portal-auth P1（#24 #25）：KBDB library filter 地基（不 merge，待總管審） (#50)

kbdb/src/routes/entries.ts

@@ -13,6 +13,14 @@ import { embedEnabled, embedOnWrite, semanticSearch } from '../embed';
 
 export const entryRoutes = new Hono<{ Bindings: Bindings }>();
 
+// library 多值參數（逗號分隔，portal-auth P1，design §3.3）。空值/全空白 → undefined（＝不過濾，
+// 行為與未帶參數一字不變——向後相容硬驗收）。
+function parseLibraryParam(raw: string | undefined): string[] | undefined {
+  if (!raw) return undefined;
+  const libs = raw.split(',').map((s) => s.trim()).filter(Boolean);
+  return libs.length > 0 ? libs : undefined;
+}
+
 // POST /entries — create (entry_type=block/value/project/workflow/...)
 entryRoutes.post('/', async (c) => {
   const body = await c.req.json().catch(() => null);
@@ -27,6 +35,7 @@ entryRoutes.post('/', async (c) => {
 // e.g. list workflows under a project: ?parent_id=PROJECT&entry_type=workflow
 // e.g. get one by idempotency key: ?page_name=skill-rag_with_arcrun
 // e.g. filter by ingest source: ?source=logseq://vault/foo.md (issue #5.1)
+// e.g. filter by library（多值逗號分隔，portal-auth P1）: ?library=finance,hr（未標記舊資料歸 general）
 // e.g. keyword filter: ?q=遷移 或 ?search=遷移（別名，Arcrun#3 發現①：caller 實測時打的是 search=，
 //   舊版完全不接這個 filter；q 與 search 兩個名字都認，避免同一個坑再踩一次）。
 // count = 本頁筆數（受 limit 影響）；total = 符合條件全部筆數（不受 limit 影響，見 total 欄位）。
@@ -37,6 +46,7 @@ entryRoutes.get('/', async (c) => {
     parent_id: c.req.query('parent_id') || undefined,
     page_name: c.req.query('page_name') || undefined,
     source: c.req.query('source') || undefined,
+    library: parseLibraryParam(c.req.query('library')),
     q: c.req.query('q') || c.req.query('search') || undefined,
     limit: c.req.query('limit') ? Number(c.req.query('limit')) : undefined,
     offset: c.req.query('offset') ? Number(c.req.query('offset')) : undefined,
@@ -44,23 +54,26 @@ entryRoutes.get('/', async (c) => {
   return c.json({ success: true, entries, count: entries.length, total });
 });
 
-// GET /entries/search?q=...&owner_id=...&source=...&entry_type=...&mode=keyword|semantic
+// GET /entries/search?q=...&owner_id=...&source=...&entry_type=...&library=...&mode=keyword|semantic
 //   - mode=keyword（預設）：D1 LIKE（base，永遠可用）。
 //   - mode=semantic：需 embed 模組開（Vectorize+AI binding）。未開 → 降級 keyword + capability_hint 告知缺能力（#7 發現閉環）。
 //   - entry_type：base 通用 filter（caller 傳任意 type，如 workflow；base 不寫死語意，workflow-discovery Q4）。
+//   - library：多值庫 filter（逗號分隔，portal-auth P1）。keyword 走 json_extract＋NULL→general；
+//     semantic 走 Vectorize $in。未帶＝全庫（行為不變）。
 entryRoutes.get('/search', async (c) => {
   const q = c.req.query('q');
   if (!q) return c.json({ success: false, error: 'q required' }, 400);
   const owner_id = c.req.query('owner_id') || undefined;
   const source = c.req.query('source') || undefined;
   const entry_type = c.req.query('entry_type') || undefined;
+  const library = parseLibraryParam(c.req.query('library'));
   const mode = c.req.query('mode') === 'semantic' ? 'semantic' : 'keyword';
 
   if (mode === 'semantic') {
-    const hits = await semanticSearch(c.env, q, { owner_id, source, entry_type });
+    const hits = await semanticSearch(c.env, q, { owner_id, source, entry_type, library });
     if (hits === null) {
       // 模組沒開：誠實降級 keyword + 告知「叫 CC 幫你開 vectorize」（不假裝有語義）。
-      const entries = await searchEntries(c.env.DB, q, owner_id, entry_type);
+      const entries = await searchEntries(c.env.DB, q, owner_id, entry_type, undefined, library);
       return c.json({
         success: true,
         entries,
@@ -78,7 +91,7 @@ entryRoutes.get('/search', async (c) => {
     return c.json({ success: true, entries, count: entries.length, mode: 'semantic' });
   }
 
-  const entries = await searchEntries(c.env.DB, q, owner_id, entry_type);
+  const entries = await searchEntries(c.env.DB, q, owner_id, entry_type, undefined, library);
   return c.json({ success: true, entries, count: entries.length, mode: 'keyword' });
 });