A comprehensive guide to building production-ready AI agents and multi-agent systems
Welcome to Agentic-AI-Systems — a curated and evolving knowledge base for mastering Agentic and Generative AI system design! This repository is a collection of resources and examples that I have found useful in my journey of building agentic AI systems.
| Chapter | Description |
|---|---|
| 1. Foundations | GenAI concepts and design, LLMs, evaluation, modern Python, and more. |
| 2. Frameworks | Tutorials and example codes for OpenAI, LangGraph, LlamaIndex, LangChain, CrewAI, Chainlit, and more. |
| 3. Agentic System Design | Agentic AI System Design: Architectures, layers, design patterns, diagrams, and code. |
| 4. Use Cases | Real-world and example agent projects and applications. |
| 5. Resources | Courses, tool stacks, protocols, and list of resources. |
- Agentic AI Design Patterns: A comprehensive overview of reusable design patterns in Gen-AI and agentic AI systems.
- RAGs: A comprehensive overview of RAG architectures, including basic RAGs, agentic RAGs, multi-modal RAGs, and advanced RAGs.
- Cookbooks: A comprehensive overview of the most useful cookbooks in designing and building agentic AI systems.
- OpenAI Agents: Comprehensive guides, tutorials, and code examples for building AI agents using the OpenAI API and Agents SDK.
- Architectures: A comprehensive overview of architectures in agentic AI systems, inlcuding architecture layers, AI-native architectures, step-by-step system design, and example architectures used by tech companies.
- Agentic AI Evaluation: A comprehensive overview of evaluating Agentic AI Systems, including evaluation layers, dimensions, methods, and frameworks.
- Code Examples: Step-by-step guides, example codes, and tutorials for building agentic workflows with Open AI agents, LangGraph, LangChain, CrewAI, LlamaIndex, and more.
- Multi-Agent Systems Examples: Building multi-agent systems using LlamaIndex, Crew AI, and more.
- Resource Library: Curated list of courses, tools, protocols, and further reading.
- AI Engineering Book Summary: GenAI system workflows and infrastructure.
- Gen-AI Systems Overview: Platform architecture and technical breakdowns.
- Gen-AI Evaluation Methods: Score-based evaluation methods and tools.
- Practical: Real code, real projects, real-world patterns
- Curated: Only the most useful frameworks, tools, and concepts
- Reference-first: Designed for quick lookup and deep dives
- Production-ready: Tested examples with deployment guides
- Community-driven: Continuously updated with latest best practices
🔜 More coming soon — contributions welcome! You can start by forking and submitting your own code-based experiments.
Pull requests are welcome! If you'd like to add new frameworks, examples, or summaries, fork the repo and submit a PR.
Made with ❤️ by Alireza Dirafzoon.