Building RAG Apps with LlamaIndex and JavaScript Online Course

Building RAG Apps with LlamaIndex and JavaScript Online Course

This course teaches you how to develop Retrieval-Augmented Generation (RAG) applications using LlamaIndex and JavaScript. You’ll begin by setting up your environment with Node.js and OpenAI API keys before exploring LlamaIndex fundamentals like data ingestion, indexing, and querying. Through hands-on projects, you’ll build basic and custom RAG systems, query structured and unstructured data, and integrate them via an Express API. You’ll also tackle advanced scenarios such as handling PDFs, managing data persistence, and deploying production-ready applications. By the end, you’ll have built a full-stack Next.js chatbot app and gained the skills to create, customize, and deploy scalable RAG applications.

Who should take this Course?

The Building RAG Apps with LlamaIndex and JavaScript Online Course is ideal for JavaScript developers, AI enthusiasts, and software professionals who want to learn how to build Retrieval-Augmented Generation (RAG) applications. It is also valuable for students, researchers, and aspiring AI developers looking to integrate LlamaIndex with JavaScript to create intelligent, data-driven applications that leverage large language models effectively.

What you will learn

• Create RAG systems with LlamaIndex and JavaScript.
• Set up and configure a full development environment for RAG apps.
• Implement data ingestion and indexing techniques using LlamaIndex.
• Build complex LlamaIndex queries with custom data loaders and engines.
• Develop a full-stack chatbot with NextJS, LlamaIndex, and OpenAI.
• Deploy scalable RAG systems with persistent data for production use.

Course Outline 

Introduction

• Introduction
• Course Prerequisites & Who is This Course For?
• Course Structure
• PLEASE WATCH - What You'll Build in This Course

Development Environment Setup

• Setup Dev. Environment - NodeJS Instructions
• Setup OpenAI Account and the OpenAI API Key

LlamaIndex Deep Dive – Fundamentals

• Deep Dive into LlamaIndex and Key Features - Overview
• RAG Crash Course
• LlamaIndex Flow - Overview
• LlamaIndex - Data Ingestion, Indexing and Query Interface Overview
• Hands-on - Setup LlamaIndex Simple RAG System
• Summary

LlamaIndex Deep Dive - Main Concepts and Data Loaders

• LlamaIndex Core Concepts - Loaders Index
• The Querying Stage - Overview
• Querying Stage - ChatEngine & Querying Engine Full Overview
• Hands-on: Create a Custom RAG System with LlamaIndex
• Hands-on: Structured Data Extraction
• Hands-on: Querying a PDF File
• Hands-on: Interacting with a RAG System Through an Express API - Full Hands-on
• Summary

Agents & Advanced Queries with LlamaIndex

• Agents and Advanced Queries - The RouterQueryEngine Overview
• Hands-on - RAG System with Multiple Data Sources
• Hands-on - Creating a RouterQueryEngine to Handle Multiple Query Engines
• Hands-on: Defining Functions and Querying Tools to Start Chatting with the Agent

Persist Your Data & Production-ready Techniques

• Production-ready Techniques - Introduction
• Hands-on: Data with LlamaIndex
• Hands-on: Load Index with the Persisted Data and Stream Response
• Summary

NextJS Full-stack Web Application Chatbot with One Command & Deployment

• Chatbot App with NextJS - Full-stack Web App - Overview
• Hands-on: Generating a Full-stack Web App with create-llama CLI Command
• Hands-on: Customizing the App with Your Own Data and Chatting with It
• Hands-on: Deploying our NextJS Full-stack Chat App to Vercel

Wrap up

• Wrap up and Next Steps