https://github.com/zackproser/rag-pipeline-tutorial
https://github.com/zackproser/rag-pipeline-tutorial
Last synced: 8 months ago
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- Host: GitHub
- URL: https://github.com/zackproser/rag-pipeline-tutorial
- Owner: zackproser
- Created: 2025-01-04T21:43:37.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-05T02:46:18.000Z (over 1 year ago)
- Last Synced: 2025-01-22T17:18:07.366Z (over 1 year ago)
- Language: TypeScript
- Size: 1.43 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# 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](https://zackproser.com/blog/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](https://github.com/zackproser/rag-pipeline-tutorial-notebook)
2. Follow the notebook instructions to prepare your vector store and necessary data
### Installation Steps
1. Clone the repository:
```bash
git clone https://github.com/yourusername/blog-starter-app.git
cd blog-starter-app
```
2. Install dependencies:
```bash
npm install
```
3. Set up your environment variables:
```bash
cp .env.example .env.local
# Add your OpenAI API key to .env.local
```
4. Run the development server:
```bash
npm run dev
```
Visit [http://localhost:3000](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](https://zackproser.com/blog/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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