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Mastering Multi-agent Systems with Azure OpenAI: Build, Orchestrate, and Deploy RAG-Enabled Multiple Autonomous Intelligent Agents at Scale

Name: Mastering Multi-agent Systems with Azure OpenAI: Build, Orchestrate, and Deploy RAG-Enabled Multiple Autonomous Intelligent Agents at Scale
Author: Abhishek Mishra
ISBN: 9798868828546

by Abhishek Mishra

September 2026

Intermediate

467 pages

8h 26m

English

Apress

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Mastering Multi-agent Systems with Azure OpenAI
Introduction
Acknowledgments
Table of Contents
About the Author
About the Technical Reviewer
1. Introduction
StructureObjectivesGenerative AI and Large Language ModelsIntroduction to Agentic AIPrompt EngineeringZero-Shot PromptingFew-Shot PromptingChain-of-Thought PromptingRole-Based PromptingPrompt Engineering Best PracticesEvolution of Rule-Based Agents to Agentic AISingle Agent and Multi-agentsPractical Examples of Multi-Agent-Based Agentic AIConclusion
2. Azure OpenAI
StructureObjectivesWhat Is Azure OpenAI?Overview of Supported Large Language ModelsText Generation ModelsCode Generation ModelsReasoning ModelsMulti-modal ModelsEmbedding ModelsImage Generation ModelsVideo Generation ModelsAudio ModelsCreate an Azure OpenAI ServiceCreate an Azure OpenAI Service DirectlyCreate OpenAI Service Using Microsoft FoundryAzure OpenAI and Microsoft FoundrySecuring the Azure OpenAI ServiceConclusion
3. Microsoft Foundry
StructureObjectivesDeploy a Model from the Model CatalogDeploy a Model Using Azure OpenAIDeploy a Model Using Microsoft FoundryWorking with PlaygroundPlayground in Azure OpenAI Service and Foundry PortalsPlayground in the Microsoft Foundry PortalFine-Tuning ModelsFine-Tuning Using the Azure OpenAI ServiceFine-Tuning Using Microsoft FoundryImplement GuardrailsImplement Guardrails in the Azure OpenAI ServiceImplement Guardrails in Microsoft FoundryBuild Your First AgentConclusion
4. Building AI Agents
StructureObjectivesWhat Is Microsoft Agent FrameworkAI Agent ArchitectureGetting Started with a Simple AgentEnable Multi-turn ConversationsFunction Tools to Create Agent SkillsPersist Context and ConversationCreate Agent WorkflowsConclusion

5. Building Multi-agent Systems Using Model Context Protocol and A2A
StructureObjectivesMulti-agent ArchitectureSequentialConcurrentHandoffGroup ChatMagenticModel Context ProtocolA2A ProtocolImplementing Multi-agent Systems Using Model Context Protocol and A2AConclusion
6. Building Retrieval-Augmented Generation (RAG)–Based Agent Systems
StructureObjectivesRetrieval-Augmented GenerationAgentic Retrieval-Augmented GenerationBuilding a Retrieval Agent Generation Solution Using Azure AI SearchCreate Azure AI SearchUpload the Knowledge PDF to Azure AI Search As EmbeddingsImplement RAG-Based SolutionBuilding an Agentic RAG-Based Solution Using Facebook AI Similarity Search (FAISS)Conclusion
7. Requirements and Design for Smart Travel Agent
StructureObjectivesProblem Statement for a Smart Travel AgentDefine RequirementsBuild the DesignConclusion
8. Smart Travel Agent Using LangGraph and LangChain
StructureObjectivesLangChain and LangGraphCurrent Scope of ImplementationImplement Chunking and EmbeddingImplement Tools for Smart Travel AgentImplement the Model Context Protocol (MCP) ServerImplement Agents and the Agent2Agent ServerExecute the ApplicationConclusion
9. Requirements and Design Smart Restaurant
StructureObjectivesProblem Statement for a Smart RestaurantDefine RequirementsBuild the DesignConclusion
10. Smart Restaurant Using Microsoft Agent Framework and Azure AI Search
StructureObjectivesCurrent Scope of ImplementationImplement Tools for the Smart RestaurantImplement AgentsExecute the ApplicationConclusion
11. Agentic AI Design and Implementation Guidance
StructureObjectivesSocial and Ethical AI ConsiderationsPrivacy and Data ProtectionZero Bias and Strict FairnessHuman FirstTransparent and ExplainableAdherence to Regulations Framed by Government Agencies and Statutory BodiesSustainabilityDesign Considerations While Building Agentic AI SolutionsAgent Goals and BoundariesDecide the Level of AutonomyHuman–Agent CollaborationKnowledge SourcesError Detection and FallbackEthics and ComplianceMulti-agent CollaborationMonitoring and GovernanceCost, Scalability, and PerformancePitfallsConclusion
Index

Content preview from Mastering Multi-agent Systems with Azure OpenAI: Build, Orchestrate, and Deploy RAG-Enabled Multiple Autonomous Intelligent Agents at Scale

A. MishraMastering Multi-agent Systems with Azure OpenAIhttps://doi.org/10.1007/979-8-8688-2854-6_2

2. Azure OpenAI

Abhishek Mishra¹

Large Language Models are used in modern AI applications. OpenAI platform offers a variety of Large Language Models like the popular GPT series, DALL-E, and Codex. The popular ChatGPT is an offering from OpenAI. These models are widely used to develop intelligent and smart applications across industries and cater to a wide variety of use cases. Azure OpenAI is an Azure offering of OpenAI on its platform.

This chapter deals with the concept of Azure OpenAI. We will learn ...

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Architecting Intelligent Agents in Azure : Building Agentic Systems with Python and the Microsoft Agent Framework

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Mastering Multi-agent Systems with Azure OpenAI: Build, Orchestrate, and Deploy RAG-Enabled Multiple Autonomous Intelligent Agents at Scale

by Abhishek Mishra

2. Azure OpenAI

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.