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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

Using Semantic Kernel to connect to AI services

To complete this section, you must have an API key. The process to obtain an API key was described at the beginning of this chapter.

In the upcoming subsections, we are only going to connect to the OpenAI text models GPT-3.5 and GPT-4. If you have access to the OpenAI models through Azure, you will need to make minor modifications to your code.

Although it would be simpler to connect to a single model, we are already going to show a simple but powerful Microsoft Semantic Kernel feature: we’re going to connect to two different models and run a simple prompt using the simpler but less expensive model, GPT-3.5, and a more complex prompt on the more advanced but also more expensive model, GPT-4.

This process of sending simpler requests to simpler models and more complex requests to more complex models is something that you will frequently do when creating your own applications. This approach is called LLM cascade, and it was...

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