How to Build an EverMem-Style Persistent AI Agent OS with Hierarchical Memory, FAISS Vector Retrieval, SQLite Storage, and Automated Memory Consolidation

This tutorial demonstrates building an EverMem-style persistent AI agent OS with hierarchical memory architecture. It combines short-term conversational context with long-term vector memory using FAISS for semantic retrieval, enabling agents to access relevant historical information before generating responses. SQLite stores structured metadata including timestamps and importance scores, implementing automated memory consolidation for improved context awareness and decision-making.