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

View More author details

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

Why subscribe?

18. Other Books You May Enjoy

Part 1:Getting Started with OpenAI APIs

In the first part, encompassing two chapters, the focus is on providing a comprehensive overview of ChatGPT and its significance for Natural Language Processing (NLP). We will discuss the fundamentals of ChatGPT, exploring its impact and usage in web applications, as well as introducing readers to the ChatGPT API. This part shows the process of building a ChatGPT clone, which is a chatbot that utilizes OpenAI’s language model to generate human-like responses to user input and retains the conversation history. The application will be built using Flask, a lightweight web framework for Python.

This part has the following chapters: