前言
Githug （不是 Github ）是一个用 Ruby 编写的、用来练习 Git 的闯关小游戏。在闯关过程中，我们可以掌握 Git 的基本用法、加深理解，同时提高熟练度。
闯关原则
在闯关过程中，要时刻明白，我们闯关的目的是学习 git ，所以请不要为了闯关而闯关，而忽略了闯关过程中的收获。我们的重点在于学习 Git 。
进行 Githug 前的准备
安装 Ruby
Ruby 是一种开源的动态编程语言。因为 Githug 是用 Ruby 写的，所以我们得先安装 Ruby （已安装则跳过此步）。Ruby 官网安装指引-https://www.ruby-lang.org/zh_cn/downloads/
Windows 用户可直接下载安装程序进行安装 :下载 Ruby 安装程序-https://rubyinstaller.org/downloads/
安装完后，打开命令行界面执行下列命令：
ruby --version
不了解命令行?👉命令行
若输出有关 Ruby 的版本号，则代表安装成功。
安装 Githug
执行下列三行命令修改默认下载源:
//删除默认需要翻墙才能用的国外下载源 gem sources --remove https://rubygems.org/
//设置下载源为国内可以访问的下载源 gem sources --a https://gems.ruby-china.org/
//查看是否安装成功 gem sources -l
换源成功后执行下列命令安装 Githug
gem install githug
初始化 Githug
首先打开一个你想要建立 githug 游戏目录的文件夹，然后在资源管理器（暂时简单理解为文件夹的页面）的地址栏(有 "C:\windows\" 这样类似文字的编辑框)输入 cmd 回车。系统会自动打开位于当前路径下的 cmd 控制台，在这个命令行界面输入 githug ，返回的预期结果如下：
*********************************************************** * Githug *
*********************************************************** No githug directory
found， do you wish to create one? [yn]
这个提示的意思是你已经进入到 Githug 的游戏界面了，但是它未检索到游戏目录，提示你是否要建立目录。此时，输入字母 y 并按回车确认，它会在该文件夹下创建名为 git_hug 的游戏文件夹，然后用如下命令行进入到 git_hug 路径下就可以进行闯关了。
cd git_hug
不会命令行的基本操作?👉命令行基本操作
常用的命令:
githug 或 githug play 检测当前关卡是否通过
githug hint 显示当前关卡的提示
githug reset 重置当前关卡
githug levels 列出所有关卡
注 · 在任意关卡退出后，再次进入 Githug ，闯关进度会保存
闯关指引
Level 1 init
Name: init Level: 1 Difficulty: * A new directory， `git_hug` ， has been
created; initialize an empty repository in it.
Level 2
Level 3
Level 4
Level 5
Level 6
Level 7
Level 8
Level 9
Level 10
Level 11
Level 12
Level 13
Level 14
Level 15
Level 16
Level 17
Level 18
Level 19
Level 20
Level 21
Level 22
Level 23
Level 24
Level 25
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Monday, 29 June 2026
Githug小白指南
一个django博客项目BlogViking666
https://github.com/wsqy/BlogViking666
（ https://github.com/brightmann/BlogViking）
Node.js Static Server in Minutes
require('http').createServer(function (request, response) {
//
// Serve files!
//
file.serve(request, response);
}).listen(8080);
把上面的代码保存为server.js ,然后运行node server.js ,就得到了一个静态文件服务器程序。
from https://stackoverflow.com/a/15830142
静态博客程序：devdojo-static
this tool Static can help convert your Node.js application into a static site suitable for deployment on GitHub Pages.
---------------------------------------
npm install -g @devdojo/staticstatic new devdojo-static-site
(此命令会在当前目录下，生成devdojo-static-site 目录。
cd devdojo-static-site
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site (main)
$ ls
CNAME collections/ includes/ package.json public/
README.md assets/ content/ layouts/ pages/ tailwind.config.js
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site (main)
$ npm install
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site (main)
$ ls
CNAME assets/ includes/ package-lock.json public/
README.md collections/ layouts/ package.json tailwind.config.js
content/ node_modules/ pages/
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site (main)
$ static build
（此命令会在当前目录下，生成_site目录。_site目录就是静态网站的根目录。static build
就是生成/更新静态网站的根目录的命令）
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site (main)
$ ls
CNAME content/ node_modules/ pages/
README.md assets/ includes/ package-lock.json public/
_site/ collections/ layouts/ package.json tailwind.config.js
（生成了_site目录）
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site (main)
$ ls _site
assets/ favicon.ico index.html robots.txt
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site (main)
$
新建源帖：
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site (main)
$ cd content
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site/content (main)
$ nano test.md
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site/content (main)
$ ls
test.md
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site/content (main)
$ cat test.md
---
title: 测试
description: 这是一篇文章
---
这是测试。。。
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site/content (main)
$ cd ..
12799@DESKTOP-B6LK9IO MINGW64 ~/devdojo-static-site (main)
$ static build
项目地址：
https://github.com/thedevdojo/static
官网：
https://static.devdojo.com/
https://static.devdojo.com/docs/getting-started/
(有问题）
Sunday, 28 June 2026
ChatDev
ChatDev 2.0: Dev All through LLM-powered Multi-Agent Collaboration
A Zero-Code Multi-Agent Platform for Developing Everything
【📚 Developers | 👥 Contributors｜⭐️ ChatDev 1.0 (Legacy)】
📖 Overview
ChatDev has evolved from a specialized software development multi-agent system into a comprehensive multi-agent orchestration platform.
- ChatDev 2.0 (DevAll) is a Zero-Code Multi-Agent Platform for "Developing Everything". It empowers users to rapidly build and execute customized multi-agent systems through simple configuration. No coding is required—users can define agents, workflows, and tasks to orchestrate complex scenarios such as data visualization, 3D generation, and deep research.
- ChatDev 1.0 (Legacy) operates as a Virtual Software Company. It utilizes various intelligent agents (e.g., CEO, CTO, Programmer) participating in specialized functional seminars to automate the entire software development life cycle—including designing, coding, testing, and documenting. It serves as the foundational paradigm for communicative agent collaboration.
🎉 News
• Jan 07, 2026: 🚀 We are excited to announce the official release of ChatDev 2.0 (DevAll)! This version introduces a zero-code multi-agent orchestration platform. The classic ChatDev (v1.x) has been moved to the chatdev1.0 branch for maintenance. More details about ChatDev 2.0 can be found on our official post.
🚀 Quick Start
📋 Prerequisites
- OS: macOS / Linux / WSL / Windows
- Python: 3.12+
- Node.js: 18+
- Package Manager: uv
📦 Installation
-
Backend Dependencies (Python managed by
uv):uv sync
-
Frontend Dependencies (Vite + Vue 3):
cd frontend && npm install
- Environment Variables:
cp .env.example .env
- Model Keys: Set
API_KEYandBASE_URLin.envfor your LLM provider. - YAML placeholders: Use
${VAR}（e.g.,${API_KEY}）in configuration files to reference these variables.
Start both Backend and Frontent:
make devThen access the Web Console at http://localhost:5173.
-
Start Backend:
# Run from the project root uv run python server_main.py --port 6400 --reload--reloadwatches the server's Python source folders only; agent-generated files underWareHouse/no longer trigger restarts. Pass--reload-diror--reload-exclude(repeatable) to customise. -
Start Frontend:
cd frontend VITE_API_BASE_URL=http://localhost:6400 npm run devThen access the Web Console at http://localhost:5173.
💡 Tip: If the frontend fails to connect to the backend, the default port
6400may already be occupied. Please switch both services to an available port, for example:- Backend: start with
--port 6401 - Frontend: set
VITE_API_BASE_URL=http://localhost:6401
- Backend: start with
-
Help command:
make help -
Sync YAML workflows to frontend:
make sync
Uploads all workflow files from
yaml_instance/to the database. -
Validate all YAML workflows:
make validate-yamls
Checks all YAML files for syntax and schema errors.
OpenClaw can integrate with ChatDev by invoking existing agent teams or dynamically creating new agent teams within ChatDev. To get started:
-
Start the ChatDev 2.0 backend.
-
Install the required skills for your OpenClaw instance:
clawdhub install chatdev
-
Ask your OpenClaw to create a ChatDev workflow. For example:
-
Automated information collection and content publishing
Create a ChatDev workflow to automatically collect trending information, generate a Xiaohongshu post, and publish it. -
Multi-agent geopolitical simulation
Create a ChatDev workflow with multiple agents to simulate possible future developments of the Middle East situation.
Alternatively, you can run the entire application using Docker Compose. This method simplifies dependency management and provides a consistent environment.
-
Prerequisites:
- Docker and Docker Compose installed.
- Ensure you have a
.envfile in the project root for your API keys.
-
Build and Run:
# From the project root docker compose up --build -
Access:
- Backend:
http://localhost:6400 - Frontend:
http://localhost:5173
- Backend:
The services will automatically restart if they crash, and local file changes will be reflected inside the containers for live development.
The DevAll interface provides a seamless experience for both construction and execution
- Tutorial: Comprehensive step-by-step guides and documentation integrated directly into the platform to help you get started quickly.
- Workflow: A visual canvas to design your multi-agent systems. Configure node parameters, define context flows, and orchestrate complex agent interactions with drag-and-drop ease.
- Launch: Initiate workflows, monitor real-time logs, inspect intermediate artifacts, and provide human-in-the-loop feedback.
For automation and batch processing, use our lightweight Python SDK to execute workflows programmatically and retrieve results directly.
from runtime.sdk import run_workflow
# Execute a workflow and get the final node message
result = run_workflow(
yaml_file="yaml_instance/demo.yaml",
task_prompt="Summarize the attached document in one sentence.",
attachments=["/path/to/document.pdf"],
variables={"API_KEY": "sk-xxxx"} # Override .env variables if needed
)
if result.final_message:
print(f"Output: {result.final_message.text_content()}")We have released the ChatDev Python SDK (PyPI package chatdev), so you can also run YAML workflow and multi-agent tasks directly in Python. For installation and version details, see PyPI: chatdev 0.1.0.
For secondary development and extensions, please proceed with this section.
Extend DevAll with new nodes, providers, and tools. The project is organized into a modular structure:
- Core Systems:
server/hosts the FastAPI backend, whileruntime/manages agent abstraction and tool execution. - Orchestration:
workflow/handles the multi-agent logic, driven by configurations inentity/. - Frontend:
frontend/contains the Vue 3 Web Console. - Extensibility:
functions/is the place for custom Python tools.
Relevant reference documentation:
- Getting Started: Start Guide
- Core Modules: Workflow Authoring, Memory, and Tooling
We provide robust, out-of-the-box templates for common scenarios. All runnable workflow configs are located in yaml_instance/.
- Demos: Files named
demo_*.yamlshowcase specific features or modules. - Implementations: Files named directly (e.g.,
ChatDev_v1.yaml) are full in-house or recreated workflows. As follows:
| Category | Workflow | Case |
|---|---|---|
| 📈 Data Visualization | data_visualization_basic.yamldata_visualization_enhanced.yaml |
Prompt: "Create 4–6 high-quality PNG charts for my large real-estate transactions dataset." |
| 🛠️ 3D Generation (Requires Blender & blender-mcp) |
blender_3d_builder_simple.yamlblender_3d_builder_hub.yamlblender_scientific_illustration.yaml |
Prompt: "Please build a Christmas tree." |
| 🎮 Game Dev | GameDev_v1.yamlChatDev_v1.yaml |
Prompt: "Please help me design and develop a Tank Battle game." |
| 📚 Deep Research | deep_research_v1.yaml |
Prompt: "Research about recent advances in the field of LLM-based agent RL" |
| 🎓 Teach Video | teach_video.yaml (Please run command uv add manim before running this workflow) |
Prompt: "讲一下什么是凸优化" |
For those implementations, you can use the Launch tab to execute them.
- Select: Choose a workflow in the Launch tab.
- Upload: Upload necessary files (e.g.,
.csvfor data analysis) if required. - Prompt: Enter your request (e.g., "Visualize the sales trends" or "Design a snake game").
from https://github.com/OpenBMB/ChatDev