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Note First chapters (free) available in the Manning Early Access Program (MEAP) .

Multi-Agent Systems with Autogen

How to think about, build, evaluate and deploy multi-agent apps

Multi-agent systems are the next frontier for building generative AI applications - Andrew Ng, 2024 . However, many questions arise—how do we design these systems? When should we use them? How can we effectively integrate them into end-user applications? InMulti-Agent Systems with AutoGen author Victor Dibia draws on experience building and maintaining AutoGen and AutoGen Studio - the leading OSS tools for building multi-agent systems - to provide a comprehensive guide to building, evaluating, and deploying multi-agent systems.
You'll learn about:
  • Core components for multi-agent systems and their implementation
  • UX design principles for multi-agent systems
  • Building agents to interact with various interface (web, mobile, desktop)
  • Evaluating systems using benchmarks like GAIA and SWEBench
  • Performance optimization through tuning and parallel processing
  • Use cases like data analysis, customer service, and creativity workflows
screenshot for Victor Dibia, book author
A book by
Victor Dibia, PhD
use mldibia for 50% discount (ends August 5)
screenshot for Victor Dibia, book author

published by Manning Publications

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AutoGen is used by thousands of developers

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“Few months ago I had mixed feelings on Microsoft AutoGen. I tried it again after seeing Matthew Berman video on AutoGen Studio https://lnkd.in/d7Hse2Tg My reaction was 🤩🤩🤩 Thanks to the Microsoft Research team for the great job! I see incredible improvements and real life usage scenarios!”

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“The same reason autogen is significant is the same reason OOP is a good idea. Autogen packages up all that complexity into an agent I can create in one line, or modify with another.”

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Book Chapter Guide

Available book chapters can be viewed on the Manning Early Access Program website here.
Note: Parts of this outline may change as the book is written.
1
Understanding Multi-Agent Systems
  • What is a Multi-Agent System (MAS)?
  • Why use multiple agents? A complex task perspective
  • Why Now?
  • Patterns in Building Multi-Agent Systems
  • Components of a Multi-Agent System
  • AutoGen - A framework for building Multi-Agent Systems
  • When to and when not to use a Multi-Agent Approach
  • Summary
  • 2
    Building Your First Multi-Agent Application
  • The AutoGen API
  • Conversational programming
  • Defining an Agent Workflow in AutoGen
  • Giving agents access to tools
  • Task termination strategies
  • Beyond Two Agents - Orchestrating Teams of Agents
  • Memory in agents
  • Summary
  • 3
    UX Considerations for a Multi-Agent System
  • User Interfaces - From Command-Line to Multimodal, Multi-Agent Interfaces
  • Software Engineering - From Software 1.0 (Traditional Software Development) to Software 3.0 (Autonomous Multi-Agent Systems)
  • Understanding the User: End User, and Developer Personas
  • Interactive vs Offline Multi-Agent Scenarios
  • Multi-Agent UX Design Principles
  • Summary
  • 4
    Interface Agents | Agents that Solve Tasks by Interacting with Applications
  • When Code and APIs Aren't Enough: The Role of Interface Agents
  • The Anatomy of an Interface Agent
  • Large Action Models and Action Sequence Generation
  • Interface Representation
  • Implementing an Interface Agent from Scratch
  • Challenges with Interface Agents
  • Summary
  • Multi-Agent News

    A carefully curated list of latest news research, products, and startups in the multi-agent systems field.
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      About the Authors

      Multi-Agent Systems with AutoGen is being written by leaders in the emerging field of multi-agent systems and generative AI applications.

      • Victor Dibia

        Principal Research Software Engineer, Microsoft Research

        Victor Dibia (PhD) is a Principal Research Software Engineer at Microsoft Research, where he has contributed to projects like GitHub Copilot that serves millions of customers. He is the creator of AutoGen Studio , a low-code tool for prototyping multi-agent applications, a core contributor to AutoGen, a multi-agent framework for AI applications, and LIDA, a widely used tool for automated visualizations using generative AI models. Victor holds a PhD in Information Systems from City University of Hong Kong, an MSc in Computer Science from Carnegie Mellon University and was previously at Cloudera and IBM Research.

      Frequently Asked Questions

      Can’t find the answer you’re looking for? Reach out on the Manning Livebook Page

      Is the book limited to AutoGen?
      No. Across the book, the goal is to teach core principles and AutoGen is used as a tool to illustrate these principles. We expect that these principles can be implemented in any sufficiently expressive multi-agent framework
      Is there a discount code for the book?
      Yes! You can pre-order the book from Manning Publications using the code mldibia for a 50% discount. This offer ends August 5.
      Can I use multiple models with the agents described in the book?
      Yes! AutoGen natively supports multiple generative AI model providers - OpenAI , Microsoft Azure OpenAI, Google gemini models, Anthropic , Cohere, Groq, Mistral etc. Learn more here.
      Is there a GitHub repository for the book?
      Yes! The GitHub repository for the book is available at victordibia/multiagent-systems-with-autogen. Take a look, open issues, and share your thoughts!
      What will the book cover?
      Great question! There is a chapter outline where you see what chapters are planned and completed in the book. You can view the chapter guide here
      Who is the book for?

      This book is ideal for you if you are:

      • A software developer looking to expand your skills in AI-driven applications and leverage multi-agent systems for complex problem-solving
      • An AI practitioner interested in understanding and applying multi-agent architectures within existing AI projects
      • A system architect or engineer aiming to design more efficient and sophisticated AI solutions that require orchestration of multiple AI agents
      • A technical product manager seeking a deeper understanding of multi-agent AI technologies to oversee the development of advanced AI features in products
      • A designer looking to create intuitive user interfaces that are based on a multi-agent solution stack
      Note: This book is developer-focused and practical. It is not written as theoretical academic text.
      I found some errors in the book, Can I report them?
      Yes, thank you so much! Please report any errors you find in the book to the authors via the Manning Livebook Page

      Acknowlegement

      This project has benefited from the support and contributions of many individuals, especially the members of the AutoGen Open Source Community.

      Many thanks to:
      Becky Whitney
      Chi Wang*
      Qingyun Wu
      Saleema Amershi
      Adam Fourney
      Gagan Bansal
      * previously a consulting author on the book.

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