Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Building AI Applications with Microsoft Semantic Kernel

You're reading from   Building AI Applications with Microsoft Semantic Kernel Easily integrate generative AI capabilities and copilot experiences into your applications

Arrow left icon
Product type Paperback
Published in Jun 2024
Publisher Packt
ISBN-13 9781835463703
Length 252 pages
Edition 1st Edition
Languages
Tools
Concepts
Arrow right icon
Author (1):
Arrow left icon
Lucas A. Meyer Lucas A. Meyer
Author Profile Icon Lucas A. Meyer
Lucas A. Meyer
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Part 1:Introduction to Generative AI and Microsoft Semantic Kernel FREE CHAPTER
2. Chapter 1: Introducing Microsoft Semantic Kernel 3. Chapter 2: Creating Better Prompts 4. Part 2: Creating AI Applications with Semantic Kernel
5. Chapter 3: Extending Semantic Kernel 6. Chapter 4: Performing Complex Actions by Chaining Functions 7. Chapter 5: Programming with Planners 8. Chapter 6: Adding Memories to Your AI Application 9. Part 3: Real-World Use Cases
10. Chapter 7: Real-World Use Case – Retrieval-Augmented Generation 11. Chapter 8: Real-World Use Case – Making Your Application Available on ChatGPT 12. Index 13. Other Books You May Enjoy

Plugins

One of the greatest strengths of Microsoft Semantic Kernel is that you can create semantic plugins that are language agnostic. Semantic plugins are collections of semantic functions that can be imported into the kernel. Creating semantic plugins allows you to separate your code from the AI function, which makes your application easier to maintain. It also allows other people to work on the prompts, making it easier to implement prompt engineering, which will be explored in Chapter 2.

Each function is defined by a directory containing two text files: config.json, which contains the configuration for the semantic function, and skprompt.txt, which contains its prompt.

The configuration of the semantic function includes the preferred engine to use, the temperature parameter, and a description of what the semantic function does and its inputs.

The text file contains the prompt that will be sent to the AI service to generate the response.

In this section, we are going...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image