justlovemaki/openclaw-china-docker — explained in plain English
Analysis updated 2026-06-26
Deploy an AI chatbot to your company's Feishu or DingTalk workspace with a single Docker Compose command
Build an AI assistant for QQ or Enterprise WeChat that can search Chinese social platforms and speak responses
Run AI-generated code safely inside a sandboxed inner container to prevent unintended changes to your server
| justlovemaki/openclaw-china-docker | 233boy/sing-box | ax/apk.sh | |
|---|---|---|---|
| Stars | 3,769 | 3,765 | 3,781 |
| Language | Shell | Shell | Shell |
| Setup difficulty | moderate | moderate | hard |
| Complexity | 3/5 | 3/5 | 3/5 |
| Audience | ops devops | ops devops | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires separate API credentials for each IM platform you want to enable plus an AI model API key, project is currently paused for new updates.
This project packages the OpenClaw AI assistant platform into a ready-to-run Docker container, with a specific focus on Chinese instant messaging services. Where the base OpenClaw project requires manual setup, this version arrives pre-configured with plugins for Feishu (also known as Lark), DingTalk, QQ bot, and Enterprise WeChat, so you can have an AI bot active on those platforms without building from scratch. The README notes the project is currently paused for new updates. The core idea is a single gateway that connects an AI model to multiple chat platforms at once. You point the container at your AI API credentials and your IM bot credentials through a configuration file, run a Docker Compose command, and the bot becomes available across whichever platforms you have set up. The project supports both a full configuration file with all available options and a minimal one for a quicker start. Beyond the IM integrations, the container bundles several additional tools: a module called Agent Reach for searching Twitter, Xiaohongshu, Weibo, and Douyin, a text-to-speech tool for Chinese audio, Playwright for browser automation, and FFmpeg for media processing. These expand what the AI bot can do inside a conversation. For safety, the project supports a Docker-in-Docker sandbox mode. When enabled, Python code and shell scripts that the AI generates are run inside an isolated inner container rather than directly on your server, reducing the risk of unintended system changes. Deployment uses a standard Docker workflow: pull the pre-built image from Docker Hub or clone the repository, fill in the environment variables, and run docker compose up. The project is licensed under GPL-3.0.
A pre-configured Docker container that connects an AI assistant to Chinese messaging platforms, Feishu, DingTalk, QQ, and Enterprise WeChat, with web search, text-to-speech, and sandboxed code execution included.
Mainly Shell. The stack also includes Docker, Docker Compose, Shell.
GPL-3.0, you can use and modify this freely, but if you distribute a modified version you must also release your source code under the same license.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly ops devops.
This repo across BitVibe Labs
Verify against the repo before relying on details.