Building Conversational AI: Mastering Memory in Custom RAG Systems

This article dives into how to create conversational interactions within a custom Retrieval-Augmented Generation (RAG) system, mirroring the chat-like behavior of tools like ChatGPT. It emphasizes the use of LangChain's Memory to remember past interactions, enabling more context-aware responses and a richer user experience. This approach opens up exciting possibilities for developers seeking to build highly customized and intelligent chatbots.

• •The article focuses on implementing a chat-like interface for custom RAG systems.
• •It uses LangChain's Memory to store and recall conversation history.
• •Redis is employed for storing and retrieving the conversation history.