Clawbrain

Claw Brain Skill 🧠

Personal AI Memory System with Soul, Bonding, and Learning for OpenClaw/ClawDBot.

Auto-Refresh on Restart: ClawBrain automatically refreshes memory when the service restarts.

Features

• 🎭 Soul/Personality - 6 evolving traits (humor, empathy, curiosity, creativity, helpfulness, honesty)
• 👤 User Profile - Learns user preferences, interests, communication style
• 💭 Conversation State - Real-time mood detection and context tracking
• 📚 Learning Insights - Continuously learns from interactions and corrections
• 🧠 get_full_context() - Everything for personalized responses
• 🔄 Auto-Refresh - Automatically refreshes memory on service restart
• 🔐 Encrypted Secrets - Store API keys and credentials securely

Quick Install

From PyPI (Recommended)

# Install with all features
pip install clawbrain[all]

# Run interactive setup
clawbrain setup

# Backup your encryption key (IMPORTANT!)
clawbrain backup-key --all

# Restart your service
sudo systemctl restart clawdbot  # or openclaw

The setup command will:

1. Detect your platform (ClawdBot or OpenClaw)
2. Generate a secure encryption key
3. Install the startup hook automatically
4. Test the installation

Alternative: From Source

# Clone to your skills directory
cd ~/.openclaw/skills  # or ~/clawd/skills or ~/.clawdbot/skills
git clone https://github.com/clawcolab/clawbrain.git
cd clawbrain
pip install -e .[all]
clawbrain setup

Configuration

After installation, optionally configure your agent ID:

# Create systemd drop-in config
sudo mkdir -p /etc/systemd/system/clawdbot.service.d  # or openclaw.service.d

sudo tee /etc/systemd/system/clawdbot.service.d/brain.conf << EOF
[Service]
Environment="BRAIN_AGENT_ID=your-agent-name"
# Optional: PostgreSQL (for production)
# Environment="BRAIN_POSTGRES_HOST=localhost"
# Environment="BRAIN_POSTGRES_PASSWORD=your-password"
# Optional: Redis (for caching)
# Environment="BRAIN_REDIS_HOST=localhost"
EOF

sudo systemctl daemon-reload
sudo systemctl restart clawdbot  # or openclaw

Environment Variables

How It Works

On Service Startup

1. Hook triggers on gateway:startup event
2. Detects storage backend (SQLite/PostgreSQL)
3. Loads memories for the configured BRAIN_AGENT_ID
4. Injects context into agent bootstrap

On /new Command

1. Hook triggers on command:new event
2. Saves current session summary to memory
3. Clears session state for fresh start

Storage Priority

1. PostgreSQL - If available and configured
2. SQLite - Fallback, zero configuration needed

Encrypted Secrets

ClawBrain supports encrypting sensitive data like API keys and credentials.

Setup:

# Run setup to generate encryption key
clawbrain setup

# Backup your key (IMPORTANT!)
clawbrain backup-key --all

Usage:

# Store encrypted secret
brain.remember(
    agent_id="assistant",
    memory_type="secret",  # Memory type 'secret' triggers encryption
    content="sk-1234567890abcdef",
    key="openai_api_key"
)

# Retrieve and automatically decrypt
secrets = brain.recall(agent_id="assistant", memory_type="secret")
api_key = secrets[0].content  # Automatically decrypted

Key Management CLI:

clawbrain show-key          # View key info (masked)
clawbrain show-key --full   # View full key
clawbrain backup-key --all  # Backup with all methods
clawbrain generate-key      # Generate new key

⚠️ Important: Backup your encryption key! Lost keys = lost encrypted data.

CLI Commands

ClawBrain includes a command-line interface:

Hooks

Development Installation

For development or manual installation:

# Clone to your skills directory
cd ~/.openclaw/skills  # or ~/clawd/skills or ~/.clawdbot/skills
git clone https://github.com/clawcolab/clawbrain.git
cd clawbrain
./install.sh

Python API

For direct Python usage (outside ClawdBot/OpenClaw):

from clawbrain import Brain

brain = Brain()

Methods

get_full_context()

context = brain.get_full_context(
    session_key="telegram_12345",  # Unique session ID
    user_id="username",              # User identifier
    agent_id="assistant",          # Bot identifier
    message="Hey, how's it going?" # Current message
)

Returns:

{
    "user_profile": {...},        # User preferences, interests
    "mood": {"mood": "happy", ...},  # Current mood
    "intent": "question",         # Detected intent
    "memories": [...],            # Relevant memories
    "personality": "...",         # Personality guidance
    "suggested_responses": [...]  # Response suggestions
}

detect_user_mood()

mood = brain.detect_user_mood("I'm so excited about this!")
# Returns: {"mood": "happy", "confidence": 0.9, "emotions": ["joy", "anticipation"]}

detect_user_intent()

intent = brain.detect_user_intent("How does AI work?")
# Returns: "question"

intent = brain.detect_user_intent("Set a reminder for 3pm")
# Returns: "command"

intent = brain.detect_user_intent("I had a great day today")
# Returns: "casual"

Example: Full Integration

import sys
sys.path.insert(0, "ClawBrain")

from clawbrain import Brain

class AssistantBot:
    def __init__(self):
        self.brain = Brain()
    
    def handle_message(self, message, chat_id):
        # Get context
        context = self.brain.get_full_context(
            session_key=f"telegram_{chat_id}",
            user_id=str(chat_id),
            agent_id="assistant",
            message=message
        )
        
        # Generate response using context
        response = self.generate_response(context)
        
        # Learn from interaction
        self.brain.learn_user_preference(
            user_id=str(chat_id),
            pref_type="interest",
            value="AI"
        )
        
        return response
    
    def generate_response(self, context):
        # Use user preferences
        name = context["user_profile"].name or "there"
        mood = context["mood"]["mood"]
        
        # Personalized response
        if mood == "frustrated":
            return f"Hey {name}, I'm here to help. Let me assist you."
        else:
            return f"Hi {name}! How can I help you today?"
    
    def shutdown(self):
        self.brain.close()

Storage Backends

SQLite (Default - Zero Setup)

No configuration needed. Data stored in local SQLite database.

brain = Brain({"storage_backend": "sqlite"})

Best for: Development, testing, single-user deployments

PostgreSQL + Redis (Production)

Requires PostgreSQL and Redis servers.

brain = Brain()  # Auto-detects

Requirements:

• PostgreSQL 14+
• Redis 6+
• Python packages: psycopg2-binary, redis

pip install psycopg2-binary redis

Best for: Production, multi-user, high-concurrency

Files

• clawbrain.py - Main Brain class with all features
• __init__.py - Module exports
• SKILL.md - This documentation
• skill.json - ClawdHub metadata
• README.md - Quick start guide

Troubleshooting

ImportError: No module named 'clawbrain'

# Ensure ClawBrain folder is in your path
sys.path.insert(0, "ClawBrain")

PostgreSQL connection failed

# Check environment variables
echo $POSTGRES_HOST
echo $POSTGRES_PORT

# Verify PostgreSQL is running
pg_isready -h $POSTGRES_HOST -p $POSTGRES_PORT

Redis connection failed

# Check Redis is running
redis-cli ping

Using SQLite (fallback)

If PostgreSQL/Redis are unavailable, Claw Brain automatically falls back to SQLite:

brain = Brain({"storage_backend": "sqlite"})

Learn More

• Repository: https://github.com/clawcolab/clawbrain
• README: See README.md for quick start
• Issues: Report bugs at GitHub Issues