NEWOpenAI Structured Outputs with Label Studio 🚀
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Prerequisites

Before following this Zero to One guide, there are some tools, technologies, and vocabulary that you should be familiar with and ready to use. If you’ve never used these tools before, don’t worry! We’ll walk you through what to do step by step, and we’ll provide you with documentation you can lean on if you need more support.

For this tutorial, we’ll keep things simple. The two requirements for you to get started are:

  • You need to have Docker installed on your machine.
  • You need to have some base-level familiarity working with the command line to launch Unix-style programs on your computer.

This tutorial won’t require a lot of horsepower and is designed for you to follow along on a laptop.

What is Docker?

Docker is a tool that creates containers to develop, ship, and run applications. One perk to using Docker is that it doesn’t require you to install new software onto your machine natively. Instead, it creates isolated environments for running and testing common applications. It’s quickly becoming one of the preferred ways of delivering applications at any scale, from simple laptop deployments to enterprise infrastructure.

New to Docker or building in containers? Check out their documentation, this handy video created by TechSquidTV explaining the basics of Docker containers, or FreeCodeCamp’s The Docker Handbook.

Terminology

Throughout this guide, you may encounter terms or tools that you may be unfamiliar with, or that may be specific to Label Studio. Here’s a quick guide to help you get more familiar with the terminology used.

Natural Language Processing (NLP)  is commonly used for text-based datasets to help computers interpret language. You’ve likely encountered the byproduct of NLP when interacting with a chatbot, navigating and detecting trends, assisting and empowering search engines, and many other text-based scenarios.