Self-Learning Memory System
A Rust-based self-learning memory system with episodic memory, pattern extraction, and intelligent retrieval capabilities.
Overview
The Self-Learning Memory System provides:
- Episodic Memory: Store and retrieve task execution episodes with context
- Pattern Extraction: Automatically extract patterns from successful task completions
- Intelligent Retrieval: Semantic search with multiple embedding providers
- MCP Server: Model Context Protocol server for AI assistant integration
- CLI Tools: Command-line interface for all operations
Key Features
| Feature | Description |
|---|---|
| Episode Management | Create, log steps, and complete episodes |
| Pattern Recognition | Extract and use patterns for recommendations |
| Multi-provider Embeddings | OpenAI, Cohere, Ollama, local models |
| Dual Storage | Turso (persistent) + redb (cache) |
| MCP Protocol | Full MCP 2025-11-25 support |
Quick Start
# Install the CLI
cargo install do-memory-cli
# Start the MCP server
do-memory-mcp-server
# Create an episode
do-memory-cli episode create --task "My task"
Architecture
The system consists of several crates:
do-memory-core: Core types and logicdo-memory-storage-turso: Turso/libSQL backenddo-memory-storage-redb: redb cache backenddo-memory-mcp: MCP serverdo-memory-cli: Command-line interface
See the Getting Started chapter for details.