Download
MemoryOS is an open-source framework designed to provide a structured memory management system for AI agents and large language model applications. The project addresses one of the major limitations of modern language models: their inability to maintain long-term context beyond the limits of their prompt window. MemoryOS introduces a hierarchical memory architecture inspired by operating system memory management principles, allowing agents to store, update, retrieve, and generate information from multiple layers of memory. These layers typically include short-term memory for immediate conversation context, mid-term memory for topic-level grouping, and long-term personal memory for persistent knowledge about users or tasks. The system dynamically updates and promotes information between these layers using structured algorithms that prioritize relevance and recency.
Features
- Hierarchical memory architecture including short-term, mid-term, and long-term memory
- Memory storage, updating, retrieval, and generation modules
- Dynamic memory promotion and summarization mechanisms
- Improved long-context reasoning for conversational AI systems
- Persistent personalization based on stored user information
- Integration with agent architectures and retrieval pipelines
Project Samples
