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LightMem

ICLR 2026 memory framework for LLMs/agents: LLMLingua pre-compression, topic segmentation and offline memory updates — leading LoCoMo/LongMemEval results at lower token cost.

1,019 92 Python MITupdated 3 days ago
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Curator's take

Research-grade memory with receipts: reproduction scripts for LoCoMo/LongMemEval plus a baseline harness that benchmarks Mem0, A-MEM and LangMem side by side — useful even if you adopt none of them. The compression-first pipeline (LLMLingua before storage) is the differentiating idea. Expect paper-adjacent ergonomics: manual model downloads and config dicts, not a polished product.

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README.md

LightMem: Lightweight and Efficient Memory-Augmented Generation

arXiv GitHub Stars License: MIT Last Commit PRs Welcome

⭐ If you like our project, please give us a star on GitHub for the latest updates!

LightMem is a lightweight and efficient memory management framework designed for Large Language Models and AI Agents. It provides a simple yet powerful memory storage, retrieval, and update mechanism to help you quickly build intelligent applications with long-term memory capabilities.

  • 🚀 Lightweight & Efficient
    Minimalist design with minimal resource consumption and fast response times

  • 🎯 Easy to Use
    Simple API design - integrate into your application with just a few lines of code

  • 🔌 Flexible & Extensible
    Modular architecture supporting custom storage engines and retrieval strategies

  • 🌐 Broad Compatibility
    Support for cloud APIs (OpenAI, DeepSeek) and local models (Ollama, vLLM, etc.)

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