Unlocking Data with Generative AI and RAG

11

Using LangChain to Get More from RAG

We have mentioned LangChain several times already, and we have shown you a lot of LangChain code, including code that implements the LangChain-specific language: LangChain Expression Language (LCEL). Now that you are familiar with different ways to implement retrieval-augmented generation (RAG) with LangChain, we thought now would be a good time to dive more into the various capabilities of LangChain that you can use to make your RAG pipeline better.

In this chapter, we explore lesser-known but highly important components in LangChain that can enhance a RAG application. We will cover the following:

• Document loaders for loading and processing documents from different sources
• Text splitters for dividing ...