ContextWeaver: Selective and Dependency-Structured Memory Construction for LLM Agents
ContextWeaver is a memory framework for LLM agents that organizes interaction history into a reasoning step graph to select only relevant context for future actions. It uses dependency-based construction, compact summaries of reasoning paths, and execution feedback to preserve crucial information within token limits. This method improves agent performance on complex tasks by focusing on logical dependencies.