In our third Python + AI session, we'll explore one of the most popular techniques used with LLMs: Retrieval Augmented Generation.

RAG is an approach that sends context to the LLM so that it can provide well-grounded answers for a particular domain.

The RAG approach can be used with many kinds of data sources like CSVs, webpages, documents, databases.
In this session, we'll walk through RAG flows in Python, starting with a simple flow and culminating in a full-stack RAG application based on Azure AI Search.