GenAI_Agents README

The project's README from github.com/NirDiamant/GenAI_Agents. As one markdown file: README.md.

PRs Welcome LinkedIn Reddit Twitter Discord

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

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. 20 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 a full module, free

🎬
7-minute
video lecture		 🛠️
Hands-on
tutorial		 🤖
AI assistant
inside Claude Code

One npm install adds the module's AI assistant to your Claude Code, and it guides you through the tutorial as you build.

Claim your free module

👉 Get the full course

🏆 Sponsors

CodeRabbit      Qodo

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

📫 Stay Updated!

🚀
Cutting-edge
Updates		 💡
Expert
Insights		 🎯
Top 0.1%
Content

Subscribe to DiamantAI Newsletter

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!

DiamantAI's newsletter

🎬 Prefer video?

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


🆕 AI Agents Are Just While Loops. That's the Scary Part.
the smallest real agent, the trap it builds for itself, and where a rule has to live — run the agent from the video


How LLMs Actually Work (and Why AI Makes Things Up)
recalling a fact and inventing one are literally the same move
Context Is the New Code
the shift from writing the code to shaping what the model sees
Stop Thinking Claude Code Is Magic. Here's How It Works
what the agent loop is actually doing on every turn

Subscribe on YouTube   Browse every episode →

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.

📚 Learn to Build Your First AI Agent

Your First AI Agent: Simpler Than You Think

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.

💡 Plus: Subscribe to the newsletter for exclusive early access to tutorials and special discounts on upcoming courses and books!

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.

🔍 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.

r/EducationalAI · Discord · LinkedIn

Key Features

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.

⭐ Featured tutorial Document Intake Agent LangGraph Office docs to LLM-ready markdown, conversion as a tool call, grounded answers
# Category Agent Name Framework Key Features
1 🌱 Beginner Simple Conversational Agent LangChain/PydanticAI Context-aware conversations, history management
2 🌱 Beginner Simple Question Answering LangChain Query understanding, concise answers
3 🌱 Beginner Simple Data Analysis LangChain/PydanticAI Dataset interpretation, natural language queries
4 🔧 Framework Introduction to LangGraph LangGraph Modular AI workflows, state management
5 🔧 Framework Model Context Protocol (MCP) MCP AI-external resource integration
6 🎓 Educational ATLAS: Academic Task System LangGraph Multi-agent academic planning, note-taking
7 🎓 Educational Scientific Paper Agent LangGraph Literature review automation
8 🎓 Educational Chiron - Feynman Learning LangGraph Adaptive learning, checkpoint system
9 💼 Business Customer Support Agent LangGraph Query categorization, sentiment analysis
10 💼 Business Essay Grading Agent LangGraph Automated grading, multiple criteria
11 💼 Business Travel Planning Agent LangGraph Personalized itineraries
12 💼 Business GenAI Career Assistant LangGraph Career guidance, learning paths
13 💼 Business Project Manager Assistant LangGraph Task generation, risk assessment
14 💼 Business Contract Analysis Assistant LangGraph Clause analysis, compliance checking
15 💼 Business E2E Testing Agent LangGraph Test automation, browser control
16 🎨 Creative GIF Animation Generator LangGraph Text-to-animation pipeline
17 🎨 Creative TTS Poem Generator LangGraph Text classification, speech synthesis
18 🎨 Creative Music Compositor LangGraph AI music composition
19 🎨 Creative Content Intelligence LangGraph Multi-platform content generation
20 🎨 Creative Business Meme Generator LangGraph Brand-aligned meme creation
21 🎨 Creative Murder Mystery Game LangGraph Procedural story generation
22 📊 Analysis Memory-Enhanced Conversational LangChain Short/long-term memory integration
23 📊 Analysis Multi-Agent Collaboration LangChain Historical research, data analysis
24 📊 Analysis Self-Improving Agent LangChain Learning from interactions
25 📊 Analysis Task-Oriented Agent LangChain Text summarization, translation
26 📊 Analysis Internet Search Agent LangChain Web research, summarization
27 📊 Analysis Research Team - Autogen AutoGen Multi-agent research collaboration
28 📊 Analysis Sales Call Analyzer LangGraph Audio transcription, NLP analysis
29 📊 Analysis Weather Emergency System LangGraph Real-time data processing
30 📊 Analysis Self-Healing Codebase LangGraph Error detection, automated fixes
31 📊 Analysis DataScribe LangGraph Database exploration, query planning
32 📊 Analysis Memory-Enhanced Email LangGraph Email triage, response generation
33 📰 News News TL;DR LangGraph News summarization, API integration
34 📰 News AInsight LangGraph AI/ML news aggregation
35 📰 News Journalism Assistant LangGraph Fact-checking, bias detection
36 📰 News Blog Writer OpenAI Swarm Collaborative content creation
37 📰 News Podcast Generator LangGraph Content search, audio generation
38 🛍️ Shopping ShopGenie LangGraph Product comparison, recommendations
39 🛍️ Shopping Car Buyer Agent

GenAI_Agents (NirDiamant/GenAI_Agents)

Searching Database…

24.6K ·GitHub
GenAI_Agents
这是什么东西?一套包含 50 多个生成式 AI 智能体技术的教程和实现，从基础的对话机器人到复杂的多智能体系统，都以可以动手实践的 Python 笔记本形式提供。
那它是要安装的库吗，还是说我实际拿到的是什么?都不是——它是一个由独立 Jupyter 笔记本教程组成的目录。每个笔记本用 Python 实现一种智能体技术，你可以阅读、运行并加以改造。
我该怎么上手其中一个?从 README 里的分类表格中选一个智能体，然后在 Jupyter 中打开它的笔记本——每个都是一步步的教程，带有自己的代码和说明文档。
我需要提前会 LangChain 或 LangGraph 吗?不需要——这条学习路线从基于 LangChain 和 PydanticAI 的入门级智能体开始，还包含框架入门内容，比如 LangGraph 介绍和模型上下文协议(Model Context Protocol)。
这东西我能拿去上线部署吗，还是纯粹用来学习?它是学习资源，不是产品——没有什么可安装或部署的东西，因为每个笔记本都是一种独立的技术。如果要上生产环境，作者推荐去看另一个单独的 Agents Towards Production 仓库。
这些教程是给新手的，还是给已经在做智能体的人看的?两者都有——这个合集从简单的对话智能体一直到高级的多智能体系统，无论是刚接触 AI 的新手还是经验丰富的从业者都适合。
我能学到构建哪些类型的智能体?都是覆盖各类场景的实用智能体:商务类(客户支持、旅行规划、合同分析)、创意类(音乐作曲、表情包生成器、谋杀悬疑游戏)、分析类(自我修复代码库、销售通话分析器)，还有 ShopGenie 这类新闻和购物智能体。
它教哪些智能体框架?主要是 LangChain 和 LangGraph，另外还有关于 PydanticAI、AutoGen、OpenAI Swarm 的教程，以及用于把 AI 连接到外部资源的模型上下文协议(MCP)。
这个合集还在持续更新吗?是的——目前列出了 55 个教程而且还在增加，最近新增的内容包括基于追踪的智能体评估(Trace-Based Agent Evaluation)、人在环审批智能体(Human-in-the-Loop Approval Agent)、文档接收智能体(Document Intake Agent)，以及使用 LightRAG 的艺术导览智能体(Art Tourguide with LightRAG)。
作者还有其他值得了解的类似仓库吗?有——包含 40 多个检索增强生成笔记本的 RAG Techniques、面向生产级智能体的 Agents Towards Production、提示词工程技巧(Prompt Engineering Techniques)，以及包含 30 个笔记本的 Agent Memory Techniques，内容涵盖向量数据库、图结构、Mem0 和 Zep。
What are similar projects?ai-agents-the-definitive-guide, agents-towards-production, agentic-rag-for-dummies, 500-AI-Agents-Projects, adk-python, awesome-llm-apps, RAG_Techniques, ai-engineering-hub
Which topics is it in?genai, langgraph, tutorials, human-in-the-loop, llms, multi-agent-systems, langchain, autonomous-agents, jupyter notebook, chatbot, rag, agentic-ai
Creator
NirDiamant
Size
259.1 MB
Stars
24.6K
Updated
CommitOct 17
Age
2y
Commits · 90 Days