Book Image

Building AI Applications with ChatGPT APIs

By : Martin Yanev
4.2 (5)
Book Image

Building AI Applications with ChatGPT APIs

4.2 (5)
By: Martin Yanev

Overview of this book

Combining ChatGPT APIs with Python opens doors to building extraordinary AI applications. By leveraging these APIs, you can focus on the application logic and user experience, while ChatGPT’s robust NLP capabilities handle the intricacies of human-like text understanding and generation. This book is a guide for beginners to master the ChatGPT, Whisper, and DALL-E APIs by building ten innovative AI projects. These projects offer practical experience in integrating ChatGPT with frameworks and tools such as Flask, Django, Microsoft Office APIs, and PyQt. Throughout this book, you’ll get to grips with performing NLP tasks, building a ChatGPT clone, and creating an AI-driven code bug fixing SaaS application. You’ll also cover speech recognition, text-to-speech functionalities, language translation, and generation of email replies and PowerPoint presentations. This book teaches you how to fine-tune ChatGPT and generate AI art using DALL-E APIs, and then offers insights into selling your apps by integrating ChatGPT API with Stripe. With practical examples available on GitHub, the book gradually progresses from easy to advanced topics, cultivating the expertise required to develop, deploy, and monetize your own groundbreaking applications by harnessing the full potential of ChatGPT APIs.
Table of Contents (19 chapters)
Free Chapter
1
Part 1:Getting Started with OpenAI APIs
4
Part 2: Building Web Applications with the ChatGPT API
8
Part 3: The ChatGPT, DALL-E, and Whisper APIs for Desktop Apps Development
14
Part 4:Advanced Concepts for Powering ChatGPT Apps

Summary

In this chapter of the book, you were introduced to 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. The application was built using Flask, a lightweight web framework for Python, and was customizable to allow for the use of different OpenAI models and other options such as the length of the generated text.

We also covered topics such as creating and generating the frontend HTML for the ChatGPT clone, intercepting ChatGPT API endpoints, passing user input from the frontend to the backend using AJAX, and displaying the generated text in the frontend.

In Chapter 3, you will learn how to create and deploy an AI-powered code bug fixing SaaS application using Flask and the ChatGPT language model. You will become proficient in using the ChatGPT API. You will learn how to create a web form that accepts user inputs, deploy the application to the Azure cloud platform, and integrate...