"Large Model Application Development: Hands-On AI Agent" is a book about the development and practice of AI Agent technology.
Purpose: This book aims to help readers understand and master the design and implementation of AI Agents, and through hands-on practice with 7 powerful Agent projects, comprehensively analyze the technical frameworks, development tools, and practical applications of Agents.
Main capabilities: The book involves cutting-edge technologies such as the GPT-4 model, OpenAI API and Assistants, LangChain, LlamaIndex, and MetaGPT, and explores the performance of Agents in fields such as office automation, intelligent scheduling, knowledge integration, and retrieval-augmented generation (RAG).
How to use: Readers follow in the footsteps of the author Kage and Xiaoxue, learning Agent development through hands-on projects. In a Douban comment, the author provided a GitHub link for code and errata:https://github.com/huangjia2019/ai-agents。作者也指出，书中大量调用OpenAI API, readers can replace it themselves with domestic large models such as Qwen, Zhipu, MiniMax, Deepseek, etc., and the basic program architecture can remain unchanged.
Applicable scenarios: Suitable for researchers, developers, and business leaders interested in or committed to entering the field of Agent technology, as well as teachers and students of related majors in higher education institutions.
Limitations: The author mentioned in a comment that some readers criticized the book as "written relatively superficially" and "impetuous," like a blog; at the same time, heavily calling the OpenAI API may cause inconvenience for readers. In addition, some readers reported that technology iterates too quickly.
