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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

Product type Paperback

Published in Jun 2024

Publisher Packt

ISBN-13 9781835463703

Length 252 pages

Edition 1st Edition

Languages

C#

Tools

ChatGPT

Concepts

GPT/LLMs

Author (1):

Lucas A. Meyer

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Table of Contents (14) Chapters

Preface

1. Part 1:Introduction to Generative AI and Microsoft Semantic Kernel

2. Chapter 1: Introducing Microsoft Semantic Kernel FREE CHAPTER

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

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13. Other Books You May Enjoy

Summary

In this chapter, we connected an application with OpenAI’s ChatGPT by developing a custom GPT and adding custom actions to it. This can enable applications to get access to a planner that is based on the latest model available to ChatGPT users, which is usually a very advanced model.

In addition, what we have learned allows you to deploy your application to hundreds of millions of users with minimal effort and get access to several new features available to ChatGPT users, such as natural language requests and voice requests. It also allows you to deploy your application to users more quickly, as you don’t have to develop a UI yourself – you can use ChatGPT as the UI as you develop and grow your application.

If you are a Python programmer, Microsoft Semantic Kernel provides a few additional features over what is already provided by the default OpenAI Python API. Among other things, you get the separation between prompt and code, native functions, planners...

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Authors (1)

Lucas A. Meyer

Lucas A. Meyer

Lucas A. Meyer is a Computer Scientist and Financial Economist with over two decades of experience in technology. Lucas joined Microsoft in 2002 to work with databases in Finance, joined Amazon in 2020 to work with fraud detection and prevention, and returned to Microsoft in 2022 as a Principal Research Scientist in the Microsoft's AI for Good Lab, where he works with Large Language Models (LLMs) and the Microsoft Semantic Kernel daily. Lucas' first NLP project, released in 2016, was a chatbot that streamlined several corporate finance operations and won the Adam Smith Award from London's Treasury Today. Lucas has an MBA and an M.Sc. in Finance from the University of Washington in Seattle.

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