• ✔️ Learn how to build a RAG application in JavaScript, and use an intelligent agent that discerns and selects from multiple data sources to answer your queries.
  • ✔️ Build a full-stack web app with an interactive frontend component that interacts and chats with your data.
  • ✔️ Learn how to persist your data, enable chatting with your data and make streaming responses possible, all implemented using the create-llama command-line tool.


What you’ll learn in this course

Get started building full-stack RAG web applications. This course introduces the basics of Retrieval Augment Generation (RAG), including its practical implementation with JavaScript. You’ll assemble an intelligent agent capable of running its own queries. This course will guide you through the process of building a full-stack JavaScript web application, from the API server to a React component that queries your data. You’ll also learn to develop persistent chat that streams your answers to an interactive front-end in real time.

Learn from Laurie Voss, VP of developer relations at LlamaIndex, web developer and the co-founder of npm, the central registry of JavaScript packages.

In this course you will learn:

  • Learn to build a RAG application in JavaScript for querying your own data.
  • Develop tools to interact with multiple data sources using a router query engine that intelligently selects the right tool for your queries.
  • Build a full-stack web application step by step, starting with a backend web app and progressing to an interactive React frontend that calls your API to display query results.
  • Learn about production-ready techniques, including persisting your data, chatting with your data, and streaming responses for multiple queries.
  • Create a user-friendly web app that can chat with data using the create-llama command line tool from LlamaIndex.

Start building RAG web applications in JavaScript that allow you to interact with your data using LlamaIndex.


Who should join?

Anyone who has basic Javascript knowledge who wants to explore RAG application development and to quickly build a full-stack web application using LlamaIndex!