Mastering the Microsoft Agent Framework: Building Enterprise AI Agents with .Net
暫譯: 精通 Microsoft Agent Framework:使用 .NET 建構企業級 AI Agent

Piridi, Sarat

  • 出版商: Apress
  • 出版日期: 2026-09-27
  • 售價: $2,140
  • 貴賓價: 9.5 折 $2,033
  • 語言: 英文
  • 頁數: 270
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798868828874
  • ISBN-13: 9798868828874
  • 相關分類: Large language model、C#、Microsoft Azure
  • 海外代購書籍(需單獨結帳)

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商品描述

Design and build enterprise AI agents using the Microsoft Agent Framework with .NET and C#.

 

The Microsoft Agent Framework is Microsoft's foundation for building AI agents on .NET. It unifies the ideas that started in Semantic Kernel and AutoGen and adds what a production system actually needs. This book teaches it from the ground up, one working agent per chapter, from your first conversational agent to agents that call each other and run in the cloud.

 

You start simple: deploy a model, connect your first agent, and understand how models, providers, and credentials fit together. Then you add the capabilities that make an agent genuinely useful. You give it tools so it can call your code. You give it memory so it remembers, both within a conversation and after a restart. You ground it in your own documents so it answers from real sources, with citations. And you put a human in the loop, so risky actions happen only after someone approves them.

 

From there, the book goes further. You connect your agent to outside tools and data through the Model Context Protocol, and package reusable capabilities as skills. You learn to coordinate several agents at once: running them in sequence, in parallel, handing off between them, or letting them collaborate in a group. Then you make agents production-ready, adding guardrails, tracing what they do with OpenTelemetry and Azure Application Insights, and measuring their quality with evaluation. Finally, you connect agents to each other and host them on Azure, and close with a chapter of hard-won best practices for building agents that last.

 

Everything in the book runs. Every code listing is a real program that builds and executes, and a companion GitHub repository gives you the complete source for every chapter. The book pins one framework version throughout, so the code works exactly as written instead of drifting out of date. Each chapter follows the same practical rhythm: here's the problem, here's the code, here's it running, and here's what to watch for in production.

 

What You Will Learn:

 

  • Deploy a model and give your agent tools to call your own code Add memory, ground answers in your documents with retrieval, and require human approval for risky steps Extend agents with the Model Context Protocol and reusable skills Coordinate multiple agents: sequential, concurrent, handoff, group chat, and Magentic orchestration Add guardrails and trace agents with OpenTelemetry and Azure Application Insights Evaluate agent quality, connect agents to each other, and host agents in the cloud with Azure

Who This Book Is For:

.NET developers who want to build real AI agents with C#. You should be comfortable with C# and have used a cloud service before. No machine learning background is needed, you deploy and call models, you don't train them.

 

商品描述(中文翻譯)

使用 .NET 和 C#,透過 Microsoft Agent Framework 設計與建置企業級 AI 代理程式。

Microsoft Agent Framework 是 Microsoft 在 .NET 上建置 AI 代理程式的基礎框架。它整合了 Semantic Kernel 和 AutoGen 的核心理念,並加入實際生產系統所需的功能。本書從基礎開始教學,每章都會建置一個可運作的代理程式,帶你從第一個對話式代理程式開始,逐步學會建置能彼此呼叫並在雲端執行的代理程式。

你會先從簡單的內容開始:部署模型、連接第一個代理程式,並了解模型、提供者(provider)與認證資訊如何彼此配合。接著,你會加入讓代理程式真正實用的能力。你可以賦予它工具,讓它呼叫自己的程式碼;加入記憶功能,讓它在對話期間以及重新啟動後都能記住資訊;以自己的文件為基礎,讓它根據真實來源並附上引用來回答問題;此外,也可以將人類納入流程,確保具風險的操作必須經過人工核准後才能執行。

接下來,本書會進一步介紹更進階的內容。你會透過 Model Context Protocol 將代理程式連接至外部工具與資料,並將可重複使用的能力封裝成技能(skills)。你會學習如何同時協調多個代理程式:依序執行、平行執行、在代理程式之間交接,或讓它們在群組中協作。接著,你會讓代理程式具備正式上線的條件,加入防護機制(guardrails),使用 OpenTelemetry 和 Azure Application Insights 追蹤代理程式的行為,並透過評估功能衡量其品質。最後,你會讓代理程式彼此連接並託管於 Azure,並在最後一章整理建置耐用且可靠之代理程式時,從實務經驗中淬鍊出的最佳實務。

本書中的所有內容都能實際執行。每段程式碼都是可以建置與執行的真實程式,而配套的 GitHub repository 則提供每章的完整原始碼。本書全程固定使用同一個框架版本,因此程式碼能如書中所示正常運作,不會因版本變動而逐漸過時。每章都遵循相同的實務節奏:這是要解決的問題、這是程式碼、這是實際執行的結果,以及這是在正式環境中需要注意的事項。

你將學會:

• 部署模型,並讓代理程式能夠呼叫自己的程式碼
• 加入記憶功能,透過檢索(retrieval)以自己的文件為回答依據,並要求高風險步驟經過人工核准
• 使用 Model Context Protocol 和可重複使用的技能擴充代理程式
• 協調多個代理程式:循序執行、並行執行、交接、群組聊天,以及 Magentic orchestration
• 加入防護機制,並使用 OpenTelemetry 和 Azure Application Insights 追蹤代理程式
• 評估代理程式品質、讓代理程式彼此連接,並使用 Azure 在雲端託管代理程式

本書適合的讀者:

想使用 C# 建置真正 AI 代理程式的 .NET 開發人員。你應熟悉 C#,並且曾經使用過雲端服務。不需要具備機器學習背景;你會部署並呼叫模型,而不是訓練模型。

作者簡介

Sarat Piridi is a Microsoft-certified Solution Architect and AI Transformation Leader with more than 14 years of experience in enterprise automation and intelligent systems. He holds multiple Microsoft credentials, including the Microsoft Certified: AI Transformation Leader and Microsoft Certified: Agentic AI Business Solutions Architect, along with Power Platform and Azure expert certifications.

He is the author of GovOps with Microsoft Power Platform and Copilot: Automating Governance and has published multiple research papers and white papers on agentic AI, hyper automation, and enterprise-scale digital transformation. Sarat actively contributes to the global tech community as a speaker, reviewer, and advisor, focusing on modernizing public-sector and enterprise systems using AI and Microsoft technologies.

作者簡介(中文翻譯)

Sarat Piridi 是一位獲 Microsoft 認證的 Solution Architect 與 AI Transformation Leader,在企業自動化和智慧系統領域擁有超過 14 年的經驗。他持有多項 Microsoft 認證,包括 Microsoft Certified: AI Transformation Leader 和 Microsoft Certified: Agentic AI Business Solutions Architect,以及 Power Platform 和 Azure 專家級認證。

他是《GovOps with Microsoft Power Platform and Copilot: Automating Governance》一書的作者,並曾發表多篇關於代理式 AI(agentic AI)、超級自動化(hyper automation)和企業級數位轉型的研究論文與白皮書。Sarat 積極以演講者、審稿人和顧問的身分參與全球技術社群,專注於運用 AI 與 Microsoft 技術,推動公共部門和企業系統的現代化。