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Team"},"license":"MIT","homepage":"https://gitee.com/tsinghua-nercbds/dwf-ai-connector#readme","keywords":["dwf","ai-agent","mcp","low-code","model-context-protocol","agent","cli"],"repository":{"type":"git","url":"git+https://gitee.com/tsinghua-nercbds/dwf-ai-connector.git"},"description":"DWF AI Connector - AI Agent console for DWF low-code platform","maintainers":[{"name":"satenruiko","email":"saten.liubo@gmail.com"}],"readme":"# DWF AI Connector\r\n\r\nDWF AI Connector 是一个面向 DWF（低代码平台）的 AI Agent 控制台，帮助用户通过自然语言与 DWF 环境交互，完成数据建模、应用建模、对象管理等操作。\r\n\r\n它包含一个 React 前端、多个 Node.js 后端服务，以及 MCP（Model Context Protocol）工具服务，支持通过浏览器或第三方 MCP 客户端使用。\r\n\r\n---\r\n\r\n## 架构概览\r\n\r\n```text\r\nBrowser / 第三方 MCP 客户端\r\n  │\r\n  ├─▶ apps/web (React + Vite)          前端管理界面  :5174\r\n  │\r\n  ├─▶ agent-gateway (Express)          Agent 控制面  :5180\r\n  │       ├─▶ SQLite / PostgreSQL 持久化\r\n  │       ├─▶ DWF backend (:9088)      环境/MCP 实例管理\r\n  │       └─▶ agent-runtime (:5190)    Agent 执行引擎\r\n  │               ├─▶ pi-coding-agent\r\n  │               ├─▶ MCP 工具 (dwf-mcp-server)\r\n  │               └─▶ dwf-cli 命令行\r\n  │\r\n  └─▶ dwf-backend (Express)            DWF 平台接入  :9088\r\n          ├─▶ SQLite / PostgreSQL 持久化\r\n          └─▶ 动态启动/管理 MCP Server 实例\r\n```\r\n\r\n## 核心能力\r\n\r\n- **DWF 环境管理**：维护多个 DWF 实例连接、端口、账号。\r\n- **MCP 实例管理**：按需启动/停止 DWF MCP Server，选择暴露给 Agent 的工具和实体类白名单。\r\n- **Agent 配置**：绑定模型 Provider、MCP 服务、Skills。\r\n- **对话式 Agent**：通过自然语言调用 DWF 工具，自动完成建模、查询、应用搭建。\r\n- **Skills 库**：可插拔的 Agent 技能，支持内置与用户自定义。\r\n- **工具进化**：收集工具调用上下文，持续优化工具描述。\r\n\r\n## 技术栈\r\n\r\n| 层级 | 技术 |\r\n|------|------|\r\n| 语言 | TypeScript 5.9，ESM |\r\n| 运行时 | Node.js >= 20 |\r\n| 包管理 | npm workspaces |\r\n| 前端 | React 18，Vite 5，Tailwind CSS，lucide-react |\r\n| 后端 | Express 5，drizzle-orm，pino |\r\n| 数据库 | SQLite（默认）/ PostgreSQL（可选） |\r\n| Agent 框架 | `@mariozechner/pi-coding-agent` |\r\n| MCP SDK | `@modelcontextprotocol/sdk` |\r\n\r\n## 目录结构\r\n\r\n```text\r\ndwf-ai-connector/\r\n├── apps/\r\n│   └── web/                    # React 前端\r\n├── packages/\r\n│   └── shared/                 # 共享类型与契约\r\n├── services/\r\n│   ├── dwf-mcp-server/         # DWF MCP 工具服务\r\n│   ├── dwf-backend/            # DWF 平台接入与管理 API\r\n│   ├── agent-runtime/          # Agent 执行引擎\r\n│   ├── agent-gateway/          # Agent 控制面（REST + SSE）\r\n│   ├── dwf-cli/                # 命令行 MCP 客户端\r\n├── .env                        # 本地开发环境变量\r\n├── .env.example                # 环境变量模板\r\n├── Dockerfile.backend          # dwf-backend 生产镜像\r\n├── Dockerfile.gateway          # gateway + web + runtime 生产镜像\r\n├── docker-compose.yml          # 三服务编排模板\r\n├── AGENTS.md                   # 开发规范（给 Coding Agent 阅读）\r\n└── docs/services-guide.md      # 服务使用文档\r\n```\r\n\r\n## 快速开始（Windows）\r\n\r\n以下命令适用于 Windows PowerShell。Linux / macOS / Git Bash 用户可将 `$env:XXX=\"...\"` 替换为 `export XXX=...`。\r\n\r\n### 环境要求\r\n\r\n- Node.js >= 20\r\n- npm >= 10\r\n- PostgreSQL >= 14（仅在需要 PostgreSQL 模式时安装）\r\n\r\n### 1. 克隆仓库并安装依赖\r\n\r\n```powershell\r\ncd dwf-ai-connector\r\nnpm install\r\n```\r\n\r\n> 默认使用 SQLite，无需安装 PostgreSQL。\r\n\r\n### 2. 配置环境变量\r\n\r\n本项目各服务通过 `dotenv` 从各自工作目录加载 `.env`。首次下载后，需要分别为以下两个服务创建 `.env`：\r\n\r\n```powershell\r\n# dwf-backend\r\nCopy-Item services\\dwf-backend\\.env.example services\\dwf-backend\\.env\r\n\r\n# agent-gateway\r\nCopy-Item services\\agent-gateway\\.env.example services\\agent-gateway\\.env\r\n```\r\n\r\n默认内容已适配本地开发（使用 SQLite）。两个服务共享同一个数据库文件 `data/connector.db`，启动时自动创建。\r\n\r\n`services/dwf-backend/.env`：\r\n\r\n```env\r\nDATABASE_URL=file:../../data/connector.db\r\nDWF_BACKEND_BASE_URL=http://127.0.0.1:9088/api/v1\r\nAGENT_SECRET_KEY=dwf-agent-dev-secret\r\n```\r\n\r\n`services/agent-gateway/.env`：\r\n\r\n```env\r\nDATABASE_URL=file:../../data/connector.db\r\nDWF_BACKEND_BASE_URL=http://127.0.0.1:9088/api/v1\r\nAGENT_GATEWAY_PORT=5180\r\nAGENT_RUNTIME_PORT=5190\r\nAGENT_SECRET_KEY=dwf-agent-dev-secret\r\n```\r\n\r\n项目根目录的 `.env.example` 仅作为总览参考，不会被服务直接读取。\r\n\r\n### 3. 创建 DWF 环境\r\n\r\n启动后，在前端 `http://localhost:5174/environments` 创建 DWF 环境：\r\n\r\n| 字段 | 说明 | 示例 |\r\n|------|------|------|  \r\n| 实例名称 | 环境标识 | `测试环境` |\r\n| 实例地址 | DWF 基础地址（含端口） | `http://172.21.11.113:6060` |\r\n| 用户名 / 密码 | DWF 登录账号 | - |\r\n\r\n填写实例地址后点击\"探测\"，系统会自动从 DWF `config.js` 获取 Modeler API Base URL 和 App API Base URL。\r\n\r\n### 4. 启动开发环境\r\n\r\n```powershell\r\nnpm run dev\r\n```\r\n\r\n启动完成后访问：\r\n\r\n- 前端：`http://localhost:5174`\r\n- Gateway API：`http://localhost:5180/agent-api`\r\n- DWF Backend API：`http://localhost:9088/api/v1`\r\n\r\n## 可选：使用 PostgreSQL\r\n\r\n如果需要使用 PostgreSQL（例如多实例部署或已有 PG 基础设施）：\r\n\r\n1. 安装 PostgreSQL 并创建数据库 `dwf_ai`。\r\n2. 在两个服务的 `.env` 中配置：\r\n\r\n```env\r\nDATABASE_URL=postgresql://postgres:postgres@localhost:5432/dwf_ai\r\n```\r\n\r\n3. 安装 `pg` 依赖：\r\n\r\n```powershell\r\nnpm install pg -w @dwf/dwf-backend\r\nnpm install pg -w @dwf/agent-gateway\r\n```\r\n\r\n4. 重新启动服务即可。\r\n\r\n## 生产部署\r\n\r\n### Docker Compose（推荐）\r\n\r\n```powershell\r\ncd dwf-ai-connector\r\n# 准备 .env\r\ncp .env.example .env\r\n# 启动全部服务\r\ndocker-compose up -d\r\n```\r\n\r\n默认暴露端口：\r\n\r\n- `5180`：前端 + gateway\r\n- `9088`：dwf-backend\r\n\r\nDocker 默认使用 SQLite，两个容器通过共享卷持久化 `data/connector.db`。\r\n\r\n### 离线环境部署\r\n\r\n如果目标服务器无法访问 Docker Hub，可在本地构建镜像后导出上传：\r\n\r\n```powershell\r\n# 本地构建\r\ndocker build -f Dockerfile.backend -t dwf-ai-connector-backend:latest .\r\ndocker build -f Dockerfile.gateway -t dwf-ai-connector-gateway:latest .\r\n\r\n# 导出\r\ndocker save dwf-ai-connector-backend:latest -o dwf-backend.tar\r\ndocker save dwf-ai-connector-gateway:latest -o dwf-gateway.tar\r\n\r\n# 上传到服务器后加载\r\ndocker load -i dwf-backend.tar\r\ndocker load -i dwf-gateway.tar\r\n```\r\n\r\n## 全局安装与 CLI 使用\r\n\r\n### 从 npm registry 安装\r\n\r\n```bash\r\nnpm install -g dwf-ai-connector\r\ndwf-ai-connector\r\n```\r\n\r\n### 从本地源码安装（开发测试）\r\n\r\n```bash\r\n# 必须先构建\r\nnpm run build\r\n\r\n# 全局安装（指向本地源码目录）\r\nnpm install -g .\r\n\r\n# 运行\r\ndwf-ai-connector\r\n```\r\n\r\n> **注意**：Windows 下 `npm install -g .` 会创建指向源码目录的 symlink，因此修改代码后只需重新 `npm run build` 即可生效。但如果修改了 `package.json` 的 `bin` / `files` / `dependencies` 字段，需要重新 `npm install -g .`。\r\n\r\n### 开发与测试全局安装\r\n\r\n如果你正在修改 CLI 代码并想通过全局安装验证：\r\n\r\n```powershell\r\n# 修改代码后\r\nnpm run build\r\n\r\n# 重新全局安装（因为 package.json 可能变了）\r\nnpm install -g .\r\n\r\n# 运行测试\r\ndwf-ai-connector\r\n```\r\n\r\n### CLI 参数\r\n\r\n| 参数 | 默认值 | 说明 |\r\n|------|--------|------|\r\n| `--data-dir <path>` | `~/.dwf-ai-connector/data` | SQLite 数据目录，数据库文件为 `connector.db` |\r\n| `--open` | `false` | 启动成功后自动用系统默认浏览器打开前端页面 |\r\n\r\n```bash\r\n# 使用自定义数据目录\r\ndwf-ai-connector --data-dir /path/to/data\r\n\r\n# 使用项目目录下的 data/（适合本地开发测试）\r\ndwf-ai-connector --data-dir ./data\r\n\r\n# 启动后自动打开浏览器\r\ndwf-ai-connector --open\r\n```\r\n\r\n终端输出的 URL 已使用 **OSC 8 超链接协议** 包装。在 Windows Terminal、VS Code 终端、iTerm2 等现代终端中，URL 会显示为蓝色可点击链接；在不支持的终端（如传统 cmd.exe、PowerShell 5.1 控制台）中会回退为普通文本，可复制后访问。\r\n\r\n#### 推荐终端：Windows Terminal\r\n\r\n- **打开方式**：按 `Win` 键搜索 `Windows Terminal` / `终端`，或按 `Win + R` 输入 `wt` 回车。\r\n- **点击链接**：启动后输出的 URL 会显示为带下划线的蓝色文字，按住 `Ctrl` 点击即可在浏览器中打开。\r\n- **设为默认（Win11）**：设置 → 隐私和安全性 → 开发者选项 → 终端 → 选择 `Windows Terminal`。之后从运行框启动的 cmd/powershell 都会用它打开。\r\n\r\n## dwf-cli 命令行工具\r\n\r\n`dwf-cli` 是 DWF MCP 的命令行客户端，安装 `dwf-ai-connector` 后即可直接使用。它会自动发现运行中的 MCP 实例并连接，无需手动查找 URL。\r\n\r\n### 前置条件\r\n\r\n1. `dwf-ai-connector` 已启动（后端在 :9088）\r\n2. 在 Web UI 中至少启动了一个 MCP 实例\r\n\r\n### 基本用法\r\n\r\n```bash\r\n# 自动发现并连接到运行中的 MCP 实例\r\ndwf-cli datamodel list-classes\r\n```\r\n\r\n如果只有一个 MCP 实例在运行，`dwf-cli` 会自动连接。如果有多个，会弹出交互式选择列表。\r\n\r\n### 查看可用 MCP 实例\r\n\r\n```bash\r\ndwf-cli instances\r\n```\r\n\r\n输出示例：\r\n\r\n```\r\n  MCP instances (backend: http://127.0.0.1:9088/api/v1)\r\n\r\n    * [running]   测试环境\r\n                  http://192.168.34.35:9088/api/v1/mcp-instance/proxy/abc123\r\n      [stopped]   生产环境\r\n\r\n  * = auto-selected when running dwf-cli without --instance\r\n```\r\n\r\n### 指定实例\r\n\r\n```bash\r\n# 按名称选择\r\ndwf-cli datamodel list-classes --instance 测试环境\r\n```\r\n\r\n### 多个实例运行时的交互选择\r\n\r\n```bash\r\ndwf-cli datamodel list-classes\r\n```\r\n\r\n输出：\r\n\r\n```\r\n  Multiple MCP instances running:\r\n\r\n    [1] 测试环境\r\n    [2] 开发环境\r\n\r\n  Select [1-2]: 1\r\n\r\n  Connecting to: 测试环境\r\n```\r\n\r\n### 直连模式（跳过自动发现）\r\n\r\n```bash\r\n# 直接指定 MCP 端点 URL\r\ndwf-cli datamodel list-classes --server-url http://localhost:30000/mcp\r\n```\r\n\r\n### wrapper 专属参数\r\n\r\n| 参数 | 说明 |\r\n|------|------|\r\n| `--instance <name>` | 按名称选择 MCP 实例 |\r\n| `--backend-url <url>` | 后端 API 地址（默认 `http://127.0.0.1:9088/api/v1`） |\r\n| `--server-url <url>` | 直连 MCP 端点，跳过自动发现 |\r\n\r\n### 常用命令示例\r\n\r\n```bash\r\n# 数据模型管理\r\ndwf-cli datamodel list-classes\r\ndwf-cli datamodel create-entity-class --class_name Student --display_name 学生\r\ndwf-cli datamodel list-objects --className Student\r\n\r\n# 认证\r\ndwf-cli auth login --host http://192.168.1.100:6060 --username admin\r\ndwf-cli auth status\r\n\r\n# Schema 查询\r\ndwf-cli schema tools\r\ndwf-cli schema classes\r\n```\r\n\r\n### 环境变量\r\n\r\n| 变量 | 说明 |\r\n|------|------|\r\n| `DWF_CLI_SERVER_URL` | MCP 端点 URL（设置后跳过自动发现） |\r\n| `DWF_BACKEND_BASE_URL` | 后端 API 地址（用于自动发现，默认 `http://127.0.0.1:9088/api/v1`） |\r\n| `DWF_CLI_TOOL_REGISTRY` | 工具注册表路径（默认自动查找） |\r\n\r\n### 启动后访问\r\n\r\n| 服务 | 地址 |\r\n|------|------|\r\n| 前端 | `http://localhost:5180` |\r\n| Gateway API | `http://localhost:5180/agent-api` |\r\n| DWF Backend API | `http://localhost:9088/api/v1` |\r\n\r\nCLI 会依次启动 dwf-backend → agent-gateway（内部自动启动 agent-runtime），并通过健康检查确认就绪后输出访问地址。\r\n\r\n### 环境变量\r\n\r\nCLI 默认使用以下端口和环境变量，可通过标准环境变量覆盖：\r\n\r\n| 变量 | 默认值 | 说明 |\r\n|------|--------|------|\r\n| `PORT` | `9088` | dwf-backend 端口 |\r\n| `AGENT_GATEWAY_PORT` | `5180` | agent-gateway 端口 |\r\n| `AGENT_RUNTIME_PORT` | `5190` | agent-runtime 端口 |\r\n| `AGENT_SECRET_KEY` | `dwf-agent-dev-secret` | Provider API Key 加密密钥 |\r\n| `DWF_BACKEND_BASE_URL` | `http://127.0.0.1:9088/api/v1` | dwf-backend API 基地址 |\r\n\r\n## 发布到 npm\r\n\r\n```bash\r\n# 1. 确保已登录到官方 registry（不要指向 cnpm 等镜像）\r\nnpm whoami --registry https://registry.npmjs.org/\r\n\r\n# 2. 发布（prepack 自动执行 npm run build）\r\nnpm publish --registry https://registry.npmjs.org/ --access public\r\n```\r\n\r\n### 发布注意事项\r\n\r\n- **Registry**：如果本地 `npm config get registry` 返回的是 `https://registry.npmmirror.com/` 等镜像，必须显式加 `--registry https://registry.npmjs.org/`，否则 `npm login` 和 `npm publish` 都会指向镜像而失败。\r\n- **2FA**：如果账号开启双因素认证，普通密码登录无法 publish。请使用 **Classic Token - Automation** 类型或 **Granular Access Token（启用 Bypass 2FA）**，并通过 `npm config set //registry.npmjs.org/:_authToken=你的token` 设置。\r\n- **版本号**：每次发布必须提升 `package.json` 的 `version` 字段。`prepack` 会自动重新 build，确保 `dist/` 是最新的。\r\n- **测试发布**：正式发布前可用 `npm pack --dry-run` 预览 tarball 内容。\r\n\r\n`package.json` 的 `files` 字段控制发布内容，包含：\r\n\r\n- `bin/` — CLI 入口（`dwf-ai-connector.js` + `dwf-cli.js` + `postinstall.js`）\r\n- `apps/web/dist/` — 前端构建产物\r\n- `packages/shared/package.json` + `dist/` — 共享类型包\r\n- `services/*/dist/` — 各服务构建产物\r\n- `services/agent-runtime/skills/builtin/` — 内置 Skills\r\n- `services/dwf-cli/config/` — CLI 工具注册表\r\n- `services/dwf-mcp-server/package.json` + `dist/` + `config/` — MCP 服务\r\n- `README.md`\r\n\r\n内部 workspace 包（`@dwf/shared`、`@dwf/dwf-mcp-server`）不会作为独立包发布。安装时 `postinstall` 脚本会自动把它们复制到 `node_modules/@dwf/` 下，供运行时解析。\r\n\r\n## 开发命令\r\n\r\n```powershell\r\n# 全量构建\r\nnpm run build\r\n\r\n# 启动生产服务（gateway 提供前端静态资源）\r\nnpm start\r\n\r\n# 单独构建某个包\r\nnpm run build -w @dwf/dwf-mcp-server\r\nnpm run build -w @dwf/agent-runtime\r\nnpm run build -w @dwf/agent-gateway\r\nnpm run build -w @dwf/web\r\n\r\n# 单独开发某个服务\r\nnpm run dev -w @dwf/web\r\nnpm run dev -w @dwf/agent-gateway\r\nnpm run dev -w @dwf/agent-runtime\r\nnpm run dev -w @dwf/dwf-backend\r\n```\r\n\r\n## 常见问题\r\n\r\n### 全局安装后启动报错 `Cannot find package 'xxx'`\r\n\r\n原因：npm 全局安装时，`@dwf/shared` 和 `@dwf/dwf-mcp-server` 这两个内部 workspace 包没有自动进入 `node_modules/@dwf/`，postinstall 脚本没有正确执行。\r\n\r\n解决：\r\n\r\n1. 确认安装时 postinstall 已执行（重新安装）：\r\n   ```bash\r\n   npm uninstall -g dwf-ai-connector\r\n   npm install dwf-ai-connector -g\r\n   ```\r\n\r\n2. 检查目录是否存在：\r\n   ```bash\r\n   ls \"$(npm root -g)/dwf-ai-connector/node_modules/@dwf/shared/dist/index.js\"\r\n   ls \"$(npm root -g)/dwf-ai-connector/node_modules/@dwf/dwf-mcp-server/dist/index.js\"\r\n   ```\r\n\r\n3. 如果确实缺失，可能是 `npm install` 加了 `--ignore-scripts`。手动执行：\r\n   ```bash\r\n   cd \"$(npm root -g)/dwf-ai-connector\"\r\n   node bin/postinstall.js\r\n   ```\r\n\r\n### 全局安装后启动报错 `EACCES` / `EPERM`\r\n\r\nWindows 下可能是旧安装残留导致。关闭所有 node 进程后删除残留目录：\r\n\r\n```powershell\r\n# 结束所有 node 进程\r\nGet-Process node | Stop-Process -Force\r\n\r\n# 删除残留安装目录\r\nRemove-Item -Recurse -Force \"$env:APPDATA\\nvm\\v22.17.0\\node_modules\\dwf-ai-connector\"\r\n\r\n# 重新安装\r\nnpm install dwf-ai-connector -g\r\n```\r\n\r\n### 端口被占用\r\n\r\nCLI 默认使用 9088 / 5180 / 5190。如果启动失败提示 `EADDRINUSE`：\r\n\r\n```powershell\r\n# 查找占用端口的进程\r\nGet-NetTCPConnection -LocalPort 9088,5180,5190 | Select-Object LocalPort, OwningProcess\r\n\r\n# 结束对应进程\r\nStop-Process -Id <PID> -Force\r\n```\r\n\r\n### npm login 跳转到 cnpm 或返回 401/404\r\n\r\n原因：本地 registry 配置成了镜像。\r\n\r\n解决：所有 npm 发布命令都显式指定官方 registry：\r\n\r\n```bash\r\nnpm login --registry https://registry.npmjs.org/\r\nnpm publish --registry https://registry.npmjs.org/ --access public\r\n```\r\n\r\n### 启动时报错 `PostgreSQL dependencies not available`\r\n\r\n原因：当前 `DATABASE_URL` 以 `postgresql://` 开头，但工作区没有安装 `pg` 包。\r\n\r\n解决：如果需要使用 PostgreSQL，安装 `pg` 依赖：\r\n\r\n```powershell\r\nnpm install pg -w @dwf/dwf-backend\r\nnpm install pg -w @dwf/agent-gateway\r\n```\r\n\r\n或者将 `.env` 中的 `DATABASE_URL` 改回 SQLite 默认值：`file:../../data/connector.db`。\r\n\r\n### 启动时报错 `client password must be a string`\r\n\r\n原因：服务使用 PostgreSQL 连接字符串，但密码为空或格式不正确。\r\n\r\n解决：确保以下两个 `.env` 文件中已正确设置 `DATABASE_URL`：\r\n\r\n- `services/dwf-backend/.env`\r\n- `services/agent-gateway/.env`\r\n\r\n```env\r\nDATABASE_URL=postgresql://postgres:postgres@localhost:5432/dwf_ai\r\n```\r\n\r\n并将 `postgres:postgres` 替换为你本地 PostgreSQL 的实际用户名和密码。\r\n\r\n## 与第三方 MCP 客户端集成\r\n\r\nDWF MCP Server 支持 stdio、streamable-http、sse 三种传输模式。当前前端默认使用 `streamable-http`。\r\n\r\n对于 OpenCode 等支持 Remote MCP 的客户端，可通过 dwf-backend 的代理端点访问：\r\n\r\n```json\r\n{\r\n  \"mcp\": {\r\n    \"dwf-dev\": {\r\n      \"type\": \"remote\",\r\n      \"url\": \"http://YOUR_HOST:9088/api/v1/mcp-instance/proxy/YOUR_MCP_INSTANCE_ID\"\r\n    }\r\n  }\r\n}\r\n```\r\n\r\n> 注：OpenCode 直连 MCP 目前处于调研阶段，相关路由与网络配置后续会进一步优化。\r\n\r\n## 开发规范\r\n\r\n详见 [`AGENTS.md`](./AGENTS.md)。\r\n\r\n## 许可证\r\n\r\n[LICENSE](../LICENSE)\r\n","readmeFilename":"README.md"}