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oreilly-ai-agents
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oreilly-ai-agents

Active·★ 322·Updated 2026-07-10

This repository serves as a comprehensive code companion for O'Reilly's AI Agents courses, guiding users from foundational concepts to advanced implementation and deployment. It explores various AI agent frameworks like LangChain, CrewAI, AutoGen, and LangGraph, alongside practical topics such as agent evaluation and building custom agents.

oreilly-ai-agents sits in the Workflow Automation category, so it is usually better judged by workflow fit, deployment style, and team needs than by isolated features alone. Based on the available metadata, it leans most clearly toward Comprehensive examples for various AI agent frameworks including CrewAI, LangChain, AutoGen, and LangGraph.. A representative use case is Developing and deploying AI agents for automating complex tasks.. GitHub stars are currently 322. Relevant tags include AI Agents, Multi-Agent Systems.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool.

#AI Agents#Multi-Agent Systems#LLM Frameworks#Workflow Automation#Agent Evaluation#Prompt Engineering#Browser Automation#Python
$ Install
$ python3.11 -m venv .venv && source .venv/bin/activate && pip install -r requirements.txt
↗ Visit site★ GitHub
01

Features

01Comprehensive examples for various AI agent frameworks including CrewAI, LangChain, AutoGen, and LangGraph.
02Practical guidance on building custom AI agents and multi-agent systems.
03Techniques for evaluating agent performance, tool selection, and output alignment.
04Demonstrations of advanced agent paradigms like Plan & Execute and Reflection.
05Exploration of browser and GUI automation with reasoning LLMs.
02

Why choose it

+Comprehensive examples for various AI agent frameworks including CrewAI, LangChain, AutoGen, and LangGraph.
+Practical guidance on building custom AI agents and multi-agent systems.
+Developing and deploying AI agents for automating complex tasks.
+Supports 5 platforms or runtime environments.
03

Trade-offs

!The final decision should still be made through side-by-side comparison with similar tools.
04

Compatibility

Python
Runtime
Verified via docs
macOS
OS
Verified via docs
Ubuntu/Debian
OS
Verified via docs
Windows
OS
Verified via docs
Jupyter Notebook
Environment
Verified via docs
05

Quick start

1
$ python3.11 -m venv .venv
2
$ source .venv/bin/activate
3
$ pip install -r requirements.txt
06

Use cases

↳Developing and deploying AI agents for automating complex tasks.
↳Orchestrating multi-agent systems for collaborative problem-solving.
↳Automating browser and GUI interactions using reasoning LLMs.
↳Implementing RAG (Retrieval-Augmented Generation) workflows with agents.
↳Evaluating and refining the performance of agentic AI systems.
07

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On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases07Alternatives
sinanuozdemir /
oreilly-ai-agents
↗

An introduction to the world of AI Agents

322
Last commit3mo ago
StatusActive
CategoryWorkflow Automation
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