一、 环境要求

组件

最低要求

推荐配置

操作系统

Linux (Ubuntu 20.04+), macOS 12+, Windows 10+ (WSL2)

Ubuntu 22.04 LTS

Docker

Docker Engine 20.10+

Docker Compose v2.0+

内存

2 GB

4 GB+

存储

5 GB

10 GB+

二、 核心步骤:拉取国内镜像

由于镜像在国内网络环境下拉取困难,我们直接通过离线下载的方式。

1. 拉取镜像

镜像下载地址,下载完成后在终端执行以下命令,将镜像拉取到本地

我用夸克网盘给你分享了「openclaw」,点击链接或复制整段内容,打开「夸克网盘APP」即可获取。
/~48b93M1xLP~:/
链接:https://pan.quark.cn/s/0b9b526fa98d

docker load --input openclaw.tar

2. 查看镜像是否下载成功

docker images -a

三、 启动 OpenClaw Gateway 服务

镜像拉取成功后,使用以下命令启动服务。注意:镜像标签较长,建议使用 docker images查看镜像 ID 后使用 ID 启动,或使用以下完整命令。

使用 Docker Run 启动

docker run -d \
  --name openclaw \
  -p 18789:18789 \
  --user root \
  -e OPENCLAW_GATEWAY_TOKEN=testtoken \
  telecom-eci-huadong1-crs-registry.crs-huadong1.ctyun.cn/base_image/openclaw:2026-01-30 \
  openclaw gateway run

或者使用 Docker Compose (推荐)

创建 docker-compose.yml文件:

version: '3.8'
services:
  openclaw:
    image: telecom-eci-huadong1-crs-registry.crs-huadong1.ctyun.cn/base_image/openclaw:2026-01-30
    container_name: openclaw
    ports:
      - "18789:18789"
    environment:
      - OPENCLAW_GATEWAY_TOKEN=your_custom_token_here
    command: openclaw gateway run
    restart: unless-stopped

启动服务:

docker-compose up -d

四、 验证与访问

  1. 查看容器状态docker logs -f openclaw

  2. 访问 Web UI:浏览器打开 http://你的服务器IP:18789?token=testtoken

  3. 输入 Token:在登录界面输入 docker-compose.yml中设置的 OPENCLAW_GATEWAY_TOKEN值(如未设置,查看启动日志获取随机生成的 Token)。

五、 修改配置

首次登录后,需在 Web UI 或通过命令行配置 AI 模型 API Key(如 OpenAI、Claude 或国内通义千问、DeepSeek 等),OpenClaw 才能正常进行推理和对话。

这里直接贴出修改的json文件

{
  "meta": {
    "lastTouchedVersion": "2026.1.29",
    "lastTouchedAt": "2026-03-01T16:53:34.972Z"
  },
  "wizard": {
    "lastRunAt": "2026-03-01T16:53:34.961Z",
    "lastRunVersion": "2026.1.29",
    "lastRunCommand": "onboard",
    "lastRunMode": "local"
  },
  "browser": {
    "enabled": true,
    "executablePath": "/usr/bin/chromium",
    "headless": true,
    "noSandbox": true
  },
  "models": {
    "providers": {
      "deepseek": {
        "baseUrl": "https://api.siliconflow.cn/v1",
        "apiKey": "sk-xxxxxx",
        "api": "openai-completions",
        "models": [
          {
            "id": "deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
            "name": "deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
            "reasoning": false,
            "input": [
              "text"
            ],
            "cost": {
              "input": 0,
              "output": 0,
              "cacheRead": 0,
              "cacheWrite": 0
            },
            "contextWindow": 32768,
            "maxTokens": 32768
          },
          {
            "id": "Pro/MiniMaxAI/MiniMax-M2.5",
            "name": "Pro/MiniMaxAI/MiniMax-M2.5",
            "reasoning": false,
            "input": [
              "text"
            ],
            "cost": {
              "input": 0,
              "output": 0,
              "cacheRead": 0,
              "cacheWrite": 0
            },
            "contextWindow": 200000,
            "maxTokens": 8192
          },
          {
            "id": "deepseek-ai/DeepSeek-V3.2",
            "name": "deepseek-ai/DeepSeek-V3.2",
            "reasoning": false,
            "input": [
              "text"
            ],
            "cost": {
              "input": 0,
              "output": 0,
              "cacheRead": 0,
              "cacheWrite": 0
            },
            "contextWindow": 200000,
            "maxTokens": 8192
          }
        ]
      },
      "minimax": {
        "baseUrl": "https://api.minimaxi.com/v1",
        "apiKey": "sk-xxxxx",
        "api": "openai-completions",
        "models": [
          {
            "id": "MiniMax-M2.5",
            "name": "MiniMax M2.5",
            "reasoning": false,
            "input": [
              "text"
            ],
            "cost": {
              "input": 0,
              "output": 0,
              "cacheRead": 0,
              "cacheWrite": 0
            },
            "contextWindow": 200000,
            "maxTokens": 8192
          },
          {
            "id": "MiniMax-M2.5-highspeed",
            "name": "MiniMax M2.5 Highspeed",
            "reasoning": false,
            "input": [
              "text"
            ],
            "cost": {
              "input": 0,
              "output": 0,
              "cacheRead": 0,
              "cacheWrite": 0
            },
            "contextWindow": 200000,
            "maxTokens": 8192
          },
          {
            "id": "MiniMax-M2.1",
            "name": "MiniMax M2.1",
            "reasoning": false,
            "input": [
              "text"
            ],
            "cost": {
              "input": 0,
              "output": 0,
              "cacheRead": 0,
              "cacheWrite": 0
            },
            "contextWindow": 200000,
            "maxTokens": 8192
          },
          {
            "id": "MiniMax-M2.1-highspeed",
            "name": "MiniMax M2.1 Highspeed",
            "reasoning": false,
            "input": [
              "text"
            ],
            "cost": {
              "input": 0,
              "output": 0,
              "cacheRead": 0,
              "cacheWrite": 0
            },
            "contextWindow": 200000,
            "maxTokens": 8192
          },
          {
            "id": "MiniMax-M2",
            "name": "MiniMax M2",
            "reasoning": false,
            "input": [
              "text"
            ],
            "cost": {
              "input": 0,
              "output": 0,
              "cacheRead": 0,
              "cacheWrite": 0
            },
            "contextWindow": 200000,
            "maxTokens": 8192
          }
        ]
      }
    }
  },
  "agents": {
    "defaults": {
      "model": {
        "primary": "deepseek/deepseek-ai/DeepSeek-V3.2"
      },
      "workspace": "/home/node/.openclaw/workspace",
      "compaction": {
        "mode": "default"
      },
      "heartbeat": {
        "model": "minimax/MiniMax-M2.5"
      },
      "maxConcurrent": 4,
      "subagents": {
        "maxConcurrent": 8
      }
    }
  },
  "messages": {
    "ackReactionScope": "group-mentions"
  },
  "commands": {
    "native": "auto",
    "nativeSkills": "auto"
  },
  "gateway": {
    "port": 28789,
    "mode": "local",
    "bind": "loopback",
    "controlUi": {
      "allowInsecureAuth": true
    },
    "auth": {
      "mode": "token",
      "token": "xxxxx"
    },
    "tailscale": {
      "mode": "off",
      "resetOnExit": false
    }
  },
  "skills": {
    "install": {
      "nodeManager": "npm"
    }
  }
}

以上就是所有内容啦,关注下方微信公众号输入“openclaw”免费体验~token有限,先到先得~

Logo

小龙虾开发者社区是 CSDN 旗下专注 OpenClaw 生态的官方阵地,聚焦技能开发、插件实践与部署教程,为开发者提供可直接落地的方案、工具与交流平台,助力高效构建与落地 AI 应用

更多推荐