Merge pull request 'feat(cypher-executor): 同步查詢 trigger + graph_neighbors 查詢面 workflow 示範' (#28) from feat/sync-query-trigger into main
This commit was merged in pull request #28.
This commit is contained in:
@@ -36,6 +36,11 @@ import type { Bindings, ComponentRunner, ServiceBinding } from '../types';
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const WASM_HTTP_RUNNER_IDS: ReadonlySet<string> = new Set([
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// 通用 HTTP 零件
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'http_request',
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// 通用 code 零件(sandbox inline JS,Arcrun#10 / 07-thin-shell §3.5 code-node):獨立 Worker,
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// URL 走 wasmWorkerUrl 通用推導(arcrun-code.{WORKER_SUBDOMAIN}.workers.dev,
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// self-hosted 由 WORKER_SUBDOMAIN var 注入自己的 subdomain,無寫死官方域名)。
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// 漏這行 = workflow 寫 `component: code` 落到 step 8 直接「找不到零件」(#29 發現)。
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'code',
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// gmail / telegram / line_notify / google_sheets 已降級為 recipe(2026-05-29 Phase 2):
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// recipe:gmail_send / telegram_send / line_notify_send / google_sheets_read|append
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// 走 step 6 KV recipe 解析,不再是零件。零件目錄已刪。
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@@ -341,6 +341,136 @@ async function triggerNamed(
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return c.json(result, result.success ? 200 : 500);
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}
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// ── 同步查詢 trigger(sync query)─────────────────────────────────────────────
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//
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// 動機:named webhook 的 /trigger 預設路徑雖已同步(await),但它回傳的是
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// `{ success, data, trace, duration_ms }` **信封**、且只有 POST 形態。
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// 查詢面(console / MCP 打 graph neighbors / traverse 之類)需要 request→response
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// **直接拿「工作流最終節點輸出」** 當 HTTP response body,且常是一個 GET。
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// 這組端點補上這個泛化:同步 await 執行 workflow graph → 把 **result.data(最終節點輸出)本身**
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// 當 response body 回(非 202、非信封)。補上它,任何查詢端點都能是一個 workflow。
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//
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// 認證:沿用 X-Arcrun-API-Key(header 形態)或 namespace 走 path(公開形態,與 /trigger path 版對稱;
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// self-hosted namespace 是明碼分區標籤非密碼,故可放 path — mindset §3 arcrun 不做授權判斷)。
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// 誠實(mindset §7):節點失敗回錯誤 + trace 摘要(非把錯誤當輸出假綠);paused 工作流無法同步
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// 給答案 → 明講(409),不假裝成功。
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// 同步查詢輸出上限(防超大 response body 撐爆 Worker / 呼叫端)。
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// 超過 → 回 413 + 誠實錯誤(請在 workflow 內先聚合/分頁),不截斷假裝成功。
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const MAX_QUERY_OUTPUT_BYTES = 5 * 1024 * 1024; // 5 MiB
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// GET:把 query string 全部欄位當 triggerContext(值皆 string)。
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function queryStringContext(c: Context<{ Bindings: Bindings }>): Record<string, unknown> {
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return { ...c.req.query() };
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}
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// POST:body(JSON object)當 triggerContext;非物件 / 無 body → 空 context。
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async function bodyContext(c: Context<{ Bindings: Bindings }>): Promise<Record<string, unknown>> {
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const body = await c.req.json().catch(() => null);
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return body && typeof body === 'object' ? (body as Record<string, unknown>) : {};
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}
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// 共用同步查詢邏輯(header 路徑與 path 路徑、GET 與 POST 都用,避免分叉)。
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async function queryNamed(
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c: Context<{ Bindings: Bindings }>,
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apiKey: string,
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name: string,
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triggerContext: Record<string, unknown>,
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) {
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const raw = await c.env.WEBHOOKS.get(kvKey(apiKey, name), 'text');
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if (!raw) {
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return c.json({ error: `找不到 workflow "${name}",請先執行 acr push` }, 404);
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}
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let record: NamedWorkflowRecord;
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try {
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record = JSON.parse(raw) as NamedWorkflowRecord;
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} catch {
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return c.json({ error: 'workflow 定義損毀' }, 500);
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}
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const graph = record.graph as { id?: string; nodes?: unknown[] };
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const workflowId = graph.id ?? name;
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const nodes = Array.isArray(graph.nodes) ? (graph.nodes as GraphNode[]) : [];
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const userAgent = c.req.header('User-Agent') ?? undefined;
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// 同步執行(await,非 waitUntil):查詢端點必須 request→response 拿到結果。
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const result = await executeWebhookGraph(
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c.env,
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record.graph,
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triggerContext,
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name,
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apiKey,
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c.executionCtx,
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userAgent,
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);
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// 執行判決寫入不阻塞回應(waitUntil,與 /trigger 一致)。
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c.executionCtx.waitUntil(
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writeExecutionVerdict(c.env, workflowId, nodes, result.success ? 'success' : 'failed', result.duration_ms, result.error ?? ''),
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);
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if (!result.success) {
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// paused(如 claude_api 等外部 callback resume)無法同步給答案 → 明講,不假裝成功。
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const paused = typeof result.error === 'string' && /workflow paused/i.test(result.error);
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return c.json(
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{
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success: false,
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error: result.error ?? '工作流執行失敗',
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trace: result.trace,
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...(paused
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? { paused: true, hint: '此工作流會暫停等待非同步 callback,無法當同步查詢端點;改用 /webhooks/named/:name/trigger?async=1 + /workflows/resume。' }
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: {}),
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},
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paused ? 409 : 500,
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);
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}
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// 成功 → 回「最終節點輸出」本身當 response body(非 202、非信封)。
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const serialized = JSON.stringify(result.data ?? null);
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const byteLen = new TextEncoder().encode(serialized).byteLength;
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if (byteLen > MAX_QUERY_OUTPUT_BYTES) {
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return c.json(
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{
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success: false,
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error: `查詢輸出過大(${byteLen} bytes > 上限 ${MAX_QUERY_OUTPUT_BYTES})。請在 workflow 內先聚合 / 分頁再回。`,
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},
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413,
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);
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}
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return new Response(serialized, {
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status: 200,
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headers: {
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'Content-Type': 'application/json; charset=UTF-8',
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'X-Arcrun-Duration-Ms': String(result.duration_ms),
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},
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});
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}
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// GET /webhooks/named/:name/query — header 認證,input 走 query string(console/MCP 主用)
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webhooksNamedRouter.get('/webhooks/named/:name/query', async (c) => {
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const apiKey = c.req.header('X-Arcrun-API-Key');
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if (!apiKey) return c.json({ error: '缺少 X-Arcrun-API-Key header' }, 401);
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return queryNamed(c, apiKey, c.req.param('name'), queryStringContext(c));
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});
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// POST /webhooks/named/:name/query — header 認證,input 走 body
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webhooksNamedRouter.post('/webhooks/named/:name/query', async (c) => {
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const apiKey = c.req.header('X-Arcrun-API-Key');
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if (!apiKey) return c.json({ error: '缺少 X-Arcrun-API-Key header' }, 401);
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return queryNamed(c, apiKey, c.req.param('name'), await bodyContext(c));
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});
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// POST /webhooks/named/:ns/:name/query — namespace 走 path(公開查詢,與 /trigger path 版對稱)
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webhooksNamedRouter.post('/webhooks/named/:ns/:name/query', async (c) => {
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return queryNamed(c, c.req.param('ns'), c.req.param('name'), await bodyContext(c));
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});
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// GET /q/:ns/:name — 簡短查詢入口(namespace 走 path,input 走 query string)
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webhooksNamedRouter.get('/q/:ns/:name', async (c) => {
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return queryNamed(c, c.req.param('ns'), c.req.param('name'), queryStringContext(c));
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});
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// GET /webhooks/named — 列出當前 api_key 下所有 workflow
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webhooksNamedRouter.get('/webhooks/named', async (c) => {
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const apiKey = c.req.header('X-Arcrun-API-Key');
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@@ -0,0 +1,56 @@
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/**
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* component-loader:`code` 零件解析測試(#29 發現的白名單缺口)。
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*
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* 背景:workflow 寫 `component: code` 時,component-loader 解析鏈 step 1-6 都不命中
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* (非 builtin / 非 URL / 非 hash / 非邏輯零件 binding / 非 recipe),必須靠 step 7 的
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* WASM_HTTP_RUNNER_IDS 白名單 → wasmWorkerUrl 通用推導。白名單漏 `code` 就會落到
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* step 8 直接丟「找不到零件」——graph_neighbors 等用 code 節點的 workflow 全滅。
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*
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* 驗證:
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* 1. `code` 能被解析成 runner(不 throw)。
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* 2. runner 打的 URL = arcrun-code.{WORKER_SUBDOMAIN}.workers.dev(通用推導、無寫死
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* 官方 code.arcrun.dev → self-hosted 換 WORKER_SUBDOMAIN 即落地)。
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*/
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import { describe, it, expect, vi, afterEach } from 'vitest';
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import { env } from 'cloudflare:test';
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import { createComponentLoader, wasmWorkerUrl } from '../src/lib/component-loader';
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import type { Bindings } from '../src/types';
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afterEach(() => {
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vi.unstubAllGlobals();
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});
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describe('component-loader:code 零件解析(WASM HTTP runner 白名單)', () => {
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it('wasmWorkerUrl 通用推導:code → arcrun-code.{subdomain}.workers.dev(self-hosted 換 subdomain 即成立)', () => {
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expect(wasmWorkerUrl('code', 'uncle6-me')).toBe('https://arcrun-code.uncle6-me.workers.dev');
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expect(wasmWorkerUrl('code', 'my-selfhosted-sub')).toBe('https://arcrun-code.my-selfhosted-sub.workers.dev');
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});
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it('component: code 能被解析成 runner,且 fetch 打 subdomain 推導的 URL', async () => {
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const fakeEnv = {
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...env,
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WORKER_SUBDOMAIN: 'test-sub',
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} as unknown as Bindings;
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const loader = createComponentLoader(fakeEnv);
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// 白名單漏 `code` 時這裡就 throw「找不到零件 "code"」(#29 的故障型態)
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const runner = await loader('code');
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expect(typeof runner).toBe('function');
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// stub fetch 捕 URL:證明 runner 打的是通用推導 URL,非寫死官方域名
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const calledUrls: string[] = [];
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const fetchSpy = vi.fn(async (url: unknown) => {
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calledUrls.push(String(url));
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return new Response(JSON.stringify({ success: true, data: { ok: true } }), {
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status: 200,
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headers: { 'Content-Type': 'application/json' },
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});
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});
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vi.stubGlobal('fetch', fetchSpy);
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const result = await runner({ code: 'return {ok:true}', input: {} }) as Record<string, unknown>;
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expect(fetchSpy).toHaveBeenCalledTimes(1);
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expect(calledUrls[0]).toBe('https://arcrun-code.test-sub.workers.dev');
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expect(result.success).toBe(true);
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});
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});
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@@ -0,0 +1,132 @@
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/**
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* 同步查詢 trigger(sync query)測試 — webhooks-named.ts 的 /query 與 /q/* 端點。
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*
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* 驗證重點(對應交辦 Part 1):
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* 1. 同步回「最終節點輸出」本身(非 202、非 {success,data,...} 信封)— GET(query string) 與 POST(body) 皆是。
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* 2. namespace 走 path 的公開形態(/q/:ns/:name、POST /webhooks/named/:ns/:name/query)。
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* 3. 節點失敗 → 誠實回錯誤 + trace(500),非假綠。
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* 4. 認證:缺 X-Arcrun-API-Key → 401;workflow 不存在 → 404。
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*
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* 用內建零件(comp_uppercase / comp_passthrough,純記憶體、無外部 fetch)當「極簡 workflow」,
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* 因此本測試就是「Part 1 同步 trigger 機制本身可用」的證據(確實同步回值而非 202)。
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*/
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import { describe, it, expect, beforeAll } from 'vitest';
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import { env, SELF } from 'cloudflare:test';
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const API_KEY = 'test-tenant-query';
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function kvKey(name: string, apiKey = API_KEY): string {
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return `${apiKey}:wf:${name}`;
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}
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// 極簡 workflow:單一 comp_uppercase 節點。caller input(text)→ 大寫 → 當最終輸出回。
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// 無 Input/Output 節點:最終節點輸出即 comp_uppercase 的回傳,乾淨可斷言。
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const UPPER_WF = {
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name: 'q_upper',
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graph: {
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id: 'q_upper',
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name: 'sync query upper',
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nodes: [{ id: 'upper', type: 'Component', componentId: 'comp_uppercase' }],
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edges: [],
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},
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description: '同步查詢:把 text 轉大寫回傳(測試用)',
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created_at: new Date().toISOString(),
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};
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// 會失敗的 workflow:引用不存在的零件 → 節點執行失敗。
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const FAIL_WF = {
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name: 'q_fail',
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graph: {
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id: 'q_fail',
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name: 'sync query fail',
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nodes: [{ id: 'boom', type: 'Component', componentId: 'comp_does_not_exist' }],
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edges: [],
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},
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description: '同步查詢:故意引用不存在零件(測試失敗路徑)',
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created_at: new Date().toISOString(),
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};
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beforeAll(async () => {
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await env.WEBHOOKS.put(kvKey(UPPER_WF.name), JSON.stringify(UPPER_WF));
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await env.WEBHOOKS.put(kvKey(FAIL_WF.name), JSON.stringify(FAIL_WF));
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});
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describe('同步查詢 trigger — 成功回最終節點輸出(非 202、非信封)', () => {
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it('POST /webhooks/named/:name/query(header 認證,body input)同步回輸出', async () => {
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const res = await SELF.fetch('http://localhost/webhooks/named/q_upper/query', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json', 'X-Arcrun-API-Key': API_KEY },
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||||
body: JSON.stringify({ text: 'hello' }),
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});
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expect(res.status).toBe(200); // 關鍵:非 202
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const data = await res.json() as Record<string, unknown>;
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||||
// 回的是「最終節點輸出本身」:頂層直接有 text=HELLO,而非包在 { data: ... } 信封裡
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expect(data.text).toBe('HELLO');
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||||
expect(data).not.toHaveProperty('duration_ms'); // 信封欄位不該出現在 body
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// duration 走 header,不污染輸出
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expect(res.headers.get('X-Arcrun-Duration-Ms')).not.toBeNull();
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||||
});
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||||
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||||
it('GET /webhooks/named/:name/query(header 認證,query string input)同步回輸出', async () => {
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||||
const res = await SELF.fetch('http://localhost/webhooks/named/q_upper/query?text=world', {
|
||||
headers: { 'X-Arcrun-API-Key': API_KEY },
|
||||
});
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||||
expect(res.status).toBe(200);
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||||
const data = await res.json() as Record<string, unknown>;
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||||
expect(data.text).toBe('WORLD');
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||||
});
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||||
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||||
it('GET /q/:ns/:name(namespace 走 path,query string input)同步回輸出', async () => {
|
||||
const res = await SELF.fetch(`http://localhost/q/${API_KEY}/q_upper?text=abc`);
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||||
expect(res.status).toBe(200);
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||||
const data = await res.json() as Record<string, unknown>;
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||||
expect(data.text).toBe('ABC');
|
||||
});
|
||||
|
||||
it('POST /webhooks/named/:ns/:name/query(namespace 走 path,body input)同步回輸出', async () => {
|
||||
const res = await SELF.fetch(`http://localhost/webhooks/named/${API_KEY}/q_upper/query`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({ text: 'path' }),
|
||||
});
|
||||
expect(res.status).toBe(200);
|
||||
const data = await res.json() as Record<string, unknown>;
|
||||
expect(data.text).toBe('PATH');
|
||||
});
|
||||
});
|
||||
|
||||
describe('同步查詢 trigger — 誠實錯誤(不假綠)', () => {
|
||||
it('節點失敗 → 500 + error + trace(非把錯誤當輸出)', async () => {
|
||||
const res = await SELF.fetch('http://localhost/webhooks/named/q_fail/query', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json', 'X-Arcrun-API-Key': API_KEY },
|
||||
body: JSON.stringify({}),
|
||||
});
|
||||
expect(res.status).toBe(500);
|
||||
const data = await res.json() as { success: boolean; error: string; trace: unknown };
|
||||
expect(data.success).toBe(false);
|
||||
expect(typeof data.error).toBe('string');
|
||||
expect(data.error.length).toBeGreaterThan(0);
|
||||
expect(data.trace).toBeDefined();
|
||||
});
|
||||
});
|
||||
|
||||
describe('同步查詢 trigger — 認證與存在性', () => {
|
||||
it('缺 X-Arcrun-API-Key(header 形態)→ 401', async () => {
|
||||
const res = await SELF.fetch('http://localhost/webhooks/named/q_upper/query', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({ text: 'x' }),
|
||||
});
|
||||
expect(res.status).toBe(401);
|
||||
});
|
||||
|
||||
it('workflow 不存在 → 404', async () => {
|
||||
const res = await SELF.fetch('http://localhost/webhooks/named/no_such_wf/query', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json', 'X-Arcrun-API-Key': API_KEY },
|
||||
body: JSON.stringify({}),
|
||||
});
|
||||
expect(res.status).toBe(404);
|
||||
});
|
||||
});
|
||||
@@ -29,6 +29,7 @@
|
||||
| `daily-digest` | cron → 多源聚合(KBDB / RSS / 等) → 推送 |
|
||||
| `parallel-fanout` | 一份輸入分發多 workflow 並行處理 |
|
||||
| `error-retry` | try_catch + wait + retry 重試外部 API |
|
||||
| `graph-neighbors` | 同步查詢:撈 KBDB triplet → 記憶體 BFS 找 N 跳鄰居(查詢面工作流,走同步查詢 trigger) |
|
||||
|
||||
## 如何用(AI 視角)
|
||||
|
||||
|
||||
@@ -0,0 +1,67 @@
|
||||
# graph-neighbors
|
||||
|
||||
## 解決什麼問題
|
||||
把 graph plugin 內建的 `GET /graph/neighbors`(同步 request→response 拿鄰居)**改寫成一條 workflow**。
|
||||
示範「查詢面工作流」:查詢端點不必是框架寫死的 route,可以是一條 `workflow.yaml` —— 撈 triplet
|
||||
記錄 → 記憶體 BFS → 同步回鄰居。任何唯讀查詢都能這樣泛化成 workflow。
|
||||
|
||||
## 依賴的框架能力(本 PR 補上的)
|
||||
**同步查詢 trigger**(cypher-executor `webhooks-named.ts`):現有 named webhook 的 `/trigger`
|
||||
回的是 `{success,data,trace,duration_ms}` 信封、且只有 POST。查詢面要 **GET + 直接拿最終節點輸出**。
|
||||
新端點同步 `await` 執行 graph → 把 `result.data`(最終節點輸出)本身當 response body 回(非 202):
|
||||
- `GET /q/:ns/:name`(namespace 走 path,input 走 query string)
|
||||
- `GET /webhooks/named/:name/query`(X-Arcrun-API-Key header,input 走 query string)
|
||||
- `POST /webhooks/named/:name/query`(header,input 走 body)
|
||||
- `POST /webhooks/named/:ns/:name/query`(namespace 走 path,input 走 body)
|
||||
|
||||
## 怎麼觸發
|
||||
```bash
|
||||
# GET(最像原本的 /graph/neighbors)——{你的-cypher-domain}/{你的-kbdb-domain} 換成自己的部署
|
||||
curl "https://{你的-cypher-domain}/q/{namespace}/graph_neighbors?node=Arcrun&depth=2&template=graph_triplet&namespace={namespace}&kbdb_base=https://{你的-kbdb-domain}"
|
||||
|
||||
# POST(header 認證)
|
||||
curl -X POST https://{你的-cypher-domain}/webhooks/named/graph_neighbors/query \
|
||||
-H "X-Arcrun-API-Key: {namespace}" \
|
||||
-d '{"node":"Arcrun","depth":2,"template":"graph_triplet","namespace":"{namespace}","kbdb_base":"https://{你的-kbdb-domain}"}'
|
||||
```
|
||||
|
||||
> ⚠️ **敏感輸入請用 `POST /query`**:`GET /q/` 的參數走 query string,會進 CF / proxy / access log
|
||||
> 各層日誌;node 名、namespace 等若屬敏感,改走 POST body。
|
||||
回傳(最終節點輸出本身,非信封):
|
||||
```json
|
||||
{ "success": true, "start": "Arcrun", "depth": 2, "directed": false,
|
||||
"neighbors": [ { "node": "cypher-executor", "predicate": "包含", "from": "Arcrun", "depth": 1 } ],
|
||||
"count": 1 }
|
||||
```
|
||||
|
||||
## 參數
|
||||
- `node`(必填):BFS 起點節點名
|
||||
- `depth`(預設 1):最大跳數
|
||||
- `template`(必填):triplet 記錄的 base template id(⚠️ 以實際部署的 kbdb-graph-plugin triplet template 為準)
|
||||
- `namespace`(必填):租戶 owner_id(self-hosted 明碼 namespace)
|
||||
- `kbdb_base`(必填):**你自己的 KBDB base URL**(如 `https://kbdb.example.com`)。
|
||||
workflow 不寫死任何一家的庫——抄示範時帶錯(或照抄別人的值)=查詢與資料流向直接打進別人的庫
|
||||
(KBDB_BASE_URL fallback 同家族坑,勿重蹈)。
|
||||
- `directed`(預設 false):`true` 只走 subject→object;否則把 triplet 當雙向邊(無向鄰居)
|
||||
|
||||
## kbdb_base 該帶哪種 URL(1042)
|
||||
cypher-executor 對 kbdb 發 fetch,若打同 zone URL 會踩 CF 1042(same-zone self-fetch)。兩條路皆可:
|
||||
1. 帶 KBDB 的 **custom domain**(跨 zone、走公網前門,天然避開 1042);
|
||||
2. self-hosted 有 **`global_fetch_strictly_public`** compatibility flag(credential-primitives-wasm
|
||||
Phase 7,cypher wrangler.toml),開了之後 **workers.dev URL 亦可**直接帶。
|
||||
|
||||
## ⚠️ 尚未 live 驗(待辦)
|
||||
- **`code` 零件尚未部署到 leo21c**(另線處理)→ 本工作流無法端到端 live 跑。
|
||||
workflow.yaml 已寫好放這裡待驗。
|
||||
- **同步查詢 trigger 本身已驗**:`cypher-executor/tests/query-trigger.test.ts`(7 測)用內建零件
|
||||
(comp_uppercase,純記憶體、無外部 fetch)證明「確實同步回最終節點輸出而非 202」。
|
||||
- 上線前另需對一次實際 triplet template id(本檔用 `{{input.template}}` 參數化,未寫死)。
|
||||
|
||||
## 對照
|
||||
記憶體 BFS 對照 `kbdb-graph-plugin` 的 `graph-traverse.ts:23-51`:triplet 當有向邊
|
||||
`subject --predicate--> object`,從起點逐跳擴張到 depth 上限,收集首次訪到的節點當鄰居。
|
||||
|
||||
## 學到什麼
|
||||
- 查詢端點可以是 workflow,不必是框架寫死的 route(同步查詢 trigger 讓這件事成立)
|
||||
- `code` 零件(sandbox inline JS)承載「非 call-api 的純計算」(BFS),不必為此鑄 domain 零件
|
||||
- 單一 `{{ref}}` pass-through 保留陣列型別 → `{{fetch_triplets.data.records}}` 拿到真陣列餵給 code
|
||||
@@ -0,0 +1 @@
|
||||
["graph", "triplet", "bfs", "neighbors", "kbdb", "sync-query", "query-endpoint", "code-node", "common-pattern"]
|
||||
@@ -0,0 +1,124 @@
|
||||
name: graph_neighbors
|
||||
description: >
|
||||
同步查詢:給一個節點 → 從 KBDB triplet 記錄建鄰接表 → 記憶體 BFS 找 N 跳鄰居 → 同步回鄰居清單。
|
||||
這是「查詢面工作流」示範:用同步查詢 trigger(GET /q/:ns/graph_neighbors 或
|
||||
POST /webhooks/named/:name/query),把 workflow 最終節點輸出直接當 HTTP response 拿回,
|
||||
取代 graph plugin 內建的 GET /graph/neighbors。對照 kbdb-graph-plugin graph-traverse.ts 的記憶體 BFS。
|
||||
|
||||
# ══════════════════════════════════════════════════════════════════════════════
|
||||
# ⚠️ 先改成你自己的 KBDB URL(self-hosted 必看)
|
||||
# fetch_triplets 的 base URL 走 {{input.kbdb_base}} 參數(每次呼叫帶),**沒有寫死官方庫**。
|
||||
# 照抄本示範時,把觸發參數 kbdb_base 換成你自己部署的 KBDB 對外 URL——
|
||||
# 抄了別人的值=你的查詢與資料流向直接打進別人的庫(KBDB_BASE_URL fallback 同家族坑)。
|
||||
# ══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
# ── 1042 與 kbdb_base 該帶哪種 URL ──
|
||||
# cypher-executor 執行 http_request 節點時對 kbdb 發 fetch。若打同 zone URL 會踩 CF 1042
|
||||
# (same-zone self-fetch)。兩條路皆可:
|
||||
# a) 帶 KBDB 的 custom domain(跨 zone、走公網前門,天然避開 1042);
|
||||
# b) self-hosted 有 `global_fetch_strictly_public` compatibility flag
|
||||
# (credential-primitives-wasm Phase 7,cypher wrangler.toml),開了之後
|
||||
# workers.dev URL 亦可直接帶。
|
||||
|
||||
# ── 觸發(同步查詢 trigger,非 202)──
|
||||
# GET https://{你的-cypher-domain}/q/{namespace}/graph_neighbors?node=Arcrun&depth=2&template=graph_triplet&namespace={namespace}&kbdb_base=https://{你的-kbdb-domain}
|
||||
# POST https://{你的-cypher-domain}/webhooks/named/graph_neighbors/query
|
||||
# -H "X-Arcrun-API-Key: {namespace}"
|
||||
# -d '{"node":"Arcrun","depth":2,"template":"graph_triplet","namespace":"{namespace}","kbdb_base":"https://{你的-kbdb-domain}"}'
|
||||
# → 直接回 { success, start, depth, directed, neighbors:[...], count }(最終節點輸出本身)。
|
||||
# (敏感輸入用 POST /query:GET /q/ 的 query string 會進各層 log,見 description.md。)
|
||||
|
||||
flow:
|
||||
- "input >> ON_SUCCESS >> fetch_triplets"
|
||||
- "fetch_triplets >> ON_SUCCESS >> bfs_neighbors"
|
||||
|
||||
config:
|
||||
# 1) 撈本租戶的 triplet 記錄。triplet = base 萬用表的一個 template(graph plugin 寫入),
|
||||
# slots = subject / predicate / object。base 端點:GET /records/by-template/:template?owner_id=
|
||||
# 回 { success, records:[{ record_id, values:{subject,predicate,object} }], count }。
|
||||
# ⚠️ template 名(此處 {{input.template}},預設由呼叫者帶 graph_triplet)以實際部署的
|
||||
# kbdb-graph-plugin triplet template id 為準——上線前對一次。
|
||||
# ⚠️ base URL 由呼叫者帶({{input.kbdb_base}})——不寫死任何一家的庫(見檔頂警示)。
|
||||
fetch_triplets:
|
||||
component: http_request
|
||||
method: GET
|
||||
url: "{{input.kbdb_base}}/records/by-template/{{input.template}}?owner_id={{input.namespace}}"
|
||||
headers:
|
||||
Accept: "application/json"
|
||||
|
||||
# 2) ★ 記憶體 BFS(通用 code 零件,sandbox inline JS,無 LLM、無 fs/網路,stdin→stdout JSON)。
|
||||
# 對照 kbdb-graph-plugin graph-traverse.ts:23-51 的記憶體 BFS:把 triplet 當有向邊
|
||||
# subject --predicate--> object 建鄰接表,從 start 逐跳擴張到 depth 上限,收集新訪節點當鄰居。
|
||||
# directed=false(預設)時把邊當雙向(無向圖鄰居);directed=true 只走 subject→object。
|
||||
bfs_neighbors:
|
||||
component: code
|
||||
code: |
|
||||
// graph_neighbors — 記憶體 BFS 找 N 跳鄰居(純函式、決定性、零 token)。
|
||||
// input(由下方 input: 映射解析後注入):
|
||||
// records[] : triplet 記錄({ values:{subject,predicate,object} } 或扁平 {subject,predicate,object})
|
||||
// start : 起點節點名(字串)
|
||||
// depth : 最大跳數(字串或數字,來自 query string 時是字串)
|
||||
// directed : "true" 只走 subject→object;否則當無向
|
||||
|
||||
const records = Array.isArray(input.records) ? input.records : [];
|
||||
const start = String(input.start == null ? '' : input.start);
|
||||
const maxDepth = Math.max(1, parseInt(String(input.depth == null ? 1 : input.depth), 10) || 1);
|
||||
const directed = String(input.directed == null ? '' : input.directed) === 'true';
|
||||
|
||||
if (!start) {
|
||||
return { success: false, error: 'graph_neighbors 缺 start(node)參數' };
|
||||
}
|
||||
|
||||
// 建鄰接表:subject --predicate--> object。無向時同時加反向邊。
|
||||
const adj = new Map();
|
||||
function addEdge(from, to, predicate) {
|
||||
if (!adj.has(from)) adj.set(from, []);
|
||||
adj.get(from).push({ node: to, predicate: predicate });
|
||||
}
|
||||
for (const r of records) {
|
||||
const v = (r && typeof r === 'object' && r.values && typeof r.values === 'object') ? r.values : r;
|
||||
if (!v || typeof v !== 'object') continue;
|
||||
const s = v.subject, p = v.predicate, o = v.object;
|
||||
if (!s || !o) continue;
|
||||
addEdge(s, o, p);
|
||||
if (!directed) addEdge(o, s, p);
|
||||
}
|
||||
|
||||
// BFS:一層一跳,收集首次訪到的節點當鄰居(記 depth / 來源 / 關係)。
|
||||
const visited = new Set([start]);
|
||||
let frontier = [start];
|
||||
const neighbors = [];
|
||||
for (let d = 1; d <= maxDepth; d++) {
|
||||
const next = [];
|
||||
for (const cur of frontier) {
|
||||
const outs = adj.get(cur) || [];
|
||||
for (const e of outs) {
|
||||
if (visited.has(e.node)) continue;
|
||||
visited.add(e.node);
|
||||
neighbors.push({ node: e.node, predicate: e.predicate, from: cur, depth: d });
|
||||
next.push(e.node);
|
||||
}
|
||||
}
|
||||
frontier = next;
|
||||
if (frontier.length === 0) break;
|
||||
}
|
||||
|
||||
return {
|
||||
success: true,
|
||||
start: start,
|
||||
depth: maxDepth,
|
||||
directed: directed,
|
||||
neighbors: neighbors,
|
||||
count: neighbors.length,
|
||||
};
|
||||
# input 映射:{{...}} 對 workflow context 展開後注入 code 沙箱的 `input` 變數。
|
||||
# {{input.X}} 的 input = 上游 input 節點輸出(=觸發 context);{{fetch_triplets.data.records}}
|
||||
# = http_request 回應 body 的 records 陣列(單一 ref pass-through 保留陣列型別)。
|
||||
input:
|
||||
records: "{{fetch_triplets.data.records}}"
|
||||
start: "{{input.node}}"
|
||||
depth: "{{input.depth}}"
|
||||
directed: "{{input.directed}}"
|
||||
limits:
|
||||
timeout_ms: 3000 # 純 CPU BFS,充裕
|
||||
max_output_bytes: 2097152 # 鄰居清單上限 2 MiB(呼叫端同步查詢輸出也有 5 MiB 硬上限)
|
||||
Reference in New Issue
Block a user