Link your C# and Python applications with the latest AI models from OpenAI
Combine and orchestrate different AI services such as text and image generators
Create your own AI apps with real-world use case examples that show you how to use basic generative AI, create images, process documents, use a vector database
Purchase of the print or Kindle book includes a free PDF eBook

Description

In the fast-paced world of AI, developers are constantly seeking efficient ways to integrate AI capabilities into their apps. Microsoft Semantic Kernel simplifies this process by using the GenAI features from Microsoft and OpenAI. Written by Lucas A. Meyer, a Principal Research Scientist in Microsoft’s AI for Good Lab, this book helps you get hands on with Semantic Kernel. It begins by introducing you to different generative AI services such as GPT-3.5 and GPT-4, demonstrating their integration with Semantic Kernel. You’ll then learn to craft prompt templates for reuse across various AI services and variables. Next, you’ll learn how to add functionality to Semantic Kernel by creating your own plugins. The second part of the book shows you how to combine multiple plugins to execute complex actions, and how to let Semantic Kernel use its own AI to solve complex problems by calling plugins, including the ones made by you. The book concludes by teaching you how to use vector databases to expand the memory of your AI services and how to help AI remember the context of earlier requests. You’ll also be guided through several real-world examples of applications, such as RAG and custom GPT agents. By the end of this book, you'll have gained the knowledge you need to start using Semantic Kernel to add AI capabilities to your applications.

Who is this book for?

This book is for beginner-level to experienced .NET or Python software developers who want to quickly incorporate the latest AI technologies into their applications, without having to learn the details of every new AI service. Product managers with some development experience will find this book helpful while creating proof-of-concept applications. This book requires working knowledge of programming basics.

What you will learn

Write reusable AI prompts and connect to different AI providers
Create new plugins that extend the capabilities of AI services
Understand how to combine multiple plugins to execute complex actions
Orchestrate multiple AI services to accomplish a task
Leverage the powerful planner to automatically create appropriate AI calls
Use vector databases as additional memory for your AI tasks
Deploy your application to ChatGPT, making it available to hundreds of millions of users

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Mojeed Abisiga Sep 09, 2024

If you are a professional in the Gen AI space looking to up your game, this Lucas's book is a must have! It offers a great deep dive into prompt engineering and building robust AI applications with Microsoft's Semantic Kernel SDK.What makes it stand out?Novel Code Design: A fresh approach to managing AI functionalities, similar to the leap classes brought to object-oriented programming.Seamless AI Integration: Streamlines the use of LLMs and other AI models for more efficient and powerful development.Flexible & Familiar: Innovates while allowing for the use of traditional Python functions - which makes the transition smooth for developers.This book is highly recommended for professionals eager to enhance their Gen AI skills.

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Alexander Ashish Sep 09, 2024

I recently read this book which is an amazing guide for Gen AI professionals seeking to build applications that require prompt engineering to construct RAGs and custom OpenAI apps.I am sharing some key points from this book here 👩🏻‍💻📗 This book provides a proper details about the Semantic Kernel’s design which supports independent development and testing of components, perfect for building scalable and maintainable large-scale applications.📘 The kernel can dynamically combine functions which enables the creation of new workflows without additional coding which is ideal for complex applications like MS Office.📙 The book talk about the supports for both Core Plugins and custom semantic plugins which allows developers to create amazing workflows using AI services like OpenAI, without impacting the overall system.📔 The book offers practical guidance on CoT prompt templating and RAG application development within the Semantic Kernel framework.Well this book is around 250 pages only which makes it easier to explain the GEN AI usages and copilot experience in our applications .

Ryan Sep 02, 2024

The Semantic Kernel feels to me like MSFT's version of CrewAI or similar type of programming + calling AI models type vibes.I liked the various examples, and found the idea of planners, where you can essentially get your code to dynamically generate plans for doing stuff you hadn't written before, particularly intriguing.Also interesting are the examples of reading Word docs and working with Excel files, since that are what business runs off of anyways.I did however find the real world examples to be a little bit weak, just RAG and making a custom GPT. The examples of working with Excel and Word I think were actually more relevant.Given that I also ditched OpenAI for Claude earlier this year, I am not as enthusiastic about the book's narrow focus on OpenAI models.If you're a MSFT person, interested in working with AI apps, this might be of interest to you.

Chandra Jul 28, 2024

This book is a great resource for Generative AI professionals seeking to build applications that require prompt engineering to construct RAGs and custom OpenAI apps. Lucas provides a high-level overview of Microsoft's Semantic Kernel SDK. This SDK integrates OpenAI, Azure OpenAI, and Hugging Face with Java, C#, and Python. Consequently, it's a valuable tool for software engineers to leverage their programming language expertise for developing Gen AI applications. Lucas offers lucid explanations of various topics including prompt engineering, image generation, document processing, and RAGs. Highly recommended for professionals eager to enhance their Gen AI skills.

Om S Jul 26, 2024

This book is a fantastic resource for anyone looking to integrate AI into their applications. Lucas A. Meyer breaks down complex concepts into easy-to-understand steps, making it accessible even for beginners. The book covers how to link C# and Python applications with OpenAI models and use various AI services, such as text and image generators.What I loved most were the real-world examples. They provide practical insights on using generative AI, creating images, processing documents, and using a vector database. The inclusion of these examples helps you see the potential applications in a tangible way.The book is well-structured, starting from basic introductions to more advanced topics like creating and combining plugins. It also explains how to use vector databases for memory expansion, which is crucial for more complex AI tasks. Great addition to my tech library!!

Building AI Applications with Microsoft Semantic Kernel : Easily integrate generative AI capabilities and copilot experiences into your applications

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