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Exploring GPT-3

You're reading from   Exploring GPT-3 An unofficial first look at the general-purpose language processing API from OpenAI

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Product type Paperback
Published in Aug 2021
Publisher Packt
ISBN-13 9781800563193
Length 296 pages
Edition 1st Edition
Languages
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Author (1):
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Steve Tingiris Steve Tingiris
Author Profile Icon Steve Tingiris
Steve Tingiris
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Understanding GPT-3 and the OpenAI API
2. Chapter 1: Introducing GPT-3 and the OpenAI API FREE CHAPTER 3. Chapter 2: GPT-3 Applications and Use Cases 4. Section 2: Getting Started with GPT-3
5. Chapter 3: Working with the OpenAI Playground 6. Chapter 4: Working with the OpenAI API 7. Chapter 5: Calling the OpenAI API in Code 8. Section 3: Using the OpenAI API
9. Chapter 6: Content Filtering 10. Chapter 7: Generating and Transforming Text 11. Chapter 8: Classifying and Categorizing Text 12. Chapter 9: Building a GPT-3-Powered Question-Answering App 13. Chapter 10: Going Live with OpenAI-Powered Apps 14. Other Books You May Enjoy

Implementing sentiment analysis

A common classification task is sentiment analysis. Using sentiment analysis, you can classify text based on its general tone – for example, happy, sad, mad, or neutral. This can be useful in a lot of applications; for example, if you're a restaurant owner and you want to respond quickly to unhappy customer reviews. Let's take a look at how we could do that using the OpenAI API classifications endpoint.

In this example, we will classify restaurant reviews. We'll label the reviews with the labels Good, Poor, or Neutral. We will use the classifications endpoint for this example, and we'll provide some example reviews with the request.

Node.js/JavaScript example

To create the review classifier example in Node.js/JavaScript, follow these steps:

  1. Log in to replit.com and open your exploring-gpt3-node REPL.
  2. Create a new file – chapter08/reviews-classifier.js.
  3. Add the following code...
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