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Hello-Agents

🤖 "Building Agent Systems from Scratch"

From foundational theory to practical applications, master the design and implementation of agent systems

🎯 Project Introduction

  If 2024 was the year of the "Battle of a Hundred Models," then 2025 has undoubtedly ushered in the "Year of Agents." The focus of technology is shifting from training larger foundation models to building smarter agent applications. However, systematic, practice-oriented tutorials are extremely scarce. For this reason, we launched the Hello-Agents project, hoping to provide the community with a comprehensive guide to building agent systems from scratch, balancing theory and practice.

  Hello-Agents is a systematic agent learning tutorial from the Datawhale community. Today, agent development is mainly divided into two schools: one is software engineering-oriented agents like Dify, Coze, and n8n, which are essentially process-driven software development with LLMs serving as data processing backends; the other is AI-native agents, truly AI-driven agents. This tutorial aims to lead you to deeply understand and build the latter—truly AI Native Agents. The tutorial will guide you through the surface of frameworks, starting from the core principles of agents, delving into their core architecture, understanding their classic paradigms, and ultimately building your own multi-agent applications. We believe that the best way to learn is through hands-on practice. We hope this tutorial can be your starting point for exploring the world of agents, transforming you from a "user" of large language models to a "builder" of agent systems.

📚 Quick Start

Online Reading

🌐 Click here to start reading online - No download required, learn anytime, anywhere

📖 Cookbook

Local Reading

If you wish to read locally or contribute content, please refer to the learning guide below.

✨ What Will You Gain?

• 📖 Datawhale Open Source & Free - Learn all project content completely free, grow with the community
• 🔍 Understand Core Principles - Deeply understand agent concepts, history, and classic paradigms
• 🏗️ Hands-on Implementation - Master popular low-code platforms and agent code frameworks
• 🛠️ Self-developed Framework HelloAgents - Build your own agent framework from scratch based on OpenAI native API
• ⚙️ Master Advanced Skills - Step-by-step implementation of context engineering, Memory, protocols, evaluation, and other systematic technologies
• 🤝 Model Training - Master Agentic RL, from SFT to GRPO full-process practical LLM training
• 🚀 Drive Real Cases - Practical development of intelligent travel assistants, cyber towns, and other comprehensive projects
• 📖 Job Interviews - Learn agent-related interview questions for job hunting

📖 Content Navigation

Community Contributions

  We welcome everyone to contribute their unique insights and practical summaries from learning Hello-Agents or Agent-related technologies to the community selection in the form of PRs. If the content is independent of the main text, you can also submit it to Extra-Chapter! Looking forward to your first contribution!

PDF Version Download

  This Hello-Agents PDF tutorial is completely open source and free. To prevent various marketing accounts from adding watermarks and selling it to multi-agent system beginners, we have pre-added a Datawhale open source logo watermark that does not affect reading in the PDF file. Please understand~

Hello-Agents PDF: https://github.com/datawhalechina/hello-agents/releases/tag/V1.0.0
Hello-Agents PDF Domestic Download: https://www.datawhale.cn/learn/summary/239

💡 How to Learn

  Welcome, future builder of intelligent systems! Before embarking on this exciting journey, please allow us to give you some clear guidance.

  This project balances theory and practice, aiming to help you systematically master the entire process of designing and developing from single agents to multi-agent systems. Therefore, it is especially suitable for AI developers, software engineers, students with some programming foundation, as well as self-learners with a strong interest in cutting-edge AI technology. Before learning this project, we hope you have basic Python programming skills and a basic conceptual understanding of large language models (for example, knowing how to call an LLM through an API). The focus of the project is on application and construction, so you do not need a deep background in algorithms or model training.

  The project is divided into five major parts, each being a solid step towards the next stage:

• Part 1: Agent and Language Model Fundamentals (Chapters 1-3), we will start from the definition, types, and development history of agents, sorting out the ins and outs of the concept of "agents." Then, we will quickly consolidate the core knowledge of large language models, laying a solid theoretical foundation for your practical journey.

• Part 2: Building Your LLM Agent (Chapters 4-7), this is the starting point of your hands-on practice. You will personally implement classic paradigms such as ReAct, experience the convenience of low-code platforms like Coze, and master the application of mainstream frameworks like Langgraph. Finally, we will also guide you to build your own agent framework from scratch, giving you the ability