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TypeScript SDK — CLI tool and programmatic API for knowledge networks and Decision Agents.","maintainers":[{"name":"mumingzi","email":"18392639409@163.com"},{"name":"yannan786","email":"yannan786@gmail.com"},{"name":"maozy13","email":"maozy13@gmail.com"},{"name":"cathy.cai","email":"cathy.cai@aishu.cn"},{"name":"nevermoreai","email":"bincheng.qian@aishu.cn"},{"name":"sh00tg0a1","email":"chenxiao911@gmail.com"},{"name":"kiki2022","email":"hankun2015@126.com"}],"readme":"# @kweaver-ai/kweaver-sdk\n\nKWeaver TypeScript SDK 和 CLI — 让 AI 智能体与应用程序以编程方式访问知识网络和 Decision Agent。\n\n[English](README.md)\n\n## 安装\n\n```bash\n# 全局安装 CLI\nnpm install -g @kweaver-ai/kweaver-sdk\n\n# 作为库使用\nnpm install @kweaver-ai/kweaver-sdk\n```\n\n需要 **Node.js >= 22**。\n\n## API 参考（TypeDoc）\n\n由源码与 TSDoc 生成 HTML，产物在 `docs/reference/typescript-api-html/index.html`（已 gitignore）。`typedoc.json` 用 **`entryPointStrategy: \"expand\"`** 自动展开 **`src/resources`**、**`src/api`**、**`src/auth`** 整目录，新增模块无需改配置。英文构建用 `README.md`，中文构建用 `README.zh.md`。**「Defined in」** 链接的 `gitRevision` 取 `TYPEDOC_GIT_REVISION` → `GITHUB_SHA` → 回退 `\"main\"`；CI 中固定到当前 SHA：`TYPEDOC_GIT_REVISION=$GITHUB_SHA npm run docs`。\n\nTypeDoc **不会在同一个站点里提供中英文切换**。做法是生成两套目录：英文界面（默认）与中文界面（**`npm run docs:zh`**），主要翻译导航等界面文案；**API 说明仍以源码里的 TSDoc（英文）为准**。\n\n```bash\ncd packages/typescript\nnpm install\nnpm run docs             # 英文界面 → docs/reference/typescript-api-html/\nnpm run docs:serve       # 生成并访问 http://127.0.0.1:8766\nnpm run docs:zh          # 中文界面 + README.zh.md → docs/reference/typescript-api-html-zh/\nnpm run docs:serve:zh    # 生成并访问 http://127.0.0.1:8767\nnpm run docs:all         # 两套产物都生成\n```\n\n> `docs/reference/**` 下的所有文件均为生成产物。请编辑 `packages/typescript/README*.md` 与源码 TSDoc 注释；`media/` 下的拷贝在下次构建时会被覆盖。\n\n## 快速上手\n\n### 认证\n\n```bash\nkweaver auth login https://your-kweaver-instance.com\n```\n\n或使用环境变量：\n\n```bash\nexport KWEAVER_BASE_URL=https://your-kweaver-instance.com\nexport KWEAVER_TOKEN=your-token\n```\n\n两者同时设置时，即使未执行 `auth login`，业务命令也会使用该 token。若 **`~/.kweaver/` 无当前平台**，仍可使用 **`kweaver auth status`**、**`kweaver auth whoami`**（支持 `--json`）、**`kweaver config show`**。环境变量模式下，`whoami` 会通过 EACP `/api/eacp/v1/user/get` 在线获取身份并展示 `Type`（user/app）、`User ID`、`Account`、`Name`，对 opaque 与 JWT token 都生效；若 EACP 不可达，则回退到本地 JWT 解码，opaque token 会给出简短提示。\n\n`kweaver config list-bd` 用于列出当前用户可访问的业务域。**应用（service）token 没有绑定终端用户**——当后端返回 `401 invalid user_id` 时，CLI 会再向 EACP 复核 token 类型，确认为 `type:\"app\"` 后将晦涩的后端原文替换为 `This command does not support app accounts.`。需要这个能力时请改用交互式 `auth login` 获得的用户 token。\n\n### 业务域（平台配置）\n\n在调用依赖租户范围的接口前，应先确认业务域；DIP 环境通常使用 **UUID**，不能长期只依赖默认 `bd_public`。\n\n```bash\nkweaver config show\nkweaver config list-bd\nkweaver config set-bd <uuid>\n```\n\n`kweaver auth login` 成功后，若尚未配置，CLI 可能自动选择业务域。也可用环境变量 `KWEAVER_BUSINESS_DOMAIN` 或各命令的 `-bd` / `--biz-domain` 覆盖。详见 [`../../skills/kweaver-core/references/config.md`](../../skills/kweaver-core/references/config.md)。\n\n### 简洁 API（推荐）\n\n```typescript\nimport kweaver from \"@kweaver-ai/kweaver-sdk/kweaver\";\n\n// 使用 `kweaver auth login` 保存的凭据，零配置\nkweaver.configure({ config: true, bknId: \"your-bkn-id\", agentId: \"your-agent-id\" });\n\n// 搜索知识网络\nconst results = await kweaver.search(\"供应链有哪些关键风险？\");\nfor (const concept of results.concepts) console.log(concept.concept_name);\n\n// 与 Agent 对话\nconst reply = await kweaver.chat(\"总结前三大风险\");\nconsole.log(reply.text);\n\n// 接入数据源或修改对象类后，重建 BKN 索引\nawait kweaver.weaver({ wait: true });\n\n// 查看所有 BKN 和 Agent\nconst bknList   = await kweaver.bkns();\nconst agentList = await kweaver.agents();\n```\n\n### 底层客户端（高级用法）\n\n```typescript\nimport { KWeaverClient } from \"@kweaver-ai/kweaver-sdk\";\n\n// 零配置：自动读取 `kweaver auth login` 保存的凭据\nconst client = new KWeaverClient();\n\n// 或显式传入凭据\nconst client = new KWeaverClient({\n  baseUrl: \"https://your-kweaver-instance.com\",\n  accessToken: \"your-token\",\n});\n\n// 知识网络\nconst kns = await client.knowledgeNetworks.list({ limit: 10 });\nconst ots = await client.knowledgeNetworks.listObjectTypes(\"bkn-id\");\nconst rts = await client.knowledgeNetworks.listRelationTypes(\"bkn-id\");\nconst ats = await client.knowledgeNetworks.listActionTypes(\"bkn-id\");\n\n// Agent 对话（单次）\nconst reply = await client.agents.chat(\"agent-id\", \"你好\");\nconsole.log(reply.text, reply.conversationId);\n\n// Agent 对话（流式）\nawait client.agents.stream(\"agent-id\", \"你好\", {\n  onTextDelta: (chunk) => process.stdout.write(chunk),\n});\n\n// BKN 引擎：实例查询、子图、Action 执行\nconst instances = await client.bkn.queryInstances(\"bkn-id\", \"ot-id\", { limit: 20 });\nconst graph     = await client.bkn.querySubgraph(\"bkn-id\", { /* 路径规格 */ });\nawait client.bkn.executeAction(\"bkn-id\", \"at-id\", { /* 参数 */ });\nconst logs      = await client.bkn.listActionLogs(\"bkn-id\");\n\n// 数据源 & vega-backend 资源\nconst dsList    = await client.datasources.list();\nconst resId     = await client.resources.create({ name: \"v\", datasourceId: \"ds-id\", table: \"orders\" });\nconst resList   = await client.resources.list({ datasourceId: \"ds-id\" });\nconst fuzzy     = await client.resources.find(\"BOM\", { wait: false });\nconst exact     = await client.resources.find(\"orders\", {\n  datasourceId: \"ds-id\",\n  exact: true,\n  wait: true,\n});\nconst res       = await client.resources.get(resId);\nconst queryRows = await client.resources.query(resId, { limit: 10, needTotal: true });\n\n// Vega — 可观测性与查询\nconst catalogs = await client.vega.listCatalogs();\nconst health   = await client.vega.health();\n// 结构化查询 — POST /api/vega-backend/v1/query/execute（body 为 JSON 字符串）\nconst structured = await client.vega.executeQuery(\n  JSON.stringify({ tables: [{ resource_id: \"res-1\" }], output_fields: [\"*\"], limit: 20 }),\n);\n// 直连 SQL 或 OpenSearch DSL — POST /api/vega-backend/v1/resources/query\n// 使用 {{resource_id}} 占位符以路由到正确的 catalog connector\nconst rows = await client.vega.sqlQuery(\n  JSON.stringify({ query: \"SELECT * FROM {{res-1}} LIMIT 5\", resource_type: \"mysql\" }),\n);\n\n// Context Loader（MCP search_schema + 通用 tools/call）\nconst cl      = client.contextLoader(mcpUrl, \"bkn-id\");\nconst schema  = await cl.searchSchema({\n  query: \"高血压 治疗\",\n  search_scope: { concept_groups: [\"clinical\"] },\n});\nconst rawTool = await cl.callTool(\"search_schema\", { query: \"高血压 治疗\" });\n\n// Skill（注册表/市场/渐进式读取）\nconst skills = await client.skills.market({ name: \"kweaver\" });\nconst skillMd = await client.skills.fetchContent(\"skill-id\");\nconst draft = await client.skills.updateMetadata(\"skill-id\", {\n  name: \"Demo\",\n  description: \"Demo skill\",\n  category: \"system\",\n});\nconst history = await client.skills.history(\"skill-id\");\n```\n\n`searchSchema()` 是 Context Loader MCP `search_schema` 的类型化封装，默认 `response_format` 为 `json`，支持 `query`、`response_format`、`search_scope`、`max_concepts`、`schema_brief`、`enable_rerank`。`search_scope.concept_groups` 用于按 BKN 概念分组 ID 限定 Schema 发现范围，不是实例数据过滤条件。解析后的返回结果可能包含 `object_types`、`relation_types`、`action_types`、`metric_types`。\n\n`client.bkn.knSearch(...)` 已过时。新接入的 Schema 发现请使用 `client.contextLoader(...).searchSchema(...)`。\n\n需要直接使用 MCP 原生 `tools/call` 时，使用 `callTool(name, args)`。这适用于服务端新增工具但 SDK 尚未提供类型化封装的场景，参数会原样透传。\n\n## 命令速查\n\n`kweaver` 采用 `gh` 风格 help 布局（详见 [docs/cli_conventions.md §8](../../docs/cli_conventions.md#8-help-文本格式must)）：\n\n```text\nkweaver --help                            # gh 风格顶层概览\nkweaver help <command>                    # 转发到 `<command> --help`\nkweaver help all                          # 完整 per-action 签名（迁移期兜底）\nkweaver <command> --help                  # 子命令概览 + 动作列表\nkweaver <command> <subcommand> --help     # 动作级 flag + 示例\n```\n\n顶层命令分组：\n\n```text\nAUTHENTICATION & CONFIG  auth · token · config\nDECISION AGENT           agent · toolbox · tool\nAI DATA PLATFORM         bkn · ds · resource · dataflow · vega · context-loader\nTRACE AI                 trace\nFOUNDATION               call · explore · model · skill · help\n```\n\n需要查阅每个动作的完整签名（可浏览 / 可 grep）时，运行 `kweaver help all`。\n\n### Dataflow CLI 示例\n\n```bash\nkweaver dataflow list\nkweaver dataflow run <dagId> --file ./demo.pdf\nkweaver dataflow run <dagId> --url https://example.com/demo.pdf --name demo.pdf\nkweaver dataflow runs <dagId>\nkweaver dataflow runs <dagId> --since 2026-04-01\nkweaver dataflow logs <dagId> <instanceId>\nkweaver dataflow logs <dagId> <instanceId> --detail\n```\n\n`kweaver dataflow runs --since` 会按本地自然日过滤；如果参数无法被 `new Date(...)` 解析，CLI 会回退到最近 20 条运行记录。`kweaver dataflow logs` 默认输出摘要；加上 `--detail` 会打印带缩进的 `input` 和 `output` 载荷。\n\n### 模型工厂 CLI 示例\n\n- **mf-model-manager**：`/api/mf-model-manager/v1`（配置 CRUD、`test`）\n- **mf-model-api**：`/api/mf-model-api/v1`（OpenAI 兼容 **`chat`**，以及小模型 **`embeddings` / `rerank`**）\n\n离线模版：`model llm --template` / `model small --template` 输出内置 **`basic`** JSON（不调后端）。大模型 **`model_type`** 在后端仅为 **`llm`**（文本）、**`rlm`**（推理）、**`vu`**（视觉/多模态，接口缩写不是 `vlm`）；列表过滤：`kweaver model llm list --type …`。详见 [`skills/kweaver-core/references/model.md`](../../skills/kweaver-core/references/model.md#llm-model-types)。\n\n```bash\nkweaver model llm list --limit 30\nkweaver model llm list --type vu\nkweaver model llm chat <model_id> -m \"你好\" --no-stream\nkweaver model llm --template > ./llm.json\nkweaver model small add --name my-emb --type embedding --batch-size 8 --max-tokens 512 --embedding-dim 1536 \\\n  --model-config-file ./cfg.json\nkweaver model small embeddings <model_id> -i \"hello\" -i \"world\"\nkweaver model small rerank <model_id> -q \"查询\" -d \"文档a\" -d \"文档b\"\nkweaver model small --template > ./embedding-model-config.json\n```\n\n完整说明见 [`skills/kweaver-core/references/model.md`](../../skills/kweaver-core/references/model.md) 与 `kweaver model --help`。\n\n### Vega `sql` CLI 示例\n\n对 Catalog 资源执行直连 SQL（`POST /api/vega-backend/v1/resources/query`）。SQL 中使用 **`{{<resource_id>}}`** 或 **`{{.<resource_id>}}`**（资源 id 来自 `vega resource list` / `get`），后端据此解析物理表与 connector。`--resource-type` 为目标数据源的连接器类型，可通过 `kweaver vega connector-type list` 查看。简单模式下请**用引号包住整个 `--query` 参数**，避免 shell 对花括号做特殊处理。\n\n```bash\n# 简单模式（推荐）：避免在 JSON 里转义整段 SQL\nkweaver vega sql --resource-type mysql --query \"SELECT * FROM {{res-1}} LIMIT 5\"\n\n# 高级模式：完整 JSON（可带 query_timeout、stream_size，或 OpenSearch DSL 对象等）\nkweaver vega sql -d '{\"resource_type\":\"mysql\",\"query\":\"SELECT * FROM {{res-1}} LIMIT 5\"}'\n```\n\n若同时提供 `-d` 与 `--query` / `--resource-type`，**仅以 `-d` 为准**。\n\n**无 OAuth 的平台：** 使用 `kweaver auth <url> --no-auth`，或照常 `auth login`；若 `POST /oauth2/clients` 返回 **404**，CLI 会提示并自动保存为 no-auth。凭据仍在 `~/.kweaver/`，可用 `auth use` / `auth list` 切换。可选环境变量 `KWEAVER_NO_AUTH=1`（未设置 `KWEAVER_TOKEN` 时）配合 `KWEAVER_BASE_URL`。SDK：`new KWeaverClient({ baseUrl, auth: false })` 或 `kweaver.configure({ baseUrl, auth: false })`。\n\n## 环境变量\n\n| 变量 | 说明 |\n|---|---|\n| `KWEAVER_BASE_URL` | KWeaver 实例地址 |\n| `KWEAVER_MF_MODEL_MANAGER_URL` | 可选：mf-model-manager API 根地址（默认 `KWEAVER_BASE_URL` + `/api/mf-model-manager/v1`） |\n| `KWEAVER_MF_MODEL_API_URL` | 可选：mf-model-api 根地址（默认 `KWEAVER_BASE_URL` + `/api/mf-model-api/v1`） |\n| `KWEAVER_BUSINESS_DOMAIN` | 业务域标识 |\n| `KWEAVER_TOKEN` | 访问令牌 |\n| `KWEAVER_TOKEN_SOURCE` | CLI 传入 `--token` 时由程序设置的内部标记；请勿手动设置 |\n| `KWEAVER_NO_AUTH` | 设为 `1`/`true`/`yes` 且未设置 `KWEAVER_TOKEN` 时使用 no-auth 占位（需 `KWEAVER_BASE_URL` 或已选平台） |\n| `KWEAVER_TLS_INSECURE` | 设为 `1` 或 `true` 时跳过 TLS 证书校验（仅开发；更推荐 `kweaver auth … --insecure` 以按平台持久化） |\n| `NODE_TLS_REJECT_UNAUTHORIZED` | Node.js 内置 TLS 开关：设为 `0` 时在本进程内跳过 HTTPS 证书校验。`kweaver` 在 `KWEAVER_TLS_INSECURE` 生效或已保存 token 为不安全 TLS 时会设置此项（范围同上；仅开发）。 |\n\n### Stateless token 模式\n\n通过 `--token` 传入访问令牌，该次调用对该 token 路径既不读也不写 `~/.kweaver/`：\n\n```bash\nkweaver --base-url https://platform.example.com --token \"$TOK\" bkn list\n```\n\n来源优先级：\n\n| 来源 | base-url | token |\n|------|----------|-------|\n| flag | `--base-url` | `--token` |\n| env  | `KWEAVER_BASE_URL` | `KWEAVER_TOKEN` |\n| 磁盘 | active platform | OAuth 会话（可 refresh） |\n\n`--token` 模式下会禁用写盘命令：`auth login` / `logout` / `use` / `delete` / `switch`、`config set-bd`、整个 `context-loader config` 子命令组 ——去掉 `--token` 或改用 `kweaver auth login`。\n\n`auth whoami` / `auth status` 通过文案区分来源：flag 模式为 `CLI (flag: --token)`，env 模式为 `env (KWEAVER_TOKEN)`（`whoami --json` 为 `\"source\": \"flag\"` 与 `\"source\": \"env\"`）。\n\n`kweaver context-loader` 运行时子命令将 `<kn-id>` 作为第一个位置参数（如 `kweaver context-loader tools <kn-id>`），也支持全局 `--kn-id <id>` / `-k <id>` flag，因此在 stateless 模式下可直接使用，无需任何持久化配置。调试参数时可先执行 `kweaver context-loader help <subcommand>` 或 `<subcommand> --help`，这些 help 路径不会触发登录、配置读取或网络请求。`context-loader config set|use|list|remove|show` 管理子命令已被标记为 deprecated（每次调用打印警告），且在 `--token` 下整组被禁用。\n\n### TLS 证书问题排查\n\n如果遇到 `fetch failed`、`self-signed certificate`、`UNABLE_TO_GET_ISSUER_CERT` 等 TLS 相关错误，通常是目标服务器使用了自签名证书或 Kubernetes Ingress 默认假证书。可按优先级尝试以下方案：\n\n1. **推荐（按平台持久化）** — 登录时加 `--insecure`：\n   ```bash\n   kweaver auth login https://your-host --insecure\n   # 或简写\n   kweaver auth login https://your-host -k\n   ```\n   该标记会写入 `~/.kweaver/` 的 `token.json`，后续所有 CLI 命令对该平台自动生效，无需额外操作。\n\n2. **临时生效（当前 shell）** — 设置环境变量：\n   ```bash\n   export KWEAVER_TLS_INSECURE=1\n   kweaver bkn list\n   ```\n\n3. **Node.js 原生方式** — 直接设置 `NODE_TLS_REJECT_UNAUTHORIZED`：\n   ```bash\n   NODE_TLS_REJECT_UNAUTHORIZED=0 kweaver bkn list\n   ```\n\n> **安全提示：** 以上方式均会跳过 HTTPS 证书校验，仅适用于开发/内网环境。生产环境请使用受信任的 CA 签发证书。\n\n### 无浏览器 / 服务器端认证\n\n适用于 SSH 远程服务器、CI 环境等无浏览器场景：\n\n**第一步 — 有浏览器的机器：** 正常运行 `kweaver auth login`。登录成功后，回调页面会显示一条可复制的命令（含 `--client-id`、`--client-secret`、`--refresh-token`）。也可以用 `kweaver auth export` 查看。\n\n**第二步 — 在没有浏览器的那台机器上：** 在 SSH 服务器、CI 等环境中执行下面这条命令：\n\n```bash\nkweaver auth login https://your-platform \\\n  --client-id abc123 \\\n  --client-secret def456 \\\n  --refresh-token ghi789\n```\n\nSDK 会用 refresh token 换取新的 access token 并保存到本地，之后自动续期正常工作。\n\n## 在 AI 智能体中使用\n\n为 Claude Code、Cursor 等 AI 编程助手安装 KWeaver 技能：\n\n```bash\nnpx skills add kweaver-ai/kweaver-sdk --skill kweaver-core\n```\n\n## 相关链接\n\n- [GitHub](https://github.com/kweaver-ai/kweaver-sdk)\n- [Python SDK on PyPI](https://pypi.org/project/kweaver-sdk/)\n\n## 许可证\n\nMIT\n","readmeFilename":"README.zh.md"}