Includes index

Introduction to agents and their world -- Harnessing the power of large language models -- Engaging GPT assistants -- Exploring multi-agent systems -- Empowering agents with actions -- Building autonomous assistants -- Assembling and using an agent platform -- Understanding agent memory and knowledge -- Mastering agent prompts with prompt flow -- Agent reasoning and evaluation -- Agent planning and feedback -- Appendix A. Accessing OpenAI large language models -- Appendix B. Python development environment

In AI Agents in Action, you'll learn how to build production-ready assistants, multi-agent systems, and behavioral agents. You'll master the essential parts of an agent, including retrieval-augmented knowledge and memory, while you create multi-agent applications that can use software tools, plan tasks autonomously, and learn from experience. As you explore the many interesting examples, you'll work with state-of-the-art tools like OpenAI Assistants API, GPT Nexus, LangChain, Prompt Flow, AutoGen, and CrewAI