<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> This repository provides comprehensive materials for "Agentic Design Patterns: A Hands-On Guide to Building Intelligent Systems," authored by Antonio Gulli. It offers a structured curriculum for learning to build sophisticated AI agent systems, targeting engineers and researchers. The benefit lies in its practical, code-driven approach to mastering complex agentic patterns.

How It Works

The project delivers a complete guide through 21 PDF chapters and accompanying Jupyter notebooks. It systematically covers foundational patterns like prompt chaining and routing, advanced techniques such as reflection and tool use, and production-ready patterns including RAG and human-in-the-loop systems. The approach emphasizes hands-on implementation via code examples, enabling deep understanding and practical application of AI agent design principles.

Quick Start & Requirements

• Installation: Clone the repository (git clone https://github.com/evoiz/Agentic-Design-Patterns.git), set up a virtual environment, and install dependencies (pip install -r requirements.txt).
• Prerequisites: Python 3.8 or higher, Jupyter Notebook. Specific notebooks may require API keys (e.g., OpenAI).
• Running: Launch Jupyter Notebook (jupyter notebook) and navigate to the chapter_notebooks/ directory to run individual chapter examples.
• Resources: Official documentation is embedded within the README structure, with links to the author's LinkedIn and original Google Drive materials.

Highlighted Details

• Covers 21 chapters and 7 appendices detailing core, advanced, production, and enterprise patterns for AI agents.
• Includes a 424-page PDF book and practical Jupyter notebooks for each chapter.
• Author donates all royalties to Save the Children.
• Topics span prompt chaining, multi-agent systems, reflection, tool use, planning, RAG, guardrails, and human-in-the-loop workflows.
• A suggested learning path guides users from beginner to expert levels.

Maintenance & Community

The repository welcomes community contributions for bug reports, feature suggestions, documentation improvements, and code enhancements. Primary community interaction channels are GitHub Issues and Discussions. The author, Antonio Gulli, can be reached via LinkedIn.

Licensing & Compatibility

Book content is copyrighted by Antonio Gulli, with educational use permitted under attribution. Code examples are provided under the MIT License, which is generally permissive for commercial use and integration into closed-source projects.

Limitations & Caveats

The README does not detail specific limitations, alpha status, or known bugs. Users should be aware that some notebooks may require external API keys for full functionality, and the book content is restricted to educational purposes.