How to build a RAG pipeline tutorial

A Next.js blog that understands its own content

Built with Next.js 14, TypeScript, and OpenAI

🚀 Overview

This project demonstrates how to build a modern blog with an AI-powered chat interface that can intelligently discuss your blog content. It's a practical implementation of Retrieval Augmented Generation (RAG) that showcases how to:

• Create a responsive, modern blog using Next.js and TypeScript
• Implement a RAG pipeline for intelligent content retrieval
• Build a real-time chat interface that understands your blog posts
• Retrieve related entities (posts, products, services, agents, etc)
• Augment streaming responses with data serialized in HTTP headers that your React UI can use to update the UI
• Correctly use the latest AI SDKs from Vercel, Pinecone and OpenAI

The patterns this tutorial demonstrates can be applied to any blog or content site, include e-commerce sites, corporate properties, and more.

This codebase is part of the comprehensive RAG Pipeline Tutorial that walks you through building intelligent content applications.

✨ Features

• Intelligent Chat Interface: Chat with an AI that understands your blog content
• Real-time Content Updates: Automatically indexes new blog posts for the RAG pipeline
• Modern Stack: Built with Next.js 14, TypeScript, and Tailwind CSS
• Markdown Support: Write posts in Markdown with front matter
• Responsive Design: Beautiful on all devices
• Developer Experience: Hot reloading, TypeScript types, and more

🛠 Quick Start

Prerequisites

Before starting with this application, you must first complete the data preparation steps in the companion Jupyter notebook:

1. Visit the RAG Pipeline Tutorial Notebook
2. Follow the notebook instructions to prepare your vector store and necessary data

Installation Steps

1. Clone the repository:

git clone https://github.com/yourusername/blog-starter-app.git
cd blog-starter-app

2. Install dependencies:

npm install

3. Set up your environment variables:

cp .env.example .env.local
# Add your OpenAI API key to .env.local

4. Run the development server:

npm run dev

Visit http://localhost:3000 to see your blog in action!

📚 Documentation

For a deep dive into how this works and how to build your own RAG pipeline:

• Complete RAG Pipeline Tutorial

📦 Tech Stack

• Frontend: Next.js 14, React, TypeScript, Tailwind CSS
• AI Integration: OpenAI API
• Content: Markdown with Gray Matter
• Styling: Tailwind CSS
• Deployment: Vercel

📝 License

MIT

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Built with ❤️ as part of the RAG Pipeline Tutorial