MUXI Framework - Memory Systems Guidelines

These rules define best practices for implementing and using memory systems

Buffer Memory (Short-Term)

• Use FAISS for efficient similarity search
• Implement proper vector normalization
• Handle document chunking appropriately
• Implement memory pruning to stay within context limits
• Properly serialize vectors for storage
• Implement efficient retrieval strategies
• Use appropriate similarity metrics (cosine, dot product, etc.)
• Optimize index parameters for your specific use case
• Implement proper error handling for retrieval failures
• Support metadata storage alongside vectors
• Implement memory summarization when needed
• Properly handle updates to existing memories

Long-Term Memory

• Use PostgreSQL with pgvector for persistent storage
• Implement proper schema design for memory storage
• Use appropriate indexes for vector columns
• Implement proper query optimization for vector searches
• Handle large volumes of data efficiently
• Implement memory cleanup and archiving
• Support metadata filtering in searches
• Implement proper error handling for database operations
• Use transactions for related operations
• Implement connection pooling
• Handle concurrent access properly
• Support memory exports and imports

Memobase (User-Aware Memory)

• Properly partition memories by user_id
• Implement access control for memories
• Support cross-user memory sharing when appropriate
• Implement proper cleanup of user memories
• Handle user deletion appropriately
• Support memory migration between users
• Implement analytics on memory usage
• Support different memory retention policies per user
• Implement memory prioritization
• Handle memory conflicts
• Support memory search across users for administrators
• Implement proper backup and restore mechanisms

Vector Operations

• Choose appropriate vector dimensions based on model
• Implement proper vector normalization when using cosine similarity
• Use dimensionality reduction for very high-dimensional vectors
• Benchmark different vector similarity approaches
• Optimize vector storage format
• Implement caching for frequent vector operations
• Use batch operations for multiple vectors
• Implement appropriate vector preprocessing
• Handle out-of-vocabulary tokens in embeddings
• Support different embedding models
• Implement fallbacks for embedding generation failures
• Document vector format and dimensionality

Memory Retrieval

• Implement relevance scoring for retrieved memories
• Support hybrid search (vector + keyword)
• Implement proper ranking algorithms
• Support different retrieval strategies based on query type
• Implement context-aware retrieval
• Support filters in retrieval operations
• Optimize top-k retrieval performance
• Implement memory deduplication
• Support time-weighted retrieval
• Implement recency bias when appropriate
• Handle retrieval errors gracefully
• Support pagination for large result sets

Memory Integration

• Properly integrate memories into prompt construction
• Handle context length limits by prioritizing memories
• Implement memory summarization for efficient context use
• Support different memory integration strategies
• Properly attribute information to memory sources
• Handle conflicting information from different memories
• Implement memory weighting based on relevance
• Support streaming memory integration
• Handle memory format conversion for different LLMs
• Support memory collection during conversations
• Implement feedback loops for memory relevance
• Document memory integration patterns

Performance and Scalability

• Optimize vector operations for performance
• Implement appropriate caching strategies
• Use batch operations for efficiency
• Monitor memory system performance
• Implement sharding for large memory stores
• Optimize database queries for vector operations
• Use connection pooling for database access
• Implement proper indexing for frequent queries
• Benchmark memory operations with realistic workloads
• Implement circuit breakers for external dependencies
• Support horizontal scaling of memory systems
• Document performance characteristics