Home/AI Agents/ai-agent-book
ai-agent-book logo

ai-agent-book

bojieli/ai-agent-book

A book on AI Agent design principles and engineering practices, including 109 accompanying experiments.

GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026

19views this month

48k stars5.4k forksLast push Sep 18, 2026 Python Apache-2.0

Decision brief

ai-agent-book is a comprehensive resource on AI Agent design principles and engineering practices, featuring 109 experiments and available in 15 languages.

Good fit when

  • Use ai-agent-book when you need a detailed guide on AI Agent design, from theory to practical implementation, especially if you are interested in the formula Agent = LLM + Context + Tools.
  • Consider ai-agent-book if you are looking for a resource that includes a significant number of practical experiments (109) to complement the theoretical knowledge.

Avoid when

  • Avoid ai-agent-book if you are seeking a resource that focuses solely on theoretical aspects of AI Agents without practical implementation details.
  • Do not use ai-agent-book if you are looking for a tool that provides real-time updates or interactive features beyond the static PDF and EPUB formats.

Observed Sep 18, 2026 · Source: enrich:decision_facts

Verify the decision

Maintenance and security

Full trust report
Maintenance
Very active (0d since push)
As of Sep 18, 2026
Provenance
Not a fork · Personal account
As of Sep 18, 2026
Security (OSV)
2 low (2 low)
As of Sep 18, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install ai-agent-book
PyPI

How it fits your stack(4)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Similar tools

Same-category neighbours not already linked as typed edges.

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

This repository contains the full text, compiled PDF, and chapter-specific code for the book 'Deep Understanding of AI Agents: Design Principles and Engineering Practices'. It covers AI Agent design from theory to practical implementation, with a focus on the formula Agent = LLM + Context + Tools.

Capability facts

Languages
python

Source: github.language+pyproject.toml · Sep 18, 2026

Categories

Tags

README

深入理解 AI Agent:设计原理与工程实践 中文 ← 当前 · English · Español · Bahasa Indonesia · العربية · 繁體中文(台灣) · Русский · Tiếng Việt · தமிழ் · 日本語 · Türkçe · 한국어 · Magyar · עברית · Português (Brasil) 📥 下载 PDF / EPUB (推荐)— 推荐使用 PDF / EPUB 离线阅读,排版最佳;也可在线阅读(支持多语言切换、章节折叠、高亮与笔记,每次推送自动更新)。 Agent = LLM...

For agents

This page has a .md twin and JSON over the API.

Was this helpful?

Anonymous feedback helps us improve pages and translations.