justlovemaki/openclaw-china-docker

★ 3,769ShellAudience · ops devopsComplexity · 3/5LicenseSetup · moderate

Mindmap

mindmap
  root((OpenClaw Docker))
    Platforms
      Feishu Lark
      DingTalk
      QQ bot
      Enterprise WeChat
    AI features
      Chat responses
      Web search
      Text to speech
    Tools
      Playwright browser
      FFmpeg media
      Sandbox mode
    Setup
      Docker Compose
      Config file
      API credentials

mindmap root((OpenClaw Docker)) Platforms Feishu Lark DingTalk QQ bot Enterprise WeChat AI features Chat responses Web search Text to speech Tools Playwright browser FFmpeg media Sandbox mode Setup Docker Compose Config file API credentials

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Things people build with this

USE CASE 1

Deploy an AI chatbot to your company's Feishu or DingTalk workspace with a single Docker Compose command

USE CASE 2

Build an AI assistant for QQ or Enterprise WeChat that can search Chinese social platforms and speak responses

USE CASE 3

Run AI-generated code safely inside a sandboxed inner container to prevent unintended changes to your server

Tech stack

DockerDocker ComposeShellPythonPlaywrightFFmpeg

Getting it running

Difficulty · moderate Time to first run · 1h+

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.

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.

In plain English

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.

Copy-paste prompts

Prompt 1

I want to deploy this OpenClaw Docker container with Feishu integration. Walk me through filling in the config file with my Feishu bot credentials and AI API key, then starting the service with Docker Compose.

Prompt 2

The container supports Docker-in-Docker sandbox mode. Explain how to enable it and what kinds of AI-generated code it can safely run without affecting the host server.

Prompt 3

Show me how to configure the Agent Reach module so my DingTalk bot can search Weibo and return a summarized result during a conversation.

Prompt 4

My OpenClaw Docker container is running but the QQ bot isn't responding. Walk me through debugging the bot credentials and checking the container logs.

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