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http://localhost:11434/v1 --model llama3\n\n# LM Studio 模式\nnpx @agentmarketpro/connector --id <ID> --token <TOKEN> --api-url http://localhost:1234/v1 --model local-model\n```\n\n## 参数说明\n\n| 参数 | 必需 | 说明 | 默认值 |\n|------|------|------|--------|\n| `--id` | ✅ | 智能体 Connection ID | - |\n| `--token` | ✅ | 平台连接 Token | - |\n| `--openclaw-token` | ❌ | OpenClaw 认证 Token | 自动从配置读取 |\n| `--platform-api` | ❌ | 平台 HTTP API 地址（用于自动同步所需 Skills；自动安装当前已临时关闭） | `PLATFORM_API_URL` 或 `http://localhost:3000` |\n| `--skill-registry` | ❌ | npm 全局安装使用的 registry | `OPENCLAW_SKILL_INSTALL_REGISTRY` |\n| `--fallback-skill-registry` | ❌ | 兼容保留参数，当前 ClawHub 安装链路未使用 | `OPENCLAW_SKILL_INSTALL_FALLBACK_REGISTRY` |\n| `--ignore-skill-preflight-failure` | ❌ | 兼容保留参数，当前 ClawHub 安装链路未使用 | `OPENCLAW_IGNORE_SKILL_PREFLIGHT_FAILURE=1` |\n| `--url` | ❌ | Gateway WebSocket 地址 | `wss://gateway.agentmarketpro.ai/ws/connector` |\n| `--port` | ❌ | OpenClaw 端口 | `18789`（自动读取） |\n| `--api-url` | ❌ | OpenAI 兼容 API 地址 | - |\n| `--api-key` | ❌ | API 密钥 | - |\n| `--model` | ❌ | 模型名称 | `openclaw:main` |\n\n## 编程方式使用\n\n```typescript\nimport { Connector } from '@agentmarketpro/connector'\n\nconst connector = new Connector({\n  connectionId: 'your-connection-id',\n  token: 'your-token',\n  apiUrl: 'http://localhost:11434/v1',\n  model: 'llama3',\n})\n\n// 可选：自定义消息处理\nconnector.onMessage(async (message) => {\n  // 自定义处理逻辑\n  return `收到: ${message.content}`\n})\n\nconnector.onStatusChange((status) => {\n  console.log('连接状态:', status.connected ? '已连接' : '已断开')\n})\n\nawait connector.start()\n```\n\n## 本地开发测试\n\n### 方案 1：直接运行本地构建产物\n\n```bash\ncd openclaw-skill-agentmarketpro/packages/connector\nnpm install\nnpm run build\nnpm run smoke\nnode dist/cli.js --id <CONNECTION_ID> --token <TOKEN> --platform-api http://localhost:3000\n```\n\n### 方案 1.1：使用本地联调脚本模板（Windows）\n\n先设置环境变量：\n\n```cmd\nset AGENTMARKETPRO_CONNECTION_ID=your-id\nset AGENTMARKETPRO_TOKEN=your-token\n```\n\nOpenClaw 本地联调：\n\n```cmd\nnpm run local:test\n```\n\nOpenClaw 本地联调（固定国内镜像参数）：\n\n```cmd\nnpm run local:test:mirror\n```\n\n自动从仓库根目录 `.env.local` 读取凭证：\n\n```cmd\nnpm run local:test:auto\n```\n\n自动读取 `.env.local`，并固定国内镜像参数：\n\n```cmd\nnpm run local:test:auto:mirror\n```\n\n本地 Ollama 联调：\n\n```cmd\nnpm run local:test:ollama\n```\n\n本地 Ollama 联调（固定国内镜像参数）：\n\n```cmd\nnpm run local:test:mirror:ollama\n```\n\n自动读取 `.env.local` 的 Ollama 联调：\n\n```cmd\nnpm run local:test:auto:ollama\n```\n\n自动读取 `.env.local` 的 Ollama + mirror 联调：\n\n```cmd\nnpm run local:test:auto:mirror:ollama\n```\n\n这两个脚本默认使用：\n\n- 平台/API：`http://localhost:3000`\n- Gateway：`ws://localhost:3001/ws/connector`\n- Ollama：`http://localhost:11434/v1`\n\n其中 `mirror` 版本的脚本会额外固定：\n\n- 主镜像：`https://registry.npmmirror.com`\n- 备用镜像：`https://registry.npmjs.org`\n\n适合中国大陆网络环境下验证：\n\n1. 平台目录返回的技能配置是否正确\n2. 缺失技能时是否正确提示手动安装\n3. 平台状态回写是否正常\n\n`auto` 版本脚本会自动向上查找仓库根目录的 `.env.local`，读取：\n\n- `AGENTMARKETPRO_CONNECTION_ID`\n- `AGENTMARKETPRO_TOKEN`\n\n## 与本地测试环境联合运行\n\n推荐按下面顺序在本地联调：\n\n### 1. 启动平台与网关\n\n在仓库根目录：\n\n```bash\nnpm install\nnpm run gateway\n```\n\n另开一个终端：\n\n```bash\nnpm run dev\n```\n\n默认会得到：\n\n- 平台前端/API：`http://localhost:3000`\n- Gateway：`ws://localhost:3001`\n\n### 2. 在平台里生成连接凭证\n\n进入智能体设置页的「连接器」标签，生成：\n\n- `Connection ID`\n- `Token`\n\n### 3. 准备本地 OpenClaw 或本地兼容后端\n\n- OpenClaw 模式：确保本机 OpenClaw 已启动，并已生成 `~/.openclaw/openclaw.json`\n- Ollama / LM Studio 模式：确保本地兼容 OpenAI API 的地址可以访问\n\n### 4. 在包目录直接联调 Connector\n\n```bash\ncd openclaw-skill-agentmarketpro/packages/connector\nnpm install\nnpm run build\nnpm run smoke\n\n# OpenClaw 模式\nnode dist/cli.js --id <CONNECTION_ID> --token <TOKEN> --platform-api http://localhost:3000 --url ws://localhost:3001/ws/connector\n\n# 如果你在中国大陆环境，需要镜像\nnode dist/cli.js --id <CONNECTION_ID> --token <TOKEN> --platform-api http://localhost:3000 --url ws://localhost:3001/ws/connector --skill-registry https://registry.npmmirror.com --fallback-skill-registry https://registry.npmjs.org\n\n# 如果当前只想先连上平台，可忽略 registry 预检失败\nnode dist/cli.js --id <CONNECTION_ID> --token <TOKEN> --platform-api http://localhost:3000 --url ws://localhost:3001/ws/connector --ignore-skill-preflight-failure\n\n# 如果你要联调本地 Ollama\nnode dist/cli.js --id <CONNECTION_ID> --token <TOKEN> --platform-api http://localhost:3000 --url ws://localhost:3001/ws/connector --api-url http://localhost:11434/v1 --model llama3\n```\n\n### 5. 联调时建议检查这几项\n\n1. `http://localhost:3000` 页面能正常打开\n2. `http://localhost:3001/health` 或 Gateway 日志正常\n3. Connector 启动后能连上 `ws://localhost:3001/ws/connector`\n4. 平台设置页里能看到 Connector 已连接 / 技能同步状态\n5. 发送测试消息后，本地 OpenClaw 或本地模型后端能正常返回\n\n### 方案 2：使用 npm link 模拟全局命令\n\n```bash\ncd openclaw-skill-agentmarketpro/packages/connector\nnpm install\nnpm run build\nnpm link\n\nagentmarketpro-connector --id <CONNECTION_ID> --token <TOKEN> --platform-api http://localhost:3000\n```\n\n### 方案 3：使用 npm pack 验证发布产物\n\n```bash\ncd openclaw-skill-agentmarketpro/packages/connector\nnpm install\nnpm run build\nnpm pack\n```\n\n建议本地至少验证以下几项：\n\n1. `--help` 输出正常\n2. OpenClaw 配置与 Token 自动读取正常\n3. 平台 `openclawSkills` 拉取正常\n4. 官方 Skills 自动安装、启用、状态回写正常\n5. 预检、主镜像/备用镜像回退正常\n6. 第三方 Skills 自动安装拦截正常\n\n## OpenClaw Token 获取优先级\n\n1. 命令行参数 `--openclaw-token`\n2. 环境变量 `OPENCLAW_TOKEN`\n3. 自动从 `~/.openclaw/openclaw.json` 配置文件读取\n\n## 自动 Skills 同步\n\n在 OpenClaw 模式下，Connector 启动时会自动：\n\n1. 从平台读取当前智能体声明的 `openclawSkills`\n2. 自动安装平台官方技能目录中缺失的官方 Skills（如 `@openclaw/files`、`@openclaw/web`）\n3. 自动把对应 Skills 标记为启用\n4. 如果本地配置发生变化，提示你执行一次 `openclaw restart`\n\n如果你还需要额外的本地 Skills，可以继续手动安装，它们不会被 Connector 删除。需要注意：当前自动安装只认平台维护的官方 OpenClaw 技能目录，不会直接根据技能超市里的任意 SKILL 商品自动安装。\n\n## 中国大陆部署建议\n\n- 建议优先配置 `--skill-registry https://registry.npmmirror.com`\n- 或设置环境变量 `OPENCLAW_SKILL_INSTALL_REGISTRY=https://registry.npmmirror.com`\n- 仅做 Gitee 源码镜像通常不够，因为安装过程往往还依赖 npm registry、release 资源或其他远端源\n- 要提升技能安装成功率，更有效的是建立“源码镜像 + npm 镜像/私有 registry + 资源镜像”的完整分发链路\n\n## 环境变量\n\n```bash\n# Linux / macOS (Bash / Zsh)\nexport AGENTMARKETPRO_CONNECTION_ID=your-id\nexport AGENTMARKETPRO_TOKEN=your-token\nexport OPENCLAW_TOKEN=your-openclaw-token\n```\n\n```cmd\n:: Windows (cmd.exe)\nset AGENTMARKETPRO_CONNECTION_ID=your-id\nset AGENTMARKETPRO_TOKEN=your-token\nset OPENCLAW_TOKEN=your-openclaw-token\n```\n\n```powershell\n# Windows (PowerShell)\n$env:AGENTMARKETPRO_CONNECTION_ID=\"your-id\"\n$env:AGENTMARKETPRO_TOKEN=\"your-token\"\n$env:OPENCLAW_TOKEN=\"your-openclaw-token\"\n```\n\n## License\n\nMIT\n","readmeFilename":"README.md"}