Free Download Microsoft Semantic Kernel in Action (MEAP V03) by Daniel Costea
English | 2025 | ISBN: 9781633435568 | 308 pages | PDF,EPUB | 13.2 MB
Build AI applications that integrate multiple models, data sources, and other components using Microsoft Semantic Kernel.
Even simple AI applications need to combine LLMs and other models, functions and plugins created in various programming languages, and custom data sources. With the Microsoft Semantic Kernel SDK, you can create chatbots, copilots, and agents by chaining individual components together using a few lines of glue code. Semantic Kernel makes it a snap to build AI apps from scratch or integrate AI features into an existing codebase.
In Microsoft Semantic Kernel in Action you'll learn how to:
Implement short-term and long-term memory in AI applications
Create and manage plugins
Design and implement multi-modal AI applications
Orchestrate complex AI tasks using function calling and planners
Microsoft Semantic Kernel in Action guides you from basics like creating and connecting your first plugins to advanced features including Semantic Kernel's powerful AI-powered orchestration capabilities. Everything you learn is put into practice with hands-on projects such as a "Smart Garden" AI assistant and a "Rain Detector" assistant that analyzes temperature, humidity, and luminosity, and then creates analysis charts in real time using generative AI. You'll learn AI orchestration techniques to achieve autonomous and semi-autonomous systems (human-in-the-loop) using tools and planners, how to use open-source small language models for on-premises systems, advanced techniques for decomposing prompts into native and semantic plugins, and much more. Plus, the book's focus on enterprise-ready solutions ensures you're always considering security, scalability, and responsible AI practices.
about the book
Microsoft Semantic Kernel in Action teaches you to create AI applications and integrate AI into existing software using C# and the lightweight Semantic Kernel SDK. The book covers both proprietary AI models like OpenAI's GPT and open-source options like Llama and Phi. As you work hands-on through several interesting and relevant projects, you'll explore assorted connectors and AI services, orchestrate complex tasks, and implement long-term memory using RAG.
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