Book Image

OpenAI API Cookbook

By : Henry Habib
Book Image

OpenAI API Cookbook

By: Henry Habib

Overview of this book

As artificial intelligence continues to reshape industries with OpenAI at the forefront of AI research, knowing how to create innovative applications such as chatbots, virtual assistants, content generators, and productivity enhancers is a game-changer. This book takes a practical, recipe-based approach to unlocking the power of OpenAI API to build high-performance intelligent applications in diverse industries and seamlessly integrate ChatGPT in your workflows to increase productivity. You’ll begin with the OpenAI API fundamentals, covering setup, authentication, and key parameters, and quickly progress to the different elements of the OpenAI API. Once you’ve learned how to use it effectively and tweak parameters for better results, you’ll follow advanced recipes for enhancing user experience and refining outputs. The book guides your transition from development to live application deployment, setting up the API for public use and application backend. Further, you’ll discover step-by-step recipes for building knowledge-based assistants and multi-model applications tailored to your specific needs. By the end of this book, you’ll have worked through recipes involving various OpenAI API endpoints and built a variety of intelligent applications, ready to apply this experience to building AI-powered solutions of your own.
Table of Contents (10 chapters)

Extending the endpoint server to accept parameters and return data

In the previous recipe, we successfully created a Cloud Function that, when invoked, returned a slogan for an ice cream company. While this is useful as it sits on the cloud, we want to amend this function so that it can do two things:

  • Accept parameters: We need to modify the function to accept input parameters as part of the HTTP request. This means we will be able to create a Cloud Function that not only returns the slogan for an ice cream business but any type of business for which we provide a description.
  • Structure the output: We don’t want to simply output the chat completion (which, in this case, is the slogan). Instead, we want to process the data and output a JSON object, as it is widely used and easy to work with in web applications.

In this recipe, we will create a public endpoint server that will accept a parameter called business_description and will return the generated slogan...