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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

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Product type Paperback
Published in Jun 2024
Publisher Packt
ISBN-13 9781835463703
Length 252 pages
Edition 1st Edition
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Author (1):
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Lucas A. Meyer Lucas A. Meyer
Author Profile Icon Lucas A. Meyer
Lucas A. Meyer
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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

Adding Memories to Your AI Application

In the previous chapter, we learned how to use planners to give our users the ability to ask our application to perform actions that we did not program explicitly. In this chapter, we are going to learn how to use external data, so that we can bring recent information and keep information between user sessions. For now, we are going to use small amounts of external data that our users may have given us by saving it to memory. Learning how to use memory will enable us to greatly expand the capabilities of AI models.

This is a building block for the next chapter, in which we are going to learn techniques to use amounts of data that vastly exceed the context window of existing models. As you may remember, a context window is the maximum size of the input you can send to an AI service. By using memory, you can save a large amount of data and only send portions of the data in each call.

We will start by understanding how LLMs convert words into...

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