darks0l/remem
🏗️ Frameworkdarks0l
Persistent, queryable semantic memory layer for AI agents with multi-agent scoping and layered storage.
Remem addresses the critical challenge of long-term state management in AI agents. Built with TypeScript, it serves as a robust memory layer that bridges the gap between ephemeral LLM context windows and persistent storage. The architecture supports layered storage, allowing developers to organize information by relevance or lifespan. Key technical innovations include advanced semantic recall, which enables agents to perform vector-based searches to retrieve contextually relevant information from their history. It also features snapshot capabilities, allowing for state versioning and easy recovery. With built-in multi-agent scoping, Remem facilitates collaborative environments where multiple agents can interact with shared memory spaces while maintaining data integrity. The system is designed for flexibility, supporting both SQLite for lightweight deployments and PostgreSQL for production-grade, scalable applications, making it a versatile tool for developers building sophisticated, stateful AI agents.
💡Highlights
- ├─Semantic recall via vector search
- ├─Multi-agent scoping support
- └─SQLite and PostgreSQL backends
🎯For
- ├─AI Engineers
- └─Backend Developers