You're reading from Building AI Applications with OpenAI APIs Leverage ChatGPT, Whisper, and DALL-E APIs to build 10 innovative AI projects

Product type Paperback

Published in Oct 2024

Publisher Packt

ISBN-13 9781835884003

Length 252 pages

Edition 2nd Edition

Languages

Python

Concepts

GPT/LLMs

Author (1):

Martin Yanev

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Table of Contents (19) Chapters

Preface

1. Part 1:Getting Started with OpenAI APIs FREE CHAPTER

2. Chapter 1: Getting Started with the ChatGPT API for NLP Tasks

3. Chapter 2: Building a ChatGPT Clone

4. Part 2: Build Web Applications with ChatGPT API

5. Chapter 3: Creating and Deploying a Code Bug-Fixing Application Using Flask

6. Chapter 4: Integrating the Code Bug-Fixing Application with a Payment Service

7. Chapter 5: Quiz Generation App with ChatGPT and Django

8. Part 3: ChatGPT, DALL-E, and Whisper APIs for Desktop Apps Development

9. Chapter 6: Language Translation Desktop App with the ChatGPT API and Microsoft Word

10. Chapter 7: Building an Outlook Email Reply Generator

11. Chapter 8: Essay Generation Tool with PyQt and the ChatGPT API

12. Chapter 9: Integrating the ChatGPT and DALL-E APIs: Building an End-to-End PowerPoint Presentation Generator

13. Chapter 10: Speech Recognition and Text-to-Speech with the Whisper API

14. Part 4: Advanced Concepts for Powering ChatGPT Apps

15. Chapter 11: Choosing the Right ChatGPT API Model

16. Chapter 12: Fine-Tuning ChatGPT to Create Unique API Models

17. Index

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Performing multiple ChatGPT API requests

Let’s first dive into the ChatGPT API requests and learn how to build your project and the app.py file. In this project, we will explore how to make multiple ChatGPT API requests to get the explanations and fixed code for our input queries. We will go through each step of the process and provide clear examples, so you can follow along with ease.

To fix users’ code, ChatGPT needs two key components: some buggy code and the error provided by the system. The idea behind the Code Bug Fixer application is that you provide ChatGPT with two separate requests simultaneously (see Figure 3.1):

Request 1: ChatGPT uses the buggy code and the error to fix the code
Request 2: ChatGPT uses the buggy code and the error to explain the error to the user in plain English