Summarizing https://www.anyscale.com/blog/a-comprehensive-guide-for-building-rag-based-llm-applications-part-1

Here's my try:

This guide provides an end-to-end tutorial on how to build RAG-based LLM applications for production, including scaling major workloads across multiple workers, evaluating different configurations, implementing LLM hybrid routing, serving the application in a highly scalable and available manner, and sharing the first and second order impacts of LLM applications on products. The guide covers the following topics:

* Extracting sections from ReadTheDocs documentation

* Splitting text into smaller chunks using RecursiveCharacterTextSplitter

* Loading data from ReadTheDocs using ReadTheDocsLoader

* Building RAG-based LLM applications with Langchain

* Evaluating different configurations for LLM applications

* Implementing LLM hybrid routing

* Serving the application in a highly scalable and available manner

* Sharing the first and second order impacts of LLM applications on products

This guide also provides an example function to chunk a sample section, which can be scaled at runtime by applying it to a larger dataset.