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Handy Multi-Agent Tutorial

Handy Multi-Agent Logo

A Practical Guide to Building Multi-Agent Systems from Scratch with the CAMEL Framework

GitHub stars GitHub forks GitHub issues GitHub license

中文 | English

🎉 Version 1.0 officially released! Complete tutorial documentation has been updated in the docs directory, with executable code available in the code directory. If you have any questions or feature suggestions, please feel free to submit an issue on GitHub~

📖 Project Introduction

Handy-Multi-Agent is a practical guide designed for developers who want to deeply understand and practice multi-agent systems. This tutorial is based on the leading domestic multi-agent framework CAMEL-AI (NeurIPS'2023), gradually guiding readers from basic single Agent development to building complex Multi-Agent applications.

🎯 Target Audience

This project focuses on practice and hands-on Agent application development, while integrating necessary theoretical knowledge. It is suitable for:

  • Learners interested in multi-agent systems, large model applications, or artificial intelligence
  • Developers who want to understand and explore LLM applications in multi-agent systems through practice

🚀 Learning Objectives

Through this project, we hope to help developers:

  1. Understand Fundamentals: Master the usage of the CAMEL framework and understand basic Agent concepts
  2. Improve Skills: Enhance capabilities in building and managing agents through practical projects involving RAG, Memory, Multi-Agent, and other technologies
  3. Apply in Practice: Apply learned knowledge to solve real-world problems, cultivating practical abilities and innovative thinking

👨‍💻 Prerequisites

  • Technical Foundation: Basic Python programming skills, ability to read and understand project source code and related theories
  • Interest & Motivation: Passionate about the AI agent field, eager to develop personalized agent capabilities at the code level

📚 Project Structure

handy-multi-agent/
├── docs/                # Tutorial documentation
│   ├── chapter0/        # Chapter 0: Preface
│   ├── chapter1/        # Chapter 1: Basic Configuration
│   ├── chapter2/        # Chapter 2: Agent Components
│   ├── chapter3/        # Chapter 3: CAMEL Framework Introduction
│   ├── chapter4/        # Chapter 4: RAG Applications with CAMEL
│   ├── chapter5/        # Chapter 5: Comprehensive Case Study
│   ├── chapter6/        # Chapter 6: Conclusion
│   ├── appendix/        # Appendix
│   ├── images/          # Document images
│   └── files/           # Related files
│
├── code/                # Supporting code
│   ├── 第一章.ipynb      # Chapter 1 code
│   ├── 第二章.ipynb      # Chapter 2 code
│   ├── 第三章.ipynb      # Chapter 3 code
│   ├── 第四章/           # Chapter 4 code
│   └── 第五章/           # Chapter 5 code
│
└── README.md            # Project documentation

📝 Table of Contents

Chapter Overview

  • Chapter 0: Preface

    • 0.1 Join Us
    • 0.2 How to Contribute?

  • Chapter 1: Basic Configuration

    • Getting CAMEL, API Setup, Hello CAMEL, Exercises

  • Chapter 2: Agent Components

    • Agent Overview, Design Principles, Models, Messages, Prompt Engineering, Memory, Tools, Exercises

  • Chapter 3: CAMEL Framework Introduction and Practice

    • Framework Introduction, First Agent Society, Creating Workforce, Exercises

  • Chapter 4: RAG Applications with CAMEL Framework

    • RAG Components, Vector Databases, Building Knowledge Base, Building RAG Applications, RAG Evaluation, Graph RAG Practice, Exercises

  • Chapter 5: Comprehensive Case Study

    • Application Overview, Intent Recognition, Travel Information Retrieval, Strategy Generation, Feedback Optimization, Knowledge Integration, Exercises

  • Appendix

    • Supported Models
    • Loader Supplement
    • MCP Supplement (Draft, online in Feishu document)

🛠️ Getting Started

Requirements

  • Python 3.10 or higher recommended

Install CAMEL

pip install "camel-ai[all]"

Learning Steps

  1. Read Documentation: Visit the docs directory or online documentation, learn theoretical knowledge in chapter order
  2. Run Code: Find corresponding chapter code files in the code directory and run practice exercises as instructed
  3. Complete Assignments: Consolidate learned knowledge through assignments at the end of each chapter
  4. Project Practice: Apply comprehensive learned content to implement your own multi-agent system

🔍 Online Reading

Complete tutorial content can be accessed through:

📅 Roadmap

  • Release first version for internal testing
  • Migrate Feishu content to repository
  • Update case source code files
  • Release first version for public testing
  • Restructure tutorial, systematically organize agent development history, add more examples and new features, update CAMEL to latest version

🧑‍💻 Contributing

  • If you want to participate in the project, check Issues for unassigned tasks
  • Report bugs in Issues 🐛
  • Interested in participating? Join discussions in Discussions 💬
  • Contact Datawhale & CAMEL community developers with any ideas

👥 Contributors

Core Contributors

Main Contributors

Special thanks to @Sm1les for help and support~

📱 Follow Us

Scan QR code to follow: Datawhale

Scan QR code to follow: CAMEL-AI

📄 License

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.