[this guide](https://python.langchain.com/docs/tutorials/rag/#query-analysis): LLM should read this page when: 1) Building a question-answering application over unstructured data 2) Learning about Retrieval Augmented Generation (RAG) architectures 3) Indexing data for use with LLMs 'This tutorial covers building a Retrieval Augmented Generation (RAG) application that can answer questions based on ingested data. It walks through loading data, chunking it, embedding and storing it in a vector store, retrieving relevant chunks for a given query, and generating an answer using an LLM. It also shows how to incorporate query analysis for improved retrieval.'

