modbender SimpleMem Skill
Integrates SimpleMem: Efficient Lifelong Memory for LLM Agents into OpenClaw.
What it does
SimpleMem provides semantic memory compression and retrieval for agents:
- Store: Compresses interactions into compact memory units
- Synthesize: Merges related memories on-the-fly
- Retrieve: Intent-aware planning for efficient context retrieval
Installation
# Install Python dependency
pip install simplemem
# Or via repo
git clone https://github.com/aiming-lab/SimpleMem.git
cd SimpleMem
pip install -r requirements.txt
Configuration (Optional - Full Features)
For full SimpleMem features, set your OpenAI API key:
$env:OPENAI_API_KEY = "your-openai-key"
Without API key: Uses JSON fallback (basic keyword search) With API key: Uses full SimpleMem with semantic embeddings
Usage
PowerShell Script
# Agregar memoria
.\simplemem.ps1 -Action add -Content "El usuario prefiere cafe con leche de avena"
# Buscar memorias
.\simplemem.ps1 -Action search -Query "cafe"
# Ver estadisticas
.\simplemem.ps1 -Action stats
Python API
from simplemem import SimpleMemSystem, set_config, SimpleMemConfig
# With API key (full features)
config = SimpleMemConfig()
config.openai_api_key = "your-key"
set_config(config)
system = SimpleMemSystem()
# Add memory
system.add("User preference: coffee with oat milk", user_id="user1")
# Retrieve
results = system.retrieve("What does user like?", user_id="user1")
Key Features
- Cross-session memory: Persistent across conversations (64% better than Claude-Mem)
- Semantic compression: 43.24% F1 on LoCoMo benchmark
- Fast retrieval: 388ms average retrieval time
- Multi-index: Semantic + Lexical + Symbolic layers
- Fallback: JSON-based storage when no API key available
Files
simplemem.py- Main Python wrappersimplemem.ps1- PowerShell CLI scriptdata/- Storage directory (created on first use)