fix(kbdb): search keyword 補 source filter(#66)+semantic 曝 top_k/min_score 帶 score(#67)

#66:/entries/search keyword 路徑 source 解析後丟棄(#5.1 只接了 listEntries 那半)——
searchEntries 尾端加 source?(既有 positional caller 全不用改),conds 補與 listEntries
同款 json_extract(metadata_json,'$.source') 謂詞;route keyword 分支與 semantic 降級
分支兩處傳入。

#67:semantic 固定 topK=20、零分數閾值、低分尾硬湊數——route 曝 top_k(預設 20、封頂
100)與 min_score(預設 0=不過濾)query 參數;semanticSearch 依 min_score 截低分尾;
semantic 回應 entry 附 score 欄(加欄不改形)。壞值(非數字/非正)視同沒帶,不 400。

向後相容:不帶新參數時輸出與現況一致(semantic 僅多 score 資訊);不動表(D6)、
不動 D1 結構(API-as-Wall)。測試:新增 search-source-and-score.test.ts 13 條
(source 謂詞形狀/route 下傳/降級不洩 filter/min_score 截斷/topK 透傳封頂/壞值防呆/
不帶參數行為不變),kbdb vitest 33/33 綠、tsc 0。

關聯 #66 #67。merge 後需 gated redeploy kbdb worker(leo 閘)。

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01JUmjwkHLVBHM3ydhT1WSW3
This commit is contained in:
Claude
2026-07-19 07:53:46 +00:00
parent 2324537165
commit 65d85eb08f
5 changed files with 269 additions and 16 deletions
+14 -9
View File
@@ -222,11 +222,13 @@ export interface SemanticHit {
* workers-types 原生 typingdesign §3.3 的 fan-out fallback 不需啟用)。未帶=行為不變。
* 註:向量 metadata 的 library 在寫入端已正規化(未標記='general'),故 $in 不需 NULL 處理;
* 但「建 library metadata index 之前」upsert 的既有向量沒有此欄 → 部署清單強制 reindex backfill。
* min_scoreissue #67):分數閾值——Vectorize 只會硬湊 topK 筆,低分尾全是無關內容;
* 過濾放查詢端(非 Vectorize 端,API 無此參數)。預設 0=不過濾(行為與舊版一字不變,向後相容)。
*/
export async function semanticSearch(
env: Bindings,
q: string,
opts: { owner_id?: string; source?: string; entry_type?: string; library?: string[]; topK?: number } = {},
opts: { owner_id?: string; source?: string; entry_type?: string; library?: string[]; topK?: number; min_score?: number } = {},
): Promise<SemanticHit[] | null> {
if (!embedEnabled(env)) return null;
const vec = await embedText(env, q);
@@ -241,12 +243,15 @@ export async function semanticSearch(
returnMetadata: 'indexed',
...(Object.keys(filter).length ? { filter } : {}),
});
return (res.matches ?? []).map((m) => ({
id: m.id,
score: m.score,
owner_id: m.metadata?.owner_id as string | undefined,
entry_type: m.metadata?.entry_type as string | undefined,
source: m.metadata?.source as string | undefined,
library: m.metadata?.library as string | undefined,
}));
const minScore = opts.min_score ?? 0;
return (res.matches ?? [])
.filter((m) => m.score >= minScore)
.map((m) => ({
id: m.id,
score: m.score,
owner_id: m.metadata?.owner_id as string | undefined,
entry_type: m.metadata?.entry_type as string | undefined,
source: m.metadata?.source as string | undefined,
library: m.metadata?.library as string | undefined,
}));
}