feat(skills,knowledge): 中文名补全与知识库沉淀支持可选大模型并明确大模型报错

技能中文名:
- 单个「AI 生成」与「一键补充中文名」均可在请求体 model_name 选择大模型
- 一键补充改为仅管理员开放
- _generate_skill_name_zh 在模型自身失败(构建/超时/API 报错)时抛
  SkillNameZhModelError,与模型返回无效名称区分;单个接口返回
  502「大模型报错,无法补全技能中文名」,批量在 model_error 中带回代表性报错

知识库沉淀:
- 对话保存到知识库 / 批量导入均新增可选 model_name(透传至 capture_thread
  → extract_thread_llm_multi)
- 批量返回 llm_fallback 计数;模型异常时仍按既有逻辑回退规则抽取并落草稿,
  前端明确提示「已改用规则抽取」(保存按钮保持后台异步)

前端新增 components/workspace/model-name-select.tsx 复用下拉(默认=系统配置模型)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

frontend-web/src/components/workspace/knowledge-save-trigger.tsx

@@ -1,17 +1,21 @@
 "use client";
 
 import { BookMarked } from "lucide-react";
+import { useState } from "react";
 import { toast } from "sonner";
 
 import { Button } from "@/components/ui/button";
 import { useKnowledgeActions } from "@/core/knowledge/hooks";
 
+import { ModelNameSelect } from "./model-name-select";
 import { useThread } from "./messages/context";
 import { Tooltip } from "./tooltip";
 
 export function KnowledgeSaveTrigger({ threadId }: { threadId: string }) {
   const { thread } = useThread();
   const { ingestThread } = useKnowledgeActions();
+  // Optional model override for the extraction (null = configured default).
+  const [model, setModel] = useState<string | null>(null);
 
   if (thread.messages.length === 0) {
     return null;
@@ -23,7 +27,7 @@ export function KnowledgeSaveTrigger({ threadId }: { threadId: string }) {
     try {
       await ingestThread.mutateAsync({
         threadId,
-        payload: { background: true },
+        payload: { background: true, model_name: model },
       });
       toast.success("已加入知识库保存队列，正在后台整理…");
     } catch (error) {
@@ -32,16 +36,24 @@ export function KnowledgeSaveTrigger({ threadId }: { threadId: string }) {
   };
 
   return (
-    <Tooltip content="保存到知识库（后台异步整理）">
-      <Button
-        className="text-muted-foreground hover:text-foreground"
-        variant="ghost"
-        onClick={() => void handleSave()}
+    <div className="flex items-center gap-1.5">
+      <ModelNameSelect
+        value={model}
+        onChange={setModel}
         disabled={ingestThread.isPending}
-      >
-        <BookMarked />
-        {ingestThread.isPending ? "保存中…" : "保存"}
-      </Button>
-    </Tooltip>
+        triggerClassName="h-8 w-[8.5rem]"
+      />
+      <Tooltip content="保存到知识库（用所选大模型后台异步整理）">
+        <Button
+          className="text-muted-foreground hover:text-foreground"
+          variant="ghost"
+          onClick={() => void handleSave()}
+          disabled={ingestThread.isPending}
+        >
+          <BookMarked />
+          {ingestThread.isPending ? "保存中…" : "保存"}
+        </Button>
+      </Tooltip>
+    </div>
   );
 }

frontend-web/src/components/workspace/model-name-select.tsx

@@ -0,0 +1,59 @@
+"use client";
+
+import {
+  Select,
+  SelectContent,
+  SelectItem,
+  SelectTrigger,
+  SelectValue,
+} from "@/components/ui/select";
+import { useModels } from "@/core/models/hooks";
+import { cn } from "@/lib/utils";
+
+/** Sentinel for "use the backend's default/configured model" (no override). */
+const DEFAULT_VALUE = "__default__";
+
+/**
+ * Compact dropdown to optionally pick an LLM model for a one-off action
+ * (skill-name generation, knowledge ingestion, …). The value is the model
+ * `name`; `null` means "use the configured default" (no override sent).
+ */
+export function ModelNameSelect({
+  value,
+  onChange,
+  disabled,
+  className,
+  triggerClassName,
+  defaultLabel = "默认模型",
+}: {
+  value: string | null;
+  onChange: (modelName: string | null) => void;
+  disabled?: boolean;
+  className?: string;
+  triggerClassName?: string;
+  defaultLabel?: string;
+}) {
+  const { models } = useModels();
+  return (
+    <Select
+      value={value ?? DEFAULT_VALUE}
+      onValueChange={(v) => onChange(v === DEFAULT_VALUE ? null : v)}
+      disabled={disabled}
+    >
+      <SelectTrigger
+        className={cn("h-8 gap-1.5 text-xs", triggerClassName, className)}
+        title="选择用于本次操作的大模型(默认使用系统配置的模型)"
+      >
+        <SelectValue placeholder={defaultLabel} />
+      </SelectTrigger>
+      <SelectContent position="popper" side="bottom" sideOffset={4}>
+        <SelectItem value={DEFAULT_VALUE}>{defaultLabel}</SelectItem>
+        {models.map((m) => (
+          <SelectItem key={m.name} value={m.name}>
+            {m.display_name || m.name}
+          </SelectItem>
+        ))}
+      </SelectContent>
+    </Select>
+  );
+}

frontend-web/src/components/workspace/settings/skill-settings-page.tsx

@@ -57,6 +57,7 @@ import {
 import { Input } from "@/components/ui/input";
 import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select";
 import { Tabs, TabsList, TabsTrigger } from "@/components/ui/tabs";
+import { ModelNameSelect } from "@/components/workspace/model-name-select";
 import { SkillDetailDialog } from "@/components/workspace/skills/skill-detail-dialog";
 import { TagChipList } from "@/components/workspace/tags/tag-chip";
 import { TagPickerDialog } from "@/components/workspace/tags/tag-picker-dialog";
@@ -163,6 +164,8 @@ function SkillSettingsList({ onClose }: { onClose?: () => void }) {
   const [viewMode, setViewMode] = useViewMode("skill");
   const reconcileMutation = useReconcileCustomSkills();
   const fillNamesMutation = useGenerateMissingSkillNameZh();
+  // Optional model override for the admin "一键补充中文名" action (null = default).
+  const [fillModel, setFillModel] = useState<string | null>(null);
   // Name + tag filtering is resolved server-side via the /api/skills query.
   const { skills, isLoading, error } = useSkills({ search, tagIds, sort });
 
@@ -249,13 +252,18 @@ function SkillSettingsList({ onClose }: { onClose?: () => void }) {
 
   const handleFillNames = async () => {
     try {
-      const result = await fillNamesMutation.mutateAsync();
+      const result = await fillNamesMutation.mutateAsync(fillModel);
       const okCount = result.generated.length;
       const failCount = result.failed.length;
       if (okCount === 0 && failCount === 0) {
         toast.info("所有技能均已配置中文名称");
       } else if (failCount === 0) {
         toast.success(`已为 ${okCount} 个技能补充中文名称`);
+      } else if (result.model_error) {
+        // Failures came from the model itself — say so explicitly.
+        toast.warning(
+          `已补充 ${okCount} 个,${failCount} 个因大模型报错失败:${result.model_error}`,
+        );
       } else {
         toast.warning(`已补充 ${okCount} 个,${failCount} 个生成失败,可稍后重试或手动填写`);
       }
@@ -354,24 +362,37 @@ function SkillSettingsList({ onClose }: { onClose?: () => void }) {
               ? t.settings.skills.rescanSkillsRunning
               : t.settings.skills.rescanSkills}
           </Button>
-          <Button
-            size="sm"
-            variant="outline"
-            className="gap-1.5 border-violet-300 bg-violet-50 font-medium text-violet-700 hover:bg-violet-100 hover:text-violet-800 dark:border-violet-500/40 dark:bg-violet-500/15 dark:text-violet-300 dark:hover:bg-violet-500/25"
-            onClick={() => void handleFillNames()}
-            disabled={
-              fillNamesMutation.isPending ||
-              env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true"
-            }
-            title="用大模型为所有尚未配置中文名称的技能自动生成中文名"
-          >
-            {fillNamesMutation.isPending ? (
-              <Loader2 className="size-4 animate-spin" />
-            ) : (
-              <SparklesIcon className="size-4" />
-            )}
-            {fillNamesMutation.isPending ? "补充中…" : "一键补充中文名"}
-          </Button>
+          {isAdmin && (
+            <>
+              <ModelNameSelect
+                value={fillModel}
+                onChange={setFillModel}
+                disabled={
+                  fillNamesMutation.isPending ||
+                  env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true"
+                }
+                triggerClassName="h-8 w-[9.5rem]"
+              />
+              <Button
+                size="sm"
+                variant="outline"
+                className="gap-1.5 border-violet-300 bg-violet-50 font-medium text-violet-700 hover:bg-violet-100 hover:text-violet-800 dark:border-violet-500/40 dark:bg-violet-500/15 dark:text-violet-300 dark:hover:bg-violet-500/25"
+                onClick={() => void handleFillNames()}
+                disabled={
+                  fillNamesMutation.isPending ||
+                  env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true"
+                }
+                title="用所选大模型为所有尚未配置中文名称的技能自动生成中文名(仅管理员)"
+              >
+                {fillNamesMutation.isPending ? (
+                  <Loader2 className="size-4 animate-spin" />
+                ) : (
+                  <SparklesIcon className="size-4" />
+                )}
+                {fillNamesMutation.isPending ? "补充中…" : "一键补充中文名"}
+              </Button>
+            </>
+          )}
           <Button
             size="sm"
             variant="outline"

frontend-web/src/components/workspace/skills/skill-detail-dialog.tsx

@@ -29,6 +29,7 @@ import { Input } from "@/components/ui/input";
 import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs";
 import { Textarea } from "@/components/ui/textarea";
 import { MarkdownContent } from "@/components/workspace/messages/markdown-content";
+import { ModelNameSelect } from "@/components/workspace/model-name-select";
 import { SkillDisplayAdapterPanel } from "@/components/workspace/skill-display-adapter-panel";
 import { SkillFilePreviewDialog } from "@/components/workspace/skills/skill-file-preview-dialog";
 import { SkillFileTree } from "@/components/workspace/skills/skill-file-tree";
@@ -109,6 +110,8 @@ export function SkillDetailDialog({
   const [draft, setDraft] = useState("");
   const [editingNameZh, setEditingNameZh] = useState(false);
   const [nameZhDraft, setNameZhDraft] = useState("");
+  // Optional model override for the "AI 生成" button (null = configured default).
+  const [nameZhModel, setNameZhModel] = useState<string | null>(null);
   const [activeTab, setActiveTab] = useState<
     "detail" | "display" | "source" | "files" | null
   >(null);
@@ -194,7 +197,10 @@ export function SkillDetailDialog({
   async function handleGenerateNameZh() {
     if (!skill) return;
     try {
-      const result = await generateNameZh.mutateAsync(skill.name);
+      const result = await generateNameZh.mutateAsync({
+        skillName: skill.name,
+        modelName: nameZhModel,
+      });
       setNameZhDraft(result.name_zh ?? "");
       toast.success("已生成中文名称");
     } catch (err) {
@@ -237,17 +243,23 @@ export function SkillDetailDialog({
                       if (event.key === "Escape") setEditingNameZh(false);
                     }}
                     placeholder={desensitize(skill?.name ?? skillName ?? "")}
-                    className="h-8 max-w-[18rem] flex-1 text-sm"
+                    className="h-8 max-w-[14rem] flex-1 text-sm"
                     autoFocus
                     disabled={generateNameZh.isPending || setNameZh.isPending}
                   />
+                  <ModelNameSelect
+                    value={nameZhModel}
+                    onChange={setNameZhModel}
+                    disabled={generateNameZh.isPending || setNameZh.isPending}
+                    triggerClassName="h-8 w-[8.5rem] shrink-0"
+                  />
                   <Button
                     size="sm"
                     variant="outline"
                     className="h-8 shrink-0 gap-1 border-violet-300 bg-violet-50 px-2.5 text-xs font-medium text-violet-700 hover:bg-violet-100 hover:text-violet-800 dark:border-violet-500/40 dark:bg-violet-500/15 dark:text-violet-300 dark:hover:bg-violet-500/25"
                     onClick={() => void handleGenerateNameZh()}
                     disabled={generateNameZh.isPending || setNameZh.isPending}
-                    title="用大模型自动生成中文名"
+                    title="用所选大模型自动生成中文名"
                   >
                     {generateNameZh.isPending ? (
                       <Loader2 className="size-3.5 animate-spin" />

frontend-web/src/core/knowledge/types.ts

@@ -101,6 +101,8 @@ export interface IngestThreadPayload {
   include_sources?: boolean;
   /** When true the backend sediments asynchronously and returns immediately. */
   background?: boolean;
+  /** Optional model override for knowledge extraction (null = configured default). */
+  model_name?: string | null;
 }
 
 export interface BatchIngestPayload {
@@ -110,6 +112,8 @@ export interface BatchIngestPayload {
   include_sources?: boolean;
   skip_existing?: boolean;
   mode?: "summary" | "full";
+  /** Optional model override for knowledge extraction (null = configured default). */
+  model_name?: string | null;
 }
 
 export interface BatchIngestResult {
@@ -118,7 +122,14 @@ export interface BatchIngestResult {
   created: number;
   skipped: number;
   failed: number;
-  items: Array<{ thread_id: string; note_id: string | null; status: string }>;
+  /** Notes that fell back to rule-based extraction because the model failed. */
+  llm_fallback?: number;
+  items: Array<{
+    thread_id: string;
+    note_id: string | null;
+    status: string;
+    llm_fallback?: boolean;
+  }>;
 }
 
 export interface GraphExportResult {

frontend-web/src/core/skills/api.ts

@@ -439,6 +439,8 @@ export interface GenerateMissingSkillNameZhResponse {
   generated: SkillNameZhResponse[];
   failed: string[];
   skipped: number;
+  /** Representative model error when some skills failed due to the LLM. */
+  model_error?: string | null;
 }
 
 /**
@@ -466,10 +468,15 @@ export async function setSkillNameZh(
 /** Ask the LLM to generate and persist a Chinese name for a single skill. */
 export async function generateSkillNameZh(
   skillName: string,
+  modelName?: string | null,
 ): Promise<SkillNameZhResponse> {
   const response = await apiFetch(
     `${getBackendBaseURL()}/api/skills/${encodeURIComponent(skillName)}/name-zh/generate`,
-    { method: "POST" },
+    {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({ model_name: modelName ?? null }),
+    },
   );
   if (!response.ok) {
     throw await parseDetailedError(response, "Failed to generate skill Chinese name");
@@ -477,11 +484,17 @@ export async function generateSkillNameZh(
   return response.json() as Promise<SkillNameZhResponse>;
 }
 
-/** One-click: generate Chinese names for every skill that lacks one. */
-export async function generateMissingSkillNameZh(): Promise<GenerateMissingSkillNameZhResponse> {
+/** One-click (admin): generate Chinese names for every skill that lacks one. */
+export async function generateMissingSkillNameZh(
+  modelName?: string | null,
+): Promise<GenerateMissingSkillNameZhResponse> {
   const response = await apiFetch(
     `${getBackendBaseURL()}/api/skills/name-zh/generate-missing`,
-    { method: "POST" },
+    {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({ model_name: modelName ?? null }),
+    },
   );
   if (!response.ok) {
     throw await parseDetailedError(response, "Failed to bulk-generate skill Chinese names");

frontend-web/src/core/skills/hooks.ts

@@ -108,8 +108,9 @@ export function useSetSkillNameZh() {
 export function useGenerateSkillNameZh() {
   const queryClient = useQueryClient();
   return useMutation({
-    mutationFn: (skillName: string) => generateSkillNameZh(skillName),
-    onSuccess: (_data, skillName) => {
+    mutationFn: ({ skillName, modelName }: { skillName: string; modelName?: string | null }) =>
+      generateSkillNameZh(skillName, modelName),
+    onSuccess: (_data, { skillName }) => {
       void queryClient.invalidateQueries({ queryKey: ["skills"] });
       void queryClient.invalidateQueries({ queryKey: ["skill", skillName] });
     },
@@ -119,7 +120,7 @@ export function useGenerateSkillNameZh() {
 export function useGenerateMissingSkillNameZh() {
   const queryClient = useQueryClient();
   return useMutation({
-    mutationFn: () => generateMissingSkillNameZh(),
+    mutationFn: (modelName?: string | null) => generateMissingSkillNameZh(modelName),
     onSuccess: () => {
       void queryClient.invalidateQueries({ queryKey: ["skills"] });
     },

frontend-web/src/pages/KnowledgeBasePage.tsx

@@ -37,6 +37,7 @@ import {
   SelectValue,
 } from "@/components/ui/select";
 import { Textarea } from "@/components/ui/textarea";
+import { ModelNameSelect } from "@/components/workspace/model-name-select";
 import {
   useKnowledgeActions,
   useKnowledgeDuplicates,
@@ -241,6 +242,8 @@ function BatchImportDialog({
   const { batchIngest } = useKnowledgeActions();
   const [limit, setLimit] = useState(50);
   const [skipExisting, setSkipExisting] = useState(true);
+  // Optional model override for extraction (null = configured default).
+  const [model, setModel] = useState<string | null>(null);
 
   const handleRun = async () => {
     try {
@@ -249,10 +252,18 @@ function BatchImportDialog({
         skip_existing: skipExisting,
         status: "approved",
         include_sources: true,
+        model_name: model,
       });
-      toast.success(
-        `批量导入完成：新增 ${result.created}，跳过 ${result.skipped}，失败 ${result.failed}`,
-      );
+      const base = `批量导入完成：新增 ${result.created}，跳过 ${result.skipped}，失败 ${result.failed}`;
+      if (result.llm_fallback && result.llm_fallback > 0) {
+        // The model failed on some threads — they were saved via rule-based
+        // extraction instead. Say so explicitly per the requirement.
+        toast.warning(
+          `${base}；其中 ${result.llm_fallback} 条因大模型异常改用了规则抽取(草稿)`,
+        );
+      } else {
+        toast.success(base);
+      }
       onOpenChange(false);
     } catch (error) {
       toast.error(error instanceof Error ? error.message : "批量导入失败");
@@ -289,6 +300,15 @@ function BatchImportDialog({
               className="size-4"
             />
           </label>
+          <label className="flex items-center justify-between gap-2 text-sm">
+            提炼大模型
+            <ModelNameSelect
+              value={model}
+              onChange={setModel}
+              disabled={batchIngest.isPending}
+              triggerClassName="h-9 w-[11rem]"
+            />
+          </label>
         </div>
         <DialogFooter>
           <Button variant="outline" onClick={() => onOpenChange(false)}>

offline-backend-20260512/backend/app/gateway/routers/knowledge.py

@@ -44,6 +44,7 @@ class IngestThreadRequest(BaseModel):
         default=False,
         description="When true, sediment the thread asynchronously in a background task and return immediately.",
     )
+    model_name: str | None = Field(default=None, description="可选:指定用于知识提炼的大模型名称;留空使用默认配置")
 
 
 class BatchIngestRequest(BaseModel):
@@ -53,6 +54,7 @@ class BatchIngestRequest(BaseModel):
     include_sources: bool = True
     skip_existing: bool = True
     mode: str = "summary"
+    model_name: str | None = Field(default=None, description="可选:指定用于知识提炼的大模型名称;留空使用默认配置")
 
 
 class SearchResultItem(BaseModel):
@@ -175,6 +177,7 @@ async def _ingest_thread_background(service, checkpointer, thread_id: str, body:
             include_sources=body.include_sources,
             reference_batches=batches,
             created_by=created_by,
+            model_name=body.model_name,
         )
     except EmptyThreadError:
         logger.warning("Background knowledge ingest skipped: thread %s has no sediment-able content", sanitize_log_param(thread_id))
@@ -224,6 +227,7 @@ async def ingest_thread(thread_id: str, body: IngestThreadRequest, request: Requ
             include_sources=body.include_sources,
             reference_batches=batches,
             created_by=get_effective_user_id(),
+            model_name=body.model_name,
         )
     except EmptyThreadError:
         raise HTTPException(status_code=400, detail="Thread has no sediment-able content")
@@ -245,6 +249,10 @@ async def ingest_threads_batch(body: BatchIngestRequest, request: Request) -> di
 
     threads = await thread_store.search(limit=body.limit, offset=body.offset)
     created = skipped = failed = 0
+    # Notes that landed via the rule-based fallback because the chosen model
+    # produced nothing usable (timeout / API error / non-JSON). Surfaced so the
+    # caller can tell the user "X 条因大模型异常改用了规则抽取".
+    llm_fallback = 0
     items: list[dict[str, Any]] = []
     for meta in threads:
         thread_id = meta.get("thread_id")
@@ -267,10 +275,13 @@ async def ingest_threads_batch(body: BatchIngestRequest, request: Request) -> di
                 reference_batches=batches,
                 created_by=get_effective_user_id(),
                 skip_existing=body.skip_existing,
+                model_name=body.model_name,
             )
+            if result.get("llm_fallback"):
+                llm_fallback += 1
             if result["created"]:
                 created += 1
-                items.append({"thread_id": thread_id, "note_id": result["note"]["id"], "status": "created"})
+                items.append({"thread_id": thread_id, "note_id": result["note"]["id"], "status": "created", "llm_fallback": bool(result.get("llm_fallback"))})
             else:
                 skipped += 1
                 items.append({"thread_id": thread_id, "note_id": result["note"]["id"], "status": "skipped"})
@@ -285,7 +296,7 @@ async def ingest_threads_batch(body: BatchIngestRequest, request: Request) -> di
             failed += 1
             items.append({"thread_id": thread_id, "note_id": None, "status": "failed"})
 
-    return {"ok": True, "processed": len(items), "created": created, "skipped": skipped, "failed": failed, "items": items}
+    return {"ok": True, "processed": len(items), "created": created, "skipped": skipped, "failed": failed, "llm_fallback": llm_fallback, "items": items}
 
 
 @router.post("/ingest/search")

offline-backend-20260512/backend/app/gateway/routers/skills.py

@@ -2366,6 +2366,15 @@ _SKILL_NAME_ZH_SYSTEM_PROMPT = (
 )
 
 
+class SkillNameZhModelError(Exception):
+    """The LLM call backing skill-name generation failed (a *model-side* problem).
+
+    Distinguishes a genuine model failure (timeout / API error / unbuildable
+    model) — which must be surfaced to the user as "大模型报错导致无法补全" — from
+    the model merely returning an unusable name (callers get ``None`` instead).
+    """
+
+
 def _clean_generated_name_zh(raw: str) -> str | None:
     """Normalise an LLM-produced Chinese name: first line, strip quotes/punct, cap length."""
     if not raw:
@@ -2388,24 +2397,45 @@ def _clean_generated_name_zh(raw: str) -> str | None:
     return text or None
 
 
-async def _generate_skill_name_zh(skill: Skill, app_config: AppConfig, model: Any = None) -> str | None:
+def _resolve_skill_name_zh_model_name(app_config: AppConfig, model_name: str | None) -> str | None:
+    """Pick the model name for skill-name generation.
+
+    An explicit ``model_name`` (user-selected in the UI) wins; otherwise fall
+    back to the curator/security-scan model setting (itself falling back to the
+    main model when unset).
+    """
+    if model_name and model_name.strip():
+        return model_name.strip()
+    if app_config.skill_evolution and app_config.skill_evolution.curator:
+        return app_config.skill_evolution.curator.model_name
+    return None
+
+
+async def _generate_skill_name_zh(skill: Skill, app_config: AppConfig, model: Any = None, *, model_name: str | None = None) -> str | None:
     """Generate a Chinese display name for ``skill`` via the LLM.
 
-    Reuses the curator/security-scan model setting (falls back to the main model).
-    Returns None when the model is unconfigured, the call times out/fails, or the
-    output cannot be normalised into a short Chinese name.
+    An explicit ``model_name`` lets the caller pick the model; otherwise it
+    reuses the curator/security-scan model setting (falls back to the main
+    model). Returns ``None`` only when the model replies but the output cannot be
+    normalised into a short Chinese name. Raises :class:`SkillNameZhModelError`
+    when the model itself fails (cannot be built / times out / API error), so the
+    caller can tell the user it was a *model* problem.
     """
     user_prompt = (
         f"技能英文名:{skill.name}\n"
         f"功能描述:{skill.description or '(无描述)'}\n\n"
         "请为该技能起一个中文名称。"
     )
-    try:
-        from deerflow.models import create_chat_model
+    if model is None:
+        try:
+            from deerflow.models import create_chat_model
 
-        if model is None:
-            model_name = app_config.skill_evolution.curator.model_name if app_config.skill_evolution and app_config.skill_evolution.curator else None
-            model = create_chat_model(name=model_name, thinking_enabled=False, app_config=app_config)
+            resolved = _resolve_skill_name_zh_model_name(app_config, model_name)
+            model = create_chat_model(name=resolved, thinking_enabled=False, app_config=app_config)
+        except Exception as e:
+            logger.warning("Skill name_zh model build failed for %s", skill.name, exc_info=True)
+            raise SkillNameZhModelError(str(e) or "无法初始化所选大模型") from e
+    try:
         response = await asyncio.wait_for(
             model.ainvoke(
                 [
@@ -2416,12 +2446,13 @@ async def _generate_skill_name_zh(skill: Skill, app_config: AppConfig, model: An
             ),
             timeout=30,
         )
-        return _clean_generated_name_zh(str(getattr(response, "content", "") or ""))
-    except asyncio.TimeoutError:
+    except asyncio.TimeoutError as e:
         logger.warning("Skill name_zh LLM call timed out for %s", skill.name)
-    except Exception:
+        raise SkillNameZhModelError("大模型响应超时(30 秒)") from e
+    except Exception as e:
         logger.warning("Skill name_zh LLM call failed for %s", skill.name, exc_info=True)
-    return None
+        raise SkillNameZhModelError(str(e) or "大模型调用失败") from e
+    return _clean_generated_name_zh(str(getattr(response, "content", "") or ""))
 
 
 async def _persist_skill_name_zh(
@@ -2475,6 +2506,13 @@ class SkillNameZhBulkResponse(BaseModel):
     generated: list[SkillNameZhResponse] = Field(default_factory=list, description="本次成功生成中文名的技能")
     failed: list[str] = Field(default_factory=list, description="生成失败的技能英文名")
     skipped: int = Field(default=0, description="已有中文名而被跳过的技能数")
+    model_error: str | None = Field(default=None, description="若有技能因大模型报错而失败,这里给出代表性的报错信息")
+
+
+class GenerateSkillNameZhRequest(BaseModel):
+    """Optional body for skill-name generation: pick the model to use."""
+
+    model_name: str | None = Field(default=None, description="可选:指定用于生成的大模型名称;留空使用默认配置")
 
 
 def _can_edit_skill_name_zh(skill: Skill, record: dict[str, Any] | None, user_id: str, *, is_admin: bool) -> bool:
@@ -2521,15 +2559,17 @@ async def set_skill_name_zh(
     "/skills/{skill_name}/name-zh/generate",
     response_model=SkillNameZhResponse,
     summary="Generate Skill Chinese Name",
-    description="用大模型为该技能生成一个中文名称并保存到数据库。",
+    description="用大模型为该技能生成一个中文名称并保存到数据库。可在请求体里通过 model_name 指定使用的大模型。",
 )
 async def generate_skill_name_zh(
     skill_name: str,
     request: Request,
+    body: GenerateSkillNameZhRequest | None = None,
     config: AppConfig = Depends(get_config),
     skill_store: SkillStore = Depends(get_skill_store),
 ) -> SkillNameZhResponse:
     try:
+        body = body or GenerateSkillNameZhRequest()
         skill_name = skill_name.replace("\r\n", "").replace("\n", "")
         user_id = _current_user_id(request)
         is_admin = _is_admin_user(request)
@@ -2537,9 +2577,12 @@ async def generate_skill_name_zh(
         skill = next((s for s in skills if s.name == skill_name), None)
         if skill is None:
             raise HTTPException(status_code=404, detail=f"Skill '{skill_name}' not found")
-        name_zh = await _generate_skill_name_zh(skill, config)
+        try:
+            name_zh = await _generate_skill_name_zh(skill, config, model_name=body.model_name)
+        except SkillNameZhModelError as e:
+            raise HTTPException(status_code=502, detail=f"大模型报错,无法补全技能中文名:{e}")
         if not name_zh:
-            raise HTTPException(status_code=502, detail="模型未能生成有效的中文名称,请稍后重试或手动填写")
+            raise HTTPException(status_code=502, detail="大模型未能生成有效的中文名称,请稍后重试或手动填写")
         stored = await _persist_skill_name_zh(skill, name_zh, skill_store, user_id, is_admin=is_admin)
         return SkillNameZhResponse(name=skill_name, name_zh=stored)
     except HTTPException:
@@ -2553,26 +2596,27 @@ async def generate_skill_name_zh(
     "/skills/name-zh/generate-missing",
     response_model=SkillNameZhBulkResponse,
     summary="Bulk Generate Missing Skill Chinese Names",
-    description="一键为库中所有尚未配置中文名称、且当前用户有权编辑的技能生成中文名(存数据库)。",
+    description="管理员一键为库中所有尚未配置中文名称的技能生成中文名(存数据库)。可在请求体里通过 model_name 指定使用的大模型。",
 )
 async def generate_missing_skill_names_zh(
     request: Request,
+    body: GenerateSkillNameZhRequest | None = None,
     config: AppConfig = Depends(get_config),
     skill_store: SkillStore = Depends(get_skill_store),
 ) -> SkillNameZhBulkResponse:
     try:
         from deerflow.models import create_chat_model
 
+        body = body or GenerateSkillNameZhRequest()
         user_id = _current_user_id(request)
         is_admin = _is_admin_user(request)
+        # 一键补充技能中文名仅对管理员开放。
+        if not is_admin:
+            raise HTTPException(status_code=403, detail="仅管理员可一键补充技能中文名")
         skills = get_or_new_skill_storage(app_config=config).load_skills(enabled_only=False)
 
-        # Existing name_zh values come from the DB. Admins see every row; others
-        # see only the rows visible to them (owned / published / built-in).
-        if is_admin:
-            records = {r["name"]: r for r in await skill_store.list_all()}
-        else:
-            records = {r["name"]: r for r in await skill_store.list_visible(user_id)}
+        # Admin sees every row, so existing name_zh values come from the full set.
+        records = {r["name"]: r for r in await skill_store.list_all()}
 
         pending: list[Skill] = []
         skipped = 0
@@ -2581,32 +2625,36 @@ async def generate_missing_skill_names_zh(
             if record and record.get("name_zh"):
                 skipped += 1
                 continue
-            # Skip skills the caller is not allowed to annotate (no error — bulk
-            # is best-effort over what the user can edit).
-            if not _can_edit_skill_name_zh(skill, record, user_id, is_admin=is_admin):
-                continue
             pending.append(skill)
 
         generated: list[SkillNameZhResponse] = []
         failed: list[str] = []
+        model_error: str | None = None
         if pending:
-            # Build the model once and reuse it for every skill.
+            # Build the model once and reuse it for every skill. A build failure
+            # is a model problem — fail fast with a clear message rather than
+            # silently producing zero results.
             try:
-                model_name = config.skill_evolution.curator.model_name if config.skill_evolution and config.skill_evolution.curator else None
-                model = create_chat_model(name=model_name, thinking_enabled=False, app_config=config)
-            except Exception:
+                resolved_name = _resolve_skill_name_zh_model_name(config, body.model_name)
+                model = create_chat_model(name=resolved_name, thinking_enabled=False, app_config=config)
+            except Exception as e:
                 logger.warning("Failed to build model for bulk name_zh generation", exc_info=True)
-                model = None
+                raise HTTPException(status_code=502, detail=f"大模型报错,无法补全技能中文名:{str(e) or '无法初始化所选大模型'}")
 
             # Generate concurrently with a small bound to avoid overloading the model.
             semaphore = asyncio.Semaphore(4)
 
-            async def _one(skill: Skill) -> tuple[Skill, str | None]:
+            async def _one(skill: Skill) -> tuple[Skill, str | None, str | None]:
                 async with semaphore:
-                    return skill, await _generate_skill_name_zh(skill, config, model=model)
+                    try:
+                        return skill, await _generate_skill_name_zh(skill, config, model=model), None
+                    except SkillNameZhModelError as e:
+                        return skill, None, str(e)
 
             results = await asyncio.gather(*[_one(s) for s in pending])
-            for skill, name_zh in results:
+            for skill, name_zh, err in results:
+                if err and model_error is None:
+                    model_error = err
                 if not name_zh:
                     failed.append(skill.name)
                     continue
@@ -2617,7 +2665,7 @@ async def generate_missing_skill_names_zh(
                     # Permission / persistence issue for this one skill — skip it.
                     failed.append(skill.name)
 
-        return SkillNameZhBulkResponse(generated=generated, failed=failed, skipped=skipped)
+        return SkillNameZhBulkResponse(generated=generated, failed=failed, skipped=skipped, model_error=model_error)
     except HTTPException:
         raise
     except Exception as e:

offline-backend-20260512/backend/packages/harness/deerflow/knowledge/service.py

@@ -222,9 +222,13 @@ class KnowledgeService:
         reference_batches: list[dict[str, Any]] | None = None,
         created_by: str | None = None,
         skip_existing: bool = False,
+        model_name: str | None = None,
     ) -> dict[str, Any]:
         """Sediment a thread into a knowledge note.
 
+        ``model_name`` optionally overrides the configured extraction model for
+        this one capture (falls back to ``config.extract_model_name``).
+
         Returns ``{"note": <note>, "created": bool}``. Raises
         :class:`EmptyThreadError` when there is nothing worth keeping.
         """
@@ -269,7 +273,7 @@ class KnowledgeService:
                     project_name=self.project_name,
                     sources=sources,
                     max_messages=self.config.max_thread_messages,
-                    model_name=self.config.extract_model_name,
+                    model_name=model_name or self.config.extract_model_name,
                     max_input_chars=self.config.extract_max_input_chars,
                     allow_multi=self.config.multi_note_enabled,
                 )