Update documentation: reflect Layers 1-3 completion

Updated README.md and ARCHITECTURE.md to reflect current implementation
status. All three layers are now complete and functional.

Changes:
- README.md: Added Layer 2 (AI Memory) and Layer 3 (Big Five) features
- README.md: Added MCP tools list and usage examples
- README.md: Added Big Five personality traits explanation
- ARCHITECTURE.md: Updated Layer 2 and 3 status to Complete
- ARCHITECTURE.md: Updated implementation strategy phases
- Archived old documentation in docs/archive/old-versions/

Current status:
- Layer 1  Complete: Pure memory storage
- Layer 2  Complete: AI interpretation + priority scoring
- Layer 3  Complete: Big Five personality analysis
- Layer 4 🔵 Planned: Game systems and companion features
- Layer 5 🔵 Future: Distribution and sharing
This commit is contained in:
Claude
2025-11-06 06:11:01 +00:00
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README.md
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# aigpt # aigpt
Simple memory storage for Claude with MCP support. AI memory system with psychological analysis for Claude via MCP.
**Layer 1: Pure Memory Storage** - A clean, SQLite-based memory system with ULID identifiers. **Current: Layers 1-3 Complete** - Memory storage, AI interpretation, and personality analysis.
## Features ## Features
### Layer 1: Pure Memory Storage
- 🗄️ **SQLite Storage**: Reliable database with ACID guarantees - 🗄️ **SQLite Storage**: Reliable database with ACID guarantees
- 🔖 **ULID IDs**: Time-sortable, 26-character unique identifiers - 🔖 **ULID IDs**: Time-sortable, 26-character unique identifiers
- 🔍 **Search**: Fast content-based search - 🔍 **Search**: Fast content-based search
- 📝 **CRUD Operations**: Complete memory management
### Layer 2: AI Memory
- 🧠 **AI Interpretation**: Claude interprets and evaluates memories
- 📊 **Priority Scoring**: Importance ratings (0.0-1.0)
- 🎯 **Smart Storage**: Memory + evaluation in one step
### Layer 3: Personality Analysis
- 🔬 **Big Five Model**: Scientifically validated personality assessment
- 📈 **Pattern Recognition**: Analyzes memory patterns to build user profile
- 💾 **Historical Tracking**: Save and compare analyses over time
### General
- 🛠️ **MCP Integration**: Works seamlessly with Claude Code - 🛠️ **MCP Integration**: Works seamlessly with Claude Code
- 🧪 **Well-tested**: Comprehensive test coverage - 🧪 **Well-tested**: Comprehensive test coverage
- 🚀 **Simple & Fast**: Minimal dependencies, pure Rust
## Quick Start ## Quick Start
@@ -47,30 +62,87 @@ aigpt stats
claude mcp add aigpt /path/to/aigpt/target/release/aigpt server claude mcp add aigpt /path/to/aigpt/target/release/aigpt server
``` ```
Then use in Claude Code: ## MCP Tools
- "Remember that tomorrow will be sunny"
- "Search for weather information" ### Layer 1: Basic Memory (6 tools)
- "Show all my memories" - `create_memory` - Simple memory creation
- `get_memory` - Retrieve by ID
- `list_memories` - List all memories
- `search_memories` - Content-based search
- `update_memory` - Update existing memory
- `delete_memory` - Remove memory
### Layer 2: AI Memory (1 tool)
- `create_ai_memory` - Create with AI interpretation and priority score
### Layer 3: Personality Analysis (2 tools)
- `save_user_analysis` - Save Big Five personality analysis
- `get_user_analysis` - Retrieve latest personality profile
## Usage Examples in Claude Code
### Layer 1: Simple Memory
```
Remember that the project deadline is next Friday.
```
Claude will use `create_memory` automatically.
### Layer 2: AI Memory with Evaluation
```
create_ai_memory({
content: "Designed a new microservices architecture",
ai_interpretation: "Shows technical creativity and strategic thinking",
priority_score: 0.85
})
```
### Layer 3: Personality Analysis
```
# After accumulating memories, analyze personality
save_user_analysis({
openness: 0.8,
conscientiousness: 0.7,
extraversion: 0.4,
agreeableness: 0.65,
neuroticism: 0.3,
summary: "High creativity and planning ability, introverted personality"
})
# Retrieve analysis
get_user_analysis()
```
## Big Five Personality Traits
- **Openness**: Creativity, curiosity, openness to new experiences
- **Conscientiousness**: Organization, planning, reliability
- **Extraversion**: Social energy, assertiveness, outgoingness
- **Agreeableness**: Cooperation, empathy, kindness
- **Neuroticism**: Emotional stability (low = stable, high = sensitive)
Scores range from 0.0 to 1.0, where higher scores indicate stronger trait expression.
## Storage Location ## Storage Location
Memories are stored in: `~/.config/syui/ai/gpt/memory.db` All data stored in: `~/.config/syui/ai/gpt/memory.db`
## Architecture ## Architecture
This is **Layer 1** of a planned multi-layer system: Multi-layer system design:
- **Layer 1** (Current): Pure memory storage - **Layer 1** ✅ Complete: Pure memory storage
- **Layer 2** (Planned): AI interpretation with priority scoring - **Layer 2** ✅ Complete: AI interpretation with priority scoring
- **Layer 3** (Planned): User evaluation and diagnosis - **Layer 3** ✅ Complete: Big Five personality analysis
- **Layer 4** (Planned): Game systems and companion features - **Layer 4** 🔵 Planned: Game systems and companion features
- **Layer 5** 🔵 Future: Distribution and sharing
See [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md) for details. See [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md) for details.
## Documentation ## Documentation
- [Layer 1 Details](docs/LAYER1.md) - Technical details of current implementation
- [Architecture](docs/ARCHITECTURE.md) - Multi-layer system design - [Architecture](docs/ARCHITECTURE.md) - Multi-layer system design
- [Layer 1 Details](docs/LAYER1.md) - Technical details of memory storage
- [Old Versions](docs/archive/old-versions/) - Previous documentation
## Development ## Development
@@ -85,6 +157,10 @@ cargo build --release
RUST_LOG=debug aigpt server RUST_LOG=debug aigpt server
``` ```
## Design Philosophy
**"AI evolves, tools don't"** - This tool provides simple, reliable storage while AI (Claude) handles interpretation, evaluation, and analysis. The tool focuses on being maintainable and stable.
## License ## License
MIT MIT

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@@ -12,29 +12,29 @@ aigptは、独立したレイヤーを積み重ねる設計です。各レイヤ
``` ```
┌─────────────────────────────────────────┐ ┌─────────────────────────────────────────┐
│ Layer 5: Distribution & Sharing │ Future │ Layer 5: Distribution & Sharing │ 🔵 Future
│ (Game streaming, public/private) │ │ (Game streaming, public/private) │
├─────────────────────────────────────────┤ ├─────────────────────────────────────────┤
│ Layer 4b: AI Companion │ Future │ Layer 4b: AI Companion │ 🔵 Planned
│ (Romance system, personality growth) │ │ (Romance system, personality growth) │
├─────────────────────────────────────────┤ ├─────────────────────────────────────────┤
│ Layer 4a: Game Systems │ Future │ Layer 4a: Game Systems │ 🔵 Planned
│ (Ranking, rarity, XP, visualization) │ │ (Ranking, rarity, XP, visualization) │
├─────────────────────────────────────────┤ ├─────────────────────────────────────────┤
│ Layer 3: User Evaluation │ Future │ Layer 3: User Evaluation │ ✅ Complete
│ (Personality diagnosis from patterns) │ (Big Five personality analysis)
├─────────────────────────────────────────┤ ├─────────────────────────────────────────┤
│ Layer 2: AI Memory │ Future │ Layer 2: AI Memory │ ✅ Complete
│ (Claude interpretation, priority_score)│ │ (Claude interpretation, priority_score)│
├─────────────────────────────────────────┤ ├─────────────────────────────────────────┤
│ Layer 1: Pure Memory Storage │ ✅ Current │ Layer 1: Pure Memory Storage │ ✅ Complete
│ (SQLite, ULID, CRUD operations) │ │ (SQLite, ULID, CRUD operations) │
└─────────────────────────────────────────┘ └─────────────────────────────────────────┘
``` ```
## Layer 1: Pure Memory Storage (Current) ## Layer 1: Pure Memory Storage
**Status**: ✅ **Implemented & Tested** **Status**: ✅ **Complete**
### Purpose ### 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。 正確なデータの保存と参照。シンプルで信頼できる基盤。
@@ -86,16 +86,16 @@ src/
--- ---
## Layer 2: AI Memory (Planned) ## Layer 2: AI Memory
**Status**: 🔵 **Planned** **Status**: **Complete**
### Purpose ### Purpose
Claudeが記憶内容を解釈し、重要度を評価。 Claudeが記憶内容を解釈し、重要度を評価。人間の記憶プロセス(記憶と同時に評価)を模倣。
### Extended Data Model ### Extended Data Model
```rust ```rust
pub struct AIMemory { pub struct Memory {
// Layer 1 fields // Layer 1 fields
pub id: String, pub id: String,
pub content: String, pub content: String,
@@ -103,63 +103,75 @@ pub struct AIMemory {
pub updated_at: DateTime<Utc>, pub updated_at: DateTime<Utc>,
// Layer 2 additions // Layer 2 additions
pub interpreted_content: String, // Claude's interpretation pub ai_interpretation: Option<String>, // Claude's interpretation
pub priority_score: f32, // 0.0 - 1.0 pub priority_score: Option<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) ### MCP Tools
- `create_memory_with_ai` - Create with Claude interpretation - `create_ai_memory` - Create memory with AI interpretation and priority score
- `reinterpret_memory` - Re-evaluate existing memory - `content`: Memory content
- `get_high_priority` - Get memories above threshold - `ai_interpretation`: Optional AI interpretation
- `priority_score`: Optional priority (0.0-1.0)
### Implementation Strategy ### Philosophy
- Feature flag: `--features ai-memory` "AIは進化しますが、ツールは進化しません" - AIが判断し、ツールは記録のみ。
- Backward compatible with Layer 1
### Implementation
- Backward compatible with Layer 1 (Optional fields)
- Automatic schema migration from Layer 1
- Claude Code does interpretation (no external API) - Claude Code does interpretation (no external API)
--- ---
## Layer 3: User Evaluation (Planned) ## Layer 3: User Evaluation
**Status**: 🔵 **Planned** **Status**: **Complete**
### Purpose ### Purpose
メモリパターンからユーザーの性格を診断 Layer 2のメモリパターンからユーザーの性格を分析。Big Five心理学モデルを使用
### Diagnosis Types ### Data Model
```rust ```rust
pub enum DiagnosisType { pub struct UserAnalysis {
Innovator, // 革新者 pub id: String,
Philosopher, // 哲学者 pub openness: f32, // 0.0-1.0: 創造性、好奇心
Pragmatist, // 実用主義者 pub conscientiousness: f32, // 0.0-1.0: 計画性、信頼性
Explorer, // 探検家 pub extraversion: f32, // 0.0-1.0: 外向性、社交性
Protector, // 保護者 pub agreeableness: f32, // 0.0-1.0: 協調性、共感性
Visionary, // 未来志向 pub neuroticism: f32, // 0.0-1.0: 神経質さ(低い=安定)
pub summary: String, // 分析サマリー
pub analyzed_at: DateTime<Utc>,
} }
``` ```
### Analysis ### Big Five Model
- Memory content patterns 心理学で最も信頼性の高い性格モデルOCEAN
- Priority score distribution - **O**penness: 新しい経験への開かれさ
- Creation frequency - **C**onscientiousness: 誠実性、計画性
- Topic diversity - **E**xtraversion: 外向性
- **A**greeableness: 協調性
- **N**euroticism: 神経質さ
### MCP Tools (Additional) ### Analysis Process
- `diagnose_user` - Run personality diagnosis 1. Layer 2メモリを蓄積
- `get_user_profile` - Get analysis summary 2. AIがパターンを分析活動の種類、優先度の傾向など
3. Big Fiveスコアを推測
4. 分析結果を保存
### MCP Tools
- `save_user_analysis` - Save Big Five personality analysis
- All 5 traits (0.0-1.0) + summary
- `get_user_analysis` - Get latest personality profile
### Storage
- SQLite table: `user_analyses`
- Historical tracking: Compare analyses over time
- Helper methods: `dominant_trait()`, `is_high()`
--- ---
## Layer 4a: Game Systems (Planned) ## Layer 4a: Game Systems
**Status**: 🔵 **Planned** **Status**: 🔵 **Planned**
@@ -184,7 +196,7 @@ pub struct GameMemory {
--- ---
## Layer 4b: AI Companion (Planned) ## Layer 4b: AI Companion
**Status**: 🔵 **Planned** **Status**: 🔵 **Planned**
@@ -236,21 +248,27 @@ pub struct Companion {
- [x] Tests - [x] Tests
- [x] Documentation - [x] Documentation
### Phase 2: Layer 2 (Next) ### Phase 2: Layer 2 ✅ (Complete)
- [ ] Add AI interpretation fields to schema - [x] Add AI interpretation fields to schema
- [ ] Implement priority scoring logic - [x] Implement priority scoring logic
- [ ] Create `create_memory_with_ai` tool - [x] Create `create_ai_memory` tool
- [ ] Update MCP server - [x] Update MCP server
- [ ] Write tests for AI features - [x] Automatic schema migration
- [x] Backward compatibility
### Phase 3: Layers 3-4 (Future) ### Phase 3: Layer 3 ✅ (Complete)
- [ ] User diagnosis system - [x] Big Five personality model
- [ ] Game mechanics - [x] UserAnalysis data structure
- [ ] Companion system - [x] user_analyses table
- [x] `save_user_analysis` tool
- [x] `get_user_analysis` tool
- [x] Historical tracking support
### Phase 4: Layer 5 (Future) ### Phase 4: Layers 4-5 (Next)
- [ ] Sharing mechanisms - [ ] Game mechanics (Layer 4a)
- [ ] Public/private modes - [ ] Companion system (Layer 4b)
- [ ] Sharing mechanisms (Layer 5)
- [ ] Public/private modes (Layer 5)
## Design Principles ## Design Principles
@@ -330,5 +348,5 @@ src/
--- ---
**Version**: 0.2.0 **Version**: 0.2.0
**Last Updated**: 2025-11-05 **Last Updated**: 2025-11-06
**Current Layer**: 1 **Current Status**: Layers 1-3 Complete, Layer 4 Planned

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# 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<Utc>,
pub updated_at: DateTime<Utc>,
}
```
### 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<Utc>,
pub updated_at: DateTime<Utc>,
// 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<Utc>,
}
```
---
## 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<String>,
pub last_interaction: DateTime<Utc>,
}
```
---
## 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

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# aigpt
Simple memory storage for Claude with MCP support.
**Layer 1: Pure Memory Storage** - A clean, SQLite-based memory system with ULID identifiers.
## Features
- 🗄️ **SQLite Storage**: Reliable database with ACID guarantees
- 🔖 **ULID IDs**: Time-sortable, 26-character unique identifiers
- 🔍 **Search**: Fast content-based search
- 🛠️ **MCP Integration**: Works seamlessly with Claude Code
- 🧪 **Well-tested**: Comprehensive test coverage
## Quick Start
### Installation
```bash
# Build
cargo build --release
# Install (optional)
cp target/release/aigpt ~/.cargo/bin/
```
### CLI Usage
```bash
# Create a memory
aigpt create "Remember this information"
# List all memories
aigpt list
# Search memories
aigpt search "keyword"
# Show statistics
aigpt stats
```
### MCP Integration with Claude Code
```bash
# Add to Claude Code
claude mcp add aigpt /path/to/aigpt/target/release/aigpt server
```
Then use in Claude Code:
- "Remember that tomorrow will be sunny"
- "Search for weather information"
- "Show all my memories"
## Storage Location
Memories are stored in: `~/.config/syui/ai/gpt/memory.db`
## Architecture
This is **Layer 1** of a planned multi-layer system:
- **Layer 1** (Current): Pure memory storage
- **Layer 2** (Planned): AI interpretation with priority scoring
- **Layer 3** (Planned): User evaluation and diagnosis
- **Layer 4** (Planned): Game systems and companion features
See [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md) for details.
## Documentation
- [Layer 1 Details](docs/LAYER1.md) - Technical details of current implementation
- [Architecture](docs/ARCHITECTURE.md) - Multi-layer system design
## Development
```bash
# Run tests
cargo test
# Build for release
cargo build --release
# Run with verbose logging
RUST_LOG=debug aigpt server
```
## License
MIT
## Author
syui