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

Building a Voice Transcriber Application

In this section, we will explore the development of a language transcription application by integrating Tkinter, a popular Python GUI toolkit, with the powerful Whisper API. This integration will allow us to create a user-friendly interface that enables the real-time transcription of spoken language. By following the step-by-step instructions and harnessing the capabilities of Tkinter and the Whisper API, you will be empowered to develop your own GUI application, opening a myriad of possibilities in speech recognition and language processing.

Whether you aspire to create a tool for transcribing interviews, generating subtitles for videos, or simply exploring the potential of speech-to-text technology, this section will equip you with the knowledge and skills to bring your ideas to life. So, let’s dive in and embark on this exciting journey of building a language transcription app with Tkinter and the Whisper API.

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