50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
GenAI Agents is a collection of 52 Jupyter Notebook tutorials covering the construction of AI agents from single-purpose conversational bots up to coordinated multi-agent systems. Notebooks are organized by complexity and cover techniques including Retrieval-Augmented Generation, LangGraph-based orchestration, memory management, tool use, and agentic loops, with concrete examples such as an HR AI Assistant, an Art Tourguide built on LightRAG, a Contextual Quoting System, and a Gutenberg Sage literary agent. The repository is LLM-agnostic in framing but leans on OpenAI and LangChain throughout; Claude integration is not a stated focus, though the MCP topic tag signals awareness of that protocol. Developers and researchers learning to build production-adjacent agents are the primary audience, with beginner-friendly walkthroughs sitting alongside advanced multi-agent pipeline designs. A notable detail is that the author accompanies the code with a companion newsletter reaching over 50,000 subscribers and a related 400-page book on RAG, positioning the repository as the practical arm of a broader educational curriculum.
- ✓License: NOASSERTION
- ✓Actively maintained (<30d)
- ✓Healthy fork ratio
- ✓Clear description
- ✓Topics declared
- ✓Mature repo (>1y old)
git clone https://github.com/NirDiamant/GenAI_Agents && cp GenAI_Agents/*.md ~/.claude/agents/Resumen de Subagents
[](http://makeapullrequest.com) [](https://www.linkedin.com/in/nir-diamant-759323134/) [](https://www.reddit.com/r/EducationalAI/) [](https://twitter.com/NirDiamantAI) [](https://discord.gg/cA6Aa4uyDX) # 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. ## 🎓 From demo agent to deployed product <div align="center"> **[Prompt to Production](https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=genai-agents--readme&click=course-waitlist-cta&target=https%3A%2F%2Fdiamant-ai.com%2Fcourse-waitlist%3Futm_source%3Dgithub%26utm_medium%3Dreadme%26utm_campaign%3Dgenai-agents&retarget=0&text=course-waitlist-cta)** - my full course on building software with AI the way professionals do: the methods and paradigms behind reliable, efficient, modular production systems, taught systematically. 16 lectures, each with a hands-on lab, from your first structured prompt to a working production system. **[Join the waiting list →](https://europe-west1-rag-techniques-views-tracker.cloudfunctions.net/rag-techniques-tracker?notebook=genai-agents--readme&click=course-waitlist-cta&target=https%3A%2F%2Fdiamant-ai.com%2Fcourse-waitlist%3Futm_source%3Dgithub%26utm_medium%3Dreadme%26utm_campaign%3Dgenai-agents&retarget=0&text=course-waitlist-cta)** · everyone on the list locks in the founding price, lower than public launch </div> ## 🏆 Sponsors <div align="center"> <a href="https://coderabbit.link/nir"><img src="images/coderabbit_Light_Type_Mark_Orange.png" height="80" alt="CodeRabbit" /></a> </div> > **Recently added:** HR AI Assistant, Art Tourguide with LightRAG, Contextual Quoting System, ML/DS Assistant, Gutenberg Sage | **52 tutorials** and growing ## 📫 Stay Updated! <div align="center"> <table> <tr> <td align="center">🚀<br><b>Cutting-edge<br>Updates</b></td> <td align="center">💡<br><b>Expert<br>Insights</b></td> <td align="center">🎯<br><b>Top 0.1%<br>Content</b></td> </tr> </table> [](https://diamantai.substack.com/?r=336pe4&utm_campaign=pub-share-checklist) *Join over 50,000 AI enthusiasts getting unique cutting-edge insights and free tutorials!* ***Plus, subscribers get exclusive early access and special 33% discounts to my book and the upcoming RAG Techniques course!*** </div> [](https://diamantai.substack.com/?r=336pe4&utm_campaign=pub-share-checklist) ## 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://diamantai.substack.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](https://github.com/NirDiamant/RAG_Techniques)** - 40+ notebooks on retrieval-augmented generation. 🚀 **[Agents Towards Production](https://github.com/NirDiamant/agents-towards-production)** - code-first tutorials for shipping production-grade agents. 🖋️ **[Prompt Engineering Techniques](https://github.com/NirDiamant/Prompt_Engineering)** - prompting strategies from basics to advanced. 🧠 **[Agent Memory Techniques](https://github.com/NirDiamant/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](https://github.com/NirDiamant/GenAI_Agents/blob/main/CONTRIBUTING.md)**. **[r/EducationalAI](https://www.reddit.com/r/EducationalAI/)** · **[Discord](https://discord.gg/cA6Aa4uyDX)** · **[LinkedIn](https://www.linkedin.com/in/nir-diamant-759323134/)** ## 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. | # | Category | Agent Name | Framework | Key Features | |----|-------------------|-------------------------------|-------------------|------------------------------------------------------------------------------| | 1 | 🌱 **Beginner** | [Simple Conversational Agent](all_agents_tutorials/simple_conversational_agent.ipynb) | LangChain/PydanticAI | Context-aware conversations, history management | | 2 | 🌱 **Beginner** | [Simple Question Answering](all_agents_tutorials/simple_question_answering_agent.ipynb) | LangChain | Query understanding, concise answers | | 3 | 🌱 **Beginner** | [Simple Data Analysis](all_agents_tutorials/simple_data_analysis_agent_notebook.ipynb) | LangChain/PydanticAI | Dataset interpretation, natural language queries | | 4 | 🔧 **Framework** | [Introduction to LangGraph](all_agents_tutorials/langgraph-tutorial.ipynb) | LangGraph | Modular AI workflows, state management | | 5 | 🔧 **Framework** | [Model Context Protocol (MCP)](all_agents_tutorials/mcp-tutorial.ipynb) | MCP | AI-external resource integration | | 6 | 🎓 **Educational**| [ATLAS: Academic Task System](all_agents_tutorials/Academic_Task_Learning_Agent_LangGraph.ipynb) | LangGraph | Multi-agent academic planning, note-taking | | 7 | 🎓 **Educational**| [Scientific Paper Agent](all_agents_tutorials/scientific_paper_agent_langgraph.ipynb) | LangGraph | Literature review automation | | 8 | 🎓 **Educational**| [Chiron - Feynman Learning](all_agents_tutorials/chiron_learning_agent_langgraph.ipynb) | LangGraph | Adaptive learning, checkpoint system | | 9 | 💼 **Business** | [Customer Support Agent](all_agents_tutorials/customer_support_agent_langgraph.ipynb) | LangGraph | Query categorization, sentiment analysis | | 10 | 💼 **Business** | [Essay Grading Agent](all_agents_tutorials/essay_grading_system_langgraph.ipynb) | LangGraph | Automated grading, multiple criteria | | 11 | 💼 **Business** | [Travel Planning Agent](all_agents_tutorials/simple_travel_planner_langgraph.ipynb) | LangGraph | Personalized itineraries | | 12 | 💼 **Business** | [GenAI Career Assistant](all_agents_tutorials/agent_hackathon_genAI_career_assistant.ipynb) | LangGraph | Career guidance, learning paths | | 13 | 💼 **Business** | [Project Manager Assistant](all_agents_tutorials/project_manager_assistant_agent.ipynb) | LangGraph | Task generation, risk assessment | | 14 | 💼 **Business** | [Contract Analysis Assistant](all_agents_tutorials/ClauseAI.ipynb) | LangGraph | Clause analysis, compliance checking | | 15 | 💼 **Business** | [E
Lo que la gente pregunta sobre GenAI_Agents
¿Qué es NirDiamant/GenAI_Agents?
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NirDiamant/GenAI_Agents es subagents para el ecosistema de Claude AI. 50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems. Tiene 22.5k estrellas en GitHub y se actualizó por última vez yesterday.
¿Cómo se instala GenAI_Agents?
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Puedes instalar GenAI_Agents clonando el repositorio (https://github.com/NirDiamant/GenAI_Agents) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
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Nuestro agente de seguridad ha analizado NirDiamant/GenAI_Agents y le ha asignado un Trust Score de 100/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
¿Quién mantiene NirDiamant/GenAI_Agents?
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NirDiamant/GenAI_Agents es mantenido por NirDiamant. La última actividad registrada en GitHub es de yesterday, con 8 issues abiertos.
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Sí. En ClaudeWave puedes explorar subagents similares en /categories/agents, ordenados por popularidad o actividad reciente.
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