Build a Full Stack Email Autoresponder with a Superbase Vector Store
Learn to build a full-stack email autoresponder application using Superbase, Next.js, and OpenAI embeddings for efficient data retrieval and question answering.
Course Timeline
🎥 Introduction
Course overview, objectives, and a sneak peek at the final application – a mini full-stack app for saving emails and chatting with them using RAG.
🚀 Superbase Project Setup
Step-by-step walkthrough of setting up a free Superbase project, creating a new organization, and creating a new project called 'AI Email Autoresponder'.
🧱 Database Design & Setup
High-level overview and creation of the 'emails' and 'email_sections' tables in Superbase PostgreSQL database. Discussion on embeddings, token limits, and breaking long emails into smaller chunks.
🔎 Vector Store Indexes
Explanation of Vector store indexes and their importance in embedding comparison. Setting up the cosine distance index in Superbase for efficient embedding similarity search.
🧑💻 Next.js App Creation & Frontend Form
Creating a Next.js application using TypeScript and Tailwind CSS. Building a frontend form using Cursor for easy email submission to the backend API.
⚙️ Backend API & Email Processing
Creating a backend API route in Superbase to handle incoming emails. Using Zod for data validation, OpenAI for embedding, and Superbase client for database interaction.
💬 RAG-powered Q&A
Building a Q&A page with UI components for asking questions. Creating a backend API route to handle questions, use vector similarity search (SQL + vector store), and leverage ChatGPT for answer generation (Retrieval Augmented Generation).