LLM applications typically remain stateless, forgetting user context between sessions. While RAG helps retrieve external data, it struggles with evolving user preferences and long-term memory. Two open-source libraries address this gap: mem0 provides explicit, developer-controlled memory items through APIs with fine-grained lifecycle management, while Supermemory automatically maintains user profiles and injects relevant context. The article demonstrates integrating both libraries into a Next.js chat application using Vercel's AI SDK, showing how each handles memory storage, retrieval, and updates differently. Choosing between them depends on whether you prioritize manual control and observability or automated context management.
Table of contents
How LLMs store contextThe emergence of Retrieval-Augmented Generation (RAG)How memory is different from RAGWhy do in-house solutions fail?Introduction to mem0Introduction to SupermemoryWhere they differHands-on: Integration with Vercel AI SDKConclusionSort: