Memory Systems
Architectures for persistent context beyond the window.
Memory Layer Architecture
| Layer |
Scope |
Persistence |
Use Case |
| L1: Working |
Current window |
None |
Active reasoning |
| L2: Short-Term |
Session |
Session |
Task continuity |
| L3: Long-Term |
Cross-session |
Persistent |
User preferences |
| L4: Entity |
Per-entity |
Persistent |
Consistency |
| L5: Temporal Graph |
Time-aware |
Persistent |
Evolving facts |
Benchmark Performance (DMR Accuracy)
| System |
Accuracy |
Approach |
| Zep |
94.8% |
Temporal knowledge graphs |
| MemGPT |
93.4% |
Hierarchical memory |
| GraphRAG |
75-85% |
Knowledge graphs |
| Vector RAG |
60-70% |
Embedding similarity |
Vector Store with Metadata
Temporal Knowledge Graph
Memory Retrieval Patterns
| Pattern |
Query |
Use Case |
| Semantic |
"Similar to X" |
General recall |
| Entity-based |
"About user John" |
Consistency |
| Temporal |
"Valid on date" |
Evolving facts |
| Hybrid |
Combine above |
Production |
File-System-as-Memory
Guidelines
- Start with file-system-as-memory (simplest)
- Add vector search for scale
- Use entity indexing for consistency
- Add temporal awareness for evolving facts
- Implement consolidation for health
- Measure retrieval accuracy
Related