Building AI Applications with ChatGPT APIs
This is the code repository for Building AI Applications with ChatGPT APIs, published by Packt.
Master ChatGPT, Whisper, and DALL-E APIs by building ten innovative AI projects
What is this book about?
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 covers the following exciting features:
- Develop a solid foundation in using the ChatGPT API for natural language processing tasks
- Build, deploy, and capitalize on a variety of desktop and SaaS AI applications
- Seamlessly integrate ChatGPT with established frameworks such as Flask, Django, and Microsoft Office APIs
- Channel your creativity by integrating DALL-E APIs to produce stunning AI-generated art within your desktop applications
- Experience the power of Whisper API's speech recognition and text-to-speech features
- Discover techniques to optimize ChatGPT models through the process of fine-tuning
If you feel this book is for you, get your copy today!
Instructions and Navigations
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
response = openai.Completion.create(
engine="text-davinci-003",
prompt=question,
max_tokens=1024,
n=1,
stop=None,
temperature=0.8,
)
Following is what you need for this book: with best practices, tips, and tricks for building applications using the ChatGPT API, this book is for programmers, entrepreneurs, and software enthusiasts. Python developers interested in AI applications involving ChatGPT, software developers who want to integrate AI technology, and web developers looking to create AI-powered web applications with ChatGPT will also find this book useful. A fundamental understanding of Python programming and experience of working with APIs will help you make the most of this book.
With the following software and hardware list you can run all code files present in the book (Chapter 1-12).
Software and Hardware List
| Chapter | Software required | OS required |
|---|---|---|
| 1-12 | Python | Windows, macOS, or Linux |
| 1-12 | Django | Windows, macOS, or Linux |
| 1-12 | Flask | Windows, macOS, or Linux |
| 1-12 | PyQt | Windows, macOS, or Linux |
| 1-12 | OpenAI library | Windows, macOS, or Linux |
| 1-12 | Stripe | Windows, macOS, or Linux |
| 1-12 | Azure CLI | Windows, macOS, or Linux |
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Get to Know the Author
Martin Yanev is an experienced Software Engineer who has worked in the aerospace and industries for over 8 years. He specializes in developing and integrating software solutions for air traffic control and chromatography systems. Martin is a well-respected instructor with over 280,000 students worldwide, and he is skilled in using frameworks like Flask, Django, Pytest, and TensorFlow. He is an expert in building, training, and fine-tuning AI systems with the full range of OpenAI APIs. Martin has dual master's degrees in Aerospace Systems and Software Engineering, which demonstrates his commitment to both practical and theoretical aspects of the industry.