This project provides a bilingual open-source book on AI agent design paired with independently runnable companion demo projects across ten chapters. Readers need external LLM API keys and Python to execute the code examples.
Project overview
This project provides a bilingual open-source book on AI agent design paired with independently runnable companion demo projects across ten chapters. Readers need external LLM API keys and Python to execute the code examples.
Project type
MCP · AI Agent · RAG
Use cases
Learning & Education
Deployment
Refer to project documentation
License
Apache-2.0
Best for
Developers and AI engineers seeking hands-on, runnable code examples accompanying theoretical explanations of AI agents.
Researchers requiring bilingual educational material covering AI agent design principles and engineering practices.
Key capabilities
Provides the full text of the AI agent book in Chinese, English, and Tamil PDF versions with source markdown.
Chapter-organized companion code examples, such as search agents, context ablation, and coding agents, configured to run with an API Key.
Demo showing cross-platform local LLM deployment using vLLM or Ollama with tool calling support.
Perception, execution, and collaboration MCP server examples using the Model Context Protocol.
Event-driven async agent demo with inbox event queuing, parallel tool execution, and interruption capabilities.
Limitations and risks
Some reproduction guides depend on external repositories that must be cloned separately.
Running the companion code requires external LLM API keys, which may incur costs.
Getting started
Clone the repository, navigate to the chapterN/project-name directory, configure your LLM API Key, and run the project via Python. The setup difficulty is medium because it requires configuring API keys, cloning external repositories, and installing pandoc and LaTeX to build the PDF book.
Evidence and sources
README: 本仓库是《深入理解 AI Agent：设计原理与工程实践》一书的开源主仓库，包含**全书正文**与**配套示例代码**。全书正文、配图与配套实验代码全部开源，欢迎把实验亲手跑一遍、提 issue 和 PR。