# Architecture: Multi-Layer Memory System ## Design Philosophy aigptは、独立したレイヤーを積み重ねる設計です。各レイヤーは： - **独立性**: 単独で動作可能 - **接続性**: 他のレイヤーと連携可能 - **段階的**: 1つずつ実装・テスト ## Layer Overview ``` ┌─────────────────────────────────────────┐ │ Layer 5: Distribution & Sharing │ Future │ (Game streaming, public/private) │ ├─────────────────────────────────────────┤ │ Layer 4b: AI Companion │ Future │ (Romance system, personality growth) │ ├─────────────────────────────────────────┤ │ Layer 4a: Game Systems │ Future │ (Ranking, rarity, XP, visualization) │ ├─────────────────────────────────────────┤ │ Layer 3: User Evaluation │ Future │ (Personality diagnosis from patterns) │ ├─────────────────────────────────────────┤ │ Layer 2: AI Memory │ Future │ (Claude interpretation, priority_score)│ ├─────────────────────────────────────────┤ │ Layer 1: Pure Memory Storage │ ✅ Current │ (SQLite, ULID, CRUD operations) │ └─────────────────────────────────────────┘ ``` ## Layer 1: Pure Memory Storage (Current) **Status**: ✅ **Implemented & Tested** ### Purpose 正確なデータの保存と参照。シンプルで信頼できる基盤。 ### Technology Stack - **Database**: SQLite with ACID guarantees - **IDs**: ULID (time-sortable, 26 chars) - **Language**: Rust with thiserror/anyhow - **Protocol**: MCP (Model Context Protocol) via stdio ### Data Model ```rust pub struct Memory { pub id: String, // ULID pub content: String, // User content pub created_at: DateTime, pub updated_at: DateTime, } ``` ### Operations - `create()` - Insert new memory - `get(id)` - Retrieve by ID - `update()` - Update existing memory - `delete(id)` - Remove memory - `list()` - List all (sorted by created_at DESC) - `search(query)` - Content-based search - `count()` - Total count ### File Structure ``` src/ ├── core/ │ ├── error.rs - Error types (thiserror) │ ├── memory.rs - Memory struct │ ├── store.rs - SQLite operations │ └── mod.rs - Module exports ├── mcp/ │ ├── base.rs - MCP server │ └── mod.rs - Module exports ├── lib.rs - Library root └── main.rs - CLI application ``` ### Storage - Location: `~/.config/syui/ai/gpt/memory.db` - Schema: Single table with indexes on timestamps - No migrations (fresh start for Layer 1) --- ## Layer 2: AI Memory (Planned) **Status**: 🔵 **Planned** ### Purpose Claudeが記憶内容を解釈し、重要度を評価。 ### Extended Data Model ```rust pub struct AIMemory { // Layer 1 fields pub id: String, pub content: String, pub created_at: DateTime, pub updated_at: DateTime, // Layer 2 additions pub interpreted_content: String, // Claude's interpretation pub priority_score: f32, // 0.0 - 1.0 pub psychological_factors: PsychologicalFactors, } pub struct PsychologicalFactors { pub emotional_weight: f32, // 0.0 - 1.0 pub personal_relevance: f32, // 0.0 - 1.0 pub novelty: f32, // 0.0 - 1.0 pub utility: f32, // 0.0 - 1.0 } ``` ### MCP Tools (Additional) - `create_memory_with_ai` - Create with Claude interpretation - `reinterpret_memory` - Re-evaluate existing memory - `get_high_priority` - Get memories above threshold ### Implementation Strategy - Feature flag: `--features ai-memory` - Backward compatible with Layer 1 - Claude Code does interpretation (no external API) --- ## Layer 3: User Evaluation (Planned) **Status**: 🔵 **Planned** ### Purpose メモリパターンからユーザーの性格を診断。 ### Diagnosis Types ```rust pub enum DiagnosisType { Innovator, // 革新者 Philosopher, // 哲学者 Pragmatist, // 実用主義者 Explorer, // 探検家 Protector, // 保護者 Visionary, // 未来志向 } ``` ### Analysis - Memory content patterns - Priority score distribution - Creation frequency - Topic diversity ### MCP Tools (Additional) - `diagnose_user` - Run personality diagnosis - `get_user_profile` - Get analysis summary --- ## Layer 4a: Game Systems (Planned) **Status**: 🔵 **Planned** ### Purpose ゲーム的要素で記憶管理を楽しく。 ### Features - **Rarity Levels**: Common → Uncommon → Rare → Epic → Legendary - **XP System**: Memory creation earns XP - **Rankings**: Based on total priority score - **Visualization**: Game-style output formatting ### Data Additions ```rust pub struct GameMemory { // Previous layers... pub rarity: RarityLevel, pub xp_value: u32, pub discovered_at: DateTime, } ``` --- ## Layer 4b: AI Companion (Planned) **Status**: 🔵 **Planned** ### Purpose 育成可能な恋愛コンパニオン。 ### Features - Personality types (Tsundere, Kuudere, Genki, etc.) - Relationship level (0-100) - Memory-based interactions - Growth through conversations ### Data Model ```rust pub struct Companion { pub id: String, pub name: String, pub personality: CompanionPersonality, pub relationship_level: u8, // 0-100 pub memories_shared: Vec, pub last_interaction: DateTime, } ``` --- ## Layer 5: Distribution (Future) **Status**: 🔵 **Future Consideration** ### Purpose ゲーム配信や共有機能。 ### Ideas - Share memory rankings - Export as shareable format - Public/private memory modes - Integration with streaming platforms --- ## Implementation Strategy ### Phase 1: Layer 1 ✅ (Complete) - [x] Core memory storage - [x] SQLite integration - [x] MCP server - [x] CLI interface - [x] Tests - [x] Documentation ### Phase 2: Layer 2 (Next) - [ ] Add AI interpretation fields to schema - [ ] Implement priority scoring logic - [ ] Create `create_memory_with_ai` tool - [ ] Update MCP server - [ ] Write tests for AI features ### Phase 3: Layers 3-4 (Future) - [ ] User diagnosis system - [ ] Game mechanics - [ ] Companion system ### Phase 4: Layer 5 (Future) - [ ] Sharing mechanisms - [ ] Public/private modes ## Design Principles 1. **Simplicity First**: Each layer adds complexity incrementally 2. **Backward Compatibility**: New layers don't break old ones 3. **Feature Flags**: Optional features via Cargo features 4. **Independent Testing**: Each layer has its own test suite 5. **Clear Boundaries**: Layers communicate through defined interfaces ## Technology Choices ### Why SQLite? - ACID guarantees - Better querying than JSON - Built-in indexes - Single-file deployment - No server needed ### Why ULID? - Time-sortable (unlike UUID v4) - Lexicographically sortable - 26 characters (compact) - No collision concerns ### Why Rust? - Memory safety - Performance - Excellent error handling - Strong type system - Great tooling (cargo, clippy) ### Why MCP? - Standard protocol for AI tools - Works with Claude Code/Desktop - Simple stdio-based communication - No complex networking ## Future Considerations ### Potential Enhancements - Full-text search (SQLite FTS5) - Tag system - Memory relationships/links - Export/import functionality - Multiple databases - Encryption for sensitive data ### Scalability - Layer 1: Handles 10K+ memories easily - Consider pagination for Layer 4 (UI display) - Indexing strategy for search performance ## Development Guidelines ### Adding a New Layer 1. **Design**: Document data model and operations 2. **Feature Flag**: Add to Cargo.toml 3. **Schema**: Extend database schema (migrations) 4. **Implementation**: Write code in new module 5. **Tests**: Comprehensive test coverage 6. **MCP Tools**: Add new MCP tools if needed 7. **Documentation**: Update this file ### Code Organization ``` src/ ├── core/ # Layer 1: Pure storage ├── ai/ # Layer 2: AI features (future) ├── evaluation/ # Layer 3: User diagnosis (future) ├── game/ # Layer 4a: Game systems (future) ├── companion/ # Layer 4b: Companion (future) └── mcp/ # MCP server (all layers) ``` --- **Version**: 0.2.0 **Last Updated**: 2025-11-05 **Current Layer**: 1