A-MEM: An Agentic Memory System for Enhanced LLM Agents
2025-03-03
Large Language Model (LLM) agents excel at complex tasks but need sophisticated memory systems to leverage past experiences. A-MEM introduces a novel agentic memory system dynamically organizing memories using Zettelkasten principles. It features intelligent indexing and linking, comprehensive note generation with structured attributes, and continuous memory evolution. Agent-driven decision-making ensures adaptive memory management. Experiments on six foundation models demonstrate superior performance compared to state-of-the-art baselines. This repository provides code to reproduce the results; for application, see the official implementation.