Updated README.md and ARCHITECTURE.md to document Layer 3.5 (Integrated Profile) implementation. README.md changes: - Updated header to reflect Layers 1-3.5 complete - Added Layer 3.5 feature section - Added get_profile to MCP tools list - Added Layer 3.5 usage examples with sample output - Updated architecture overview with Layer 3.5 - Added design philosophy explanation ARCHITECTURE.md changes: - Updated layer overview diagram with Layer 3.5 - Added comprehensive Layer 3.5 section: - Purpose and problem solved - Data model (UserProfile, TraitScore) - Integration logic (5 extraction methods) - Caching strategy with update triggers - Usage patterns for AI - Design philosophy - Updated implementation strategy (Phase 3.5) - Updated code organization to reflect current structure - Updated version metadata Layer 3.5 provides unified user profile by integrating Layers 1-3 data, implementing "internal complexity, external simplicity" design philosophy.
5.8 KiB
5.8 KiB
aigpt
AI memory system with psychological analysis for Claude via MCP.
Current: Layers 1-3.5 Complete - Memory storage, AI interpretation, personality analysis, and integrated profile.
Features
Layer 1: Pure Memory Storage
- 🗄️ SQLite Storage: Reliable database with ACID guarantees
- 🔖 ULID IDs: Time-sortable, 26-character unique identifiers
- 🔍 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
Layer 3.5: Integrated Profile
- 🎯 Essential Summary: Unified view of personality, interests, and values
- 🤖 AI-Optimized: Primary tool for AI to understand the user
- ⚡ Smart Caching: Auto-updates only when necessary
- 🔍 Flexible Access: Detailed data still accessible when needed
General
- 🛠️ MCP Integration: Works seamlessly with Claude Code
- 🧪 Well-tested: Comprehensive test coverage
- 🚀 Simple & Fast: Minimal dependencies, pure Rust
Quick Start
Installation
# Build
cargo build --release
# Install (optional)
cp target/release/aigpt ~/.cargo/bin/
CLI Usage
# 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
# Add to Claude Code
claude mcp add aigpt /path/to/aigpt/target/release/aigpt server
MCP Tools
Layer 1: Basic Memory (6 tools)
create_memory- Simple memory creationget_memory- Retrieve by IDlist_memories- List all memoriessearch_memories- Content-based searchupdate_memory- Update existing memorydelete_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 analysisget_user_analysis- Retrieve latest personality profile
Layer 3.5: Integrated Profile (1 tool)
get_profile- Primary tool: Get integrated user profile with essential summary
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()
Layer 3.5: Integrated Profile (Recommended)
# Get essential user profile - AI's primary tool
get_profile()
# Returns:
{
"dominant_traits": [
{"name": "openness", "score": 0.8},
{"name": "conscientiousness", "score": 0.7},
{"name": "extraversion", "score": 0.4}
],
"core_interests": ["Rust", "architecture", "design", "system", "memory"],
"core_values": ["simplicity", "efficiency", "maintainability"],
"key_memory_ids": ["01H...", "01H...", ...],
"data_quality": 0.85
}
Usage Pattern:
- AI normally uses
get_profile()to understand the user - For specific details, AI can call
get_memory(id),list_memories(), etc. - Profile auto-updates when needed (10+ memories, new analysis, or 7+ days)
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
All data stored in: ~/.config/syui/ai/gpt/memory.db
Architecture
Multi-layer system design:
- Layer 1 ✅ Complete: Pure memory storage
- Layer 2 ✅ Complete: AI interpretation with priority scoring
- Layer 3 ✅ Complete: Big Five personality analysis
- Layer 3.5 ✅ Complete: Integrated profile (unified summary)
- Layer 4 🔵 Planned: Game systems and companion features
- Layer 5 🔵 Future: Distribution and sharing
Design Philosophy: "Internal complexity, external simplicity"
- Layers 1-3 handle detailed data collection and analysis
- Layer 3.5 provides a simple, unified view for AI consumption
- Detailed data remains accessible when needed
See docs/ARCHITECTURE.md for details.
Documentation
- Architecture - Multi-layer system design
- Layer 1 Details - Technical details of memory storage
- Old Versions - Previous documentation
Development
# Run tests
cargo test
# Build for release
cargo build --release
# Run with verbose logging
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
MIT
Author
syui