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)

Using the embedding model for text comparisons and other use cases

OpenAI has a model and endpoint that enables users to create embeddings. It’s a lesser-known feature of the API but has vast applications in enabling plenty of use cases (searching through text, text classification, and much more).

What are embeddings? Text embedding is a sophisticated technique employed in NLP that transforms text into a numerical format that machines can understand. Essentially, embeddings are high-dimensional vectors that capture the essence of words, sentences, or even entire documents, encapsulating not just their individual meanings but also the nuances and relationships between them.

Mathematically, a vector is a point in an n-dimensional vector space, but for our purposes, you can think of a vector as just a list of numbers. However, the recipes discussed in this chapter do not require you to work with the process and science behind converting words to numbers. For more information...