Extract flight data with an LLM

In this tutorial, we’ll show you how to build a web application powered by AI! We’ll demonstrate how to connect an Anvil Server Module to a Large Language Model (LLM) and use the incredible capabilities of AI to extract information from unstructured text.

The finished app will extract flight details from an email using OpenAI’s Chat API, and display them in a table where you can see your flight’s origin, destination, arrival and departure time. We’ll set up an email service and user authentication so that each user only sees their own flight details.

This tutorial assumes you have some prior knowledge of Anvil. If Anvil is completely new to you, you may want to complete the feedback form tutorial first.

The final app will look something like this:

Chapters

In this tutorial, you'll:

Set up the Anvil server module and email service

Add the LLM code into an Anvil server module and set up the email service.

Add a data table

Add a data table to save the output from the LLM

Build a user interface

Build a frontend to display all your flight details in one place

Click the following link to clone the finished app and explore it yourself, or read on for a step-by-step guide to building the app.

If at any point you need some more background on Anvil features, you can get help from the documentation.