This lab provides hands-on experience with LiteLLM, an open-source AI gateway that centralizes and manages access to Large Language Models (LLMs). Throughout the five modules, you'll learn how to set up and use LiteLLM to control, monitor, and optimize your AI model interactions.

In this lab, we'll be focusing on the programatic steps of Retrieval Augmented Generation (RAG). First, we'll discuss data chunking, how we break down our documents. Then, we'll explore how these chunks become embeddings, numerical representations. Finally, we'll see how a vector database helps us efficiently retrieve this information.