MemEngine: A Unified and Modular Library for Developing Advanced Memory of LLM-based Agents

Recently, large language model based (LLM-based) agents have been widely applied across various fields. As a critical part, their memory capabilities have captured significant interest from both industrial and academic communities. Despite the proposal of many advanced memory models in recent research, however, there remains a lack of unified implementations under a general framework. To address this issue, we develop a unified and modular library for developing advanced memory models of LLM-based agents, called MemEngine. Based on our framework, we implement abundant memory models from recent research works. Additionally, our library facilitates convenient and extensible memory development, and offers user-friendly and pluggable memory usage. For benefiting our community, we have made our project publicly available atthis https URL.

@article{zhang2025_2505.02099,
  title={ MemEngine: A Unified and Modular Library for Developing Advanced Memory of LLM-based Agents },
  author={ Zeyu Zhang and Quanyu Dai and Xu Chen and Rui Li and Zhongyang Li and Zhenhua Dong },
  journal={arXiv preprint arXiv:2505.02099},
  year={ 2025 }
}