Conversation Memory

Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory

Capabilities

• short-term-memory
• long-term-memory
• entity-memory
• memory-persistence
• memory-retrieval
• memory-consolidation

Prerequisites

• Knowledge: LLM conversation patterns, Database basics, Key-value stores
• Skills_recommended: context-window-management, rag-implementation

Scope

• Does_not_cover: Knowledge graph construction, Semantic search implementation, Database administration
• Boundaries: Focus is memory patterns for LLMs, Covers storage and retrieval strategies

Ecosystem

Primary_tools

• Mem0 - Memory layer for AI applications
• LangChain Memory - Memory utilities in LangChain
• Redis - In-memory data store for session memory

Patterns

Tiered Memory System

Different memory tiers for different purposes

When to use: Building any conversational AI

interface MemorySystem { // Buffer: Current conversation (in context) buffer: ConversationBuffer;

// Short-term: Recent interactions (session)
shortTerm: ShortTermMemory;

// Long-term: Persistent across sessions
longTerm: LongTermMemory;

// Entity: Facts about people, places, things
entity: EntityMemory;

}

class TieredMemory implements MemorySystem { async addMessage(message: Message): Promise { // Always add to buffer this.buffer.add(message);

    // Extract entities
    const entities = await extractEntities(message);
    for (const entity of entities) {
        await this.entity.upsert(entity);
    }

    // Check for memorable content
    if (await isMemoryWorthy(message)) {
        await this.shortTerm.add({
            content: message.content,
            timestamp: Date.now(),
            importance: await scoreImportance(message)
        });
    }
}

async consolidate(): Promise<void> {
    // Move important short-term to long-term
    const memories = await this.shortTerm.getOld(24 * 60 * 60 * 1000);
    for (const memory of memories) {
        if (memory.importance > 0.7 || memory.referenced > 2) {
            await this.longTerm.add(memory);
        }
        await this.shortTerm.remove(memory.id);
    }
}

async buildContext(query: string): Promise<string> {
    const parts: string[] = [];

    // Relevant long-term memories
    const longTermRelevant = await this.longTerm.search(query, 3);
    if (longTermRelevant.length) {
        parts.push('## Relevant Memories\n' +
            longTermRelevant.map(m => `- ${m.content}`).join('\n'));
    }

    // Relevant entities
    const entities = await this.entity.getRelevant(query);
    if (entities.length) {
        parts.push('## Known Entities\n' +
            entities.map(e => `- ${e.name}: ${e.facts.join(', ')}`).join('\n'));
    }

    // Recent conversation
    const recent = this.buffer.getRecent(10);
    parts.push('## Recent Conversation\n' + formatMessages(recent));

    return parts.join('\n\n');
}