GenAI Agents: Comprehensive Repository for Development and Implementation 🚀

Welcome to one of the most extensive and dynamic collections of Generative AI (GenAI) agent tutorials and implementations available today. This repository serves as a comprehensive resource for learning, building, and sharing GenAI agents, ranging from simple conversational bots to complex, multi-agent systems.

<h2 align="center">🎓 From demo agent to deployed product</h2> <div align="center">

Prompt to Production - my full course on building software with AI the way professionals do: the methods and paradigms behind reliable, efficient, modular production systems, taught systematically. 17 modules, each pairing a video lecture with a hands-on lab, from your first structured prompt to a working production system.

The course is live. Every module is out, lecture and lab.

🎁 Try it on your own repo, free

Your coding agent starts every session knowing nothing about your project, so it guesses. Paste one line into the agent you already have open, and about fifteen minutes later your repository has a docs layer written from the code itself, plus a card scoring what your agent knew before and after.

We ran it on six repositories you already depend on. Each one was asked five questions about itself, cold, then again after the layer was written. The last column counts statements in that project's own documentation that its own code disproves:

| repo | before | after | own docs its code disproves | |---|---|---|---| | fastapi | 2 of 5 | 5 of 5 | 2 | | flask | 3 of 5 | 5 of 5 | 6 | | django | 3 of 5 | 4 of 5 | 1 | | express | 2 of 5 | 4 of 5 | 4 | | requests | 2 of 5 | 4 of 5 | 0 | | langchain | 5 of 5 | 4 of 5 | 5 |

Flask's six include four documentation examples that raise TypeError when you run them. Langchain scored lower afterwards, because it already ships a 380-line agent instruction file and the cold read was grading theirs; that row is in the table anyway.

Clone any of those repos, paste the same line, and check the number yourself. No signup.

<a href="https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=genai-agents--readme&click=course-free-module-direct&target=https%3A%2F%2Fp2p-course.diamant-ai.com%2Flectures%2F00-present%3Futm_source%3Dgithub%26utm_medium%3Dreadme%26utm_campaign%3Dgenai-agents-direct&retarget=0&text=course-free-module-direct"><img src="images/free-module-button.svg" alt="Claim your free module" width="420"></a>

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Recently added: Trace-Based Agent Evaluation, Human-in-the-Loop Approval Agent, Document Intake Agent, HR AI Assistant, Art Tourguide with LightRAG | 55 tutorials and growing

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<h2 align="center">🎬 Prefer video?</h2> <div align="center">

I break these ideas down into short, one-idea-per-episode explainers on YouTube.

<p align="center"> <a href="https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=genai-agents--readme&amp;click=youtube-readme-loop&amp;target=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DFN1n_NVD9KM%26list%3DPLBrpE2PttR2k&amp;retarget=0&amp;text=youtube-readme-loop"> <img src="https://img.youtube.com/vi/FN1n_NVD9KM/maxresdefault.jpg" width="60%" alt=""> <br><b>🆕 AI Agents Are Just While Loops. That's the Scary Part.</b> </a><br> _{the smallest real agent, the trap it builds for itself, and where a rule has to live — <a href="all_agents_tutorials/agent_while_loop_from_scratch.ipynb">run the agent from the video</a>} </p> <table> <tr> <td width="33%" align="center" valign="top"> <a href="https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=genai-agents--readme&amp;click=youtube-readme-llm&amp;target=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DtKXvKKVQ1Dc&amp;retarget=0&amp;text=youtube-readme-llm"> <img src="https://img.youtube.com/vi/tKXvKKVQ1Dc/mqdefault.jpg" width="100%" alt=""> <br><b>How LLMs Actually Work (and Why AI Makes Things Up)</b> </a><br> _{recalling a fact and inventing one are literally the same move} </td> <td width="33%" align="center" valign="top"> <a href="https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=genai-agents--readme&amp;click=youtube-readme-ctx&amp;target=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3Da7bteK6c3Ng&amp;retarget=0&amp;text=youtube-readme-ctx"> <img src="https://img.youtube.com/vi/a7bteK6c3Ng/mqdefault.jpg" width="100%" alt=""> <br><b>Context Is the New Code</b> </a><br> _{the shift from writing the code to shaping what the model sees} </td> <td width="33%" align="center" valign="top"> <a href="https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=genai-agents--readme&amp;click=youtube-readme-cc&amp;target=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3D0fU8GdipOjc&amp;retarget=0&amp;text=youtube-readme-cc"> <img src="https://img.youtube.com/vi/0fU8GdipOjc/mqdefault.jpg" width="100%" alt=""> <br><b>Stop Thinking Claude Code Is Magic. Here's How It Works</b> </a><br> _{what the agent loop is actually doing on every turn} </td> </tr> </table>

  Browse every episode →

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Introduction

Generative AI agents are at the forefront of artificial intelligence, revolutionizing the way we interact with and leverage AI technologies. This repository is designed to guide you through the development journey, from basic agent implementations to advanced, cutting-edge systems.

<div align="center"> <table> <tr> <td> <h3>📚 Learn to Build Your First AI Agent</h3> <p><strong><a href="https://newsletter.diamant-ai.com/p/your-first-ai-agent-simpler-than">Your First AI Agent: Simpler Than You Think</a></strong></p> <p>This detailed blog post complements the repository by providing a complete A-Z walkthrough with in-depth explanations of core concepts, step-by-step implementation, and the theory behind AI agents. It's designed to be incredibly simple to follow while covering everything you need to know to build your first working agent from scratch.</p> <p><em>💡 Plus: Subscribe to the newsletter for exclusive early access to tutorials and special discounts on upcoming courses and books!</em></p> </td> </tr> </table> </div>

Our goal is to provide a valuable resource for everyone - from beginners taking their first steps in AI to seasoned practitioners pushing the boundaries of what's possible. By offering a range of examples from foundational to complex, we aim to facilitate learning, experimentation, and innovation in the rapidly evolving field of GenAI agents.

Furthermore, this repository serves as a platform for showcasing innovative agent creations. Whether you've developed a novel agent architecture or found an innovative application for existing techniques, we encourage you to share your work with the community.

Related Projects

🔍 RAG Techniques - 40+ notebooks on retrieval-augmented generation.

🚀 Agents Towards Production - code-first tutorials for shipping production-grade agents.

🖋️ Prompt Engineering Techniques - prompting strategies from basics to advanced.

🧠 Agent Memory Techniques - 30 notebooks on agent memory: vector stores, graphs, Mem0, Zep.

Join the community

Contributions make this better - propose ideas, share techniques, or give feedback via CONTRIBUTING.md.

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Key Features

• 🎓 Learn to build GenAI agents from beginner to advanced levels
• 🧠 Explore a wide range of agent architectures and applications
• 📚 Step-by-step tutorials and comprehensive documentation
• 🛠️ Practical, ready-to-use agent implementations
• 🌟 Regular updates with the latest advancements in GenAI
• 🤝 Share your own agent creations with the community

GenAI Agent Implementations

Below is a comprehensive overview of our GenAI agent implementations, organized by category and functionality. Each implementation is designed to showcase different aspects of AI agent development, from basic conversational agents to complex multi-agent systems.

<table width="100%"> <tr style="background-color:#FBF3DB"> <td width="4%" align="center">⭐</td> <td width="14%"><img src="https://img.shields.io/badge/⭐_FEATURED-D9B44A" height="20" alt="Featured tutorial">