Retrieval-Augmented Generation (RAG) is a cutting-edge technique that enhances the capabilities of generative models by integrating external knowledge sources, leading to higher quality and reliability in generated content. LangChain is a powerful framework designed specifically for building and deploying robust language model applications. This tutorial series offers a comprehensive, step-by-step guide to help you implement RAG using LangChain. It starts with an introduction to the fundamental RAG process and gradually delves into areas like query transformation, document embedding, routing mechanisms, query construction, indexing strategies, retrieval techniques, and the generation stage. Ultimately, it integrates all these concepts into a practical scenario, showcasing the power and flexibility of RAG.