Developing RAG Apps with LlamaIndex and JS

Developing RAG Apps with LlamaIndex and JS

by Paulo Dichone
Released September 2024
Publisher(s): Packt Publishing
ISBN: 9781836646112

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Video description

In this course, you will explore the development of Retrieval-Augmented Generation (RAG) applications using LlamaIndex and JavaScript. You'll start with an introduction to the course structure, prerequisites, and project goals. Initial sections focus on setting up the development environment, including configuring Node.js and obtaining OpenAI API keys to facilitate seamless interaction with LlamaIndex.

Next, you'll delve into LlamaIndex fundamentals, covering data ingestion, indexing, and querying. Through hands-on sessions, you'll build basic and custom RAG systems, query structured data, and interact with LlamaIndex using an Express API. These practical exercises will equip you with the skills to handle complex scenarios, such as querying PDF files and integrating multiple data sources.

The final sections focus on advanced topics, including managing data persistence and deploying production-ready applications. You'll learn to create a full-stack chatbot app with NextJS, utilizing the create-llama CLI for rapid setup and customization. By course end, you'll be able to build, customize, and deploy scalable RAG applications with confidence.

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.

Audience

This course is designed for developers with a solid foundation in JavaScript who want to explore RAG systems using LlamaIndex. Prior experience with Node.js and familiarity with APIs are recommended. If you're interested in building scalable, AI-powered applications, this course is for you.

About the Author

Paulo Dichone: Paulo Dichone, a dedicated developer and educator in Android, Java, and Flutter, has empowered over 80,000 students globally with both soft and technical skills through his platform, Build Apps with Paulo. Holding a Computer Science degree and with extensive experience in mobile and web development, Paulo's passion lies in guiding learners to become proficient developers. Beyond his 5 years of online teaching, he cherishes family time, music, and travel, aiming to make impactful developers irrespective of their background.

Table of contents

  1. Chapter 1 : Introduction
    1. Introduction
    2. Course Prerequisites Who is This Course For?
    3. Course Structure
    4. PLEASE WATCH - What You'll Build in This Course
  2. Chapter 2 : Development Environment Setup
    1. Setup Dev. Environment - NodeJS Instructions
    2. Setup OpenAI Account and the OpenAI API Key
  3. Chapter 3 : LlamaIndex Deep Dive – Fundamentals
    1. Deep Dive into LlamaIndex and Key Features - Overview
    2. RAG Crash Course
    3. LlamaIndex Flow - Overview
    4. LlamaIndex - Data Ingestion, Indexing and Query Interface Overview
    5. Hands-on - Setup LlamaIndex Simple RAG System
    6. Summary
  4. Chapter 4 : LlamaIndex Deep Dive - Main Concepts and Data Loaders
    1. LlamaIndex Core Concepts - Loaders Index
    2. The Querying Stage - Overview
    3. Querying Stage - ChatEngine Querying Engine Full Overview
    4. Hands-on: Create a Custom RAG System with LlamaIndex
    5. Hands-on: Structured Data Extraction
    6. Hands-on: Querying a PDF File
    7. Hands-on: Interacting with a RAG System Through an Express API - Full Hands-on
    8. Summary
  5. Chapter 5 : Agents Advanced Queries with LlamaIndex
    1. Agents and Advanced Queries - The RouterQueryEngine Overview
    2. Hands-on - RAG System with Multiple Data Sources
    3. Hands-on - Creating a RouterQueryEngine to Handle Multiple Query Engines
    4. Hands-on: Defining Functions and Querying Tools to Start Chatting with the Agent
  6. Chapter 6 : Persist Your Data Production-ready Techniques
    1. Production-ready Techniques - Introduction
    2. Hands-on: Data with LlamaIndex
    3. Hands-on: Load Index with the Persisted Data and Stream Response
    4. Summary
  7. Chapter 7 : NextJS Full-stack Web Application Chatbot with One Command Deployment
    1. Chatbot App with NextJS - Full-stack Web App - Overview
    2. Hands-on: Generating a Full-stack Web App with create-llama CLI Command
    3. Hands-on: Customizing the App with Your Own Data and Chatting with It
    4. Hands-on: Deploying our NextJS Full-stack Chat App to Vercel
  8. Chapter 8 : Wrap up
    1. Wrap up and Next Steps

Product information

  • Title: Developing RAG Apps with LlamaIndex and JS
  • Author(s): Paulo Dichone
  • Release date: September 2024
  • Publisher(s): Packt Publishing
  • ISBN: 9781836646112