Agent Memory Compressor: Intelligent Memory Compression for Long-Running LLM Agents

A 10-turn agent session can easily accumulate 20,000+ tokens of raw history, leaving almost no room for the current task. Naive truncation drops older turns wholesale, including the decisions and discovered facts the agent needs to avoid repeating work. Developers need a principled way to compress history rather than discard it. Agent Memory Compressor is a Python library that implements an intelligent memory compression pipeline for long-running LLM agents. It combines importance-based scoring,