This repository documents the course JavaScript RAG Web Apps with LlamaIndex, provided by DeepLearning.AI in collaboration with LlamaIndex.

The course teaches how to build retrieval-augmented generation (RAG) web applications with JavaScript, integrating LlamaIndex for powerful querying and information retrieval.

Large Language Models (LLMs) are powerful but limited by the data they were trained on. Retrieval-Augmented Generation (RAG) bridges this gap by combining LLMs with external knowledge sources.

This course provides a hands-on journey into building JavaScript RAG applications, from setting up the basics to deploying production-ready systems.

By the end of this course, you will be able to:

• Understand the principles of Retrieval-Augmented Generation (RAG).
• Build a full-stack web app powered by LlamaIndex.
• Design and execute advanced queries with agents.
• Apply production-ready techniques for scalability and robustness.

• Introduction to Retrieval-Augmented Generation (RAG).
• Why RAG is important for extending LLM capabilities.
• Key components of a RAG pipeline (retrievers, indexes, and LLMs).
• Setting up JavaScript + LlamaIndex for your first RAG queries.

• Creating a front-end interface for RAG-powered apps.
• Connecting a Node.js/Express backend with LlamaIndex.
• Managing context and prompts for user queries.
• Deploying your first end-to-end RAG web application.

• Understanding agents and their role in structured querying.
• Configuring LlamaIndex query engines and tools.
• Building multi-step reasoning pipelines.
• Handling complex user queries with dynamic workflows.

• Scaling your RAG application for multiple users.
• Performance optimization (indexing strategies, caching).
• Error handling and fail-safes for robust deployments.
• Best practices for monitoring, logging, and maintenance.

• 🌐 DeepLearning.AI – Course Page
• 📘 LlamaIndex Documentation
• 💻 JavaScript Official Docs
• 🛠 Node.js Official Docs

This course is brought to you by:

• DeepLearning.AI – Leaders in AI education and training.
• LlamaIndex – Framework for connecting LLMs with external data.