Build a Full Stack RAG System with React, Langchain & Node.js

Published: 01 January 1970
on channel: notJust․dev

16,505

477

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📚 Get the step-by-step guide: https://assets.notjust.dev/youtube-chat

Want to chat with any YouTube video using AI? 🤖 In this tutorial, you’ll learn how to build a full-stack Retrieval-Augmented Generation (RAG) system that lets you ask questions about YouTube content and get accurate, AI-generated answers. You’ll learn how to scrape video transcripts using BrightData, process them with Langchain, and connect to powerful LLMs like OpenAI and Anthropic—all deployed with Genezio. 🤖 🚀

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📝 This video includes a lot of tools and technologies, providing an excellent opportunity to learn:
👉 How to scrape YouTube video transcripts using BrightData
👉 How to build a NodeJS and Express backend for a RAG system
👉 How to process YouTube transcripts and generate embeddings with Langchain
👉 How to query OpenAI and Anthropic models for context-aware answers
👉 How to store and retrieve embeddings from a PostgreSQL vector database
👉 How to create a React web app to chat with YouTube videos in real time
👉 How to deploy a full-stack AI app seamlessly using Genezio
.. and MORE!

💡 Have an idea for a future tutorial? Share it on our Idea Board: https://github.com/orgs/notJust-dev/d...

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