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

Using PyDub for Longer Audio Inputs

In this section, we will explore the integration of PyDub, a powerful audio processing library for Python, with the Whisper API to overcome the file size limitation of 25 MB imposed by the API. With PyDub, we can efficiently split large audio files into smaller segments, enabling the seamless transcription of lengthy recordings. By following the instructions and leveraging PyDub’s capabilities, you will be able to harness the full potential of the Whisper API for transcribing audio files of any size.

Leveraging the power of PyDub to enhance your language transcription workflow is a straightforward process. By utilizing this library, you can effortlessly divide lengthy audio files into smaller segments. For instance, if you have a 10-minute audio file, you can easily split it into two separate files, each with a duration of 5 minutes. These smaller files can then be submitted to the Whisper API for transcription, ensuring that your files...