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Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

By : Martin Yanev
4.4 (27)
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Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

4.4 (27)
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)
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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

Download the example code files

You can download the example code files for this book from GitHub at https://github.com/PacktPublishing/Building-AI-Applications-with-ChatGPT-APIs. If there’s an update to the code, it will be updated in the GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames and user input. Here is an example: “Create a new file called app.py.”

A block of code is set as follows:

response = openai.Completion.create(
    engine="text-davinci-003",
    prompt=question,
    max_tokens=1024,
    n=1,
    stop=None,
    temperature=0.8,
)

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

answer = response["choices"][0]["text"]
print(answer)

Any command-line input or output is written as follows:

$ pip install openai
"What would you like to ask ChatGPT?

Bold: Indicates a new term, an important word, or words that you see on screen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “Select the Terminal button from the View menu.”

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