Generated Customer Emails with GPT-4 Chains using Inngest
This example aims to be a complete end to end simple e-commerce flow that is as realistic as feasible without going to far into the weeds with implementation details.
That said, to be realistic, we need a handful of things:
- A database to store our data
- An ORM to interact with our database
- Authentication
- Serverless Queueing
- Email sending
As a basis we used T3 Stack to bootstrap the project using the NextAuth.js, Tailwind, tRPC, and Drizzle options.
Drizzle is going to use Planetscale as the database, which will allow us to leverage edge functions.
We are using the Next.js app router. We also need email so we will use Resend and react-email.
Additionally, we are going to use Sanity.io for our CMS. This will allow us to create a simple CMS for our product pages, but we also get some flexibility and power for defining workflows and other things.
Making it realistic means setting up accounts with various services.
This is kind of a chore, but it's not too bad. We need to set up accounts with:
Getting Started
The primary goal of the app is to demonstrate how to use Inngest to generate chained conversations with GPT-4. This approach is useful for creating higher quality generated text that is acceptable to use for customer communications.
Here's an example from a production application that's using this approach:
Various events in the application trigger async workflows that occur in queued serverless background jobs.
- an event is received
- steps/actions are performed
- we can sleep or wait for other events within the workflow
- we can send events that trigger other workflows
In this example app we are