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

Implementing Text Translation and Transcription with the Whisper API

In this section, we will explore the capabilities of the Whisper API to transcribe and translate audio files seamlessly using Python. With the advancements in speech recognition and translation technology, we now can effortlessly convert spoken language into text and bridge language barriers effectively. By following the step-by-step instructions provided, you will be equipped with the knowledge and skills necessary to integrate the Whisper API into your Python projects and unlock the potential of audio-based data.

Throughout this section, we will explore the different aspects of transcribing and translating audio files. Starting with the setup and installation requirements, we will ensure that you have the necessary tools, including Python, a code editor, a Python virtual environment, and an OpenAI API key.

To proceed with transcribing and translating audio files using the Whisper API in Python, it is recommended...