  
  return await runtime.getMemories({
    spaceId,
    visibility: ['public', runtime.agentId]
  });
}

// Memory synchronization
async function syncMemories(
  runtime: IAgentRuntime,
  otherAgentId: UUID
) {
  const sharedSpace = await runtime.getSharedSpace(otherAgentId);
  const updates = await runtime.getMemoryUpdates(sharedSpace.lastSync);
  
  for (const update of updates) {
    await runtime.applyMemoryUpdate(update);
  }
  
  sharedSpace.lastSync = Date.now();
}

Best Practices

Always provide embeddings: Pre-compute embeddings when creating memories for better search performance
Use appropriate retrieval methods: Semantic search for meaning, recency for context, filters for precision
Implement memory hygiene: Regular pruning and consolidation to maintain performance
Cache strategically: Multi-level caching for frequently accessed memories
Batch operations: Process multiple memories together when possible
Index appropriately: Create indexes for common query patterns
Monitor memory growth: Track memory usage and implement limits
Preserve important memories: Mark and protect critical information from pruning
Version memory schemas: Plan for memory structure evolution
Test retrieval accuracy: Regularly evaluate search relevance

Troubleshooting

Common Issues

Memory Search Not Finding Expected Results

// Debug search issues
async function debugSearch(runtime: IAgentRuntime, query: string) {
  // Check embedding generation
  const embedding = await runtime.embed(query);
  console.log('Query embedding:', embedding.slice(0, 5));
  
  // Test with different thresholds
  const thresholds = [0.9, 0.8, 0.7, 0.6, 0.5];
  for (const threshold of thresholds) {
    const results = await runtime.searchMemoriesByEmbedding(embedding, {
      match_threshold: threshold,
      count: 5
    });
    console.log(`Threshold ${threshold}: ${results.length} results`);
  }
  
  // Check if memories exist at all
  const allMemories = await runtime.getMemories({ count: 100 });
  console.log(`Total memories: ${allMemories.length}`);
}

Memory Leaks

// Monitor memory usage
class MemoryMonitor {
  private metrics = {
    totalMemories: 0,
    averageSize: 0,
    growthRate: 0
  };
  
  async monitor(runtime: IAgentRuntime) {
    setInterval(async () => {
      const stats = await runtime.getMemoryStats();
      
      this.metrics = {
        totalMemories: stats.count,
        averageSize: stats.totalSize / stats.count,
        growthRate: (stats.count - this.metrics.totalMemories) / this.metrics.totalMemories
      };
      
      if (this.metrics.growthRate > 0.1) {  // 10% growth
        console.warn('High memory growth detected:', this.metrics);
      }
    }, 60000);  // Check every minute
  }
}

What’s Next?

Character Interface

Define your agent’s character configuration

Personality & Behavior

Craft unique agent personalities

Runtime & Lifecycle

Learn how memory integrates with the runtime

Plugin Development

Build providers that contribute to state

GETTING STARTED

GUIDES

PROJECTS

AGENTS

PLUGINS

RUNTIME

​Memory Architecture Overview

​Core Memory Concepts

​Memory Interface

​Memory Lifecycle

​1. Creation

​2. Storage

​3. Retrieval

​Context Management

​Context Window

​Context Selection Strategies

​Recency-Based

​Importance-Based

​Hybrid Approach

​State Composition

​Memory Types

​Short-term Memory

​Long-term Memory

​Knowledge Memory

​Memory Operations

​Creating Memories

​Retrieving Memories

​Searching Memories

​Embeddings and Vectors

​Embedding Generation

​Vector Search

​State Management

​State Structure

​State Updates

​Performance Optimization

​Memory Pruning

​Caching Strategies

​Database Optimization

​Advanced Patterns

​Memory Networks

​Temporal Patterns

​Multi-agent Memory

​Best Practices

​Troubleshooting

​Common Issues

​Memory Search Not Finding Expected Results

​Memory Leaks

​What’s Next?