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BytesAgain β€Ί Skills β€Ί Simplemem
πŸ¦€ ClawHub

Simplemem

by @nantes

Efficient Lifelong Memory for LLM Agents - semantic compression, cross-session memory, and intent-aware retrieval

Versionv1.0.1
Downloads1,411
Stars⭐ 2
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TERMINAL
clawhub install simplemem

πŸ“– About This Skill

name: simplemem version: 1.0.0 description: Efficient Lifelong Memory for LLM Agents - semantic compression, cross-session memory, and intent-aware retrieval metadata: {"openclaw": {"emoji": "🧠", "requires": {"bins": ["python"], "env": ["OPENAI_API_KEY"]}, "primaryEnv": "OPENAI_API_KEY", "homepage": "https://github.com/aiming-lab/SimpleMem"}}

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 wrapper
  • simplemem.ps1 - PowerShell CLI script
  • data/ - Storage directory (created on first use)

    • Credits

  • Repo: https://github.com/aiming-lab/SimpleMem
  • Paper: https://arxiv.org/abs/2601.02553
  • Discord: https://discord.gg/KA2zC32M

    • πŸ’‘ Examples

    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")