Learn to Work in Realtime with GPT 4o and Get Millisecond Responses with Tau.js
What you will learn
What Realtime API Is
What Tau.js Is
How to Output Voice with Tau.js and Realtime API
How to Input Voice with the Tau.js Debugger
Why take this course?
In this short introductory course, we’ll learn how to install and get started with `tau.js` to create and work with realtime websocket-based GPTย connections to 4o realtime and mini
In this course we’ll:
– Review What Realtime GPTย api is and how it differs from normalย GPT
– What Tau.js is and how it helps facilitate development
– We’ll build a tau.js project from scratch with VSCode
– We’ll get to hello world with websocket-based realtime connections in under 5 minutes
What is tau.js
tau.js is a node library that greatly simplifies the Websocket API used to communicate with realtime AI models like 4o-realtime, and adds essential features like realtime voice debugging.
With tau.js, Starting a session and generating a voice response is as simple as:
import { create_session } from “@tau/core”
let session = await create_session()
await session.system(“Whenever prompted to respond, state a different teaching of the Sun Tzu.”)
await session.response()
// “The supreme art of war is to subdue the enemy without fighting.”
Why Use tau.js?
tau.js greatly reduces ramp-up time when building applications with OpenAI’s 4o-realtime and 4o-mini-realtime models.
Simple Async/Await Interface
Realtime AI sessions are based on Websockets. This is very good, as websockets are extremely fast and they’re a critical part of delivering a fast user experience. But Websockets are hard to develop for and tend to create messy code that can’t be maintained.
tau.js solves this problem by black-boxing away all websocket logic and instead providing a dead-simple async/await API with which to build powerful realtime apps.