Merge branch 'master-nj' of http://192.168.0.200/knowledge-base-bj/deerflow-code into master-zl

# Conflicts:
#	frontend-web/src/components/workspace/input-box.tsx
#	frontend-web/src/components/workspace/skill-display-sources.tsx

.gitignore

@@ -87,24 +87,35 @@ offline-backend-20260512/backend/skill_evolution.json
 skills/
 hermes-agent-main/
 .gitignore
-offline-backend-20260512/backend/tests/*
+offline-backend-20260512/backend/tests/*
-!offline-backend-20260512/backend/tests/test_llmwiki_weknora.py
+!offline-backend-20260512/backend/tests/test_llmwiki_weknora.py
-!offline-backend-20260512/backend/tests/test_health_auth_bypass.py
+!offline-backend-20260512/backend/tests/test_health_auth_bypass.py
-# Keep the model configuration regression coverage versioned even though
+# Keep the model configuration regression coverage versioned even though
-# this deployment repository otherwise ignores newly added backend tests.
+# this deployment repository otherwise ignores newly added backend tests.
-!offline-backend-20260512/backend/tests/test_model_management.py
+!offline-backend-20260512/backend/tests/test_model_management.py
-# Deep-research reliability regression coverage.
+# Keep fixed-question exact-match and streaming regression coverage versioned.
-!offline-backend-20260512/backend/tests/test_deep_research_persistence.py
+!offline-backend-20260512/backend/tests/test_fixed_questions.py
-!offline-backend-20260512/backend/tests/test_deep_research_event_sink.py
+# Keep configurable es_query system-prompt routing regression coverage versioned.
+!offline-backend-20260512/backend/tests/test_es_query_routing_prompt.py
+# Keep the local LLMWiki vector-index and external API regression coverage versioned.
+!offline-backend-20260512/backend/tests/test_llmwiki_local_index_repository.py
+!offline-backend-20260512/backend/tests/test_llmwiki_vector_search.py
+!offline-backend-20260512/backend/tests/test_llmwiki_wiki_sync.py
+!offline-backend-20260512/backend/tests/test_external_llmwiki_search.py
+!offline-backend-20260512/backend/tests/test_llmwiki_wiki_retrieval.py
+!offline-backend-20260512/backend/tests/test_public_llmwiki_embed.py
+# Deep-research reliability regression coverage.
+!offline-backend-20260512/backend/tests/test_deep_research_persistence.py
+!offline-backend-20260512/backend/tests/test_deep_research_event_sink.py
 !offline-backend-20260512/backend/tests/test_deep_research_executor_reliability.py
 !offline-backend-20260512/backend/tests/test_deep_research_start_job.py
 !offline-backend-20260512/backend/tests/test_summarization_human_message.py
 !offline-backend-20260512/backend/tests/test_compact_menu_overrides.py
 # Independent enterprise-research persistence, HTTP and race regressions.
 !offline-backend-20260512/backend/tests/test_enterprise_research_tasks.py
-# Position-roundtable per-turn write/present cap (weak-model duplicate artifacts).
+# Position-roundtable per-turn write/present cap (weak-model duplicate artifacts).
-!offline-backend-20260512/backend/tests/test_position_artifact_cap.py
+!offline-backend-20260512/backend/tests/test_position_artifact_cap.py
-deploy
+deploy
 .history
 
 # Cloned third-party repos (local only)

frontend-web/src/App.tsx

@@ -38,6 +38,7 @@ import EmbedChatPage from "./pages/EmbedChatPage";
 import EmbedRoundtablePage from "./pages/EmbedRoundtablePage";
 import DashboardStandalonePage from "@/roundtable-planning/pages/DashboardStandalonePage";
 import PositionRoundtablePage from "@/position-roundtable/pages/PositionRoundtablePage";
+import WeKnoraWikiPageView from "@/strategy-components/components/resource-management/llmwiki/WeKnoraWikiPageView";
 import {
   isPositionRoundtableStandaloneMode,
   POSITION_ROUNDTABLE_ROUTE,
@@ -45,7 +46,12 @@ import {
 import { ChatRuntime } from "./pages/WorkspaceRoutes";
 import { NotFoundPage } from "./pages/NotFoundPage";
 
-const PUBLIC_EMBED_PREFIXES = ["/share/", "/public/", "/roundtable-share/"];
+const PUBLIC_EMBED_PREFIXES = [
+  "/share/",
+  "/public/",
+  "/roundtable-share/",
+  "/embed/knowledge/",
+];
 
 function AppProviders({ children }: { children: React.ReactNode }) {
   const locale = useMemo(() => detectLocale(), []);
@@ -102,16 +108,17 @@ function AppProviders({ children }: { children: React.ReactNode }) {
       forcedTheme={forcedTheme}
     >
       <QueryClientProvider>
-        <I18nProvider initialLocale={locale}>
+        <AuthSyncWatcher disabled={positionStandaloneMode}>
-          <ThemeProvider>
+          <I18nProvider initialLocale={locale}>
-            <ChatProvider>
+            <ThemeProvider>
-              {!positionStandaloneMode && <AuthSyncWatcher />}
+              <ChatProvider>
-              {!positionStandaloneMode && <DesensitizeWordsLoader />}
+                {!positionStandaloneMode && <DesensitizeWordsLoader />}
-              <FontScaleApplier />
+                <FontScaleApplier />
-              {children}
+                {children}
-            </ChatProvider>
+              </ChatProvider>
-          </ThemeProvider>
+            </ThemeProvider>
-        </I18nProvider>
+          </I18nProvider>
+        </AuthSyncWatcher>
       </QueryClientProvider>
     </NextThemesProvider>
   );
@@ -188,6 +195,10 @@ export function App() {
             }
           />
           <Route path="/embed/roundtable" element={<EmbedRoundtablePage />} />
+          <Route
+            path="/embed/knowledge/:noteId"
+            element={<WeKnoraWikiPageView publicEmbed />}
+          />
           <Route
             path="/roundtable-dashboard"
             element={<DashboardStandalonePage />}

frontend-web/src/components/page-sidebar.tsx

@@ -10,6 +10,7 @@ import {
   FolderOpen,
   Gauge,
   ListTree,
+  MessageSquareText,
   MousePointerClick,
   BriefcaseBusiness,
   Settings,
@@ -237,6 +238,14 @@ function SecondaryNavSidebar({ headerHidden }: { headerHidden: boolean }) {
                       按钮管理
                     </DropdownMenuItem>
                   )}
+                  {isAdmin && (
+                    <DropdownMenuItem
+                      onClick={() => navigate("/page/strategy/admin/fixed-questions")}
+                    >
+                      <MessageSquareText className="size-4" />
+                      问题配置
+                    </DropdownMenuItem>
+                  )}
                   {isAdmin && (
                     <DropdownMenuItem
                       onClick={() => navigate("/page/strategy/admin/position-roles")}
@@ -558,6 +567,12 @@ function LegacyAccordionSidebar({
                   按钮管理
                 </DropdownMenuItem>
               )}
+              {isAdmin && (
+                <DropdownMenuItem onClick={() => navigate("/page/strategy/admin/fixed-questions")}>
+                  <MessageSquareText className="size-4" />
+                  问题配置
+                </DropdownMenuItem>
+              )}
               {isAdmin && (
                 <DropdownMenuItem onClick={() => navigate("/page/strategy/admin/position-roles")}>
                   <BriefcaseBusiness className="size-4" />

frontend-web/src/components/workspace/artifacts/artifact-directory.tsx

@@ -0,0 +1,226 @@
+import {
+  ChevronDownIcon,
+  ChevronRightIcon,
+  FolderIcon,
+  FolderOpenIcon,
+  RefreshCwIcon,
+} from "lucide-react";
+import { useMemo, useState } from "react";
+
+import { Button } from "@/components/ui/button";
+import { artifactPathname, artifactRelativePath } from "@/core/artifacts/listing";
+import { getFileIcon, getFileName } from "@/core/utils/files";
+import { cn } from "@/lib/utils";
+
+type DirectoryNode = {
+  name: string;
+  path: string;
+  directories: DirectoryNode[];
+  files: Array<{ artifact: string; name: string; relativePath: string }>;
+};
+
+function buildDirectoryTree(artifacts: string[]): DirectoryNode {
+  const root: DirectoryNode = {
+    name: "生成文件",
+    path: "",
+    directories: [],
+    files: [],
+  };
+
+  for (const artifact of artifacts) {
+    const relativePath = artifactRelativePath(artifact);
+    const parts = relativePath.split("/").filter(Boolean);
+    if (parts.length === 0) continue;
+
+    let current = root;
+    for (const directoryName of parts.slice(0, -1)) {
+      let child = current.directories.find((node) => node.name === directoryName);
+      if (!child) {
+        child = {
+          name: directoryName,
+          path: current.path ? `${current.path}/${directoryName}` : directoryName,
+          directories: [],
+          files: [],
+        };
+        current.directories.push(child);
+      }
+      current = child;
+    }
+
+    current.files.push({
+      artifact,
+      name: parts.at(-1) ?? getFileName(artifact),
+      relativePath,
+    });
+  }
+
+  const sort = (node: DirectoryNode) => {
+    node.directories.sort((left, right) =>
+      left.name.localeCompare(right.name, "zh-CN"),
+    );
+    node.files.sort((left, right) =>
+      left.name.localeCompare(right.name, "zh-CN"),
+    );
+    node.directories.forEach(sort);
+  };
+  sort(root);
+  return root;
+}
+
+function DirectoryBranch({
+  node,
+  depth,
+  collapsedDirectories,
+  onToggleDirectory,
+  selectedArtifact,
+  onSelect,
+}: {
+  node: DirectoryNode;
+  depth: number;
+  collapsedDirectories: Set<string>;
+  onToggleDirectory: (path: string) => void;
+  selectedArtifact: string | null;
+  onSelect: (artifact: string) => void;
+}) {
+  return (
+    <>
+      {node.directories.map((directory) => {
+        const collapsed = collapsedDirectories.has(directory.path);
+        return (
+          <div key={directory.path}>
+            <button
+              type="button"
+              className="text-muted-foreground hover:bg-muted/70 hover:text-foreground flex h-8 w-full items-center gap-1.5 rounded-md pr-2 text-left text-xs"
+              style={{ paddingLeft: `${8 + depth * 14}px` }}
+              onClick={() => onToggleDirectory(directory.path)}
+              title={directory.path}
+            >
+              {collapsed ? (
+                <ChevronRightIcon className="size-3.5 shrink-0" />
+              ) : (
+                <ChevronDownIcon className="size-3.5 shrink-0" />
+              )}
+              {collapsed ? (
+                <FolderIcon className="size-4 shrink-0 text-amber-500" />
+              ) : (
+                <FolderOpenIcon className="size-4 shrink-0 text-amber-500" />
+              )}
+              <span className="truncate">{directory.name}</span>
+            </button>
+            {!collapsed && (
+              <DirectoryBranch
+                node={directory}
+                depth={depth + 1}
+                collapsedDirectories={collapsedDirectories}
+                onToggleDirectory={onToggleDirectory}
+                selectedArtifact={selectedArtifact}
+                onSelect={onSelect}
+              />
+            )}
+          </div>
+        );
+      })}
+      {node.files.map((file) => {
+        const selected =
+          !!selectedArtifact &&
+          artifactPathname(selectedArtifact) === artifactPathname(file.artifact);
+        return (
+          <button
+            key={file.relativePath}
+            type="button"
+            className={cn(
+              "hover:bg-muted/70 flex min-h-8 w-full items-center gap-2 rounded-md py-1 pr-2 text-left text-xs",
+              selected
+                ? "bg-primary/10 text-primary font-medium"
+                : "text-foreground/85",
+            )}
+            style={{ paddingLeft: `${27 + depth * 14}px` }}
+            onClick={() => onSelect(file.artifact)}
+            title={file.relativePath}
+            aria-current={selected ? "page" : undefined}
+          >
+            <span className="shrink-0">{getFileIcon(file.artifact, "size-4")}</span>
+            <span className="truncate">{file.name}</span>
+          </button>
+        );
+      })}
+    </>
+  );
+}
+
+export function ArtifactDirectory({
+  className,
+  artifacts,
+  selectedArtifact,
+  onSelect,
+  onRefresh,
+  refreshing = false,
+}: {
+  className?: string;
+  artifacts: string[];
+  selectedArtifact: string | null;
+  onSelect: (artifact: string) => void;
+  onRefresh?: () => void;
+  refreshing?: boolean;
+}) {
+  const tree = useMemo(() => buildDirectoryTree(artifacts), [artifacts]);
+  const [collapsedDirectories, setCollapsedDirectories] = useState<Set<string>>(
+    () => new Set(),
+  );
+
+  const toggleDirectory = (path: string) => {
+    setCollapsedDirectories((current) => {
+      const next = new Set(current);
+      if (next.has(path)) next.delete(path);
+      else next.add(path);
+      return next;
+    });
+  };
+
+  return (
+    <aside
+      className={cn(
+        "bg-muted/20 flex min-h-0 w-48 shrink-0 flex-col border-r xl:w-56",
+        className,
+      )}
+      aria-label="生成文件目录"
+    >
+      <div className="flex h-12 shrink-0 items-center justify-between gap-2 border-b px-3">
+        <div className="min-w-0">
+          <div className="truncate text-sm font-semibold">生成文件</div>
+          <div className="text-muted-foreground text-[11px]">{artifacts.length} 个文件</div>
+        </div>
+        {onRefresh && (
+          <Button
+            type="button"
+            size="icon-sm"
+            variant="ghost"
+            className="size-7 shrink-0"
+            onClick={onRefresh}
+            disabled={refreshing}
+            title="刷新文件目录"
+            aria-label="刷新文件目录"
+          >
+            <RefreshCwIcon className={cn("size-3.5", refreshing && "animate-spin")} />
+          </Button>
+        )}
+      </div>
+      <div className="min-h-0 flex-1 overflow-y-auto p-2">
+        {artifacts.length > 0 ? (
+          <DirectoryBranch
+            node={tree}
+            depth={0}
+            collapsedDirectories={collapsedDirectories}
+            onToggleDirectory={toggleDirectory}
+            selectedArtifact={selectedArtifact}
+            onSelect={onSelect}
+          />
+        ) : (
+          <div className="text-muted-foreground px-2 py-8 text-center text-xs leading-5">
+            生成的文件会显示在这里
+          </div>
+        )}
+      </div>
+    </aside>
+  );
+}

frontend-web/src/components/workspace/artifacts/index.ts

@@ -1,4 +1,5 @@
-export * from "./artifact-file-detail";
+export * from "./artifact-file-detail";
-export * from "./artifact-file-list";
+export * from "./artifact-directory";
+export * from "./artifact-file-list";
 export * from "./artifact-trigger";
 export * from "./context";

frontend-web/src/components/workspace/chats/chat-box.tsx

@@ -1,4 +1,5 @@
 import type { Message } from "@langchain/langgraph-sdk";
+import { useQuery } from "@tanstack/react-query";
 import { FilesIcon, XIcon } from "lucide-react";
 import { usePathname } from "next/navigation";
 import { useEffect, useMemo, useRef, useState } from "react";
@@ -13,6 +14,10 @@ import {
 } from "@/components/ui/resizable";
 import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs";
 import { apiFetch } from "@/core/api";
+import {
+  listThreadArtifacts,
+  mergeArtifactPaths,
+} from "@/core/artifacts/listing";
 import { getBackendBaseURL } from "@/core/config";
 import { isThreadRagModeLocked, useLocalSettings } from "@/core/settings";
 import { isSingleRoundRagMessage } from "@/core/threads/use-single-round-rag";
@@ -32,6 +37,7 @@ import { cn } from "@/lib/utils";
 
 import {
   ArtifactFileDetail,
+  ArtifactDirectory,
   ArtifactFileList,
   useArtifacts,
 } from "../artifacts";
@@ -40,6 +46,7 @@ import { SkillDisplaySources } from "../skill-display-sources";
 
 const CLOSE_MODE = { chat: 100, artifacts: 0 };
 const OPEN_MODE = { chat: 60, artifacts: 40 };
+const DIRECTORY_OPEN_MODE = { chat: 48, artifacts: 52 };
 const SHOW_REFERENCE_EVENT = "workspace:show-reference";
 
 type BackendReferenceSource = Parameters<typeof SkillDisplaySources>[0]["sources"][number];
@@ -78,7 +85,7 @@ const ChatBox: React.FC<{
   threadId,
   disableArtifacts = false,
 }) => {
-  const { thread } = useThread();
+  const { isMock, thread } = useThread();
   const pathname = usePathname();
   const threadIdRef = useRef(threadId);
   const artifactsCountRef = useRef(0);
@@ -92,6 +99,8 @@ const ChatBox: React.FC<{
   const [pinnedReferenceId, setPinnedReferenceId] = useState<string | null>(null);
   const [backendReferenceBatches, setBackendReferenceBatches] = useState<BackendReferenceBatch[]>([]);
   const [settings] = useLocalSettings();
+  const artifactDirectoryModeEnabled =
+    settings.display.artifactDirectoryModeEnabled ?? false;
   const ragModeEnabled =
     settings.display.ragModeEnabled || isThreadRagModeLocked(threadId);
   // Frontend RAG modes write their own hidden source tool messages. They use
@@ -110,6 +119,52 @@ const ChatBox: React.FC<{
     referencesEnabled && !hasFrontendRag;
   const { skills } = useSkills();
 
+  const canScanArtifactDirectory =
+    artifactDirectoryModeEnabled &&
+    !disableArtifacts &&
+    !isMock &&
+    !!threadId &&
+    threadId !== "new";
+  const artifactListingQuery = useQuery({
+    queryKey: ["artifact-directory", threadId],
+    queryFn: ({ signal }) => listThreadArtifacts(threadId, signal),
+    enabled: canScanArtifactDirectory,
+    refetchInterval: thread.isLoading ? 1_500 : false,
+    retry: false,
+  });
+  const checkpointArtifacts = useMemo(
+    () => (disableArtifacts ? [] : (thread.values.artifacts ?? [])),
+    [disableArtifacts, thread.values.artifacts],
+  );
+  const checkpointArtifactSignature = checkpointArtifacts.join("\n");
+  const availableArtifacts = useMemo(
+    () =>
+      artifactDirectoryModeEnabled
+        ? mergeArtifactPaths(
+            checkpointArtifacts,
+            (artifactListingQuery.data?.files ?? []).map((file) => file.path),
+          )
+        : checkpointArtifacts,
+    [
+      artifactDirectoryModeEnabled,
+      artifactListingQuery.data?.files,
+      checkpointArtifacts,
+    ],
+  );
+
+  useEffect(() => {
+    if (!canScanArtifactDirectory || thread.isLoading) return;
+    // Run once after streaming settles as well as when checkpoint artifacts
+    // change, so files written without present_files are not missed by the
+    // last polling tick.
+    void artifactListingQuery.refetch();
+  }, [
+    artifactListingQuery.refetch,
+    canScanArtifactDirectory,
+    checkpointArtifactSignature,
+    thread.isLoading,
+  ]);
+
   const {
     artifacts,
     open: artifactsOpen,
@@ -302,7 +357,8 @@ const ChatBox: React.FC<{
     };
   }, []);
   useEffect(() => {
-    if (threadIdRef.current !== threadId) {
+    const threadChanged = threadIdRef.current !== threadId;
+    if (threadChanged) {
       threadIdRef.current = threadId;
       artifactsCountRef.current = 0;
       deselect();
@@ -316,15 +372,21 @@ const ChatBox: React.FC<{
     }
 
     // Update artifacts from the current thread
-    const nextArtifacts = disableArtifacts ? [] : (thread.values.artifacts ?? []);
+    const nextArtifacts = availableArtifacts;
     const hadArtifacts = artifactsCountRef.current > 0;
     const hasNewArtifact = nextArtifacts.length > artifactsCountRef.current;
     artifactsCountRef.current = nextArtifacts.length;
-    setArtifacts(nextArtifacts);
+    const artifactsChanged =
+      artifacts.length !== nextArtifacts.length ||
+      artifacts.some((artifact, index) => artifact !== nextArtifacts[index]);
+    if (artifactsChanged) {
+      setArtifacts(nextArtifacts);
+    }
     if (
       !disableArtifacts &&
-      (hasNewArtifact || (!hadArtifacts && nextArtifacts.length > 0)) &&
+      nextArtifacts.length > 0 &&
-      !selectedArtifact
+      ((artifactDirectoryModeEnabled && threadChanged) ||
+        ((hasNewArtifact || !hadArtifacts) && !selectedArtifact))
     ) {
       selectArtifact(nextArtifacts[nextArtifacts.length - 1]!);
       setArtifactsOpen(true);
@@ -351,15 +413,41 @@ const ChatBox: React.FC<{
     }
   }, [
     threadId,
+    artifactDirectoryModeEnabled,
     autoSelectFirstArtifact,
     deselect,
     selectArtifact,
     selectedArtifact,
+    artifacts,
     setArtifacts,
-    thread.values.artifacts,
+    availableArtifacts,
     disableArtifacts,
   ]);
 
+  const directoryModeWasEnabledRef = useRef(artifactDirectoryModeEnabled);
+  useEffect(() => {
+    const wasEnabled = directoryModeWasEnabledRef.current;
+    directoryModeWasEnabledRef.current = artifactDirectoryModeEnabled;
+    if (
+      wasEnabled ||
+      !artifactDirectoryModeEnabled ||
+      availableArtifacts.length === 0
+    ) {
+      return;
+    }
+    if (!selectedArtifact) {
+      selectArtifact(availableArtifacts[availableArtifacts.length - 1]!);
+    }
+    setArtifactsOpen(true);
+    setSideTab("document");
+  }, [
+    artifactDirectoryModeEnabled,
+    availableArtifacts,
+    selectArtifact,
+    selectedArtifact,
+    setArtifactsOpen,
+  ]);
+
   const artifactPanelOpen = useMemo(() => {
     if (disableArtifacts) {
       return false;
@@ -370,7 +458,10 @@ const ChatBox: React.FC<{
     return artifactsOpen;
   }, [artifactsOpen, artifacts, disableArtifacts]);
   const sidePanelOpen = artifactPanelOpen || (hasCitationReferences && referencesOpen);
-  const showTabs = !!selectedArtifact && hasCitationReferences;
+  const showTabs =
+    hasCitationReferences &&
+    (!!selectedArtifact ||
+      (artifactDirectoryModeEnabled && artifacts.length > 0));
 
   useEffect(() => {
     if (selectedArtifact) {
@@ -390,12 +481,103 @@ const ChatBox: React.FC<{
   useEffect(() => {
     if (layoutRef.current) {
       if (sidePanelOpen) {
-        layoutRef.current.setLayout(OPEN_MODE);
+        layoutRef.current.setLayout(
+          artifactDirectoryModeEnabled && artifactPanelOpen
+            ? DIRECTORY_OPEN_MODE
+            : OPEN_MODE,
+        );
       } else {
         layoutRef.current.setLayout(CLOSE_MODE);
       }
     }
-  }, [sidePanelOpen]);
+  }, [artifactDirectoryModeEnabled, artifactPanelOpen, sidePanelOpen]);
+
+  const artifactDocumentPanel = artifactDirectoryModeEnabled ? (
+    <div className="flex size-full min-w-0 overflow-hidden rounded-lg border">
+      <ArtifactDirectory
+        artifacts={artifacts}
+        selectedArtifact={selectedArtifact}
+        onSelect={(artifact) => {
+          selectArtifact(artifact);
+          setArtifactsOpen(true);
+        }}
+        onRefresh={
+          canScanArtifactDirectory
+            ? () => void artifactListingQuery.refetch()
+            : undefined
+        }
+        refreshing={artifactListingQuery.isFetching}
+      />
+      <div className="relative min-w-0 flex-1 overflow-hidden">
+        {selectedArtifact ? (
+          <ArtifactFileDetail
+            key={selectedArtifactKey ?? selectedArtifact}
+            className="size-full"
+            filepath={selectedArtifact}
+            threadId={threadId}
+            allowVirtualMarkdownEdit
+          />
+        ) : (
+          <>
+            <div className="absolute top-1 right-1 z-30">
+              <Button
+                size="icon-sm"
+                variant="ghost"
+                onClick={() => setArtifactsOpen(false)}
+              >
+                <XIcon />
+              </Button>
+            </div>
+            <ConversationEmptyState
+              icon={<FilesIcon />}
+              title="请选择文件"
+              description="从左侧目录中选择一个文件进行查看"
+            />
+          </>
+        )}
+      </div>
+    </div>
+  ) : selectedArtifact ? (
+    <ArtifactFileDetail
+      key={selectedArtifactKey ?? selectedArtifact}
+      className="size-full"
+      filepath={selectedArtifact}
+      threadId={threadId}
+      allowVirtualMarkdownEdit
+    />
+  ) : (
+    <div className="relative flex size-full justify-center">
+      <div className="absolute top-1 right-1 z-30">
+        <Button
+          size="icon-sm"
+          variant="ghost"
+          onClick={() => setArtifactsOpen(false)}
+        >
+          <XIcon />
+        </Button>
+      </div>
+      {artifacts.length === 0 ? (
+        <ConversationEmptyState
+          icon={<FilesIcon />}
+          title="No artifact selected"
+          description="Select an artifact to view its details"
+        />
+      ) : (
+        <div className="flex size-full max-w-(--container-width-sm) flex-col justify-center p-4 pt-8">
+          <header className="shrink-0">
+            <h2 className="text-lg font-medium">Artifacts</h2>
+          </header>
+          <main className="min-h-0 grow">
+            <ArtifactFileList
+              className="max-w-(--container-width-sm) p-4 pt-12"
+              files={artifacts}
+              threadId={threadId}
+            />
+          </main>
+        </div>
+      )}
+    </div>
+  );
 
   if (disableArtifacts) {
     return (
@@ -455,13 +637,7 @@ const ChatBox: React.FC<{
                 </Button>
               </div>
               <TabsContent value="document" className="min-h-0 flex-1 overflow-hidden p-0">
-                <ArtifactFileDetail
+                {artifactDocumentPanel}
-                  key={selectedArtifactKey ?? selectedArtifact}
-                  className="size-full"
-                  filepath={selectedArtifact}
-                  threadId={threadId}
-                  allowVirtualMarkdownEdit
-                />
               </TabsContent>
               <TabsContent value="references" className="min-h-0 flex-1 overflow-y-auto p-0">
                 <ReferencePanel
@@ -470,14 +646,8 @@ const ChatBox: React.FC<{
                 />
               </TabsContent>
             </Tabs>
-          ) : selectedArtifact ? (
+          ) : artifactPanelOpen ? (
-            <ArtifactFileDetail
+            artifactDocumentPanel
-              key={selectedArtifactKey ?? selectedArtifact}
-              className="size-full"
-              filepath={selectedArtifact}
-              threadId={threadId}
-              allowVirtualMarkdownEdit
-            />
           ) : hasCitationReferences ? (
             <div className="relative size-full overflow-hidden">
               <div className="absolute top-1 right-1 z-30">
@@ -497,41 +667,7 @@ const ChatBox: React.FC<{
                 sources={referenceSources}
               />
             </div>
-          ) : (
+          ) : null}
-            <div className="relative flex size-full justify-center">
-              <div className="absolute top-1 right-1 z-30">
-                <Button
-                  size="icon-sm"
-                  variant="ghost"
-                  onClick={() => {
-                    setArtifactsOpen(false);
-                  }}
-                >
-                  <XIcon />
-                </Button>
-              </div>
-              {thread.values.artifacts?.length === 0 ? (
-                <ConversationEmptyState
-                  icon={<FilesIcon />}
-                  title="No artifact selected"
-                  description="Select an artifact to view its details"
-                />
-              ) : (
-                <div className="flex size-full max-w-(--container-width-sm) flex-col justify-center p-4 pt-8">
-                  <header className="shrink-0">
-                    <h2 className="text-lg font-medium">Artifacts</h2>
-                  </header>
-                  <main className="min-h-0 grow">
-                    <ArtifactFileList
-                      className="max-w-(--container-width-sm) p-4 pt-12"
-                      files={thread.values.artifacts ?? []}
-                      threadId={threadId}
-                    />
-                  </main>
-                </div>
-              )}
-            </div>
-          )}
         </div>
       </ResizablePanel>
     </ResizablePanelGroup>

frontend-web/src/components/workspace/input-box.tsx

@@ -2,12 +2,13 @@
 
 import type { ChatStatus } from "ai";
 import {
-  BarChart3Icon,
+  BarChart3Icon,
-  BrainCircuitIcon,
+  BrainCircuitIcon,
-  BookMarkedIcon,
+  BookMarkedIcon,
-  CheckIcon,
+  CheckIcon,
-  ClipboardCheckIcon,
+  ClipboardCheckIcon,
-  FileTextIcon,
+  FileTextIcon,
+  FolderTreeIcon,
   GraduationCapIcon,
   LightbulbIcon,
   MessageCircleQuestionIcon,
@@ -446,12 +447,20 @@ export function InputBox({
     [onContextChange, context],
   );
 
-  const handleWritingModeToggle = useCallback(() => {
+  const handleWritingModeToggle = useCallback(() => {
     onContextChange?.({
       ...context,
       writing_mode: !context.writing_mode,
     });
-  }, [context, onContextChange]);
+  }, [context, onContextChange]);
+
+  const artifactDirectoryModeEnabled =
+    localSettings.display.artifactDirectoryModeEnabled ?? false;
+  const handleArtifactDirectoryModeToggle = useCallback(() => {
+    setLocalSettings("display", {
+      artifactDirectoryModeEnabled: !artifactDirectoryModeEnabled,
+    });
+  }, [artifactDirectoryModeEnabled, setLocalSettings]);
 
   const memoryInjectionEnabled = context.memory_injection_enabled ?? true;
   const handleMemoryInjectionToggle = useCallback(() => {
@@ -854,7 +863,7 @@ export function InputBox({
                 )}
               />
             )}
-            {!frontendRagActive && <Tooltip
+            {!frontendRagActive && <Tooltip
               content={
                 context.writing_mode
                   ? "写作模式已开启：最终输出会强制保存为 Markdown 文件"
@@ -878,9 +887,38 @@ export function InputBox({
                 )}
                 <FileTextIcon className="size-3" />
                 <span className="text-xs font-normal">写作</span>
-              </PromptInputButton>
+              </PromptInputButton>
-            </Tooltip>}
+            </Tooltip>}
-            {!frontendRagActive && <Tooltip
+            {!frontendRagActive && <Tooltip
+              content={
+                artifactDirectoryModeEnabled
+                  ? "文件模式已开启：右侧会显示当前对话生成的全部文件目录"
+                  : "开启文件模式：在右侧目录中浏览当前对话生成的全部文件"
+              }
+            >
+              <PromptInputButton
+                type="button"
+                aria-pressed={artifactDirectoryModeEnabled}
+                disabled={disabled}
+                className={cn(
+                  "gap-1.5! rounded-full px-3! shadow-none",
+                  compact && "rounded-lg px-2.5! py-1! text-[11px] font-medium",
+                  artifactDirectoryModeEnabled
+                    ? "border border-sky-300 bg-sky-50 text-sky-700 hover:bg-sky-100 dark:border-sky-600 dark:bg-sky-950/45 dark:text-sky-200"
+                    : compact
+                      ? "border border-transparent bg-muted/40 text-muted-foreground hover:bg-muted hover:text-foreground"
+                      : "border-0 bg-transparent text-muted-foreground hover:bg-muted/70 hover:text-foreground dark:text-slate-400 dark:hover:bg-slate-700/70 dark:hover:text-slate-100",
+                )}
+                onClick={handleArtifactDirectoryModeToggle}
+              >
+                {artifactDirectoryModeEnabled && (
+                  <CheckIcon className="size-3 text-sky-700 dark:text-sky-200" />
+                )}
+                <FolderTreeIcon className="size-3" />
+                <span className="text-xs font-normal">文件</span>
+              </PromptInputButton>
+            </Tooltip>}
+            {!frontendRagActive && <Tooltip
               content={
                 memoryInjectionEnabled
                   ? "记忆注入已开启：对话前会注入历史记忆"

frontend-web/src/components/workspace/llmwiki-knowledge-selector.tsx

@@ -76,6 +76,7 @@ function SelectionContent({
   error,
   source,
   variant,
+  readOnly,
 }: {
   rows: LlmWikiKnowledgeBase[];
   value: string[];
@@ -86,6 +87,7 @@ function SelectionContent({
   error: unknown;
   source: SelectorSource;
   variant: SelectorVariant;
+  readOnly: boolean;
 }) {
   const selected = useMemo(() => new Set(value), [value]);
   const filtered = useMemo(() => {
@@ -97,6 +99,7 @@ function SelectionContent({
   }, [rows, search]);
   const groups = useMemo(() => groupRows(filtered), [filtered]);
   const toggle = (id: string) => {
+    if (readOnly) return;
     onChange(selected.has(id) ? value.filter((item) => item !== id) : [...value, id]);
   };
 
@@ -168,6 +171,7 @@ function SelectionContent({
                   <DropdownMenuCheckboxItem
                     key={item.id}
                     checked={selected.has(item.id)}
+                    disabled={readOnly}
                     onCheckedChange={() => toggle(item.id)}
                     onSelect={(event) => event.preventDefault()}
                     className={cn(
@@ -183,6 +187,7 @@ function SelectionContent({
                     type="button"
                     role="checkbox"
                     aria-checked={selected.has(item.id)}
+                    disabled={readOnly}
                     onClick={() => toggle(item.id)}
                     className={cn(
                       "my-0.5 flex min-h-11 w-full items-center gap-2 rounded-md px-2 py-1.5 text-left outline-none transition-colors hover:bg-muted/60 focus-visible:ring-2 focus-visible:ring-primary",
@@ -205,15 +210,21 @@ function SelectionContent({
       </div>
 
       <div className="flex items-center justify-between gap-2 border-t bg-muted/20 px-2.5 py-2">
-        <span className="text-[11px] text-muted-foreground">已选择 {value.length} 个</span>
+        <span className="text-[11px] text-muted-foreground">
-        <div className="flex items-center gap-1">
+          {readOnly ? `本对话已选 ${value.length} 个` : `已选择 ${value.length} 个`}
-          <Button type="button" variant="ghost" size="sm" className="h-7 px-2 text-xs" onClick={() => onChange(filtered.map((item) => item.id))}>
+        </span>
-            全选
+        {readOnly ? (
-          </Button>
+          <span className="text-[11px] text-muted-foreground">对话开始后不可更改</span>
-          <Button type="button" variant="ghost" size="sm" className="h-7 px-2 text-xs" onClick={() => onChange([])}>
+        ) : (
-            清空
+          <div className="flex items-center gap-1">
-          </Button>
+            <Button type="button" variant="ghost" size="sm" className="h-7 px-2 text-xs" onClick={() => onChange(filtered.map((item) => item.id))}>
-        </div>
+              全选
+            </Button>
+            <Button type="button" variant="ghost" size="sm" className="h-7 px-2 text-xs" onClick={() => onChange([])}>
+              清空
+            </Button>
+          </div>
+        )}
       </div>
     </>
   );
@@ -226,6 +237,7 @@ export function LlmWikiKnowledgeSelector({
   agentId,
   autoSelectAll = false,
   disabled = false,
+  readOnly = false,
   className,
   label = "知识空间",
   variant = "popover",
@@ -236,6 +248,8 @@ export function LlmWikiKnowledgeSelector({
   agentId?: string | null;
   autoSelectAll?: boolean;
   disabled?: boolean;
+  /** Keep the selected knowledge spaces visible without allowing the thread scope to change. */
+  readOnly?: boolean;
   className?: string;
   label?: string;
   variant?: SelectorVariant;
@@ -293,6 +307,7 @@ export function LlmWikiKnowledgeSelector({
       error={error}
       source={source}
       variant={variant}
+      readOnly={readOnly}
     />
   );
 
@@ -315,9 +330,14 @@ export function LlmWikiKnowledgeSelector({
     );
   }
 
-  const selectedName = value.length === 1
+  const selectedNames = value
-    ? rows.find((item) => item.id === value[0])?.name
+    .map((id) => rows.find((item) => item.id === id)?.name)
-    : null;
+    .filter((name): name is string => !!name);
+  const selectedLabel = selectedNames.length > 0
+    ? selectedNames.join("、")
+    : value.length > 0
+      ? `已选 ${value.length} 个知识空间`
+      : label;
 
   return (
     <DropdownMenu open={open} onOpenChange={setOpen}>
@@ -332,9 +352,10 @@ export function LlmWikiKnowledgeSelector({
             className,
           )}
           disabled={disabled || loading}
+          title={value.length > 0 ? selectedLabel : undefined}
         >
           {loading ? <Loader2 className="size-3.5 animate-spin" /> : <Database className="size-3.5" />}
-          <span className="truncate text-xs font-normal">{selectedName || label}</span>
+          <span className="truncate text-xs font-normal">{selectedLabel}</span>
           {value.length > 0 && (
             <span className="flex size-4 items-center justify-center rounded-full bg-primary text-[9px] font-semibold text-primary-foreground">
               {value.length}

frontend-web/src/components/workspace/messages/message-group.tsx

@@ -341,9 +341,9 @@ function ToolCall({
   ragModeEnabled?: boolean;
 }) {
   const { t } = useI18n();
-  const displayMatch =
+  const displayMatch =
-    result !== undefined && isDisplaySamplePayload(result)
+    result !== undefined && isDisplaySamplePayload(result)
-      ? null
+      ? null
       : (findDisplayConfigForTool(name, skillDisplayMap, args) ??
         null);
   const displayItems =
@@ -352,18 +352,24 @@ function ToolCall({
           ...item,
           index: index + 1,
           skillName: displayMatch.skillName,
-          mode: item.displayMode ?? displayMatch.display.mode,
+          mode: item.displayMode ?? displayMatch.display.mode,
-        }))
+        }))
-      : [];
+      : [];
-  if (displayItems.length > 0) {
+  const wikiQuery = name === "llmwiki_search" ? resolveSearchQuery(args, result) : "";
-    return (
+  const wikiSearchLabel = name === "llmwiki_search"
-      <ChainOfThoughtStep
+    ? wikiQuery
-        key={id}
+      ? `Wiki 文档检索 "${wikiQuery}"`
-        label={
+      : "Wiki 文档检索"
-          displayMatch?.display.mode === "citation" || !displayMatch
+    : null;
-            ? "检索参考来源"
+  if (displayItems.length > 0) {
-            : `获取 ${displayItems.length} 条结果`
+    return (
-        }
+      <ChainOfThoughtStep
+        key={id}
+        label={
+          wikiSearchLabel || (displayMatch?.display.mode === "citation" || !displayMatch
+            ? "检索参考来源"
+            : `获取 ${displayItems.length} 条结果`)
+        }
         icon={SearchIcon}
       >
         <DisplayResultsList results={displayItems} />
@@ -387,7 +393,7 @@ function ToolCall({
       mode: "citation" as const,
     }));
     return (
-      <ChainOfThoughtStep key={id} label="检索参考来源" icon={SearchIcon}>
+      <ChainOfThoughtStep key={id} label={wikiSearchLabel || "检索参考来源"} icon={SearchIcon}>
         <DisplayResultsList results={defaultItems} />
       </ChainOfThoughtStep>
     );

frontend-web/src/components/workspace/skill-display-sources.tsx

@@ -1,4 +1,4 @@
-import { ExternalLinkIcon, FileTextIcon } from "lucide-react";
+import { BookOpenTextIcon, ChevronRightIcon, ExternalLinkIcon, FileTextIcon } from "lucide-react";
 
 import { Button } from "@/components/ui/button";
 import {
@@ -15,9 +15,11 @@ import {
 } from "@/core/llmwiki/source-links";
 import { useLocalSettings } from "@/core/settings";
 import { useCitationDisplaySettings } from "@/core/system-settings/hooks";
+import { reasoningPlugins } from "@/core/streamdown";
 import { cn } from "@/lib/utils";
 import { useState } from "react";
 import { WeKnoraSourceDrawer } from "@/strategy-components/components/resource-management/llmwiki/WeKnoraSourceDrawer";
+import { MarkdownContent } from "@/components/workspace/messages/markdown-content";
 
 /** Whether a source URL is an internal WeKnora preview pointer. */
 export function isWeKnoraSourcePreviewUrl(url?: string | null): boolean {
@@ -71,8 +73,20 @@ export function SourceCard({
   const cleanupWords =
     citationDisplay?.cleanup_words ?? settings.display.citationCleanupWords ?? [];
   const content = cleanReferenceText(source.content || source.snippet, cleanupWords);
-  const snippet = compactReferenceText(content).slice(0, 280);
+  const isWikiSource = Boolean(previewTarget?.wikiSlug) || source.type === "llmwiki_wiki";
-  const paragraphs = segmentReferenceText(content);
+  const matchedHeading = isWikiSource
+    ? String(
+        (source.raw?.matched_heading as string | undefined) ||
+          (source.raw?.matched_sections as Array<{ heading?: string }> | undefined)?.find(
+            (section) => section.heading,
+          )?.heading ||
+          "",
+      ).trim()
+    : "";
+  const summary = isWikiSource && typeof source.raw?.summary === "string"
+    ? source.raw.summary
+    : "";
+  const snippet = plainTextReferencePreview(summary || content).slice(0, 280);
   const score =
     typeof source.score === "number"
       ? source.score <= 1
@@ -81,13 +95,22 @@ export function SourceCard({
       : null;
   const meta = [
     source.source,
+    isWikiSource ? "检索对象：Wiki 文档" : null,
+    matchedHeading ? `命中章节：${matchedHeading}` : null,
     source.author ? `作者 ${source.author}` : null,
-    source.type && source.type !== "result" ? source.type : null,
+    !isWikiSource && source.type && source.type !== "result" ? source.type : null,
     source.time,
     score ? `相关度 ${score}` : null,
   ].filter(Boolean);
   const isCitation = source.mode === "citation";
   const showReferenceNumber = isCitation;
+  const openSource = () => {
+    if (previewTarget) {
+      setDetailOpen(true);
+    } else {
+      setRelatedOpen(true);
+    }
+  };
 
   return (
     <>
@@ -102,11 +125,11 @@ export function SourceCard({
             "border-amber-300 bg-amber-50/80 shadow-[0_0_0_2px_rgba(251,191,36,0.14)]",
           "cursor-pointer",
         )}
-        onClick={() => setRelatedOpen(true)}
+        onClick={openSource}
         onKeyDown={(event) => {
           if (event.key === "Enter" || event.key === " ") {
             event.preventDefault();
-            setRelatedOpen(true);
+            openSource();
           }
         }}
       >
@@ -136,11 +159,16 @@ export function SourceCard({
               </p>
             )}
           </div>
-          {source.url && (
+          {(source.url || isWikiSource) && (
             previewTarget ? (
-              <span className="text-primary bg-primary/10 mt-0.5 inline-flex shrink-0 items-center gap-1 rounded-md px-1.5 py-1 text-[11px] font-medium">
+              <span className={cn(
-                <FileTextIcon className="size-3.5" />
+                "mt-0.5 inline-flex shrink-0 items-center gap-1 rounded-md px-1.5 py-1 text-[11px] font-medium",
-                查看原文
+                isWikiSource
+                  ? "bg-emerald-100 text-emerald-700 dark:bg-emerald-950 dark:text-emerald-300"
+                  : "bg-primary/10 text-primary",
+              )}>
+                {isWikiSource ? <BookOpenTextIcon className="size-3.5" /> : <FileTextIcon className="size-3.5" />}
+                {isWikiSource ? "Wiki 文档" : "查看原文"}
               </span>
             ) : (
               <ExternalLinkIcon className="text-muted-foreground/60 group-hover:text-primary mt-1 size-3.5 shrink-0 transition-colors" />
@@ -148,19 +176,9 @@ export function SourceCard({
           )}
         </div>
         {previewTarget && (
-          <div className="mt-3 flex justify-start border-t pt-2">
+          <div className="mt-3 flex items-center justify-between border-t pt-2 text-xs text-muted-foreground">
-            <Button
+            <span>{isWikiSource ? "点击卡片查看完整 Wiki" : "点击卡片查看详情"}</span>
-              size="sm"
+            <ChevronRightIcon className="size-3.5 transition-transform group-hover:translate-x-0.5" />
-              variant="ghost"
-              className="text-muted-foreground hover:text-primary h-7 px-1.5 text-xs"
-              onClick={(event) => {
-                event.stopPropagation();
-                setDetailOpen(true);
-              }}
-            >
-              <ExternalLinkIcon className="mr-1.5 size-3.5" />
-              查看详情
-            </Button>
           </div>
         )}
       </div>
@@ -173,7 +191,7 @@ export function SourceCard({
           onOpenChange={setDetailOpen}
         />
       )}
-      <Dialog open={relatedOpen} onOpenChange={setRelatedOpen}>
+      {!previewTarget && <Dialog open={relatedOpen} onOpenChange={setRelatedOpen}>
         <DialogContent className="max-h-[90vh] w-[calc(100vw-2rem)] max-w-3xl overflow-hidden">
           <DialogHeader>
             <div className="flex items-start justify-between gap-3 pr-8">
@@ -210,13 +228,23 @@ export function SourceCard({
               )}
             </div>
           </DialogHeader>
-          {paragraphs.length > 0 ? (
+          {content ? (
-            <div className="text-foreground max-h-[55vh] space-y-3 overflow-y-auto text-sm leading-relaxed">
+            <div className="max-h-[62vh] overflow-y-auto rounded-xl border bg-slate-50/70 p-4 dark:bg-slate-950/40 sm:p-6">
-              {paragraphs.map((paragraph, index) => (
+              {isWikiSource && (
-                <p key={index} className="whitespace-pre-wrap">
+                <div className="mb-4 flex items-center gap-2 border-b pb-3 text-xs font-medium text-emerald-700 dark:text-emerald-300">
-                  {paragraph}
+                  <BookOpenTextIcon className="size-4" />
-                </p>
+                  本次检索命中的 Wiki 文档内容
-              ))}
+                </div>
+              )}
+              <article className="mx-auto max-w-3xl rounded-lg bg-background px-4 py-5 shadow-sm ring-1 ring-border/70 sm:px-7">
+                <MarkdownContent
+                  className="max-w-none"
+                  content={content}
+                  isLoading={false}
+                  remarkPlugins={reasoningPlugins.remarkPlugins}
+                  rehypePlugins={reasoningPlugins.rehypePlugins}
+                />
+              </article>
             </div>
           ) : null}
           {source.url && !previewTarget && (
@@ -225,7 +253,7 @@ export function SourceCard({
             </div>
           )}
         </DialogContent>
-      </Dialog>
+      </Dialog>}
     </>
   );
 }
@@ -254,44 +282,18 @@ function compactReferenceText(text: string): string {
   return text.replace(/\s+/g, " ").trim();
 }
 
-function segmentReferenceText(text: string): string[] {
+function plainTextReferencePreview(text: string): string {
-  const explicit = text
+  return compactReferenceText(
-    .split(/\n{2,}/)
+    text
-    .map((item) => item.trim())
+      .replace(/^---[\s\S]*?---\s*/m, "")
-    .filter(Boolean);
+      .replace(/```[\s\S]*?```/g, " ")
-  const base = explicit.length > 1 ? explicit : splitLongParagraph(text);
+      .replace(/!\[([^\]]*)\]\([^)]*\)/g, "$1")
-  return base.slice(0, 80);
+      .replace(/\[([^\]]+)\]\([^)]*\)/g, "$1")
-}
+      .replace(/\[\[[^\]\s|]+[|\s]+([^\]]+)\]\]/g, "$1")
-
+      .replace(/\[\[([^\]]+)\]\]/g, "$1")
-function splitLongParagraph(text: string): string[] {
+      .replace(/^#{1,6}\s+/gm, "")
-  const normalized = text
+      .replace(/^\s*[-*+]\s+/gm, "")
-    .split(/\n+/)
+      .replace(/^\s*\d+[.)]\s+/gm, "")
-    .map((item) => item.trim())
+      .replace(/[>*_`~|]/g, " "),
-    .filter(Boolean)
+  );
-    .join("\n");
-  if (normalized.length <= 360) {
-    return normalized ? [normalized] : [];
-  }
-
-  const sentences = normalized
-    .split(/(?<=[。！？!?；;])\s*/)
-    .map((item) => item.trim())
-    .filter(Boolean);
-  if (sentences.length <= 1) {
-    return normalized.match(/[\s\S]{1,360}/g) ?? [];
-  }
-
-  const paragraphs: string[] = [];
-  let current = "";
-  for (const sentence of sentences) {
-    if ((current + sentence).length > 360 && current) {
-      paragraphs.push(current.trim());
-      current = "";
-    }
-    current += sentence;
-  }
-  if (current.trim()) {
-    paragraphs.push(current.trim());
-  }
-  return paragraphs;
 }

frontend-web/src/components/workspace/workspace-nav-menu.tsx

@@ -13,6 +13,7 @@ import {
   HistoryIcon,
   ListTreeIcon,
   MessageCircleQuestionIcon,
+  MessageSquareTextIcon,
   ScrollTextIcon,
   Settings2Icon,
   SettingsIcon,
@@ -288,6 +289,16 @@ export function WorkspaceNavMenu() {
                       推荐问题配置
                     </DropdownMenuItem>
                   )}
+                  {isAdmin && (
+                    <DropdownMenuItem
+                      onClick={() =>
+                        navigate("/page/strategy/admin/fixed-questions")
+                      }
+                    >
+                      <MessageSquareTextIcon />
+                      问题配置
+                    </DropdownMenuItem>
+                  )}
                   {isAdmin && logSystem?.enabled && logSystem.url && (
                     <DropdownMenuItem
                       onClick={() =>

frontend-web/src/core/artifacts/listing.ts

@@ -0,0 +1,113 @@
+import { apiFetch } from "@/core/api";
+import { getBackendBaseURL } from "@/core/config";
+
+export interface ArtifactListingFile {
+  path: string;
+  name: string;
+  sizeBytes: number;
+  mimeType: string | null;
+  modifiedAt: string;
+}
+
+export interface ArtifactListing {
+  threadId: string;
+  files: ArtifactListingFile[];
+}
+
+/**
+ * Scan the thread's outputs directory instead of relying only on artifacts
+ * explicitly surfaced by `present_files`. This is used by file mode so files
+ * written by any tool are still discoverable from the right-hand directory.
+ */
+export async function listThreadArtifacts(
+  threadId: string,
+  signal?: AbortSignal,
+): Promise<ArtifactListing> {
+  const response = await apiFetch(
+    `${getBackendBaseURL()}/api/threads/${encodeURIComponent(threadId)}/artifacts`,
+    { method: "GET", signal },
+  );
+  if (!response.ok) {
+    const detail = await response.text().catch(() => "");
+    throw new Error(
+      `Failed to list artifacts (${response.status})${detail ? `: ${detail}` : ""}`,
+    );
+  }
+
+  const data = (await response.json()) as {
+    thread_id?: string;
+    files?: Array<{
+      path: string;
+      name: string;
+      size_bytes: number;
+      mime_type: string | null;
+      modified_at: string;
+    }>;
+  };
+
+  return {
+    threadId: data.thread_id ?? threadId,
+    files: (data.files ?? []).map((file) => ({
+      path: file.path,
+      name: file.name,
+      sizeBytes: file.size_bytes,
+      mimeType: file.mime_type,
+      modifiedAt: file.modified_at,
+    })),
+  };
+}
+
+/** Return the generated file path represented by a real or streaming artifact. */
+export function artifactPathname(artifact: string): string {
+  const trimmed = artifact.trim();
+  if (!trimmed.startsWith("write-file:")) {
+    return trimmed.replace(/^\/+/, "");
+  }
+  try {
+    return decodeURIComponent(new URL(trimmed).pathname).replace(/^\/+/, "");
+  } catch {
+    return trimmed;
+  }
+}
+
+export function artifactRelativePath(artifact: string): string {
+  const pathname = artifactPathname(artifact);
+  return pathname.replace(/^mnt\/user-data\/outputs\/?/i, "") || pathname;
+}
+
+/**
+ * Keep the checkpoint order, append files found only on disk from old to new,
+ * and replace a completed streaming URL with its durable path.
+ */
+export function mergeArtifactPaths(
+  checkpointArtifacts: string[],
+  discoveredArtifacts: string[],
+): string[] {
+  const merged: string[] = [];
+  const indexByPath = new Map<string, number>();
+
+  for (const artifact of checkpointArtifacts) {
+    const key = artifactPathname(artifact);
+    if (!key || indexByPath.has(key)) continue;
+    indexByPath.set(key, merged.length);
+    merged.push(artifact);
+  }
+
+  // The listing endpoint returns newest first. Append in chronological order
+  // so the last item remains the newest artifact for the existing auto-open.
+  for (const artifact of [...discoveredArtifacts].reverse()) {
+    const key = artifactPathname(artifact);
+    if (!key) continue;
+    const existingIndex = indexByPath.get(key);
+    if (existingIndex !== undefined) {
+      if (merged[existingIndex]?.startsWith("write-file:")) {
+        merged[existingIndex] = artifact;
+      }
+      continue;
+    }
+    indexByPath.set(key, merged.length);
+    merged.push(artifact);
+  }
+
+  return merged;
+}

frontend-web/src/core/auth/index.ts

@@ -49,6 +49,17 @@ function normalizeIdentityPart(value: unknown): string {
   return typeof value === "string" ? value.trim().toLowerCase() : "";
 }
 
+function identityFromLoginName(value: unknown): string | null {
+  const normalized = normalizeIdentityPart(value);
+  if (!normalized) return null;
+  // Explicit email login is domain-specific. Bare username login is the
+  // stable business principal even if the backend's synthetic email domain or
+  // internal UUID changes.
+  return normalized.includes("@")
+    ? `email:${normalized}`
+    : `account:${normalized}`;
+}
+
 function readUserInfoIdentity(): string | null {
   let info: Record<string, unknown> | null = null;
   try {
@@ -81,20 +92,24 @@ function readUserInfoIdentity(): string | null {
 /**
  * A stable cross-tab identity key for "did the account really change?" checks.
  *
- * Some external login paths can re-issue a backend ``user_id`` while resolving
+ * Some external login paths can re-issue a backend ``user_id`` or use a
- * to the same business account. Prefer business-facing identifiers
+ * different synthetic email domain while resolving to the same business
- * (email/username/userInfo) and keep ``user_id`` only as the final fallback.
+ * account. Prefer the raw login username returned by the backend, then the
+ * email local-part, and keep ``user_id`` only as the final fallback.
  */
 export function getAccountIdentityKey(
   auth: LoginByUsernameResponse | null = getStoredAuth(),
 ): string | null {
   if (!auth) return null;
 
-  const email = normalizeIdentityPart(auth.email);
+  const loginIdentity = identityFromLoginName(auth.username);
-  if (email) return `email:${email}`;
+  if (loginIdentity) return loginIdentity;
 
-  const username = normalizeIdentityPart(auth.username);
+  const email = normalizeIdentityPart(auth.email);
-  if (username) return `username:${username}`;
+  if (email) {
+    const localPart = email.split("@", 1)[0];
+    return localPart ? `account:${localPart}` : `email:${email}`;
+  }
 
   const userInfoIdentity = readUserInfoIdentity();
   if (userInfoIdentity) return `userInfo:${userInfoIdentity}`;

frontend-web/src/core/auth/sync.tsx

@@ -1,9 +1,15 @@
 "use client";
 
-import { useEffect, useRef } from "react";
+import { Fragment, useEffect, useRef, useState, type ReactNode } from "react";
+import { useLocation, useNavigate } from "react-router-dom";
+import { useQueryClient } from "@tanstack/react-query";
 import { toast } from "sonner";
 
-import { getAccountIdentityKey } from "@/core/auth";
+import {
+  AUTH_STATE_CHANGED_EVENT,
+  getAccountDisplayName,
+  getAccountIdentityKey,
+} from "@/core/auth";
 import { isEmbedActive, isIsolatedSession } from "@/core/embed/embed-session";
 
 const AUTH_STORAGE_KEY = "deerflow.auth";
@@ -14,14 +20,37 @@ function readIdentityKey(): string | null {
   return getAccountIdentityKey();
 }
 
+function freshRouteForAccount(pathname: string): string {
+  // A thread URL belongs to the old account. Keep its workspace/agent context
+  // but move to a valid new conversation before the user can submit into the
+  // stale thread. Other pages can stay in place and are remounted below.
+  const chatMatch = pathname.match(/^(.*\/chats)\/[^/]+\/?$/);
+  return chatMatch ? `${chatMatch[1]}/new` : pathname;
+}
+
 /**
- * Mount once at the app root. Watches localStorage auth changes from other
+ * Cross-tab auth boundary for normal pages.
- * tabs and lets the user decide when to refresh on account switches.
+ *
+ * Same-account token re-issuance is ignored. A genuine account change clears
+ * account-scoped query state, remounts the page, and moves an open chat to its
+ * fresh-chat route without a full browser reload. Embedded/isolated tabs keep
+ * their sessionStorage identity and never participate in this synchronization.
  */
-export function AuthSyncWatcher() {
+export function AuthSyncWatcher({
+  children,
+  disabled = false,
+}: {
+  children?: ReactNode;
+  disabled?: boolean;
+}) {
   const lastIdentityRef = useRef<string | null>(readIdentityKey());
+  const [revision, setRevision] = useState(0);
+  const queryClient = useQueryClient();
+  const navigate = useNavigate();
+  const location = useLocation();
 
   useEffect(() => {
+    if (disabled) return;
     // 嵌入(iframe)态 / 独立会话态(?isolate=1)：鉴权走按标签页的 sessionStorage，本就不与其它标签页
     // 共享，且不应被其它标签页的 localStorage 账号变更打扰 —— 直接不挂跨标签监听。
     if (isEmbedActive() || isIsolatedSession()) return;
@@ -36,18 +65,27 @@ export function AuthSyncWatcher() {
 
       lastIdentityRef.current = nextIdentity;
 
+      void queryClient.cancelQueries();
+      queryClient.clear();
+      window.dispatchEvent(new Event(AUTH_STATE_CHANGED_EVENT));
+      setRevision((value) => value + 1);
+
       if (nextIdentity === null) {
+        toast.info("账号已在其它页面退出", {
+          id: IDENTITY_TOAST_ID,
+          description: "当前页面已同步退出状态。",
+        });
+        navigate("/login", { replace: true });
         return;
       }
 
-      toast.warning("检测到账号在其它标签页发生变化", {
+      const freshRoute = freshRouteForAccount(location.pathname);
+      if (freshRoute !== location.pathname) {
+        navigate(freshRoute, { replace: true });
+      }
+      toast.info("账号已在页面间自动同步", {
         id: IDENTITY_TOAST_ID,
-        description: "当前标签页仍是原会话。如需与新账号同步,请刷新页面。",
+        description: `当前账号：${getAccountDisplayName()}。无需刷新页面。`,
-        duration: Infinity,
-        action: {
-          label: "刷新同步",
-          onClick: () => window.location.reload(),
-        },
       });
     }
 
@@ -68,14 +106,24 @@ export function AuthSyncWatcher() {
       settleTimer = setTimeout(evaluateSettledIdentity, SETTLE_DELAY_MS);
     }
 
+    function handleSameTabAuthChange() {
+      // `storage` never fires in the tab that called setStoredAuth/clearStoredAuth.
+      // Keep the comparison baseline current so a later same-account token
+      // renewal from another normal page is not compared with the pre-login
+      // `null` identity and falsely classified as an account switch.
+      lastIdentityRef.current = readIdentityKey();
+    }
+
     window.addEventListener("storage", handleStorage);
+    window.addEventListener(AUTH_STATE_CHANGED_EVENT, handleSameTabAuthChange);
     return () => {
       window.removeEventListener("storage", handleStorage);
+      window.removeEventListener(AUTH_STATE_CHANGED_EVENT, handleSameTabAuthChange);
       if (settleTimer) {
         clearTimeout(settleTimer);
       }
     };
-  }, []);
+  }, [disabled, location.pathname, navigate, queryClient]);
 
-  return null;
+  return children ? <Fragment key={revision}>{children}</Fragment> : null;
 }

frontend-web/src/core/auth/use-live-account.ts

@@ -8,7 +8,7 @@ import {
   getAccountIdentityKey,
   getStoredAuth,
 } from "@/core/auth";
-import { isEmbedActive } from "@/core/embed/embed-session";
+import { isEmbedActive, isIsolatedSession } from "@/core/embed/embed-session";
 
 const AUTH_STORAGE_KEY = "deerflow.auth";
 
@@ -65,7 +65,9 @@ export function useLiveAccount(): LiveAccount {
         refresh();
       }
     }
-    if (!isEmbedActive()) {
+    // Normal pages share localStorage identity across tabs. Embedded and
+    // isolated pages deliberately keep their per-tab sessionStorage identity.
+    if (!isEmbedActive() && !isIsolatedSession()) {
       window.addEventListener("storage", onStorage);
     }
     window.addEventListener(AUTH_STATE_CHANGED_EVENT, refresh);

frontend-web/src/core/i18n/locales/en-US.ts

@@ -456,7 +456,7 @@ export const enUS: Translations = {
       lightDescription: "Bright palette with higher contrast for daytime.",
       darkDescription: "Dim palette that reduces glare for focus.",
       lightblueDescription: "A crisp light palette built around blue.",
-      lightgreenDescription: "A crisp light palette built around WeKnora green.",
+      lightgreenDescription: "A crisp light palette built around fresh green tones.",
       iceblueDescription: "An airy palette built around #9BCEF1 with accessible blue actions.",
       lightyellowDescription: "A soft palette built around #F3FBD9 with readable olive actions.",
       languageTitle: "Language",

frontend-web/src/core/i18n/locales/zh-CN.ts

@@ -437,7 +437,7 @@ export const zhCN: Translations = {
       lightDescription: "更明亮的配色，适合日间使用。",
       darkDescription: "更暗的配色，减少眩光方便专注。",
       lightblueDescription: "以蓝色为主色的清爽浅色配色。",
-      lightgreenDescription: "采用 WeKnora 绿色的清爽浅色配色。",
+      lightgreenDescription: "采用清新绿色的浅色配色。",
       iceblueDescription: "以 #9BCEF1 为主色，搭配冰蓝留白与沉稳交互色。",
       lightyellowDescription: "以 #F3FBD9 为主色，搭配柔和浅黄留白与深橄榄交互色。",
       languageTitle: "语言",

frontend-web/src/core/llmwiki/source-links.ts

@@ -44,7 +44,7 @@ export function parseWeKnoraPreviewUrl(url?: string | null): WeKnoraSourceTarget
     params.get("wikiSlug")?.trim() ||
     params.get("slug")?.trim() ||
     "";
-  return knowledgeBaseId && chunkId
+  return knowledgeBaseId && (wikiSlug || chunkId || documentId)
     ? {
         knowledgeBaseId,
         chunkId,
@@ -75,6 +75,7 @@ export function resolveWeKnoraSourceTarget(source: KnowledgeSourceLike): WeKnora
     fromPreview?.documentId ||
     "";
   const chunkId = source.chunk_id || source.chunkId || fromPreview?.chunkId || "";
+  if (!wikiSlug && !chunkId && !documentId) return null;
   return {
     knowledgeBaseId,
     chunkId: chunkId || undefined,
@@ -94,6 +95,43 @@ export function buildWeKnoraSourceIframeUrl(target: WeKnoraSourceTarget): string
   return `/#/page/workspace/knowledge/${encodeURIComponent(target.knowledgeBaseId)}${query ? `?${query}` : ""}`;
 }
 
+/**
+ * Lightweight native reader for one Wiki page. Unlike the knowledge-base
+ * detail route this does not create a WeKnora iframe session.
+ */
+export function buildWeKnoraWikiPageUrl(
+  knowledgeBaseId: string,
+  wikiSlug: string,
+): string {
+  return `/#${buildWeKnoraWikiPagePath(knowledgeBaseId, wikiSlug)}`;
+}
+
+export function buildWeKnoraWikiPagePath(
+  knowledgeBaseId: string,
+  wikiSlug: string,
+): string {
+  const params = new URLSearchParams({ wikiSlug });
+  return `/page/workspace/knowledge/${encodeURIComponent(knowledgeBaseId)}/wiki/view?${params.toString()}`;
+}
+
+/** Public, chrome-free Wiki reader intended for third-party iframe embedding. */
+export function buildPublicKnowledgeWikiPath(
+  knowledgeBaseId: string,
+  wikiSlug?: string,
+): string {
+  const params = new URLSearchParams();
+  if (wikiSlug) params.set("wikiSlug", wikiSlug);
+  const query = params.toString();
+  return `/embed/knowledge/${encodeURIComponent(knowledgeBaseId)}${query ? `?${query}` : ""}`;
+}
+
+export function buildPublicKnowledgeWikiUrl(
+  knowledgeBaseId: string,
+  wikiSlug?: string,
+): string {
+  return `/#${buildPublicKnowledgeWikiPath(knowledgeBaseId, wikiSlug)}`;
+}
+
 export function buildLegacyKnowledgeSourceUrl(source: KnowledgeSourceLike): string {
   const recUuid = source.recUuid || source.rec_uuid || source.url || "";
   if (!recUuid) return "";
@@ -108,7 +146,9 @@ export function buildLegacyKnowledgeSourceUrl(source: KnowledgeSourceLike): stri
 export function openKnowledgeSource(source: KnowledgeSourceLike): boolean {
   const weknoraTarget = resolveWeKnoraSourceTarget(source);
   const href = weknoraTarget
-    ? buildWeKnoraSourceIframeUrl(weknoraTarget)
+    ? weknoraTarget.wikiSlug
+      ? buildWeKnoraWikiPageUrl(weknoraTarget.knowledgeBaseId, weknoraTarget.wikiSlug)
+      : buildWeKnoraSourceIframeUrl(weknoraTarget)
     : buildLegacyKnowledgeSourceUrl(source);
   if (!href) return false;
   window.open(href, "_blank", "noopener,noreferrer");

frontend-web/src/core/llmwiki/wiki-page-markdown.ts

@@ -0,0 +1,56 @@
+import { buildWeKnoraWikiPageUrl } from "@/core/llmwiki/source-links";
+
+export type WikiPageUrlBuilder = (
+  knowledgeBaseId: string,
+  wikiSlug: string,
+) => string;
+
+export function stripWikiFrontmatter(value: string) {
+  return value.replace(/^\s*---\s*\n[\s\S]*?\n---\s*(?:\n|$)/, "").trim();
+}
+
+export function safeWikiFileName(value: string) {
+  return value.replace(/[\\/:*?"<>|\r\n]+/g, "_").replace(/\s+/g, " ").trim() || "wiki-page";
+}
+
+export function exportableWikiMarkdown(title: string, summary: string, content: string) {
+  const body = content.trim();
+  const hasTitle = /^#\s+/m.test(body);
+  return [hasTitle ? "" : `# ${title}`, summary && !body.includes(summary) ? `> ${summary}` : "", body]
+    .filter(Boolean)
+    .join("\n\n");
+}
+
+export function wikiLinkMarkdown(
+  markdown: string,
+  knowledgeBaseId: string,
+  buildPageUrl: WikiPageUrlBuilder = buildWeKnoraWikiPageUrl,
+) {
+  const link = (slugValue: string, labelValue?: string) => {
+    const slug = slugValue.trim();
+    const fallbackLabel = slug.split("/").filter(Boolean).at(-1) || slug;
+    const label = (labelValue || fallbackLabel).trim().replace(/\]/g, "\\]");
+    return `[${label}](${buildPageUrl(knowledgeBaseId, slug)})`;
+  };
+  return markdown
+    .replace(/\[\[([^\]|]+)\|([^\]]+)\]\]/g, (_match, slug, label) => link(slug, label))
+    .replace(/\[\[([^\]\s]+)\s+([^\]]+)\]\]/g, (_match, slug, label) => link(slug, label))
+    .replace(/\[\[([^\]]+)\]\]/g, (_match, slug) => link(slug));
+}
+
+export function renderableWikiMarkdown(
+  title: string,
+  content: string,
+  knowledgeBaseId: string,
+  buildPageUrl?: WikiPageUrlBuilder,
+) {
+  const lines = content.trim().split("\n");
+  if (lines[0]?.replace(/^#+\s*/, "").trim() === title.trim()) {
+    lines[0] = `# ${title}`;
+  }
+  return wikiLinkMarkdown(
+    exportableWikiMarkdown(title, "", lines.join("\n")),
+    knowledgeBaseId,
+    buildPageUrl,
+  );
+}

frontend-web/src/core/llmwiki/wiki-tree.ts

@@ -0,0 +1,146 @@
+import type { LlmWikiWikiPage } from "@/strategy-components/api/llmwiki";
+
+export type WikiTreeNode = {
+  key: string;
+  label: string;
+  page: LlmWikiWikiPage | null;
+  children: WikiTreeNode[];
+  count: number;
+};
+
+export type WikiTree = {
+  roots: WikiTreeNode[];
+  parentKeysBySlug: Map<string, string[]>;
+};
+
+function pageDirectoryParts(page: LlmWikiWikiPage): string[] {
+  const wikiPath = (page.wiki_path || "").split("/").map((item) => item.trim()).filter(Boolean);
+  if (wikiPath.length > 2) return wikiPath.slice(1, -1);
+  const category = page.category_path?.filter(Boolean) || [];
+  if (category.length > 0) return category;
+  const parts = (page.slug || "").split("/").filter(Boolean);
+  return parts.length > 1 ? parts.slice(0, -1) : ["未分类"];
+}
+
+export function filterWikiPagesWithAncestors(
+  pages: LlmWikiWikiPage[],
+  query: string,
+): LlmWikiWikiPage[] {
+  const words = query.trim().toLowerCase().split(/\s+/).filter(Boolean);
+  if (words.length === 0) return pages;
+  const matched = pages.filter((page) => {
+    const haystack = [
+      page.title,
+      page.slug,
+      page.summary,
+      page.page_type,
+      page.parent_slug,
+      ...(page.aliases || []),
+      ...(page.category_path || []),
+    ]
+      .filter(Boolean)
+      .join(" ")
+      .toLowerCase();
+    return words.every((word) => haystack.includes(word));
+  });
+  const bySlug = new Map(pages.map((page) => [page.slug, page]));
+  const result = new Map<string, LlmWikiWikiPage>();
+  for (const page of matched) {
+    let current: LlmWikiWikiPage | undefined = page;
+    const visited = new Set<string>();
+    while (current?.slug && !visited.has(current.slug)) {
+      visited.add(current.slug);
+      result.set(current.slug, current);
+      current = current.parent_slug ? bySlug.get(current.parent_slug) : undefined;
+    }
+  }
+  return Array.from(result.values());
+}
+
+function attachNode(parent: WikiTreeNode | null, roots: WikiTreeNode[], node: WikiTreeNode) {
+  const siblings = parent ? parent.children : roots;
+  if (!siblings.some((item) => item.key === node.key)) siblings.push(node);
+}
+
+function sortWikiNodes(nodes: WikiTreeNode[]) {
+  nodes.sort((left, right) => {
+    if (!!left.children.length !== !!right.children.length) return left.children.length ? -1 : 1;
+    return left.label.localeCompare(right.label, "zh-Hans-CN");
+  });
+  nodes.forEach((node) => sortWikiNodes(node.children));
+}
+
+function countPages(node: WikiTreeNode): number {
+  node.count = (node.page ? 1 : 0) + node.children.reduce((sum, child) => sum + countPages(child), 0);
+  return node.count;
+}
+
+export function buildWikiTree(pages: LlmWikiWikiPage[]): WikiTree {
+  const roots: WikiTreeNode[] = [];
+  const pageNodes = new Map<string, WikiTreeNode>();
+  const directoryNodes = new Map<string, WikiTreeNode>();
+  const parentKeysBySlug = new Map<string, string[]>();
+
+  for (const page of pages) {
+    if (!page.slug) continue;
+    pageNodes.set(page.slug, {
+      key: `page:${page.slug}`,
+      label: page.title || page.slug,
+      page,
+      children: [],
+      count: 1,
+    });
+  }
+
+  const directoryNode = (path: string[]) => {
+    const key = `dir:${path.join("/")}`;
+    const existing = directoryNodes.get(key);
+    if (existing) return existing;
+    const node: WikiTreeNode = {
+      key,
+      label: path[path.length - 1] || "未分类",
+      page: null,
+      children: [],
+      count: 0,
+    };
+    directoryNodes.set(key, node);
+    return node;
+  };
+
+  for (const page of pages) {
+    const node = pageNodes.get(page.slug);
+    if (!node) continue;
+    const ancestorKeys: string[] = [];
+    const parentSlug = page.parent_slug?.trim();
+    if (parentSlug && pageNodes.has(parentSlug)) {
+      const parent = pageNodes.get(parentSlug)!;
+      attachNode(parent, roots, node);
+      ancestorKeys.push(parent.key);
+      let current = parent.page?.parent_slug ? pageNodes.get(parent.page.parent_slug) : undefined;
+      const seen = new Set<string>([parent.key]);
+      while (current && !seen.has(current.key)) {
+        seen.add(current.key);
+        ancestorKeys.unshift(current.key);
+        current = current.page?.parent_slug ? pageNodes.get(current.page.parent_slug) : undefined;
+      }
+      parentKeysBySlug.set(page.slug, ancestorKeys);
+      continue;
+    }
+
+    let parent: WikiTreeNode | null = null;
+    const path: string[] = [];
+    for (const part of pageDirectoryParts(page)) {
+      path.push(part);
+      const directory = directoryNode(path);
+      attachNode(parent, roots, directory);
+      parent = directory;
+      ancestorKeys.push(directory.key);
+    }
+    attachNode(parent, roots, node);
+    parentKeysBySlug.set(page.slug, ancestorKeys);
+  }
+
+  roots.forEach(countPages);
+  sortWikiNodes(roots);
+  return { roots, parentKeysBySlug };
+}

frontend-web/src/core/settings/local.ts

@@ -4,10 +4,11 @@ export const DEFAULT_LOCAL_SETTINGS: LocalSettings = {
   notification: {
     enabled: true,
   },
-  display: {
+  display: {
-    streamSpeedMeterEnabled: true,
+    streamSpeedMeterEnabled: true,
-    ragModeEnabled: false,
+    ragModeEnabled: false,
-    contextCompressionEnabled: false,
+    artifactDirectoryModeEnabled: false,
+    contextCompressionEnabled: false,
     citationCleanupWords: [],
     fontScale: 1,
   },
@@ -43,7 +44,12 @@ export interface LocalSettings {
      * Global switch for skill result display adapters. When disabled, chat
      * messages render tool results with the legacy generic search UI only.
      */
-    ragModeEnabled: boolean;
+    ragModeEnabled: boolean;
+    /**
+     * When enabled, the artifact panel scans every generated output and keeps
+     * a directory tree visible beside the selected file preview.
+     */
+    artifactDirectoryModeEnabled: boolean;
     /**
      * Per-user switch for context compression (上下文压缩). When enabled, long
      * conversations are summarized transiently before the model call to save

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

@@ -761,17 +761,15 @@ export function useThreadStream({
         }
         return;
       }
-      // A "thread not found" 404 almost always means the URL points at a
+      // A "thread not found" 404 means this route cannot accept another turn.
-      // thread from a previous login session — either this tab outlived a
+      // Move to a fresh chat without a full browser reload; the old reload path
-      // logout/re-login or the thread genuinely belongs to a different user.
+      // made every click look like a crash and could loop indefinitely when a
-      // Re-frame the error around the *current* logged-in identity and bounce
+      // different tab's cookie kept overriding this tab's Bearer token.
-      // the user to a fresh chat instead of leaving them stuck on the stale
+      if (isThreadNotAccessibleError(message)) {
-      // route looking at a raw HTTP 404.
+        const userLabel = buildCurrentUserLabel();
-      if (isThreadNotAccessibleError(message)) {
+        toast.info(
-        const userLabel = buildCurrentUserLabel();
+          `当前登录用户为 ${userLabel}，原对话不存在或无权访问，已为你打开新对话。`,
-        toast.info(
+        );
-          `当前登录用户为 ${userLabel}，原对话不存在或无权访问，正在为你刷新页面…`,
-        );
         // Prefer staying inside an agent chat context when the user is on an
         // agent thread URL — otherwise fall back to the global new chat.
         const hash = typeof window !== "undefined" ? window.location.hash : "";
@@ -782,18 +780,7 @@ export function useThreadStream({
           : iframeMatch
             ? "/page/workspace/chats_iframe/new"
             : "/page/workspace/chats/new";
-        // First navigate to a safe URL so the post-reload page lands on a
+        navigate(target, { replace: true });
-        // valid route. Then full-reload so TanStack Query cache, context
-        // providers and any other state captured under the previous user's
-        // identity get rebuilt against the current login.
-        if (typeof window !== "undefined") {
-          window.location.hash = target;
-          window.setTimeout(() => {
-            window.location.reload();
-          }, 900);
-        } else {
-          navigate(target, { replace: true });
-        }
         return;
       }
       // 上一轮还没结束又发了新问题（409）或并发达到上限（429）：

frontend-web/src/core/threads/thread-access-error.ts

@@ -13,8 +13,9 @@ import { getStoredAuth } from "@/core/auth";
  * 404 just leaves the user staring at a scary error. Both the chat stream
  * (``core/threads/hooks.ts``) and the AI-writing stream
  * (``open-canvas/contexts/AIWritingContext.tsx``) funnel their stream errors
- * through here so the UX is identical: detect the login-change 404 and prompt
+ * through here so the UX is identical: detect the login-change 404 and reset
- * the user to refresh against the current identity instead of erroring out.
+ * the stale in-memory session against the current identity instead of showing
+ * a raw error or reloading the browser page.
  */
 
 /** Normalize an unknown stream error into a human-readable message string. */
@@ -108,22 +109,15 @@ export function buildCurrentUserLabel(): string {
 }
 
 /**
- * Re-frame a login-change 404 around the current identity and reload the page.
+ * Re-frame a login-change 404 around the current identity and reset its view.
  *
- * Shows a friendly toast naming the current login, then full-reloads after a
+ * Streams whose session id lives in component state pass a local reset callback
- * short delay so the toast is visible and so TanStack Query cache / context
+ * so they can discard the inaccessible session without a browser reload.
- * providers / any state captured under the previous user get rebuilt against
- * the current login. Used by streams whose session id lives in component state
- * (not the URL) — a plain reload lands them back on a fresh, valid page.
  */
-export function notifyThreadAccessChangedAndReload(): void {
+export function notifyThreadAccessChanged(onReset: () => void): void {
   const userLabel = buildCurrentUserLabel();
   toast.info(
-    `当前登录用户为 ${userLabel}，原会话不存在或无权访问，正在为你刷新页面…`,
+    `当前登录用户为 ${userLabel}，原会话不存在或无权访问，已为你重置为新会话。`,
   );
-  if (typeof window !== "undefined") {
+  onReset();
-    window.setTimeout(() => {
-      window.location.reload();
-    }, 900);
-  }
 }

frontend-web/src/open-canvas/contexts/AIWritingContext.tsx

@@ -18,7 +18,7 @@ import { getAPIClient } from '@/core/api';
 import {
   getStreamErrorMessage,
   isThreadNotAccessibleError,
-  notifyThreadAccessChangedAndReload,
+  notifyThreadAccessChanged,
 } from '@/core/threads/thread-access-error';
 
 import { useCanvasGraphContext } from '../contexts/CanvasGraphContext';
@@ -299,10 +299,13 @@ const AIWritingStreamHost = memo(function AIWritingStreamHost({
       // thread belongs to a previous login session — the user switched accounts
       // (or this tab outlived a re-login), so the current account legitimately
       // can't access the old thread. Instead of dumping the raw HTTP 404 into
-      // the panel, re-frame it around the current identity and reload — same UX
+      // the panel, re-frame it around the current identity and discard the
-      // the chat stream gives (see core/threads/hooks.ts).
+      // stale component-state session without reloading the browser page.
       if (isThreadNotAccessibleError(message)) {
-        notifyThreadAccessChangedAndReload();
+        notifyThreadAccessChanged(() => {
+          continueTargetRef.current = null;
+          dispatchRef.current?.({ type: 'reset' });
+        });
         return;
       }
       dispatchRef.current?.({ type: 'set_error', message });
@@ -410,6 +413,13 @@ export function AIWritingProvider({ children }: { children: ReactNode }) {
   // （刷新会断开 SSE，后端默认 on_disconnect=cancel 取消该 run，不留孤儿）。
   const threadId = state.sessionId ?? undefined;
 
+  const resetAfterThreadAccessError = useCallback(() => {
+    setArtifact(null);
+    seenInterruptRef.current = null;
+    continueTargetRef.current = null;
+    dispatch({ type: 'reset' });
+  }, [setArtifact]);
+
   useEffect(() => {
     const s = state.status;
     const savable = s === 'done' || s === 'error' || s.startsWith('awaiting_');
@@ -473,12 +483,12 @@ export function AIWritingProvider({ children }: { children: ReactNode }) {
     } catch (err) {
       const message = getStreamErrorMessage(err);
       if (isThreadNotAccessibleError(message)) {
-        notifyThreadAccessChangedAndReload();
+        notifyThreadAccessChanged(resetAfterThreadAccessError);
         return;
       }
       dispatch({ type: 'set_error', message });
     }
-  }, [state.status]);
+  }, [state.status, resetAfterThreadAccessError]);
 
   const submitIntervention = useCallback(async (payload: UserInterventionPayload) => {
     if (!state.sessionId || !state.currentPause) return;
@@ -585,14 +595,14 @@ export function AIWritingProvider({ children }: { children: ReactNode }) {
     } catch (err) {
       const message = getStreamErrorMessage(err);
       if (isThreadNotAccessibleError(message)) {
-        notifyThreadAccessChangedAndReload();
+        notifyThreadAccessChanged(resetAfterThreadAccessError);
         return;
       }
       dispatch({ type: 'set_error', message });
     }
   }, [state.sessionId, state.currentPause, state.materials, state.outline,
   state.currentDraftTitle, state.currentDraftMarkdown, state.reviewResult,
-  state.status]);
+  state.status, resetAfterThreadAccessError]);
 
   const pauseWriting = useCallback(() => {
     // 真停：取消当前 run（graph 已完成的阶段已落 checkpoint）。继续时从该 checkpoint 续跑。
@@ -626,13 +636,13 @@ export function AIWritingProvider({ children }: { children: ReactNode }) {
       } catch (err) {
         const message = getStreamErrorMessage(err);
         if (isThreadNotAccessibleError(message)) {
-          notifyThreadAccessChangedAndReload();
+          notifyThreadAccessChanged(resetAfterThreadAccessError);
           return;
         }
         dispatch({ type: 'set_error', message });
       }
     })();
-  }, [state.request]);
+  }, [state.request, resetAfterThreadAccessError]);
 
   // Restore an unfinished history session: make it active, load its checkpoint, then let
   // the host skip completed awaiting_* stages or re-run the current unfinished stage.

frontend-web/src/pages/AgentChatPage.tsx

@@ -776,6 +776,17 @@ export default function AgentChatPage({
                         onContextChange={(context) =>
                           setSettings("context", context)
                         }
+                        knowledgeSelector={
+                          <LlmWikiKnowledgeSelector
+                            source="agent"
+                            agentId={agent_id}
+                            value={selectedKnowledgeBaseIds}
+                            onChange={changeKnowledgeSelection}
+                            disabled={isDemoMode || knowledgeSelectionLoading}
+                            readOnly
+                            label="知识空间"
+                          />
+                        }
                         onFollowupsVisibilityChange={setShowFollowups}
                         onSubmit={handleSubmit}
                         onStop={handleStop}

frontend-web/src/pages/ChatPage.tsx

@@ -838,20 +838,19 @@ export default function ChatPage() {
                           : undefined
                       }
                       knowledgeSelector={
-                        isLandingState ? (
+                        <LlmWikiKnowledgeSelector
-                          <LlmWikiKnowledgeSelector
+                          source={selectedAgentId ? "agent" : "all"}
-                            source={selectedAgentId ? "agent" : "all"}
+                          agentId={selectedAgentId}
-                            agentId={selectedAgentId}
+                          value={selectedKnowledgeBaseIds}
-                            value={selectedKnowledgeBaseIds}
+                          onChange={changeKnowledgeSelection}
-                            onChange={changeKnowledgeSelection}
+                          autoSelectAll={isLandingState && !!selectedAgentId}
-                            autoSelectAll={!!selectedAgentId}
+                          disabled={
-                            disabled={
+                            env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true" ||
-                              env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true" ||
+                            knowledgeSelectionLoading
-                              knowledgeSelectionLoading
+                          }
-                            }
+                          readOnly={!isLandingState}
-                            label="知识空间"
+                          label="知识空间"
-                          />
+                        />
-                        ) : undefined
                       }
                       onFollowupsVisibilityChange={setShowFollowups}
                       onSubmit={handleSubmit}

frontend-web/src/pages/EnterpriseResearchPage.tsx

@@ -37,11 +37,11 @@ import { cn } from "@/lib/utils";
 import { openKnowledgeSource } from "@/core/llmwiki/source-links";
 import MarkdownRenderer from "@/strategy-components/MarkdownRenderer";
 import {
-  type LlmWikiSearchResult,
   useLlmWikiKnowledgeBases,
   useLlmWikiRuntime,
 } from "@/strategy-components/api/llmwiki";
 import {
+  type EnterpriseResearchEvidence,
   type EnterpriseResearchTask,
   type EnterpriseResearchTaskStatus,
   type EnterpriseResearchReportEvent,
@@ -636,7 +636,7 @@ function EvidencePane({
   onStartReport, onCancelReport, onRestoreReport, onSourceSelect,
 }: {
   task: EnterpriseResearchTask | null;
-  source: LlmWikiSearchResult | null;
+  source: EnterpriseResearchEvidence | null;
   reportJob: EnterpriseResearchReportJob | null;
   reportJobs: EnterpriseResearchReportJob[];
   reportDraft: string;
@@ -665,7 +665,7 @@ function EvidencePane({
   const latestRewrite = reportJobs.find((job) => job.action === "rewrite" && job.status === "completed" && job.original_report);
   const latestCommittedJob = reportJobs.find((job) => job.action !== "followup" && job.status === "completed");
   const completedFollowups = reportJobs.filter((job) => job.action === "followup" && job.status === "completed");
-  const selectedSources = task.selected_source_ids.map((id) => task.sources.find((item) => item.chunk_id === id)).filter(Boolean) as LlmWikiSearchResult[];
+  const selectedSources = task.selected_source_ids.map((id) => task.sources.find((item) => item.chunk_id === id)).filter(Boolean) as EnterpriseResearchEvidence[];
   const citationIndex = new Map(selectedSources.map((item, index) => [item.chunk_id, index + 1]));
   const renderedReport = currentReport.replace(/\[资料:([^\]]+)\]/g, (match, id: string) => {
     const index = citationIndex.get(id.trim());

frontend-web/src/pages/FixedQuestionsPage.tsx

@@ -0,0 +1,310 @@
+"use client";
+
+import { useEffect, useMemo, useState } from "react";
+import { Navigate } from "react-router-dom";
+import {
+  Info,
+  MessageSquareText,
+  Plus,
+  Save,
+  Search,
+  Trash2,
+  Zap,
+} from "lucide-react";
+import { toast } from "sonner";
+
+import { Button } from "@/components/ui/button";
+import { Input } from "@/components/ui/input";
+import { Switch } from "@/components/ui/switch";
+import { Textarea } from "@/components/ui/textarea";
+import { getStoredAuth } from "@/core/auth";
+import {
+  type FixedQuestion,
+  useFixedQuestionActions,
+  useFixedQuestions,
+} from "@/strategy-components/api/fixed-questions";
+
+let sequence = 1;
+
+function newId(): string {
+  if (typeof crypto !== "undefined" && "randomUUID" in crypto) {
+    return crypto.randomUUID();
+  }
+  return `fixed-${Date.now()}-${sequence++}`;
+}
+
+function serialize(rows: FixedQuestion[]): string {
+  return JSON.stringify(
+    rows
+      .map(({ id, question, answer, enabled, tokensPerSecond, sortOrder }) => ({
+        id,
+        question,
+        answer,
+        enabled,
+        tokensPerSecond,
+        sortOrder,
+      }))
+      .sort((a, b) => a.id.localeCompare(b.id)),
+  );
+}
+
+export default function FixedQuestionsPage() {
+  const isAdmin = getStoredAuth()?.system_role === "admin";
+  const { data: serverQuestions = [], isLoading } = useFixedQuestions();
+  const { save } = useFixedQuestionActions();
+  const [rows, setRows] = useState<FixedQuestion[]>([]);
+  const [loadedKey, setLoadedKey] = useState<string | null>(null);
+  const [query, setQuery] = useState("");
+
+  const sourceKey = useMemo(
+    () => serialize(serverQuestions),
+    [serverQuestions],
+  );
+  useEffect(() => {
+    if (loadedKey !== sourceKey) {
+      setRows(serverQuestions);
+      setLoadedKey(sourceKey);
+    }
+  }, [loadedKey, serverQuestions, sourceKey]);
+
+  const dirty = useMemo(() => serialize(rows) !== sourceKey, [rows, sourceKey]);
+  const search = query.trim().toLowerCase();
+  const visibleRows = useMemo(
+    () =>
+      search
+        ? rows.filter(
+            (row) =>
+              row.question.toLowerCase().includes(search) ||
+              row.answer.toLowerCase().includes(search),
+          )
+        : rows,
+    [rows, search],
+  );
+  const enabledCount = rows.filter(
+    (row) => row.enabled && row.question.trim() && row.answer.trim(),
+  ).length;
+
+  if (!isAdmin) {
+    return <Navigate to="/page/workspace/chats/new" replace />;
+  }
+
+  const patchRow = (id: string, patch: Partial<FixedQuestion>) => {
+    setRows((current) =>
+      current.map((row) => (row.id === id ? { ...row, ...patch } : row)),
+    );
+  };
+
+  const addRow = () => {
+    setRows((current) => [
+      {
+        id: newId(),
+        question: "",
+        answer: "",
+        enabled: true,
+        tokensPerSecond: 100,
+        sortOrder: current.length,
+      },
+      ...current,
+    ]);
+  };
+
+  const removeRow = (id: string) => {
+    setRows((current) => current.filter((row) => row.id !== id));
+  };
+
+  const handleSave = async () => {
+    const cleaned = rows.map((row, index) => ({
+      ...row,
+      question: row.question.trim(),
+      tokensPerSecond: Math.round(row.tokensPerSecond),
+      sortOrder: index,
+    }));
+    for (const row of cleaned) {
+      if (!row.question) {
+        toast.error("问题不能为空");
+        return;
+      }
+      if (!row.answer.trim()) {
+        toast.error(`问题「${row.question}」的回答不能为空`);
+        return;
+      }
+      if (
+        !Number.isFinite(row.tokensPerSecond) ||
+        row.tokensPerSecond < 1 ||
+        row.tokensPerSecond > 1000
+      ) {
+        toast.error(`问题「${row.question}」的流式速度须为 1–1000 token/s`);
+        return;
+      }
+    }
+    const seen = new Set<string>();
+    for (const row of cleaned) {
+      if (seen.has(row.question)) {
+        toast.error(`问题「${row.question}」重复，请删除或修改重复项`);
+        return;
+      }
+      seen.add(row.question);
+    }
+    try {
+      await save.mutateAsync(cleaned);
+      toast.success("问题配置已保存并生效");
+    } catch (error) {
+      toast.error(error instanceof Error ? error.message : "保存失败");
+    }
+  };
+
+  return (
+    <div className="size-full overflow-auto bg-muted/20 px-4 py-6 sm:px-6">
+      <div className="mx-auto max-w-5xl space-y-5">
+        <section className="rounded-2xl border bg-background p-5 shadow-sm">
+          <div className="flex flex-col justify-between gap-4 md:flex-row md:items-center">
+            <div className="flex items-start gap-3">
+              <div className="rounded-xl bg-primary/10 p-2.5 text-primary">
+                <MessageSquareText className="size-5" />
+              </div>
+              <div>
+                <div className="flex flex-wrap items-center gap-2">
+                  <h1 className="text-xl font-semibold">问题配置</h1>
+                  <span className="rounded-full bg-muted px-2.5 py-1 text-xs text-muted-foreground">
+                    {rows.length} 条 / {enabledCount} 条启用
+                  </span>
+                </div>
+                <p className="mt-1 text-sm text-muted-foreground">
+                  为完全相同的问题配置固定回答，命中时直接流式返回，不调用大模型。
+                </p>
+              </div>
+            </div>
+            <div className="flex gap-2">
+              <Button variant="outline" onClick={addRow}>
+                <Plus className="size-4" />
+                新增问题
+              </Button>
+              <Button
+                onClick={handleSave}
+                disabled={!dirty || save.isPending}
+              >
+                <Save className="size-4" />
+                {save.isPending ? "保存中…" : "保存配置"}
+              </Button>
+            </div>
+          </div>
+          <div className="mt-4 flex items-start gap-2 rounded-xl border border-amber-200 bg-amber-50 px-3.5 py-3 text-sm text-amber-900">
+            <Info className="mt-0.5 size-4 shrink-0" />
+            <span>
+              匹配区分大小写、标点和空格；停用的配置会保留但不参与匹配。带附件或图片的提问不会使用固定回答。
+            </span>
+          </div>
+        </section>
+
+        <section className="flex flex-col gap-3 rounded-2xl border bg-background p-4 shadow-sm sm:flex-row sm:items-center sm:justify-between">
+          <div className="relative w-full sm:max-w-sm">
+            <Search className="absolute left-3 top-1/2 size-4 -translate-y-1/2 text-muted-foreground" />
+            <Input
+              value={query}
+              onChange={(event) => setQuery(event.target.value)}
+              placeholder="搜索问题或回答…"
+              className="pl-9"
+            />
+          </div>
+          <div className="flex items-center gap-1.5 text-xs text-muted-foreground">
+            <Zap className="size-3.5 text-amber-500" />
+            启用项保存后立即生效
+          </div>
+        </section>
+
+        {isLoading ? (
+          <div className="rounded-2xl border bg-background py-16 text-center text-sm text-muted-foreground">
+            加载中…
+          </div>
+        ) : visibleRows.length === 0 ? (
+          <div className="rounded-2xl border border-dashed bg-background py-16 text-center text-sm text-muted-foreground">
+            {rows.length === 0
+              ? "暂无问题配置，点击「新增问题」开始配置"
+              : "没有匹配的问题或回答"}
+          </div>
+        ) : (
+          <div className="space-y-3">
+            {visibleRows.map((row, index) => (
+              <section
+                key={row.id}
+                className={`rounded-2xl border bg-background p-4 shadow-sm transition-opacity ${
+                  row.enabled ? "" : "opacity-60"
+                }`}
+              >
+                <div className="mb-3 flex items-center justify-between gap-3">
+                  <div className="flex items-center gap-2 text-sm font-medium">
+                    <span className="flex size-6 items-center justify-center rounded-full bg-muted text-xs text-muted-foreground">
+                      {index + 1}
+                    </span>
+                    固定问答
+                  </div>
+                  <div className="flex flex-wrap items-center justify-end gap-3">
+                    <label className="flex items-center gap-2 text-sm text-muted-foreground">
+                      <span>流式速度</span>
+                      <Input
+                        type="number"
+                        min={1}
+                        max={1000}
+                        step={10}
+                        value={row.tokensPerSecond}
+                        onChange={(event) =>
+                          patchRow(row.id, {
+                            tokensPerSecond: Number(event.target.value),
+                          })
+                        }
+                        className="h-8 w-24"
+                        aria-label="流式返回速度"
+                      />
+                      <span>token/s</span>
+                    </label>
+                    <label className="flex items-center gap-2 text-sm text-muted-foreground">
+                      <Switch
+                        checked={row.enabled}
+                        onCheckedChange={(enabled) =>
+                          patchRow(row.id, { enabled })
+                        }
+                      />
+                      {row.enabled ? "已启用" : "已停用"}
+                    </label>
+                    <button
+                      type="button"
+                      title="删除"
+                      onClick={() => removeRow(row.id)}
+                      className="flex size-8 items-center justify-center rounded-lg text-muted-foreground transition-colors hover:bg-destructive/10 hover:text-destructive"
+                    >
+                      <Trash2 className="size-4" />
+                    </button>
+                  </div>
+                </div>
+                <div className="grid gap-3 md:grid-cols-2">
+                  <label className="space-y-1.5 text-sm font-medium">
+                    <span>问题</span>
+                    <Textarea
+                      value={row.question}
+                      onChange={(event) =>
+                        patchRow(row.id, { question: event.target.value })
+                      }
+                      placeholder="输入需要精确匹配的问题"
+                      className="min-h-28 resize-y"
+                    />
+                  </label>
+                  <label className="space-y-1.5 text-sm font-medium">
+                    <span>回答</span>
+                    <Textarea
+                      value={row.answer}
+                      onChange={(event) =>
+                        patchRow(row.id, { answer: event.target.value })
+                      }
+                      placeholder="输入命中后流式返回的回答（支持 Markdown）"
+                      className="min-h-28 resize-y"
+                    />
+                  </label>
+                </div>
+              </section>
+            ))}
+          </div>
+        )}
+      </div>
+    </div>
+  );
+}

frontend-web/src/pages/LlmWikiKnowledgePage.tsx

@@ -1,6 +1,6 @@
 import { Loader2, Settings2 } from "lucide-react";
 import { useState } from "react";
-import { Navigate } from "react-router-dom";
+import { Navigate, useParams, useSearchParams } from "react-router-dom";
 
 import { Button } from "@/components/ui/button";
 import {
@@ -10,6 +10,7 @@ import {
   DialogTitle,
 } from "@/components/ui/dialog";
 import { getStoredAuth } from "@/core/auth";
+import { buildWeKnoraWikiPagePath } from "@/core/llmwiki/source-links";
 import { useLlmWikiRuntime } from "@/strategy-components/api/llmwiki";
 import WeKnoraKnowledgeWorkspace, {
   ConnectionSettings,
@@ -66,7 +67,14 @@ export default function LlmWikiKnowledgePage({
 }: {
   mode?: LlmWikiKnowledgePageMode;
 }) {
+  const { noteId = "" } = useParams();
+  const [searchParams] = useSearchParams();
   const runtime = useLlmWikiRuntime();
+  const wikiSlug = searchParams.get("wikiSlug")?.trim() || "";
+
+  if (mode === "detail" && noteId && wikiSlug) {
+    return <Navigate to={buildWeKnoraWikiPagePath(noteId, wikiSlug)} replace />;
+  }
 
   if (runtime.isLoading) {
     return <RuntimeLoading />;

frontend-web/src/pages/StrategyRoutes.tsx

@@ -47,6 +47,7 @@ import LightAppListPage from "./LightAppListPage";
 import LightAppManagementPage from "./LightAppManagementPage";
 import MenuManagementPage from "./MenuManagementPage";
 import LoginWhitelistPage from "./LoginWhitelistPage";
+import FixedQuestionsPage from "./FixedQuestionsPage";
 import SensitiveWordsPage from "./SensitiveWordsPage";
 import SkillAddressesPage from "./SkillAddressesPage";
 import TaskButtonsPage from "./TaskButtonsPage";
@@ -454,6 +455,16 @@ export default function StrategyRoutes() {
                 )
               }
             />
+            <Route
+              path="admin/fixed-questions"
+              element={
+                getStoredAuth()?.system_role === "admin" ? (
+                  <FixedQuestionsPage />
+                ) : (
+                  <Navigate to="/page/workspace/chats/new" replace />
+                )
+              }
+            />
             <Route
               path="admin/sensitive-words"
               element={

frontend-web/src/pages/WorkspaceRoutes.tsx

@@ -40,6 +40,7 @@ import ScheduledTaskRunDetailPage from './ScheduledTaskRunDetailPage';
 import ScheduledTasksPage from './ScheduledTasksPage';
 import LlmWikiKnowledgePage from './LlmWikiKnowledgePage';
 import WeKnoraWikiManagementPage from '@/strategy-components/components/resource-management/llmwiki/WeKnoraWikiManagementPage';
+import WeKnoraWikiPageView from '@/strategy-components/components/resource-management/llmwiki/WeKnoraWikiPageView';
 import MarkdownDocxEditorPage from './MarkdownDocxEditorPage';
 import LlmMetricsPage from './LlmMetricsPage';
 import CheckpointMigrationPage from './CheckpointMigrationPage';
@@ -678,6 +679,14 @@ export default function WorkspaceRoutes({
             </WorkspaceLayout>
           }
         />
+        <Route
+          path="knowledge/:noteId/wiki/view"
+          element={
+            <WorkspaceLayout {...layoutProps}>
+              <WeKnoraWikiPageView />
+            </WorkspaceLayout>
+          }
+        />
         <Route
           path="knowledge/:noteId/wiki"
           element={

frontend-web/src/pages/deep-research/WorkflowConfigDialog.tsx

@@ -77,6 +77,7 @@ import {
 } from "@/strategy-components/api/report-structures";
 import { useSkills } from "@/core/skills/hooks";
 import { desensitize } from "@/lib/desensitize";
+import { cn } from "@/lib/utils";
 
 // ── shared helpers ───────────────────────────────────────────────────────────
 
@@ -1213,12 +1214,16 @@ export function WorkflowConfigButton({
     return structuresQuery.data?.find((structure) => structure.content.trim() === content)?.title ?? null;
   }, [appliedContent, structuresQuery.data]);
   const buttonLabel = selectedWorkflowTitle || "工作流配置";
+  const isSelected = Boolean(selectedWorkflowTitle);
 
   return (
     <>
       <Button
         aria-label={selectedWorkflowTitle ? `已选择工作流：${selectedWorkflowTitle}` : "工作流配置"}
-        className={className}
+        className={cn(
+          className,
+          isSelected && "bg-accent text-accent-foreground dark:bg-accent/50",
+        )}
         disabled={disabled}
         onClick={() => setOpen(true)}
         size={size}

frontend-web/src/roundtable-planning/hooks/useStep1Intent.ts

@@ -452,6 +452,11 @@ export function useStep1Intent(options: UseStep1IntentOptions): UseStep1IntentRe
         // 跨 worker 单飞——重复 / 双击命中既有回合即幂等返回，杜绝并发下双发意图。
         const clientTurnId = createClientId();
 
+        // ask_clarification 是本轮的严格暂停点。某些模型在工具调用已经产出
+        // 选项卡后还会继续吐一段“请做选择”等正文；从第一张卡出现起忽略后续
+        // 文本 delta，但继续消费流以收齐同轮的其它澄清卡和终态帧。
+        let clarificationSeen = false;
+
         const res = await streamIntent({
           threadId: intentThreadId,
           message: trimmed,
@@ -462,6 +467,7 @@ export function useStep1Intent(options: UseStep1IntentOptions): UseStep1IntentRe
           files: fileRefs,
           signal: aborter.signal,
           onTextDelta: (delta) => {
+            if (clarificationSeen) return;
             setInteractiveMessages((prev) =>
               prev.map((m) =>
                 m.id === agentMsgId
@@ -504,6 +510,7 @@ export function useStep1Intent(options: UseStep1IntentOptions): UseStep1IntentRe
             );
           },
           onClarification: (clarification, index) => {
+            clarificationSeen = true;
             // 实时把每条澄清问题灌进气泡 —— 用户能边流边看到「协助过程」逐个出现,
             // 而不是等终态帧(终态帧只带第 1 个问题)。同时往步骤链补一条
             // 「追问 N:<问题>」,与「强化步骤链」诉求对齐。

frontend-web/src/strategy-components/api/enterprise-research.ts

@@ -1,10 +1,26 @@
 import { apiFetch } from "@/core/api/fetch-client";
 import { getBackendBaseURL } from "@/core/config";
 
-import type { LlmWikiSearchResult } from "./llmwiki";
-
 const API = () => `${getBackendBaseURL()}/api/enterprise-research`;
 
+/**
+ * Enterprise research snapshots raw WeKnora evidence chunks. This is
+ * intentionally separate from LlmWikiSearchResult, whose public search shape
+ * now represents processed Wiki pages only.
+ */
+export interface EnterpriseResearchEvidence {
+  chunk_id: string;
+  content: string;
+  knowledge_id: string;
+  knowledge_base_id: string;
+  knowledge_base_name: string;
+  title: string;
+  filename: string;
+  score: number;
+  chunk_index: number;
+  url: string;
+}
+
 export type EnterpriseResearchTaskStatus = "draft" | "collecting" | "ready" | "partial" | "failed";
 
 export interface EnterpriseResearchTask {
@@ -15,7 +31,7 @@ export interface EnterpriseResearchTask {
   knowledge_base_ids: string[];
   queries: string[];
   selected_source_ids: string[];
-  sources: LlmWikiSearchResult[];
+  sources: EnterpriseResearchEvidence[];
   plan_markdown?: string | null;
   report_markdown?: string | null;
   report_summary?: string | null;

frontend-web/src/strategy-components/api/fixed-questions.ts

@@ -0,0 +1,122 @@
+/** Administrator-managed exact-match fixed question/answer API. */
+
+import { useMutation, useQuery, useQueryClient } from "@tanstack/react-query";
+
+import { apiFetch } from "@/core/api/fetch-client";
+import { getBackendBaseURL } from "@/core/config";
+import { OptType, writeYLog } from "@/core/log/y-log";
+
+const BASE = () => `${getBackendBaseURL()}/api/fixed-questions`;
+
+export interface FixedQuestion {
+  id: string;
+  question: string;
+  answer: string;
+  enabled: boolean;
+  tokensPerSecond: number;
+  sortOrder: number;
+  updatedBy?: string | null;
+  updatedAt?: string | null;
+}
+
+interface ServerFixedQuestion {
+  id: string;
+  question: string;
+  answer: string;
+  enabled: boolean;
+  tokens_per_second: number;
+  sort_order: number;
+  updated_by?: string | null;
+  updated_at?: string | null;
+}
+
+function fromServer(row: ServerFixedQuestion): FixedQuestion {
+  return {
+    id: row.id,
+    question: row.question ?? "",
+    answer: row.answer ?? "",
+    enabled: row.enabled ?? true,
+    tokensPerSecond: row.tokens_per_second ?? 100,
+    sortOrder: row.sort_order ?? 0,
+    updatedBy: row.updated_by ?? null,
+    updatedAt: row.updated_at ?? null,
+  };
+}
+
+function toServer(row: FixedQuestion): ServerFixedQuestion {
+  return {
+    id: row.id,
+    question: row.question,
+    answer: row.answer,
+    enabled: row.enabled,
+    tokens_per_second: row.tokensPerSecond,
+    sort_order: row.sortOrder,
+  };
+}
+
+async function readJson<T>(response: Response, context: string): Promise<T> {
+  if (!response.ok) {
+    const data = await response.json().catch(() => null as unknown);
+    const detail =
+      data && typeof data === "object" && "detail" in data
+        ? String((data as { detail: unknown }).detail)
+        : `${context} failed (${response.status})`;
+    throw new Error(detail);
+  }
+  return (await response.json()) as T;
+}
+
+export async function listFixedQuestions(): Promise<FixedQuestion[]> {
+  const response = await apiFetch(BASE(), { method: "GET" });
+  const data = await readJson<{ questions: ServerFixedQuestion[] }>(
+    response,
+    "list fixed questions",
+  );
+  return (data.questions ?? []).map(fromServer);
+}
+
+export async function replaceFixedQuestions(
+  questions: FixedQuestion[],
+): Promise<FixedQuestion[]> {
+  const response = await apiFetch(BASE(), {
+    method: "PUT",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ questions: questions.map(toServer) }),
+  });
+  const data = await readJson<{ questions: ServerFixedQuestion[] }>(
+    response,
+    "save fixed questions",
+  );
+  const saved = (data.questions ?? []).map(fromServer);
+  writeYLog({
+    optType: OptType.edit,
+    optDetail: "CM助手-全量-问题配置-保存",
+    url: "/api/fixed-questions",
+    reqParam: { questions },
+    returnParam: saved,
+  });
+  return saved;
+}
+
+const FIXED_QUESTIONS_KEY = "fixed-questions";
+
+export function useFixedQuestions() {
+  return useQuery({
+    queryKey: [FIXED_QUESTIONS_KEY],
+    queryFn: listFixedQuestions,
+    refetchOnWindowFocus: false,
+    staleTime: 30_000,
+  });
+}
+
+export function useFixedQuestionActions() {
+  const queryClient = useQueryClient();
+  return {
+    save: useMutation({
+      mutationFn: replaceFixedQuestions,
+      onSuccess: (questions) => {
+        queryClient.setQueryData([FIXED_QUESTIONS_KEY], questions);
+      },
+    }),
+  };
+}

frontend-web/src/strategy-components/api/llmwiki.ts

@@ -5,6 +5,7 @@ import { useLiveAccount } from "@/core/auth/use-live-account";
 import { getBackendBaseURL } from "@/core/config";
 
 const API = () => `${getBackendBaseURL()}/api/llmwiki`;
+const PUBLIC_API = () => `${getBackendBaseURL()}/api/public/llmwiki`;
 const SETTINGS_API = () => `${getBackendBaseURL()}/api/system-settings/llmwiki`;
 
 export type LlmWikiProvider = "legacy" | "weknora";
@@ -143,6 +144,22 @@ export interface LlmWikiWikiPageList {
   total_pages: number;
 }
 
+export interface LlmWikiWikiIndexStatus {
+  knowledge_base_id: string;
+  state: "not_synced" | "idle" | "running" | "partial" | "failed" | "rebuilding" | "rebuild_required";
+  local_index_enabled: boolean;
+  wiki_index_enabled: boolean;
+  fully_vectorized: boolean;
+  retrieval_mode: "vector" | "wiki_api";
+  local_page_count?: number;
+  ready_page_count?: number;
+  failed_page_count?: number;
+  vector_count?: number;
+  last_error?: string | null;
+  last_started_at?: string | null;
+  last_completed_at?: string | null;
+}
+
 export interface LlmWikiSourceContext {
   knowledge_base_name?: string;
   document_title?: string;
@@ -159,16 +176,38 @@ export interface LlmWikiSourceContext {
 }
 
 export interface LlmWikiSearchResult {
-  chunk_id: string;
+  kind: "wiki_page";
+  id: string;
+  wiki_page_id: string;
+  wiki_slug: string;
   content: string;
-  knowledge_id: string;
   knowledge_base_id: string;
   knowledge_base_name: string;
   title: string;
-  filename: string;
+  summary?: string;
+  page_type?: string;
+  page_version?: number;
+  updated_at?: string | null;
+  matched_heading?: string | null;
+  matched_sections?: Array<{
+    section_index: number;
+    heading?: string | null;
+    content: string;
+    score: number;
+  }>;
   score: number;
-  chunk_index: number;
   url: string;
+  retrieval_mode?: "vector" | "wiki_api";
+}
+
+export interface LlmWikiSearchResponse {
+  query: string;
+  mode: "vector" | "wiki_api" | "mixed";
+  results: LlmWikiSearchResult[];
+  knowledge_base_count: number;
+  partial: boolean;
+  warnings: string[];
+  fallback_knowledge_base_ids: string[];
 }
 
 export interface LlmWikiWeKnoraEmbedSession {
@@ -203,14 +242,22 @@ export interface LlmWikiWikiPageUpdate {
   wiki_path?: string;
 }
 
+function userFacingKnowledgeMessage(value: string): string {
+  return value.replace(/weknora/gi, "知识服务");
+}
+
 async function readJson<T>(response: Response, context: string): Promise<T> {
   if (!response.ok) {
     const payload = await response.json().catch(() => null as unknown);
-    const detail =
+    const rawDetail = payload && typeof payload === "object" && "detail" in payload
-      payload && typeof payload === "object" && "detail" in payload
+      ? (payload as { detail: unknown }).detail
-        ? String((payload as { detail: unknown }).detail)
+      : null;
+    const detail = rawDetail && typeof rawDetail === "object" && "message" in rawDetail
+      ? String((rawDetail as { message: unknown }).message)
+      : rawDetail
+        ? String(rawDetail)
         : `${context}失败（${response.status}）`;
-    throw new Error(detail);
+    throw new Error(userFacingKnowledgeMessage(detail));
   }
   if (response.status === 204) return undefined as T;
   return (await response.json()) as T;
@@ -266,7 +313,7 @@ export async function createLlmWikiWeKnoraEmbedSession(
       `${API()}/knowledge-bases/${encodeURIComponent(id)}/weknora/session?tab=${encodeURIComponent(tab)}`,
       { method: "POST" },
     ),
-    "创建 WeKnora 详情会话",
+    "创建知识库详情会话",
   );
 }
 
@@ -412,6 +459,66 @@ export async function getLlmWikiWikiPage(
   );
 }
 
+export async function getLlmWikiWikiIndexStatus(
+  knowledgeBaseId: string,
+): Promise<LlmWikiWikiIndexStatus> {
+  return readJson(
+    await apiFetch(
+      `${API()}/knowledge-bases/${encodeURIComponent(knowledgeBaseId)}/wiki-index-status`,
+    ),
+    "读取 Wiki 向量化状态",
+  );
+}
+
+export async function vectorizeLlmWikiKnowledgeBase(
+  knowledgeBaseId: string,
+): Promise<{ job_id: string; status: string; knowledge_base_id: string }> {
+  return readJson(
+    await apiFetch(
+      `${API()}/knowledge-bases/${encodeURIComponent(knowledgeBaseId)}/vectorize`,
+      { method: "POST" },
+    ),
+    "触发 Wiki 向量化",
+  );
+}
+
+export async function exportLlmWikiWikiExcel(
+  knowledgeBaseId: string,
+  knowledgeBaseName = "LLMWiki",
+): Promise<void> {
+  const response = await apiFetch(
+    `${API()}/knowledge-bases/${encodeURIComponent(knowledgeBaseId)}/wiki/export.xlsx`,
+  );
+  if (!response.ok) {
+    await readJson<void>(response, "导出 Wiki Excel");
+    return;
+  }
+  const blob = await response.blob();
+  const objectUrl = URL.createObjectURL(blob);
+  const link = document.createElement("a");
+  link.href = objectUrl;
+  link.download = `${knowledgeBaseName.replace(/[\\/:*?"<>|]/g, "_") || "LLMWiki"}-Wiki.xlsx`;
+  document.body.appendChild(link);
+  link.click();
+  link.remove();
+  URL.revokeObjectURL(objectUrl);
+}
+
+/** Read the DeerFlow-local Wiki mirror used by new vector citations. */
+export async function getLocalLlmWikiWikiPage(
+  knowledgeBaseId: string,
+  slug: string,
+): Promise<LlmWikiWikiPage> {
+  const safeSlug = slug.split("/").map(encodeURIComponent).join("/");
+  const page = await readJson<LlmWikiWikiPage & { page_version?: number }>(
+    await apiFetch(
+      `${API()}/knowledge-bases/${encodeURIComponent(knowledgeBaseId)}/local-wiki/pages/${safeSlug}`,
+    ),
+    "读取本地 Wiki 页面详情",
+  );
+  return { ...page, version: page.version ?? page.page_version ?? 0 };
+}
+
 export async function createLlmWikiWikiPage(
   knowledgeBaseId: string,
   input: LlmWikiWikiPageCreate,
@@ -554,8 +661,8 @@ export async function searchLlmWiki(input: {
   query: string;
   scope: LlmWikiScope;
   knowledge_base_ids?: string[];
-}): Promise<LlmWikiSearchResult[]> {
+}): Promise<LlmWikiSearchResponse> {
-  const payload = await readJson<{ results: LlmWikiSearchResult[] }>(
+  return readJson<LlmWikiSearchResponse>(
     await apiFetch(`${API()}/search`, {
       method: "POST",
       headers: { "Content-Type": "application/json" },
@@ -563,7 +670,44 @@ export async function searchLlmWiki(input: {
     }),
     "检索知识库",
   );
-  return payload.results ?? [];
+}
+
+export async function getPublicLlmWikiKnowledgeBase(
+  id: string,
+): Promise<LlmWikiKnowledgeBase> {
+  return readJson(
+    await apiFetch(`${PUBLIC_API()}/knowledge-bases/${encodeURIComponent(id)}`),
+    "读取公开知识库详情",
+  );
+}
+
+export async function listPublicLlmWikiWikiPages(
+  knowledgeBaseId: string,
+  page: number,
+  pageSize: number,
+  query = "",
+): Promise<LlmWikiWikiPageList> {
+  const params = new URLSearchParams({ page: String(page), page_size: String(pageSize) });
+  if (query.trim()) params.set("query", query.trim());
+  return readJson(
+    await apiFetch(
+      `${PUBLIC_API()}/knowledge-bases/${encodeURIComponent(knowledgeBaseId)}/wiki/pages?${params.toString()}`,
+    ),
+    "读取公开 Wiki 页面",
+  );
+}
+
+export async function getPublicLlmWikiWikiPage(
+  knowledgeBaseId: string,
+  slug: string,
+): Promise<LlmWikiWikiPage> {
+  const safeSlug = slug.split("/").map(encodeURIComponent).join("/");
+  return readJson(
+    await apiFetch(
+      `${PUBLIC_API()}/knowledge-bases/${encodeURIComponent(knowledgeBaseId)}/wiki/pages/${safeSlug}`,
+    ),
+    "读取公开 Wiki 页面详情",
+  );
 }
 
 export async function createLlmWikiConversationDeposit(input: {
@@ -586,7 +730,7 @@ export async function createLlmWikiConversationDeposit(input: {
 }
 
 export async function getLlmWikiSettings(): Promise<LlmWikiSettings> {
-  return readJson(await apiFetch(SETTINGS_API()), "读取 WeKnora 连接配置");
+  return readJson(await apiFetch(SETTINGS_API()), "读取知识服务连接配置");
 }
 
 export async function saveLlmWikiSettings(input: {
@@ -600,7 +744,7 @@ export async function saveLlmWikiSettings(input: {
       headers: { "Content-Type": "application/json" },
       body: JSON.stringify(input),
     }),
-    "保存 WeKnora 连接配置",
+    "保存知识服务连接配置",
   );
 }
 
@@ -620,7 +764,7 @@ export async function testLlmWikiConnection(
       headers: { "Content-Type": "application/json" },
       body: JSON.stringify({ api_base_url: apiBaseUrl }),
     }),
-    "测试 WeKnora 连接",
+    "测试知识服务连接",
   );
 }
 
@@ -755,6 +899,62 @@ export function useLlmWikiWikiPage(
   });
 }
 
+export function usePublicLlmWikiKnowledgeBase(
+  knowledgeBaseId: string | null,
+  enabled = true,
+) {
+  return useQuery({
+    queryKey: ["public-llmwiki", "knowledge-base", knowledgeBaseId],
+    queryFn: () => getPublicLlmWikiKnowledgeBase(knowledgeBaseId!),
+    enabled: enabled && !!knowledgeBaseId,
+    staleTime: 60_000,
+  });
+}
+
+export function usePublicLlmWikiWikiPages(
+  knowledgeBaseId: string | null,
+  page: number,
+  pageSize = 50,
+  query = "",
+  enabled = true,
+) {
+  return useQuery({
+    queryKey: ["public-llmwiki", "wiki-pages", knowledgeBaseId, page, pageSize, query],
+    queryFn: () => listPublicLlmWikiWikiPages(knowledgeBaseId!, page, pageSize, query),
+    enabled: enabled && !!knowledgeBaseId,
+    staleTime: 60_000,
+  });
+}
+
+export function usePublicLlmWikiWikiPage(
+  knowledgeBaseId: string | null,
+  slug: string | null,
+  enabled = true,
+) {
+  return useQuery({
+    queryKey: ["public-llmwiki", "wiki-page", knowledgeBaseId, slug],
+    queryFn: () => getPublicLlmWikiWikiPage(knowledgeBaseId!, slug!),
+    enabled: enabled && !!knowledgeBaseId && !!slug,
+    staleTime: 60_000,
+  });
+}
+
+export function useLlmWikiWikiIndexStatus(
+  knowledgeBaseId: string | null,
+  enabled = true,
+) {
+  const { userId } = useLiveAccount();
+  return useQuery({
+    queryKey: ["llmwiki", "wiki-index-status", knowledgeBaseId, userId ?? "anonymous"],
+    queryFn: () => getLlmWikiWikiIndexStatus(knowledgeBaseId!),
+    enabled: enabled && !!knowledgeBaseId,
+    refetchInterval: (query) => {
+      const state = query.state.data?.state;
+      return state === "running" || state === "rebuilding" ? 2_000 : 10_000;
+    },
+  });
+}
+
 export function useLlmWikiSettings(enabled = true) {
   const { userId } = useLiveAccount();
   return useQuery({
@@ -822,6 +1022,14 @@ export function useLlmWikiActions() {
         deleteLlmWikiWikiPage(id, slug),
       onSuccess: invalidateKnowledge,
     }),
+    vectorizeWiki: useMutation({
+      mutationFn: ({ id }: { id: string }) => vectorizeLlmWikiKnowledgeBase(id),
+      onSuccess: invalidateKnowledge,
+    }),
+    exportWikiExcel: useMutation({
+      mutationFn: ({ id, name }: { id: string; name?: string }) =>
+        exportLlmWikiWikiExcel(id, name),
+    }),
     publication: useMutation({
       mutationFn: ({ id, publish }: { id: string; publish: boolean }) =>
         setLlmWikiPublication(id, publish),

frontend-web/src/strategy-components/components/resource-management/llmwiki/WeKnoraKnowledgeDetailPage.tsx

@@ -1,4 +1,4 @@
-import { AlertCircle, Edit3, FileText, Loader2, RefreshCw, Trash2, Upload } from "lucide-react";
+import { AlertCircle, Edit3, FileText, Loader2, RefreshCw, Trash2 } from "lucide-react";
 import { useEffect, useRef, useState } from "react";
 import { Navigate, useNavigate, useParams, useSearchParams } from "react-router-dom";
 import { toast } from "sonner";
@@ -14,6 +14,7 @@ import { Input } from "@/components/ui/input";
 import { Textarea } from "@/components/ui/textarea";
 import { MarkdownCodeEditor } from "@/components/wiki/MarkdownCodeEditor";
 import { getBackendBaseURL } from "@/core/config";
+import { buildWeKnoraWikiPagePath } from "@/core/llmwiki/source-links";
 import {
   createLlmWikiWeKnoraEmbedSession,
   getLlmWikiSourceContext,
@@ -100,14 +101,11 @@ export function WeKnoraKnowledgeDetailPage() {
   const [searchParams] = useSearchParams();
   const navigate = useNavigate();
   const frameRef = useRef<HTMLIFrameElement>(null);
-  const fileInputRef = useRef<HTMLInputElement>(null);
   const [frameSrc, setFrameSrc] = useState("");
   const [frameVersion, setFrameVersion] = useState(0);
   const [frameError, setFrameError] = useState<string | null>(null);
-  const [uploading, setUploading] = useState(false);
   const runtime = useLlmWikiRuntime();
   const details = useLlmWikiKnowledgeBase(knowledgeBaseId || null, !!knowledgeBaseId);
-  const actions = useLlmWikiActions();
 
   const detailsReady = !!details.data;
   const requestedTab = searchParams.get("tab");
@@ -120,12 +118,15 @@ export function WeKnoraKnowledgeDetailPage() {
   const sourceChunkId = searchParams.get("sourceChunkId") || searchParams.get("chunkId") || "";
   const documentId = searchParams.get("documentId") || "";
   const wikiSlug = searchParams.get("wikiSlug") || "";
+  const nativeWikiPageUrl = knowledgeBaseId && wikiSlug && preferredTab === "wiki"
+    ? buildWeKnoraWikiPagePath(knowledgeBaseId, wikiSlug)
+    : "";
 
   useEffect(() => {
     let cancelled = false;
     setFrameSrc("");
     setFrameError(null);
-    if (!knowledgeBaseId || runtime.data?.provider !== "weknora" || !detailsReady) {
+    if (nativeWikiPageUrl || !knowledgeBaseId || runtime.data?.provider !== "weknora" || !detailsReady) {
       return () => {
         cancelled = true;
       };
@@ -158,7 +159,7 @@ export function WeKnoraKnowledgeDetailPage() {
     return () => {
       cancelled = true;
     };
-  }, [detailsReady, documentId, knowledgeBaseId, preferredTab, runtime.data?.provider, sourceChunkId, wikiSlug]);
+  }, [detailsReady, documentId, knowledgeBaseId, nativeWikiPageUrl, preferredTab, runtime.data?.provider, sourceChunkId, wikiSlug]);
 
   useEffect(() => {
     if (!frameSrc) return;
@@ -178,6 +179,10 @@ export function WeKnoraKnowledgeDetailPage() {
     };
   }, [frameSrc]);
 
+  if (nativeWikiPageUrl) {
+    return <Navigate to={nativeWikiPageUrl} replace />;
+  }
+
   if (runtime.isLoading || details.isLoading) {
     return (
       <div className="flex h-full items-center justify-center text-sm text-muted-foreground">
@@ -225,53 +230,15 @@ export function WeKnoraKnowledgeDetailPage() {
     );
   }
 
-  const canUpload = details.data.can_write && !details.data.is_conversation_deposit;
+  const canWrite = details.data.can_write && !details.data.is_conversation_deposit;
   const canEditCurrentWikiArticle =
-    canUpload && !!details.data.indexing_strategy?.wiki_enabled && !!wikiSlug;
+    canWrite && !!details.data.indexing_strategy?.wiki_enabled && !!wikiSlug;
-  const canManageWiki = canUpload && !!details.data.indexing_strategy?.wiki_enabled;
+  const canManageWiki = canWrite && !!details.data.indexing_strategy?.wiki_enabled;
 
   return (
     <div className="flex h-full min-h-0 flex-col bg-background">
-      {(canUpload || canEditCurrentWikiArticle) && (
+      {canManageWiki && (
         <div className="flex min-h-12 shrink-0 flex-wrap items-center justify-between gap-2 border-b px-4 py-2">
-          <input
-            ref={fileInputRef}
-            type="file"
-            multiple
-            className="hidden"
-            onChange={(event) => {
-              const files = Array.from(event.currentTarget.files ?? []);
-              event.currentTarget.value = "";
-              if (files.length === 0) return;
-              void (async () => {
-                setUploading(true);
-                const failed: string[] = [];
-                try {
-                  for (const file of files) {
-                    try {
-                      await actions.upload.mutateAsync({ id: knowledgeBaseId, file });
-                    } catch {
-                      failed.push(file.name);
-                    }
-                  }
-                  const succeeded = files.length - failed.length;
-                  if (succeeded > 0) {
-                    await details.refetch();
-                    setFrameVersion((value) => value + 1);
-                  }
-                  if (failed.length === 0) {
-                    toast.success(`已上传 ${succeeded} 个文件，正在处理`);
-                  } else if (succeeded > 0) {
-                    toast.warning(`上传完成：成功 ${succeeded} 个，失败 ${failed.length} 个`);
-                  } else {
-                    toast.error("文件上传失败");
-                  }
-                } finally {
-                  setUploading(false);
-                }
-              })();
-            }}
-          />
           <div className="min-w-0 flex-1">
             {canEditCurrentWikiArticle && (
               <CurrentWikiArticleActions
@@ -288,7 +255,6 @@ export function WeKnoraKnowledgeDetailPage() {
             )}
           </div>
           <div className="flex shrink-0 items-center gap-2">
-          {canManageWiki && (
             <Button
               size="sm"
               variant="outline"
@@ -297,22 +263,6 @@ export function WeKnoraKnowledgeDetailPage() {
               <FileText className="mr-2 size-4" />
               Wiki管理
             </Button>
-          )}
-          {canUpload && (
-            <Button
-              size="sm"
-              className="shrink-0"
-              onClick={() => fileInputRef.current?.click()}
-              disabled={uploading}
-            >
-              {uploading ? (
-                <Loader2 className="mr-2 size-4 animate-spin" />
-              ) : (
-                <Upload className="mr-2 size-4" />
-              )}
-              上传文件
-            </Button>
-          )}
           </div>
         </div>
       )}
@@ -323,7 +273,7 @@ export function WeKnoraKnowledgeDetailPage() {
           title={`${details.data.name || "知识库"} 详情`}
           src={frameSrc}
           className="h-full min-h-0 w-full flex-1 border-0 bg-background"
-          sandbox="allow-same-origin allow-scripts allow-forms allow-downloads allow-popups"
+          sandbox="allow-same-origin allow-scripts allow-forms allow-downloads allow-popups allow-popups-to-escape-sandbox"
           referrerPolicy="no-referrer"
           onLoad={() => postThemeToFrame(frameRef.current)}
         />

frontend-web/src/strategy-components/components/resource-management/llmwiki/WeKnoraKnowledgeWorkspace.tsx

@@ -1,5 +1,7 @@
 import {
   BookOpen,
+  BookOpenText,
+  ChevronRight,
   Database,
   FileText,
   Globe2,
@@ -29,8 +31,11 @@ import { Input } from "@/components/ui/input";
 import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs";
 import { Textarea } from "@/components/ui/textarea";
 import { getStoredAuth } from "@/core/auth";
+import { WeKnoraSourceDrawer } from "@/strategy-components/components/resource-management/llmwiki/WeKnoraSourceDrawer";
 import {
   type LlmWikiKnowledgeBase,
+  type LlmWikiSearchResponse,
+  type LlmWikiSearchResult,
   type LlmWikiScope,
   searchLlmWiki,
   useLlmWikiActions,
@@ -53,6 +58,49 @@ function messageOf(error: unknown): string {
   return error instanceof Error ? error.message : "操作失败，请稍后重试";
 }
 
+function searchModeLabel(mode: LlmWikiSearchResponse["mode"]) {
+  if (mode === "vector") return "本地 Wiki 向量检索";
+  if (mode === "mixed") return "Wiki 混合检索";
+  return "Wiki 接口检索";
+}
+
+function wikiPageTypeLabel(value?: string) {
+  const normalized = (value || "").trim().toLowerCase();
+  if (normalized === "directory") return "目录页";
+  if (normalized === "overview") return "概览页";
+  if (normalized === "article") return "文章页";
+  return value?.trim() || "Wiki 页面";
+}
+
+function formatSearchTime(value?: string | null) {
+  if (!value) return "";
+  const date = new Date(value);
+  return Number.isNaN(date.getTime())
+    ? value
+    : date.toLocaleString("zh-CN", { hour12: false });
+}
+
+function resultPreview(result: LlmWikiSearchResult) {
+  const text = (
+    result.matched_sections?.map((section) => section.content).filter(Boolean).join("\n\n") ||
+    result.summary ||
+    result.content ||
+    ""
+  );
+  return text
+    .replace(/^---[\s\S]*?---\s*/m, "")
+    .replace(/```[\s\S]*?```/g, " ")
+    .replace(/!\[([^\]]*)\]\([^)]*\)/g, "$1")
+    .replace(/\[([^\]]+)\]\([^)]*\)/g, "$1")
+    .replace(/\[\[[^\]\s|]+[|\s]+([^\]]+)\]\]/g, "$1")
+    .replace(/\[\[([^\]]+)\]\]/g, "$1")
+    .replace(/^#{1,6}\s+/gm, "")
+    .replace(/^\s*[-*+]\s+/gm, "")
+    .replace(/[>*_`~|]/g, " ")
+    .replace(/\s+/g, " ")
+    .trim();
+}
+
 export function WeKnoraKnowledgeWorkspace() {
   const navigate = useNavigate();
   const isAdmin = getStoredAuth()?.system_role === "admin";
@@ -63,15 +111,13 @@ export function WeKnoraKnowledgeWorkspace() {
   const [createOpen, setCreateOpen] = useState(false);
   const [searchText, setSearchText] = useState("");
   const [searching, setSearching] = useState(false);
-  const [searchResults, setSearchResults] = useState<Array<{
+  const [searchResponse, setSearchResponse] = useState<LlmWikiSearchResponse | null>(null);
-    chunk_id: string;
+  const [selectedSearchResult, setSelectedSearchResult] = useState<LlmWikiSearchResult | null>(null);
-    title: string;
-    content: string;
-    score: number;
-    knowledge_base_name: string;
-  }>>([]);
 
-  useEffect(() => setSearchResults([]), [tab]);
+  useEffect(() => {
+    setSearchResponse(null);
+    setSelectedSearchResult(null);
+  }, [tab]);
 
   const busy = actions.create.isPending || actions.remove.isPending || actions.publication.isPending;
   const openDetails = (item: LlmWikiKnowledgeBase) => {
@@ -87,7 +133,7 @@ export function WeKnoraKnowledgeWorkspace() {
     if (!query) return;
     setSearching(true);
     try {
-      setSearchResults(await searchLlmWiki({ query, scope }));
+      setSearchResponse(await searchLlmWiki({ query, scope }));
     } catch (error) {
       toast.error(messageOf(error));
     } finally {
@@ -154,9 +200,9 @@ export function WeKnoraKnowledgeWorkspace() {
                 <div className="flex w-full max-w-xl items-center gap-2 rounded-xl border bg-background/80 p-1 shadow-sm sm:w-auto">
                   <div className="relative min-w-0 flex-1 sm:w-80">
                     <Search className="absolute left-3 top-1/2 size-4 -translate-y-1/2 text-muted-foreground" />
-                    <Input value={searchText} onChange={(event) => setSearchText(event.target.value)} onKeyDown={(event) => event.key === "Enter" && void runSearch()} placeholder={tab === "public" ? "检索公共知识" : "检索我的知识"} className="border-0 bg-transparent pl-9 shadow-none focus-visible:ring-0" />
+                    <Input value={searchText} onChange={(event) => setSearchText(event.target.value)} onKeyDown={(event) => event.key === "Enter" && void runSearch()} placeholder={tab === "public" ? "检索公共 Wiki 文档" : "检索我的 Wiki 文档"} className="border-0 bg-transparent pl-9 shadow-none focus-visible:ring-0" />
                   </div>
-                  <Button variant="secondary" className="rounded-lg px-4" onClick={() => void runSearch()} disabled={searching || !searchText.trim()}>{searching ? <Loader2 className="size-4 animate-spin" /> : "检索"}</Button>
+                  <Button variant="secondary" className="rounded-lg px-4" onClick={() => void runSearch()} disabled={searching || !searchText.trim()}>{searching ? <Loader2 className="size-4 animate-spin" /> : "检索 Wiki"}</Button>
                 </div>
               )}
             </div>
@@ -166,15 +212,95 @@ export function WeKnoraKnowledgeWorkspace() {
             {isAdmin && <TabsContent value="settings" className="mt-5"><ConnectionSettings /></TabsContent>}
           </Tabs>
 
-          {searchResults.length > 0 && tab !== "settings" && (
+          {searchResponse && tab !== "settings" && (
-            <Card className="mt-5">
+            <Card className="mt-5 overflow-hidden border-emerald-200/70 bg-gradient-to-br from-emerald-50/70 via-card to-card shadow-sm dark:border-emerald-900/60 dark:from-emerald-950/20">
-              <CardHeader className="pb-3"><CardTitle className="text-base">检索结果</CardTitle><CardDescription>结果由知识服务检索返回，问答中使用同一授权链路。</CardDescription></CardHeader>
+              <CardHeader className="border-b border-emerald-200/60 pb-4 dark:border-emerald-900/50">
-              <CardContent className="space-y-3">{searchResults.map((result) => <div key={result.chunk_id} className="rounded-lg border p-3"><div className="flex items-center justify-between gap-3 text-sm font-medium"><span>{result.title || "未命名来源"}</span><Badge variant="outline">{result.knowledge_base_name}</Badge></div><p className="mt-2 line-clamp-3 whitespace-pre-wrap text-sm text-muted-foreground">{result.content}</p></div>)}</CardContent>
+                <div className="flex flex-wrap items-start justify-between gap-3">
+                  <div className="flex min-w-0 items-start gap-3">
+                    <div className="flex size-10 shrink-0 items-center justify-center rounded-xl bg-emerald-600 text-white shadow-sm shadow-emerald-600/20">
+                      <BookOpenText className="size-5" />
+                    </div>
+                    <div className="min-w-0">
+                      <CardTitle className="flex flex-wrap items-center gap-2 text-base">
+                        Wiki 文档检索
+                        <Badge className="border-emerald-200 bg-emerald-100 text-emerald-800 hover:bg-emerald-100 dark:border-emerald-800 dark:bg-emerald-950 dark:text-emerald-200">
+                          {searchResponse.results.length} 个 Wiki 页面
+                        </Badge>
+                      </CardTitle>
+                      <CardDescription className="mt-1.5 leading-5">
+                        本次直接检索知识库生成的 Wiki 页面，不检索上传原文或原文分块。
+                      </CardDescription>
+                    </div>
+                  </div>
+                  <Badge variant="outline" className="shrink-0 bg-background/80 text-emerald-700 dark:text-emerald-300">
+                    {searchModeLabel(searchResponse.mode)}
+                  </Badge>
+                </div>
+              </CardHeader>
+              <CardContent className="space-y-3 p-4">
+                {searchResponse.results.length === 0 ? (
+                  <div className="flex min-h-36 flex-col items-center justify-center rounded-xl border border-dashed bg-background/70 px-6 text-center">
+                    <BookOpenText className="mb-3 size-8 text-muted-foreground/60" />
+                    <div className="text-sm font-medium">已完成 Wiki 文档检索，暂未命中相关页面</div>
+                    <div className="mt-1 text-xs text-muted-foreground">可以缩短关键词或换一个主题后重试。</div>
+                  </div>
+                ) : searchResponse.results.map((result) => {
+                  const heading = result.matched_heading || result.matched_sections?.find((section) => section.heading)?.heading;
+                  const updatedAt = formatSearchTime(result.updated_at);
+                  return (
+                    <button
+                      type="button"
+                      key={`${result.knowledge_base_id}:${result.wiki_slug || result.id}`}
+                      className="group w-full rounded-xl border bg-background/90 p-4 text-left shadow-sm transition hover:-translate-y-0.5 hover:border-emerald-300 hover:shadow-md focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-emerald-500/40"
+                      onClick={() => setSelectedSearchResult(result)}
+                    >
+                      <div className="flex items-start gap-3">
+                        <div className="mt-0.5 flex size-9 shrink-0 items-center justify-center rounded-lg bg-emerald-100 text-emerald-700 dark:bg-emerald-950 dark:text-emerald-300">
+                          <BookOpenText className="size-4.5" />
+                        </div>
+                        <div className="min-w-0 flex-1">
+                          <div className="flex flex-wrap items-center gap-2">
+                            <Badge variant="secondary" className="bg-emerald-50 text-emerald-700 dark:bg-emerald-950 dark:text-emerald-300">Wiki 文档</Badge>
+                            <Badge variant="outline">{wikiPageTypeLabel(result.page_type)}</Badge>
+                            <span className="truncate text-xs text-muted-foreground">{result.knowledge_base_name}</span>
+                          </div>
+                          <div className="mt-2 line-clamp-2 text-[15px] font-semibold leading-6 text-foreground">{result.title || "未命名 Wiki 页面"}</div>
+                          {heading && <div className="mt-1 text-xs font-medium text-emerald-700 dark:text-emerald-300">命中章节：{heading}</div>}
+                          <p className="mt-2 line-clamp-3 whitespace-pre-wrap text-sm leading-6 text-muted-foreground">{resultPreview(result)}</p>
+                          <div className="mt-3 flex flex-wrap items-center justify-between gap-2 border-t pt-3 text-xs text-muted-foreground">
+                            <div className="flex flex-wrap items-center gap-x-3 gap-y-1">
+                              <span>相关度 {Math.round(Math.max(0, result.score || 0) * 100)}%</span>
+                              {updatedAt && <span>更新于 {updatedAt}</span>}
+                            </div>
+                            <span className="inline-flex items-center font-medium text-emerald-700 transition group-hover:translate-x-0.5 dark:text-emerald-300">
+                              抽屉查看完整 Wiki <ChevronRight className="ml-1 size-3.5" />
+                            </span>
+                          </div>
+                        </div>
+                      </div>
+                    </button>
+                  );
+                })}
+              </CardContent>
             </Card>
           )}
         </div>
       </div>
 
+      <WeKnoraSourceDrawer
+        open={selectedSearchResult !== null}
+        target={selectedSearchResult ? {
+          knowledgeBaseId: selectedSearchResult.knowledge_base_id,
+          wikiSlug: selectedSearchResult.wiki_slug,
+          tab: "wiki",
+        } : null}
+        title={selectedSearchResult?.title}
+        quote={selectedSearchResult ? resultPreview(selectedSearchResult) : ""}
+        onOpenChange={(open) => {
+          if (!open) setSelectedSearchResult(null);
+        }}
+      />
+
       <CreateKnowledgeDialog open={createOpen} pending={actions.create.isPending} onOpenChange={setCreateOpen} onCreate={async (input) => {
         try {
           const created = await actions.create.mutateAsync(input);

frontend-web/src/strategy-components/components/resource-management/llmwiki/WeKnoraSourceDrawer.tsx

@@ -1,5 +1,14 @@
-import { Download, FileText, Loader2, Maximize2, Minimize2 } from "lucide-react";
+import {
+  BookOpenText,
+  Download,
+  FileDown,
+  FileText,
+  Loader2,
+  Maximize2,
+  Minimize2,
+} from "lucide-react";
 import { useEffect, useMemo, useRef, useState } from "react";
+import { Link } from "react-router-dom";
 import { toast } from "sonner";
 
 import { Badge } from "@/components/ui/badge";
@@ -17,10 +26,21 @@ import { SpreadsheetPreview } from "@/components/workspace/artifacts/spreadsheet
 import { MarkdownContent } from "@/components/workspace/messages/markdown-content";
 import { cn } from "@/lib/utils";
 import { reasoningPlugins } from "@/core/streamdown";
+import { buildWeKnoraWikiPagePath } from "@/core/llmwiki/source-links";
+import {
+  exportableWikiMarkdown,
+  renderableWikiMarkdown,
+  safeWikiFileName,
+  stripWikiFrontmatter,
+  wikiLinkMarkdown,
+} from "@/core/llmwiki/wiki-page-markdown";
+import { markdownToDocxBlob } from "@/core/scheduled-tasks/markdown-docx";
 import {
   getLlmWikiDocument,
   getLlmWikiDocumentPreview,
+  getLlmWikiWikiIndexStatus,
   getLlmWikiWikiPage,
+  getLocalLlmWikiWikiPage,
   listLlmWikiDocumentChunks,
   type LlmWikiChunk,
   type LlmWikiDocument,
@@ -61,8 +81,34 @@ type CachedSourceDetail = {
 
 const sourceDetailCache = new Map<string, CachedSourceDetail>();
 
+async function getAvailableWikiPage(
+  knowledgeBaseId: string,
+  wikiSlug: string,
+): Promise<LlmWikiWikiPage> {
+  const status = await getLlmWikiWikiIndexStatus(knowledgeBaseId).catch(() => null);
+  if (status?.local_index_enabled) {
+    return getLocalLlmWikiWikiPage(knowledgeBaseId, wikiSlug).catch(() =>
+      getLlmWikiWikiPage(knowledgeBaseId, wikiSlug),
+    );
+  }
+  if (status?.local_index_enabled === false) {
+    return getLlmWikiWikiPage(knowledgeBaseId, wikiSlug);
+  }
+  try {
+    return await getLlmWikiWikiPage(knowledgeBaseId, wikiSlug);
+  } catch (remoteError) {
+    try {
+      return await getLocalLlmWikiWikiPage(knowledgeBaseId, wikiSlug);
+    } catch {
+      // Do not mask the useful remote-page error with a local-index-disabled
+      // response when the status request itself was unavailable.
+      throw remoteError;
+    }
+  }
+}
+
 async function resolveTargetDetail(target: WeKnoraSourceTarget): Promise<DetailTarget> {
-  if (target.documentId || target.wikiSlug || !target.chunkId) {
+  if (target.wikiSlug || !target.chunkId) {
     return target;
   }
   const params = new URLSearchParams({
@@ -74,12 +120,14 @@ async function resolveTargetDetail(target: WeKnoraSourceTarget): Promise<DetailT
   );
   const payload = (await response.json().catch(() => null)) as SourceContextResponse | null;
   if (!response.ok || payload?.success !== true) {
-    throw new Error("无法定位原文文档详情");
+    if (target.documentId) return target;
+    throw new Error("无法定位当前引用详情");
   }
   const documentId = payload.data?.document_id?.trim();
   const wikiSlug = payload.data?.wiki_page?.slug?.trim();
   if (!documentId && !wikiSlug) {
-    throw new Error("当前引用缺少原文文档标识，无法打开详情");
+    if (target.documentId) return target;
+    throw new Error("当前引用缺少 Wiki 页面或文档标识，无法打开详情");
   }
   return {
     ...target,
@@ -96,8 +144,14 @@ function formatDate(value?: string | null) {
 }
 
 function displayType(document?: LlmWikiDocument | null, wiki?: LlmWikiWikiPage | null) {
+  if (wiki) {
+    const pageType = String(wiki.page_type || "").toLowerCase();
+    if (pageType === "directory") return "Wiki 目录页";
+    if (pageType === "overview") return "Wiki 概览页";
+    if (pageType === "article") return "Wiki 文章页";
+    return "Wiki 文档";
+  }
   return (
-    wiki?.page_type ||
     document?.file_type ||
     document?.type ||
     document?.source ||
@@ -109,8 +163,23 @@ function cleanText(value?: string | null) {
   return (value || "").replace(/\r\n/g, "\n").replace(/\n{3,}/g, "\n\n").trim();
 }
 
-function stripFrontmatter(value: string) {
+function downloadMarkdown(markdown: string, fileName: string) {
-  return value.replace(/^\s*---\s*\n[\s\S]*?\n---\s*(?:\n|$)/, "").trim();
+  downloadBlob(
+    new Blob([markdown], { type: "text/markdown;charset=utf-8" }),
+    `${safeWikiFileName(fileName)}.md`,
+  );
+}
+
+function downloadBlob(blob: Blob, fileName: string) {
+  const url = URL.createObjectURL(blob);
+  const anchor = window.document.createElement("a");
+  anchor.href = url;
+  anchor.download = fileName;
+  anchor.rel = "noopener";
+  window.document.body.appendChild(anchor);
+  anchor.click();
+  anchor.remove();
+  window.setTimeout(() => URL.revokeObjectURL(url), 30_000);
 }
 
 function fileExtension(document?: LlmWikiDocument | null) {
@@ -183,7 +252,7 @@ function isWordDocument(document?: LlmWikiDocument | null) {
 }
 
 function markdownFromChunks(chunks: LlmWikiChunk[]) {
-  return stripFrontmatter(
+  return stripWikiFrontmatter(
     chunks.map((chunk) => cleanText(chunk.content)).filter(Boolean).join("\n\n"),
   );
 }
@@ -468,6 +537,7 @@ export function WeKnoraSourceDrawer({
   const [previewLoading, setPreviewLoading] = useState(false);
   const [fullscreen, setFullscreen] = useState(false);
   const [downloading, setDownloading] = useState(false);
+  const [wikiDownload, setWikiDownload] = useState<"md" | "word" | null>(null);
   const [resolvedDocumentId, setResolvedDocumentId] = useState("");
 
   const targetKey = useMemo(() => {
@@ -518,7 +588,9 @@ export function WeKnoraSourceDrawer({
 
     void (async () => {
       const detailTarget = await resolveTargetDetail(target);
-      if (!cancelled) setResolvedDocumentId(detailTarget.documentId || "");
+      const isWikiTarget = Boolean(detailTarget.wikiSlug);
+      const previewDocumentId = isWikiTarget ? "" : detailTarget.documentId || "";
+      if (!cancelled) setResolvedDocumentId(previewDocumentId);
       const tasks: Promise<void>[] = [];
       let loadedDocument: LlmWikiDocument | null = null;
       let loadedWikiPage: LlmWikiWikiPage | null = null;
@@ -528,24 +600,23 @@ export function WeKnoraSourceDrawer({
 
       if (detailTarget.wikiSlug) {
         tasks.push(
-          getLlmWikiWikiPage(detailTarget.knowledgeBaseId, detailTarget.wikiSlug)
+          getAvailableWikiPage(detailTarget.knowledgeBaseId, detailTarget.wikiSlug)
             .then((page) => {
               loadedWikiPage = page;
               if (!cancelled) setWikiPage(page);
-            })
+            }),
-            .catch(() => undefined),
         );
       }
 
-      if (detailTarget.documentId) {
+      if (previewDocumentId) {
         loadedDocument = await getLlmWikiDocument(
           detailTarget.knowledgeBaseId,
-          detailTarget.documentId,
+          previewDocumentId,
         );
         if (!cancelled) setDocument(loadedDocument);
         loadedChunks = await listLlmWikiDocumentChunks(
           detailTarget.knowledgeBaseId,
-          detailTarget.documentId,
+          previewDocumentId,
           1,
           200,
         )
@@ -557,7 +628,7 @@ export function WeKnoraSourceDrawer({
         }
         const previewBlobPromise = isWordDocument(loadedDocument)
           ? Promise.resolve(new Blob())
-          : getLlmWikiDocumentPreview(detailTarget.knowledgeBaseId, detailTarget.documentId);
+          : getLlmWikiDocumentPreview(detailTarget.knowledgeBaseId, previewDocumentId);
         const previewTask = previewBlobPromise
             .then((blob) => {
               return buildPreviewState(
@@ -585,11 +656,11 @@ export function WeKnoraSourceDrawer({
       }
 
       if (tasks.length === 0) {
-        throw new Error("当前引用缺少原文文档标识，无法打开详情");
+        throw new Error("当前引用缺少 Wiki 页面或文档标识，无法打开详情");
       }
       await Promise.all(tasks);
       sourceDetailCache.set(targetKey, {
-        documentId: detailTarget.documentId || "",
+        documentId: previewDocumentId,
         document: loadedDocument,
         wikiPage: loadedWikiPage,
         preview: loadedPreview,
@@ -617,7 +688,20 @@ export function WeKnoraSourceDrawer({
     title ||
     "文档详情";
   const summary = cleanText(wikiPage?.summary || document?.description);
-  const wikiContent = stripFrontmatter(cleanText(wikiPage?.content));
+  const wikiContent = stripWikiFrontmatter(cleanText(wikiPage?.content));
+  const wikiDisplayContent = wikiPage && target
+    ? renderableWikiMarkdown(resolvedTitle, wikiContent, target.knowledgeBaseId)
+    : "";
+  const wikiMarkdown = wikiPage
+    ? wikiLinkMarkdown(
+        exportableWikiMarkdown(resolvedTitle, summary, wikiContent),
+        target?.knowledgeBaseId || "",
+      )
+    : "";
+  const resolvedWikiSlug = wikiPage?.slug || target?.wikiSlug || "";
+  const wikiWorkspacePath = target && resolvedWikiSlug
+    ? buildWeKnoraWikiPagePath(target.knowledgeBaseId, resolvedWikiSlug)
+    : "";
 
   const downloadOriginal = async () => {
     if (!target || !resolvedDocumentId) return;
@@ -639,6 +723,28 @@ export function WeKnoraSourceDrawer({
     }
   };
 
+  const downloadWiki = async (format: "md" | "word") => {
+    if (!wikiMarkdown) {
+      toast.error("当前 Wiki 页面没有可下载内容");
+      return;
+    }
+    setWikiDownload(format);
+    try {
+      if (format === "md") {
+        downloadMarkdown(wikiMarkdown, resolvedTitle);
+        toast.success("Markdown 文件已生成");
+      } else {
+        const blob = await markdownToDocxBlob(wikiMarkdown, resolvedTitle);
+        downloadBlob(blob, `${safeWikiFileName(resolvedTitle)}.docx`);
+        toast.success("Word 文件已生成");
+      }
+    } catch (error) {
+      toast.error(error instanceof Error ? error.message : "下载 Wiki 页面失败");
+    } finally {
+      setWikiDownload(null);
+    }
+  };
+
   return (
     <Sheet open={open} onOpenChange={onOpenChange}>
       <SheetContent
@@ -649,48 +755,74 @@ export function WeKnoraSourceDrawer({
         )}
       >
         <SheetTitle className="sr-only">{resolvedTitle}</SheetTitle>
-        <SheetDescription className="sr-only">知识库文档详情</SheetDescription>
+        <SheetDescription className="sr-only">知识库 Wiki 页面详情</SheetDescription>
         <div className="relative flex h-full min-h-0 flex-col bg-background">
-          <div className="shrink-0 border-b px-5 py-4 pr-64">
+          <div className="shrink-0 border-b px-5 py-4 pr-12">
-            <div className="flex min-w-0 items-center gap-3">
+            <div className="flex flex-wrap items-start justify-between gap-3">
-              <div className="flex size-10 shrink-0 items-center justify-center rounded-lg bg-emerald-100 text-emerald-700">
+              <div className="flex min-w-64 flex-1 items-center gap-3">
-                <FileText className="size-5" />
+                <div className="flex size-10 shrink-0 items-center justify-center rounded-lg bg-emerald-100 text-emerald-700">
-              </div>
+                  {wikiPage ? <BookOpenText className="size-5" /> : <FileText className="size-5" />}
-              <div className="min-w-0">
+                </div>
-                <div className="truncate text-base font-semibold text-foreground">{resolvedTitle}</div>
+                <div className="min-w-0">
-                <div className="mt-1 flex flex-wrap items-center gap-2 text-xs text-muted-foreground">
+                  <div className="truncate text-base font-semibold text-foreground">{resolvedTitle}</div>
-                  <Badge variant="outline">{displayType(document, wikiPage)}</Badge>
+                  <div className="mt-1 flex flex-wrap items-center gap-2 text-xs text-muted-foreground">
-                  {formatDate(document?.created_at || wikiPage?.created_at) && (
+                    <Badge variant="outline">{displayType(document, wikiPage)}</Badge>
-                    <span>{formatDate(document?.created_at || wikiPage?.created_at)}</span>
+                    {formatDate(document?.created_at || wikiPage?.created_at) && (
-                  )}
+                      <span>{formatDate(document?.created_at || wikiPage?.created_at)}</span>
-                  {document?.parse_status && <span>{document.parse_status}</span>}
+                    )}
+                    {document?.parse_status && <span>{document.parse_status}</span>}
+                  </div>
                 </div>
               </div>
-            </div>
+              <div className="flex flex-wrap items-center justify-end gap-2">
-            <div className="absolute top-4 right-12 flex items-center gap-2">
+                {wikiPage && (
-              {resolvedDocumentId && (
+                  <>
-                <Button type="button" size="sm" variant="outline" onClick={() => void downloadOriginal()} disabled={downloading}>
+                    <Button type="button" size="sm" variant="outline" onClick={() => void downloadWiki("md")} disabled={wikiDownload !== null}>
-                  {downloading ? <Loader2 className="size-4 animate-spin" /> : <Download className="size-4" />}
+                      {wikiDownload === "md" ? <Loader2 className="size-4 animate-spin" /> : <FileDown className="size-4" />}
-                  下载原文
+                      下载 MD
+                    </Button>
+                    <Button type="button" size="sm" variant="outline" onClick={() => void downloadWiki("word")} disabled={wikiDownload !== null}>
+                      {wikiDownload === "word" ? <Loader2 className="size-4 animate-spin" /> : <FileText className="size-4" />}
+                      下载 Word
+                    </Button>
+                    {wikiWorkspacePath && (
+                      <Button type="button" size="sm" variant="outline" asChild>
+                        <Link
+                          to={wikiWorkspacePath}
+                          state={{ wikiPage }}
+                          onClick={() => onOpenChange(false)}
+                        >
+                          <BookOpenText className="size-4" />
+                          打开所在 Wiki
+                        </Link>
+                      </Button>
+                    )}
+                  </>
+                )}
+                {resolvedDocumentId && (
+                  <Button type="button" size="sm" variant="outline" onClick={() => void downloadOriginal()} disabled={downloading}>
+                    {downloading ? <Loader2 className="size-4 animate-spin" /> : <Download className="size-4" />}
+                    下载原文
+                  </Button>
+                )}
+                <Button
+                  type="button"
+                  size="sm"
+                  variant="outline"
+                  onClick={() => setFullscreen((value) => !value)}
+                  aria-label={fullscreen ? "退出放大查看" : "单独放大查看文档"}
+                >
+                  {fullscreen ? <Minimize2 className="size-4" /> : <Maximize2 className="size-4" />}
+                  {fullscreen ? "退出放大" : "放大查看"}
                 </Button>
-              )}
+              </div>
-              <Button
-                type="button"
-                size="sm"
-                variant="outline"
-                onClick={() => setFullscreen((value) => !value)}
-                aria-label={fullscreen ? "退出放大查看" : "单独放大查看文档"}
-              >
-                {fullscreen ? <Minimize2 className="size-4" /> : <Maximize2 className="size-4" />}
-                {fullscreen ? "退出放大" : "放大查看"}
-              </Button>
             </div>
           </div>
 
           {loading && (
             <div className="flex min-h-0 flex-1 items-center justify-center text-sm text-muted-foreground">
               <Loader2 className="mr-2 size-5 animate-spin" />
-              正在加载完整文档预览
+              正在加载完整 Wiki 文档
             </div>
           )}
 
@@ -780,13 +912,16 @@ export function WeKnoraSourceDrawer({
                 </section>
               ) : null}
 
-              {wikiContent && (
+              {wikiDisplayContent && (
                 <section className="border-b px-5 py-4">
-                  <div className="mb-2 text-sm font-medium text-foreground">Wiki 原文</div>
+                  <div className="mb-2 flex items-center gap-2 text-sm font-medium text-foreground">
+                    <BookOpenText className="size-4 text-emerald-600" />
+                    Wiki 文档正文
+                  </div>
                   <div className="rounded-lg border bg-background p-5">
                     <MarkdownContent
                       className="max-w-none"
-                      content={wikiContent}
+                      content={wikiDisplayContent}
                       isLoading={false}
                       remarkPlugins={reasoningPlugins.remarkPlugins}
                       rehypePlugins={reasoningPlugins.rehypePlugins}

frontend-web/src/strategy-components/components/resource-management/llmwiki/WeKnoraWikiManagementPage.tsx

@@ -1,4 +1,4 @@
-import { ArrowLeft, ChevronDown, ChevronRight, FilePlus2, FileText, Folder, Loader2, RefreshCw, Save, Search, Trash2 } from "lucide-react";
+import { ArrowLeft, ChevronDown, ChevronRight, Cpu, Download, FilePlus2, FileText, Folder, Loader2, RefreshCw, Save, Search, Trash2 } from "lucide-react";
 import { type Dispatch, type SetStateAction, useEffect, useMemo, useState } from "react";
 import { Navigate, useNavigate, useParams } from "react-router-dom";
 import { toast } from "sonner";
@@ -13,6 +13,7 @@ import {
   useLlmWikiActions,
   useLlmWikiKnowledgeBase,
   useLlmWikiRuntime,
+  useLlmWikiWikiIndexStatus,
   useLlmWikiWikiPage,
   useLlmWikiWikiPages,
 } from "@/strategy-components/api/llmwiki";
@@ -298,6 +299,7 @@ export function WeKnoraWikiManagementPage() {
 
   const canWrite = !!details.data?.can_write && !details.data?.is_conversation_deposit;
   const pages = useLlmWikiWikiPages(noteId || null, 1, 500, "", !!noteId);
+  const indexStatus = useLlmWikiWikiIndexStatus(noteId || null, !!noteId);
   const detail = useLlmWikiWikiPage(
     noteId || null,
     selectedSlug || null,
@@ -561,6 +563,34 @@ export function WeKnoraWikiManagementPage() {
     }
   };
 
+  const vectorize = async () => {
+    if (!canWrite) return;
+    try {
+      await actions.vectorizeWiki.mutateAsync({ id: noteId });
+      toast.success("已提交整库 Wiki 向量化任务");
+      await indexStatus.refetch();
+    } catch (error) {
+      toast.error(error instanceof Error ? error.message : "触发向量化失败");
+    }
+  };
+
+  const exportExcel = async () => {
+    try {
+      await actions.exportWikiExcel.mutateAsync({ id: noteId, name: title });
+      toast.success("Wiki 已全部导出为 Excel");
+    } catch (error) {
+      toast.error(error instanceof Error ? error.message : "导出 Wiki Excel 失败");
+    }
+  };
+
+  const vectorStatusText = !indexStatus.data?.local_index_enabled
+    ? "本地向量未启用，检索使用 Wiki 接口"
+    : indexStatus.data.fully_vectorized
+      ? `整库已向量化（${indexStatus.data.vector_count ?? 0} 个向量章节）`
+      : indexStatus.data.state === "running" || indexStatus.data.state === "rebuilding"
+        ? "整库向量化进行中，完成前检索使用 Wiki 接口"
+        : "整库尚未完成向量化，检索使用 Wiki 接口";
+
   return (
     <div className="flex h-full min-h-0 flex-col bg-background">
       <header className="flex min-h-14 shrink-0 flex-wrap items-center justify-between gap-3 border-b px-4 py-2">
@@ -571,9 +601,26 @@ export function WeKnoraWikiManagementPage() {
             </Button>
             <h1 className="truncate text-base font-semibold text-foreground">{title}</h1>
           </div>
-          <p className="ml-9 mt-0.5 text-xs text-muted-foreground">Wiki 文档新增、编辑、删除</p>
+          <p className="ml-9 mt-0.5 text-xs text-muted-foreground">Wiki 文档新增、编辑、删除 · {vectorStatusText}</p>
         </div>
         <div className="flex items-center gap-2">
+          <Button
+            variant="outline"
+            size="sm"
+            onClick={() => void vectorize()}
+            disabled={!canWrite || actions.vectorizeWiki.isPending || indexStatus.data?.state === "running" || indexStatus.data?.state === "rebuilding"}
+          >
+            {actions.vectorizeWiki.isPending || indexStatus.data?.state === "running" || indexStatus.data?.state === "rebuilding" ? (
+              <Loader2 className="mr-2 size-4 animate-spin" />
+            ) : (
+              <Cpu className="mr-2 size-4" />
+            )}
+            手动向量化
+          </Button>
+          <Button variant="outline" size="sm" onClick={() => void exportExcel()} disabled={actions.exportWikiExcel.isPending}>
+            {actions.exportWikiExcel.isPending ? <Loader2 className="mr-2 size-4 animate-spin" /> : <Download className="mr-2 size-4" />}
+            导出 Excel
+          </Button>
           <Button variant="outline" size="sm" onClick={() => void pages.refetch()}>
             <RefreshCw className="mr-2 size-4" />
             刷新

frontend-web/src/strategy-components/components/resource-management/llmwiki/WeKnoraWikiPageView.tsx

@@ -0,0 +1,479 @@
+import {
+  ArrowLeft,
+  BookOpenText,
+  ChevronDown,
+  ChevronRight,
+  Download,
+  FileText,
+  Folder,
+  Loader2,
+  RefreshCw,
+  Search,
+} from "lucide-react";
+import { type ReactNode, useEffect, useMemo, useState } from "react";
+import { Link, useLocation, useNavigate, useParams, useSearchParams } from "react-router-dom";
+import { toast } from "sonner";
+
+import { Badge } from "@/components/ui/badge";
+import { Button } from "@/components/ui/button";
+import { Input } from "@/components/ui/input";
+import { MarkdownContent } from "@/components/workspace/messages/markdown-content";
+import {
+  buildPublicKnowledgeWikiPath,
+  buildWeKnoraWikiPagePath,
+} from "@/core/llmwiki/source-links";
+import {
+  buildWikiTree,
+  filterWikiPagesWithAncestors,
+  type WikiTreeNode,
+} from "@/core/llmwiki/wiki-tree";
+import { usePublicBackground } from "@/core/embed/background";
+import { reasoningPlugins } from "@/core/streamdown";
+import { markdownToDocxBlob } from "@/core/scheduled-tasks/markdown-docx";
+import {
+  exportableWikiMarkdown,
+  renderableWikiMarkdown,
+  safeWikiFileName,
+  stripWikiFrontmatter,
+  wikiLinkMarkdown,
+} from "@/core/llmwiki/wiki-page-markdown";
+import {
+  type LlmWikiWikiPage,
+  useLlmWikiKnowledgeBase,
+  useLlmWikiWikiPage,
+  useLlmWikiWikiPages,
+  usePublicLlmWikiKnowledgeBase,
+  usePublicLlmWikiWikiPage,
+  usePublicLlmWikiWikiPages,
+} from "@/strategy-components/api/llmwiki";
+
+const LIST_PATH = "/page/workspace/knowledge";
+
+function cleanText(value?: string | null) {
+  return (value || "").replace(/\r\n/g, "\n").replace(/\n{3,}/g, "\n\n").trim();
+}
+
+function formatDate(value?: string | null) {
+  if (!value) return "";
+  const date = new Date(value);
+  return Number.isNaN(date.getTime())
+    ? value
+    : date.toLocaleString("zh-CN", { hour12: false });
+}
+
+function pageTypeLabel(value?: string) {
+  const pageType = String(value || "").toLowerCase();
+  if (pageType === "directory") return "Wiki 目录页";
+  if (pageType === "overview") return "Wiki 概览页";
+  if (pageType === "article") return "Wiki 文章页";
+  return "Wiki 文档";
+}
+
+function directoryLabel(value: string) {
+  const labels: Record<string, string> = {
+    concept: "概念",
+    entity: "实体",
+    summary: "摘要",
+    index: "索引",
+    "未分类": "其他页面",
+  };
+  return labels[value.toLowerCase()] || value;
+}
+
+function downloadBlob(blob: Blob, fileName: string) {
+  const url = URL.createObjectURL(blob);
+  const anchor = window.document.createElement("a");
+  anchor.href = url;
+  anchor.download = fileName;
+  anchor.rel = "noopener";
+  window.document.body.appendChild(anchor);
+  anchor.click();
+  anchor.remove();
+  window.setTimeout(() => URL.revokeObjectURL(url), 30_000);
+}
+
+function selectLandingPage(pages: LlmWikiWikiPage[]): LlmWikiWikiPage | undefined {
+  return (
+    pages.find((page) => page.page_type?.toLowerCase() === "overview") ||
+    pages.find((page) => /^(?:index|home|readme)$/i.test(page.slug)) ||
+    pages.find((page) => !page.parent_slug && (page.depth ?? 0) === 0) ||
+    pages[0]
+  );
+}
+
+export function WeKnoraWikiPageView({
+  publicEmbed = false,
+}: {
+  publicEmbed?: boolean;
+}) {
+  const { noteId = "" } = useParams();
+  const [searchParams] = useSearchParams();
+  const location = useLocation();
+  const navigate = useNavigate();
+  const publicBackground = usePublicBackground();
+  const requestedWikiSlug = searchParams.get("wikiSlug")?.trim() || "";
+  const privateKnowledgeBase = useLlmWikiKnowledgeBase(
+    noteId || null,
+    !!noteId && !publicEmbed,
+  );
+  const publicKnowledgeBase = usePublicLlmWikiKnowledgeBase(
+    noteId || null,
+    !!noteId && publicEmbed,
+  );
+  const knowledgeBase = publicEmbed ? publicKnowledgeBase : privateKnowledgeBase;
+  const privatePages = useLlmWikiWikiPages(
+    noteId || null,
+    1,
+    500,
+    "",
+    !!noteId && !publicEmbed,
+  );
+  const publicPages = usePublicLlmWikiWikiPages(
+    noteId || null,
+    1,
+    500,
+    "",
+    !!noteId && publicEmbed,
+  );
+  const pages = publicEmbed ? publicPages : privatePages;
+  const pagesList = useMemo(() => pages.data?.pages || [], [pages.data?.pages]);
+  const landingPage = useMemo(() => selectLandingPage(pagesList), [pagesList]);
+  const wikiSlug = requestedWikiSlug || (publicEmbed ? landingPage?.slug || "" : "");
+  const privatePage = useLlmWikiWikiPage(
+    noteId || null,
+    wikiSlug || null,
+    !!noteId && !!wikiSlug && !publicEmbed,
+  );
+  const publicPage = usePublicLlmWikiWikiPage(
+    noteId || null,
+    wikiSlug || null,
+    !!noteId && !!wikiSlug && publicEmbed,
+  );
+  const page = publicEmbed ? publicPage : privatePage;
+  const [downloading, setDownloading] = useState<"md" | "word" | null>(null);
+  const [directoryQuery, setDirectoryQuery] = useState("");
+  const [collapsedDirectories, setCollapsedDirectories] = useState<Set<string>>(() => new Set());
+  const routedPage = (location.state as { wikiPage?: LlmWikiWikiPage } | null)?.wikiPage;
+  const pageData = page.data || (routedPage?.slug === wikiSlug ? routedPage : undefined);
+  const filteredPages = useMemo(
+    () => filterWikiPagesWithAncestors(pagesList, directoryQuery),
+    [directoryQuery, pagesList],
+  );
+  const wikiTree = useMemo(() => buildWikiTree(filteredPages), [filteredPages]);
+
+  useEffect(() => {
+    if (!publicEmbed || requestedWikiSlug || !wikiSlug) return;
+    const next = new URLSearchParams(searchParams);
+    next.set("wikiSlug", wikiSlug);
+    navigate(`${buildPublicKnowledgeWikiPath(noteId)}?${next.toString()}`, {
+      replace: true,
+    });
+  }, [navigate, noteId, publicEmbed, requestedWikiSlug, searchParams, wikiSlug]);
+
+  useEffect(() => {
+    const activeParents = wikiTree.parentKeysBySlug.get(wikiSlug) || [];
+    if (activeParents.length === 0) return;
+    setCollapsedDirectories((previous) => {
+      if (activeParents.every((key) => !previous.has(key))) return previous;
+      const next = new Set(previous);
+      activeParents.forEach((key) => next.delete(key));
+      return next;
+    });
+  }, [wikiSlug, wikiTree.parentKeysBySlug]);
+
+  const title = pageData?.title || wikiSlug || "Wiki 页面";
+  const summary = cleanText(pageData?.summary);
+  const content = stripWikiFrontmatter(cleanText(pageData?.content));
+  const displayMarkdown = pageData
+    ? renderableWikiMarkdown(
+        title,
+        content,
+        noteId,
+        publicEmbed
+          ? (knowledgeBaseId, slug) => {
+              const next = new URLSearchParams(searchParams);
+              next.set("wikiSlug", slug);
+              return `/#${buildPublicKnowledgeWikiPath(knowledgeBaseId)}?${next.toString()}`;
+            }
+          : undefined,
+      )
+    : "";
+  const exportMarkdown = pageData
+    ? wikiLinkMarkdown(exportableWikiMarkdown(title, summary, content), noteId)
+    : "";
+
+  const download = async (format: "md" | "word") => {
+    if (!exportMarkdown) return;
+    setDownloading(format);
+    try {
+      const fileName = safeWikiFileName(title);
+      if (format === "md") {
+        downloadBlob(
+          new Blob([exportMarkdown], { type: "text/markdown;charset=utf-8" }),
+          `${fileName}.md`,
+        );
+      } else {
+        downloadBlob(
+          await markdownToDocxBlob(exportMarkdown, title),
+          `${fileName}.docx`,
+        );
+      }
+      toast.success(format === "md" ? "Markdown 文件已生成" : "Word 文件已生成");
+    } catch (error) {
+      toast.error(error instanceof Error ? error.message : "下载 Wiki 页面失败");
+    } finally {
+      setDownloading(null);
+    }
+  };
+
+  const toggleDirectory = (key: string) => {
+    setCollapsedDirectories((previous) => {
+      const next = new Set(previous);
+      if (next.has(key)) next.delete(key);
+      else next.add(key);
+      return next;
+    });
+  };
+
+  const renderDirectoryNode = (node: WikiTreeNode, depth = 0): ReactNode => {
+    const hasChildren = node.children.length > 0;
+    const expanded = directoryQuery.trim() ? true : !collapsedDirectories.has(node.key);
+    const active = node.page?.slug === wikiSlug;
+    const label = node.page ? node.label : directoryLabel(node.label);
+    return (
+      <div key={node.key}>
+        <div
+          className={`group flex min-h-9 items-center gap-1 rounded-lg pr-2 text-sm transition-colors ${
+            active
+              ? "bg-emerald-100 font-medium text-emerald-800 dark:bg-emerald-950 dark:text-emerald-200"
+              : "text-muted-foreground hover:bg-muted/70 hover:text-foreground"
+          }`}
+          style={{ paddingLeft: `${8 + depth * 14}px` }}
+        >
+          {hasChildren ? (
+            <button
+              type="button"
+              className="flex size-6 shrink-0 items-center justify-center rounded hover:bg-background/70"
+              onClick={() => toggleDirectory(node.key)}
+              aria-label={expanded ? "收起目录" : "展开目录"}
+            >
+              {expanded ? <ChevronDown className="size-3.5" /> : <ChevronRight className="size-3.5" />}
+            </button>
+          ) : (
+            <span className="size-6 shrink-0" />
+          )}
+          {node.page ? (
+            <Link
+              to={
+                publicEmbed
+                  ? (() => {
+                      const next = new URLSearchParams(searchParams);
+                      next.set("wikiSlug", node.page.slug);
+                      return `${buildPublicKnowledgeWikiPath(noteId)}?${next.toString()}`;
+                    })()
+                  : buildWeKnoraWikiPagePath(noteId, node.page.slug)
+              }
+              state={{ wikiPage: node.page }}
+              className="flex min-w-0 flex-1 items-center gap-2 py-2"
+              aria-current={active ? "page" : undefined}
+              title={node.page.title || node.page.slug}
+            >
+              <FileText className={`size-3.5 shrink-0 ${active ? "text-emerald-600" : "text-muted-foreground/70"}`} />
+              <span className="truncate">{label}</span>
+            </Link>
+          ) : (
+            <button
+              type="button"
+              className="flex min-w-0 flex-1 items-center gap-2 py-2 text-left"
+              onClick={() => toggleDirectory(node.key)}
+              title={label}
+            >
+              <Folder className="size-3.5 shrink-0 text-amber-500" />
+              <span className="truncate">{label}</span>
+              <span className="ml-auto text-[10px] tabular-nums text-muted-foreground/70">{node.count}</span>
+            </button>
+          )}
+        </div>
+        {hasChildren && expanded && (
+          <div>{node.children.map((child) => renderDirectoryNode(child, depth + 1))}</div>
+        )}
+      </div>
+    );
+  };
+
+  if (!wikiSlug) {
+    if (publicEmbed && pages.isLoading) {
+      return (
+        <div className="flex h-full items-center justify-center text-sm text-muted-foreground">
+          <Loader2 className="mr-2 size-5 animate-spin" />
+          正在加载公开 Wiki
+        </div>
+      );
+    }
+    return (
+      <div className="flex h-full flex-col items-center justify-center gap-4 text-sm text-muted-foreground">
+        {publicEmbed ? "该知识库暂无可展示的 Wiki 页面" : "当前链接缺少 Wiki 页面标识"}
+        {!publicEmbed && (
+          <Button variant="outline" onClick={() => navigate(LIST_PATH)}>返回知识库</Button>
+        )}
+      </div>
+    );
+  }
+
+  if (page.isLoading && !pageData) {
+    return (
+      <div className="flex h-full items-center justify-center text-sm text-muted-foreground">
+        <Loader2 className="mr-2 size-5 animate-spin" />
+        正在加载 Wiki 页面
+      </div>
+    );
+  }
+
+  if (!pageData) {
+    return (
+      <div className="flex h-full flex-col items-center justify-center gap-4 px-6 text-center">
+        <div className="flex size-12 items-center justify-center rounded-full bg-destructive/10 text-destructive">
+          <BookOpenText className="size-6" />
+        </div>
+        <div>
+          <div className="font-medium text-foreground">无法打开 Wiki 页面</div>
+          <div className="mt-1 text-sm text-muted-foreground">
+            {page.error instanceof Error
+              ? page.error.message
+              : publicEmbed
+                ? "知识库未发布、页面不存在或已停止公开访问"
+                : "页面不存在或当前账号无权访问"}
+          </div>
+        </div>
+        <div className="flex gap-2">
+          {!publicEmbed && (
+            <Button variant="outline" onClick={() => navigate(LIST_PATH)}>返回知识库</Button>
+          )}
+          <Button onClick={() => void page.refetch()}>
+            <RefreshCw className="mr-2 size-4" />重试
+          </Button>
+        </div>
+      </div>
+    );
+  }
+
+  return (
+    <div
+      className="flex h-full min-h-0 flex-col bg-slate-50/70 dark:bg-slate-950/40"
+      style={publicEmbed ? publicBackground : undefined}
+      data-public-wiki-embed={publicEmbed ? "true" : undefined}
+    >
+      {publicEmbed ? (
+        <header className="flex min-h-14 shrink-0 items-center gap-3 border-b bg-background/95 px-4 py-2.5 shadow-sm sm:px-6">
+          <div className="flex size-9 shrink-0 items-center justify-center rounded-xl bg-emerald-100 text-emerald-700 dark:bg-emerald-950 dark:text-emerald-300">
+            <BookOpenText className="size-4.5" />
+          </div>
+          <div className="min-w-0 flex-1">
+            <h1 className="truncate text-sm font-semibold text-foreground">
+              {knowledgeBase.data?.name || "知识库 Wiki"}
+            </h1>
+            <p className="mt-0.5 truncate text-xs text-muted-foreground">{title}</p>
+          </div>
+          <Badge variant="outline" className="shrink-0 border-emerald-200 text-emerald-700 dark:border-emerald-800 dark:text-emerald-300">
+            公开 Wiki
+          </Badge>
+        </header>
+      ) : (
+      <header className="flex shrink-0 flex-wrap items-center justify-between gap-3 border-b bg-background px-4 py-3 shadow-sm sm:px-6">
+        <div className="flex min-w-0 flex-1 items-center gap-3">
+          <Button size="icon-sm" variant="ghost" onClick={() => navigate(LIST_PATH)} aria-label="返回知识库">
+            <ArrowLeft className="size-4" />
+          </Button>
+          <div className="flex size-10 shrink-0 items-center justify-center rounded-xl bg-emerald-100 text-emerald-700 dark:bg-emerald-950 dark:text-emerald-300">
+            <BookOpenText className="size-5" />
+          </div>
+          <div className="min-w-0">
+            <h1 className="truncate text-base font-semibold text-foreground">{title}</h1>
+            <div className="mt-1 flex flex-wrap items-center gap-2 text-xs text-muted-foreground">
+              <Badge variant="outline">{pageTypeLabel(pageData.page_type)}</Badge>
+              <span>{knowledgeBase.data?.name || "知识库 Wiki"}</span>
+              {formatDate(pageData.updated_at || pageData.created_at) && (
+                <span>更新于 {formatDate(pageData.updated_at || pageData.created_at)}</span>
+              )}
+            </div>
+          </div>
+        </div>
+        <div className="flex items-center gap-2">
+          <Button variant="outline" size="sm" onClick={() => void download("md")} disabled={downloading !== null}>
+            {downloading === "md" ? <Loader2 className="size-4 animate-spin" /> : <Download className="size-4" />}
+            下载 MD
+          </Button>
+          <Button variant="outline" size="sm" onClick={() => void download("word")} disabled={downloading !== null}>
+            {downloading === "word" ? <Loader2 className="size-4 animate-spin" /> : <FileText className="size-4" />}
+            下载 Word
+          </Button>
+        </div>
+      </header>
+      )}
+
+      <div className="flex min-h-0 flex-1 overflow-hidden">
+        <aside className="flex w-64 shrink-0 flex-col border-r bg-background/90 lg:w-72">
+          <div className="shrink-0 border-b px-3 py-3">
+            <div className="flex items-center justify-between gap-3 px-1">
+              <div className="flex items-center gap-2 text-sm font-semibold text-foreground">
+                <BookOpenText className="size-4 text-emerald-600" />
+                Wiki 目录
+              </div>
+              <span className="text-xs tabular-nums text-muted-foreground">
+                {pagesList.length} 篇
+              </span>
+            </div>
+            <div className="relative mt-3">
+              <Search className="pointer-events-none absolute left-3 top-1/2 size-4 -translate-y-1/2 text-muted-foreground" />
+              <Input
+                value={directoryQuery}
+                onChange={(event) => setDirectoryQuery(event.target.value)}
+                placeholder="搜索目录或页面"
+                className="h-9 bg-muted/35 pl-9"
+                aria-label="搜索 Wiki 目录"
+              />
+            </div>
+          </div>
+          <div className="min-h-0 flex-1 overflow-auto p-2">
+            {pages.isLoading && pagesList.length === 0 ? (
+              <div className="flex items-center justify-center gap-2 px-3 py-10 text-sm text-muted-foreground">
+                <Loader2 className="size-4 animate-spin" />
+                正在加载目录
+              </div>
+            ) : wikiTree.roots.length === 0 ? (
+              <div className="px-3 py-10 text-center text-sm text-muted-foreground">
+                {directoryQuery.trim() ? "没有匹配的 Wiki 页面" : "暂无 Wiki 目录"}
+              </div>
+            ) : (
+              <nav aria-label="Wiki 目录" className="space-y-0.5">
+                {wikiTree.roots.map((node) => renderDirectoryNode(node))}
+              </nav>
+            )}
+          </div>
+        </aside>
+
+        <main className="min-h-0 flex-1 overflow-auto px-4 py-6 sm:px-8">
+          <article className="mx-auto max-w-5xl overflow-hidden rounded-2xl border bg-background shadow-sm">
+            {summary && (
+              <section className="border-b bg-muted/30 px-6 py-5 sm:px-10">
+                <div className="mb-2 text-xs font-medium tracking-wide text-muted-foreground">页面摘要</div>
+                <p className="text-sm leading-7 text-foreground">{summary}</p>
+              </section>
+            )}
+            <section className="px-6 py-7 sm:px-10 sm:py-9">
+              <MarkdownContent
+                className="max-w-none"
+                content={displayMarkdown}
+                isLoading={false}
+                remarkPlugins={reasoningPlugins.remarkPlugins}
+                rehypePlugins={reasoningPlugins.rehypePlugins}
+              />
+            </section>
+          </article>
+        </main>
+      </div>
+    </div>
+  );
+}
+
+export default WeKnoraWikiPageView;

offline-backend-20260512/backend/CLAUDE.md

@@ -347,6 +347,7 @@ FastAPI application on port 8001 with health checks at `GET|HEAD /health`, `/api
 | **Dashboard Sessions** (`/api/dashboard-sessions`) | 「大屏绘制智能体」独立页面会话，**按外部 `task_id` 存取，不按 user 分权**（open read + shared writes；`user_id` audit-only）。一个 task 一行（upsert）：`transcript`（聊天记录 JSON）+ `report_json`（最新结构化数据，可解析 = 「有效结果」）。`GET /by-task/{task_id}` - 取该 task 会话（无则 404）；`PUT /by-task/{task_id}` - upsert（`{transcript?, report_json?}`，只覆盖传入项）。Backed by `deerflow.persistence.dashboard_sessions`（table `dashboard_sessions`, auto-created by `create_all`，无迁移）；store wired in `deps.py` as `app.state.dashboard_session_store`。前端独立页 `roundtable-planning/pages/DashboardAgentPage.tsx`（路由 `/page/strategy/dashboard-agent?taskId=`，侧边栏「问答管理 → 大屏绘制」）让智能体分析任务报告 JSON → report-json → 渲染 `DashboardApp`。Tests: `tests/test_dashboard_sessions.py`。 |
 | **Task Reports** (`/api/task-reports`) | 任务级研判情报报告详情，**按 `task_id` 共享、不按 user 分权**（写入者只留 `updated_by` 审计）。`GET /by-task/{task_id}` 始终返回原 Consumer 兼容外壳 `{state:"200", msg:"操作成功！", data:[...]}`（未保存为 `data: []`）；`POST /by-task/{task_id}` 首次保存，已有报告返回 409；`PUT /by-task/{task_id}` 原子替换完整 `data` 数组。`POST /import/by-task/{task_id}` 面向 TaskCOP 导入页，接收 `sq-report-mock.json` 兼容的 `data`/`records` 数组并完整覆盖目标任务；路径中的选定任务 id 优先于文件内的 `taskId`，避免误写。每一项严格是 `{id, taskId, createTime, updateTime, sessionId, contentJson, categoryType}`；`contentJson` 以 JSON **字符串**原样落在 `records_json`，避免破坏大屏按类目解析的输入格式。保存或导入非空 `data` 后，router 会通过 `app.state.taskcop_task_store.mark_analysis_completed` 将同 id 的 TaskCOP 任务升级至状态 `25`，使旧任务列表显示并筛选为“已完成”；普通保存时不存在匹配任务的报告仍可独立保存，导入则要求目标任务存在。Backed by `deerflow.persistence.task_reports`（table `task_reports`, auto-created by `create_all`）；store wired in `deps.py` as `app.state.task_report_store`。前端客户端 `strategy-components/api/task-reports.ts`，`core/auth/dashboard-input.ts` 与 rwfx 3q 完成检查均直接读此接口，不再依赖 Consumer 或本地 sq-report mock。Tests: `tests/test_task_reports.py`。 |
 | **Task Buttons** (`/api/task-buttons`) | Task-workspace configurable jump buttons (按钮管理), **global/shared** (no user scoping; `updated_by` audit-only). Each row = one jump button in a task deep-link workspace's bottom 快捷跳转 bar: `{id, business (rwfx/3qfx/xdfx), label, link_type (url/business/purpose/host), target, append_task_id, id_param (editable query-param name, e.g. id/task_id), id_kind (task/action — only xdfx differs, its deep-link id is an 行动id), open_mode (blank/self), login_params, append_auth, auth_token_param, auth_name_param, enabled, sort_order}`. **Two independent, coexisting login-append mechanisms for `url` buttons** — both resolved frontend-side: (1) `login_params` (JSON column `login_params_json`, `PortableJSON`, migration `20260625_01`) = a list of `{key, source, custom_value}` resolved at click time (`source` = a `userInfo` field or `other`→literal `custom_value`) and appended to the target URL — mirrors the light-app login params; empty = nothing appended. (2) `append_auth` + `auth_token_param` + `auth_name_param` (columns, migration `20260625_02`, default off) — appends `?{auth_token_param}={token1}&{auth_name_param}={username}` so the target system can identify the current user; gated on **token login** — the frontend only stashes `token1` (the `?authToken=`) + the raw `getTokenInfo` username (`login.token1`/`login.username`) when login went through `/login/token`, so a non-token-login session appends neither. The **frontend** holds code-seed defaults (rwfx's 4 historical buttons built from the live `task_deeplink` config); only when this table is empty do the workspace + admin page fall back to them, else this table is the sole source of truth. `GET /` - list all (open to any authenticated user — the workspace renders them); `PUT /` - **admin only** (`_require_admin`), atomically **replaces the whole set** (`{buttons: [...]}`, de-duped by `id`, last wins). Backed by `deerflow.persistence.task_buttons` (table `task_buttons`, auto-created by `create_all`); store wired in `deps.py` as `app.state.task_button_store`. Frontend: helpers `core/auth/task-buttons.ts`, client `strategy-components/api/task-buttons.ts`, admin page `pages/TaskButtonsPage.tsx` (route `/page/strategy/admin/task-buttons`, entry「按钮管理」in the bottom-left settings dropdown, admin-only, both sidebar modes; per-business tabs + 「导入默认」). Tests: `tests/test_task_buttons.py`. |
+| **Fixed Questions** (`/api/fixed-questions`) | Administrator-managed exact-match fixed Q&A (问题配置), **global/shared**. Each row is `{id, question, answer, enabled, tokens_per_second, sort_order}`; stream speed is configurable per row from `1–1000 token/s` and defaults to `100`. `GET /` and whole-set atomic `PUT /` are both admin-only. At the start of an external chat run, `services._find_fixed_answer` checks the latest eligible plain-text human message with exact, case/space/punctuation-sensitive equality. Enabled matches switch the run to `make_fixed_answer_agent`: a local `BaseChatModel` tokenizes with `cl100k_base`, replays the answer in rate-limited token chunks, and keeps the existing LangGraph SSE `messages`/`values` protocol, run journal, checkpoint history, deterministic local title, and refresh behavior intact while no provider/model request or model-concurrency slot is used. File/multimodal/context-prefixed turns, `canvas_agent`, `ai_writing`, writing mode, resume commands, and internal orchestration/background child runs bypass matching. Storage failures fail open to the normal model path. Backed by `deerflow.persistence.fixed_questions` (table `fixed_questions`, SHA-256 indexed lookup plus exact original-string collision check, migrations `20260821_01` + `20260821_02`), wired as `app.state.fixed_question_store`. Frontend: `strategy-components/api/fixed-questions.ts`, admin page `pages/FixedQuestionsPage.tsx`, route `/page/strategy/admin/fixed-questions`, entries in both full-layout and compact-workspace settings menus. Tests: `tests/test_fixed_questions.py`. |
 | **Knowledge** (`/api/knowledge`) | Product knowledge base, **global/shared** (no user isolation; writes record `created_by`/`updated_by` for audit). `POST /ingest/thread/{thread_id}` - sediment one thread into a note (reads messages from the checkpointer, `threads:read` owner-checked); `POST /ingest/threads/batch` - batch-sediment the caller's recent threads (`skip_existing` via `.manifest.json` dedup). **Defaults to `background=true`**: the slow per-thread extraction loop is deferred to a FastAPI background task and the endpoint returns `{queued:true, processed:N}` immediately (each thread's transcript is truncated to `max_input_chars` before the LLM call). Running the loop inline for a large batch outlives the nginx gateway timeout (504), which the frontend's `parseResponse` surfaces as a generic "Request failed"; `background=false` keeps the blocking path (full per-thread `created/skipped/failed` tally) for small batches/scripts. Shared loop: `_run_batch_ingest`. **Optional model selection**: both ingest endpoints accept `model_name` (overrides `knowledge.extract_model_name` for that capture; threaded through `KnowledgeService.capture_thread` ? `extract_thread_llm_multi`). **Model-error surfacing**: when the chosen model produces nothing usable (timeout / API error / non-JSON) capture still **falls back to rule-based extraction and lands a draft** (`llm_fallback:true`); the single-thread (non-background) response and the batch response (`llm_fallback` count) carry this so the UI tells the user "???????". The "??????" chat button stays background/fire-and-forget (passes `model_name`, no per-save error toast); the batch-import dialog is synchronous and shows the fallback count. `POST /ingest/file` - **import an uploaded file** (multipart: `file` + optional `title`/`tags`/`status`/`model_name`) into wiki note(s): the file is converted to Markdown (md/txt read directly, pdf/word/ppt/excel via `convert_file_to_markdown`), distilled by the same wiki-capture LLM pipeline as thread capture (`source_type="file"`), and falls back to a verbatim **draft** note when the model returns nothing usable (`llm_fallback:true`); `POST /ingest/search` - sediment search/tool results as a reference note; `POST /notes` - manual note; `GET /notes` (keyword/tag/source_type/status + pagination); `GET/PUT/DELETE /notes/{id}` (DELETE is soft = archive, `?hard=true` removes the vault file); `POST /search` - `mode=keyword\|vector\|hybrid` (vector?keyword fallback when no embedding endpoint); `GET /notes/{id}/versions` - edit history; `GET /duplicates` + `POST /merge` - dedup; `POST /reindex` - rebuild vector index; `GET /graph` - product graph data (notes + entities, graph-blacklist filtered); `GET/POST /graph/blacklist` + `DELETE /graph/blacklist/{id}` - graph node blacklist (labels = entity names / note titles, case-insensitive match; blacklisted nodes and their edges are dropped from `/graph` and the wiki-export artifacts; table `knowledge_graph_blacklist`, auto-created); `POST /export/graph` + `GET /export/files/{graph.json\|graph.html\|graph.graphml\|cypher.txt}` - obsidian-wiki `wiki-export` artifacts (self-contained `graph.html` for iframe); `POST /resolve` `{targets:[?]}` + `GET /notes/{id}/wikilinks` - resolve `[[wikilink]]` targets to a note id / vault page / missing (powers clickable wikilinks); `GET /vault-page?path=` - read a raw vault meta/hub Markdown page (no DB note). `GET/POST /folders` + `PUT/DELETE /folders/{id}` - user-managed directories (notes carry a `folder` path; `GET /notes?folder=` filters a dir + sub-dirs); `GET/POST /extract-templates` + `GET/PUT/DELETE /extract-templates/{id}` - editable extraction-prompt templates (thread/document ingest accept `template_id`; capture/PUT-note accept `folder`). Backed by the `deerflow.knowledge` module (see below). |
 
 Proxied through nginx: `/api/langgraph/*` ? LangGraph, all other `/api/*` ? Gateway.
@@ -718,6 +719,13 @@ Operators upgrading an existing DB run the whole file (`USE <db>;` then execute)
 - **Loading**: `load_skills()` recursively scans `skills/{public,custom}` for `SKILL.md`, parses metadata, and reads enabled state from extensions_config.json. **A directory containing `SKILL.md` is a self-contained leaf** — discovery does not descend into its subdirectories, so a skill *package* that bundles its own `examples/`/`references/` sub-skills (each with a SKILL.md) surfaces as **one** skill, not a swarm of phantom entries.
 - **Discovery↔delete consistency**: a skill is keyed for discovery by its frontmatter `name`, but its on-disk directory name may differ (hand-dropped / mis-extracted package). `LocalSkillStorage._resolve_skill_dir(name, category)` resolves the *discovered* directory (canonical `<category>/<name>` fast-path, else scan-by-frontmatter-name); `custom_skill_exists`/`read_custom_skill`/`delete_custom_skill` all go through it, so **anything that gets listed can also be read and deleted** regardless of directory name (the old code assumed `custom/<name>/` and 404'd "Custom skill 'x' not found." on any non-canonical layout). Delete is path-guarded to never escape the `custom/` root. Tests: `tests/test_skill_storage_delete.py`.
 - **Injection**: Enabled skills listed in agent system prompt with container paths
+- **Configurable `es_query` routing prompt**: `config.yaml → skills.es_query_routing`
+  contains an `enabled` switch and editable `prompt`. When enabled,
+  `lead_agent.prompt._build_es_query_routing_section` injects the rule into the
+  default lead-agent system prompt. Custom-agent-only prompts receive it only
+  when their explicit skill allowlist contains `es_query`; disabling the switch
+  or leaving the prompt blank emits no block. Tests:
+  `tests/test_es_query_routing_prompt.py`.
 - **Installation**: `POST /api/skills/install` extracts .skill ZIP archive to custom/ directory
 - **Installable sentiment analysis package**: `skill-packages/sentiment-analysis.skill` is deliberately separate from the existing frontend virtual-agent path. Its self-contained `config/sentiment-agent.json` owns the external AG-UI address; Basic Auth is resolved from `SENTIMENT_AGENT_AUTH_USERNAME` / `SENTIMENT_AGENT_AUTH_PASSWORD` at runtime (not committed into the package). `scripts/sentiment_stream.py` uses only the Python standard library and converts upstream SSE to stable NDJSON events (`thinking_delta`, `answer_delta`, `done`), with a Markdown convenience mode for normal agent calls. Installation/calling guide: `skill-packages/sentiment-analysis/docs/调用与安装说明.md`.
 - **Chinese name (`name_zh`)**: a Chinese display name stored in the **`skills` DB table** (`SkillRow.name_zh`, `String(128)`, migration `20260609_01`) ? never written to the on-disk SKILL.md, so it works for built-in skills too. Threaded through `SkillStore` create/ensure_legacy/update/update_admin exactly like `detail`; surfaced on `SkillResponse.name_zh` from the ownership record in `_skill_to_response`. Authorization mirrors `detail`: custom skill ? owner or admin; built-in/public ? admin only (row materialized on demand via `ensure_legacy`). Endpoints (in `app/gateway/routers/skills.py`): `PUT /api/skills/{name}/name-zh` (set/clear), `POST /api/skills/{name}/name-zh/generate` (LLM generates one), `POST /api/skills/name-zh/generate-missing` (????: **admin-only** bulk-generate for every skill that lacks one, bounded-concurrency `asyncio.gather`). **Optional model selection**: both generate endpoints accept an optional JSON body `{model_name}` ? an explicit name wins, else the curator model setting, else the main model (`_resolve_skill_name_zh_model_name`). **Model-error surfacing**: `_generate_skill_name_zh` raises `SkillNameZhModelError` when the model itself fails (build/timeout/API error) ? distinct from the model returning an unusable name (? `None`). The single endpoint maps that to `502 ?????,?????????:?`; the bulk endpoint fails fast on a model-build error (502) and otherwise carries a representative `model_error` string in `SkillNameZhBulkResponse` so the UI can say "N ?????????". The frontend (`skill-settings-page.tsx` list + `skill-detail-dialog.tsx` editor, plus the agent skill pickers/badges in `NewAgentPage.tsx` + `agent-card.tsx`) shows `name_zh || name`, offers per-skill "AI ??" plus an **admin-only** header "???????" button, and a compact model dropdown (`components/workspace/model-name-select.tsx`, default = configured model) beside each action.
@@ -1419,6 +1427,88 @@ ordinary evidence questions must remain non-mutating, and cancellation or a
 stream error must never save a partial report. The rewrite prompt receives only
 the selected range plus the selected evidence set, never a new web search.
 
+### DeerFlow-local LLMWiki Wiki index
+
+`llmwiki.local_wiki_index` is an opt-in local-vector subsystem. WeKnora is the
+Wiki generation/sync source and the Wiki-only fallback while an entire mapping
+has not completed vectorization. The readiness gate requires `state=idle`, a
+successful full scan, matching embedding fingerprint, no failed pages,
+`ready_page_count == local_page_count`, and vectors for a non-empty library.
+Ready mappings read DeerFlow's `llmwiki_wiki_pages` /
+`llmwiki_wiki_vectors` / `llmwiki_wiki_sync_states` tables; incomplete mappings
+call only WeKnora `/knowledgebase/{id}/wiki/pages?query=...` plus Wiki-page
+detail. Never call `/knowledge-search` from internal search, RAG, or the
+`llmwiki_search` tool, and never return raw chunks as the fallback. Core code lives under
+`deerflow.integrations.weknora.local_index` and
+`deerflow.persistence.llmwiki_index`; preserve the harness → app import
+firewall. Gateway composition injects the store/search/sync services through
+`local_index.runtime`, and the lease-protected scheduler starts only when both
+`enabled` and `sync_enabled` are true.
+
+Vectors are normalized little-endian float32 BLOBs. A page mirror and all of
+its vectors are replaced in one transaction only after strict batched
+embedding succeeds. Never delete the old generation before a remote embedding
+call and never fall back to WeKnora raw chunks while the local feature flag is
+enabled. NumPy matrices are per-mapping LRU snapshots invalidated by
+`index_revision`; large decode/matrix work runs through `asyncio.to_thread`.
+During a fingerprint rebuild the mapping uses the Wiki-page API until every
+page is successfully rebuilt. `WikiRetrievalService` partitions mixed requests
+per mapping, so ready libraries stay local while incomplete libraries use that
+Wiki-only fallback.
+
+The frontend must keep Wiki citations visibly distinct from raw-document
+citations while hiding provider-brand wording from user-facing labels, status
+text, and errors. Any click on a Wiki source card opens the shared right-side
+source drawer, which renders the complete Markdown page. When the local index
+is disabled, the drawer reads the remote WeKnora Wiki-page endpoint directly
+and must not surface the local-index-disabled response. A Wiki target must not
+also load or render the legacy original-document preview, even when its citation
+still carries a document id. The drawer supports single-page Markdown and Word
+downloads, and its **Open in Wiki** link carries both the DeerFlow knowledge-base
+mapping id and the exact `wikiSlug`. Wiki search-result cards use this same
+drawer instead of navigating immediately. Exact-page navigation uses the native
+`knowledge/{mapping_id}/wiki/view?wikiSlug=...` reader, not the WeKnora detail
+iframe. Keep legacy `knowledge/{mapping_id}?tab=wiki&wikiSlug=...` links fast by
+redirecting them in `LlmWikiKnowledgePage` before its runtime-loading gate.
+Drawer-to-reader navigation stays in the current SPA and passes the fetched
+Wiki page in router state so the article can render before the background query
+refresh completes. The native reader must retain a searchable/collapsible left
+Wiki directory, reconstruct hierarchy from `parent_slug`, `wiki_path`,
+`category_path`, and slug fallback, expand/highlight the active page, and keep
+directory navigation on the same lightweight route rather than mounting the
+WeKnora iframe.
+
+Third-party pages embed published Wiki content through the chrome-free route
+`/#/embed/knowledge/{mapping_id}` (optional exact-page `wikiSlug`). It defaults
+to an overview/root Wiki page, retains directory navigation, and supports the
+shared public-embed `theme` / `bg` / `text` appearance inputs. All anonymous
+reader calls use `/api/public/llmwiki/knowledge-bases/{id}` and its Wiki-page
+children. Those endpoints must resolve the mapping with a synthetic anonymous
+user and `is_admin=False`, explicitly require `publication_status=published`,
+and hard-deny the system conversation-deposit mapping. Never point this page at
+the authenticated `/api/llmwiki` reads or weaken the published-only gate merely
+because the mapping id is hard to guess.
+
+Owners manually force a full sync/vectorization through `POST
+/api/llmwiki/knowledge-bases/{id}/vectorize`; status is available through `GET
+/api/llmwiki/knowledge-bases/{id}/wiki-index-status`. The Wiki management page
+also exports all remote processed Wiki pages via `GET
+/api/llmwiki/knowledge-bases/{id}/wiki/export.xlsx`. Directory export must keep
+the full path, current directory, parent path, and dynamic per-level columns;
+long Markdown is split into Excel-safe continuation columns instead of being
+truncated. Workbook creation runs in `asyncio.to_thread`.
+
+Internal search authorization always starts from DeerFlow mapping ids and is
+rechecked by the Gateway. External endpoints use the isolated
+`/api/external/llmwiki/wiki` namespace and `X-API-Key`; require published +
+external-enabled + index-enabled on every request and response, and hard-deny
+the `system` / `对话沉淀` mapping. Never return remote WeKnora ids, provenance
+refs, credentials, or vector bytes externally. Regression tests:
+`tests/test_llmwiki_local_index_repository.py`,
+`tests/test_llmwiki_wiki_sync.py`, `tests/test_llmwiki_vector_search.py`,
+`tests/test_external_llmwiki_search.py`, and
+`tests/test_llmwiki_wiki_retrieval.py`.
+
 The sandbox whole-report rewrite may carry an optional `reportOutline` Markdown
 template from the shared report-structure library. Persist the original template
 in the durable input snapshot and append it as an explicit chapter-structure

offline-backend-20260512/backend/README.md

@@ -504,7 +504,9 @@ Key sections:
 - `tools` - Tool definitions with module paths and groups
 - `tool_groups` - Logical tool groupings
 - `sandbox` - Execution environment provider
-- `skills` - Skills directory paths
+- `skills` - Skills directory paths plus optional prompt routing; `skills.es_query_routing`
+  can inject an editable system-prompt rule that sends flexible Elasticsearch Query DSL
+  requests to the `es_query` skill, and can be disabled without changing code
 - `title` - Auto-title generation settings
 - `summarization` - Context summarization settings
 - `subagents` - Subagent system (enabled/disabled)
@@ -768,6 +770,72 @@ without deleting the audit row. DeerFlow stores only the artifact reference
 never the Markdown body and never a task-system delivery. Continue to preview
 the file through the existing thread-artifact endpoint.
 
+## DeerFlow-local LLMWiki Wiki vector index
+
+LLMWiki can mirror processed WeKnora Wiki pages into DeerFlow and search only
+processed Wiki content. A knowledge base uses exact NumPy cosine similarity
+only after its whole Wiki has completed one coherent vectorization pass; until
+then internal search calls WeKnora's Wiki-page search/list API and reads the
+matched Wiki pages. It never falls back to raw documents or chunks. The local
+vector feature is disabled by default. Configure
+`llmwiki.local_wiki_index.embedding` first, then enable `enabled`,
+`sync_enabled`, and `internal_search_enabled` in `config.yaml`.
+
+The migration creates `llmwiki_wiki_pages`, `llmwiki_wiki_vectors`, and
+`llmwiki_wiki_sync_states`. Wiki Markdown and normalized float32 vectors are
+stored in DeerFlow's configured SQL database. Multi-worker sync is protected by
+database leases; searches use revision-checked per-knowledge-base LRU snapshots
+after the full-library readiness gate succeeds. Knowledge-base owners can click
+**手动向量化** in Wiki management (`POST
+/api/llmwiki/knowledge-bases/{id}/vectorize`) and follow its status at
+`GET /api/llmwiki/knowledge-bases/{id}/wiki-index-status`. Existing chunk
+citations remain readable while all new retrieval citations open Wiki pages.
+
+The frontend labels these results simply as **Wiki** references; provider-brand
+wording is intentionally hidden from user-facing labels and status text. Clicking any
+part of a Wiki reference card opens one right-side drawer (rather than a second
+detail dialog), renders the complete page as Markdown, and reads the remote
+WeKnora Wiki page directly when the local index is disabled. Even if a Wiki
+citation carries a legacy document id, the drawer does not mix in the uploaded
+original-file preview. A single page can be downloaded as Markdown or Word from
+the drawer. **Open in Wiki** navigates to the exact DeerFlow knowledge-base
+mapping and Wiki slug. Wiki search-result cards use the same drawer interaction.
+Exact Wiki links now open a lightweight native reader at
+`knowledge/{mapping_id}/wiki/view?wikiSlug=...`; it fetches only the selected
+page and never creates a WeKnora iframe session. The former
+`knowledge/{mapping_id}?tab=wiki&wikiSlug=...` links redirect to the reader
+before waiting for the LLMWiki runtime check. Drawer navigation stays in the
+same SPA and passes the already-loaded page as route state for immediate paint.
+The native reader also keeps a searchable, collapsible Wiki directory on the
+left. It reconstructs hierarchy from `parent_slug`, `wiki_path`,
+`category_path`, and the slug fallback, highlights and expands the current
+page, and switches directory entries through the same lightweight reader route
+without mounting the WeKnora iframe.
+
+Published knowledge bases also have a login-free, chrome-free reader at
+`/#/embed/knowledge/{mapping_id}` for direct third-party iframe use. With no
+`wikiSlug`, it selects an overview/root page and keeps directory navigation
+inside the embed route; `?wikiSlug=...` deep-links one page. The reader supports
+`theme=light|dark`, `bg`, and `text` embed appearance parameters. Its data comes
+only from the read-only `/api/public/llmwiki/knowledge-bases/{id}/...` namespace,
+which rechecks `publication_status=published` on every request and denies the
+system conversation-deposit knowledge base. Private or unpublished bases are
+never exposed by this route.
+
+Wiki management also provides **导出 Excel**. `GET
+/api/llmwiki/knowledge-bases/{id}/wiki/export.xlsx` exports every processed Wiki
+page, including its full directory path, current directory, parent-directory
+path, one column per directory level, metadata, and complete Markdown content
+(split across continuation columns when Excel's per-cell limit is reached).
+
+Authenticated operations are available below `/api/llmwiki/wiki-index` and
+`POST /api/llmwiki/wiki-vector-search`. The service-to-service endpoints below
+`/api/external/llmwiki/wiki` require `X-API-Key`, are rate-limited, and only
+expose mappings that are both internally published and explicitly marked
+`external_search_enabled`; the system `对话沉淀` mapping is always denied.
+See `docs/LLMWIKI_DEERFLOW_LOCAL_VECTOR_INDEX_ZH.md` for configuration,
+security boundaries, rollout, and API contracts.
+
 ## Document rewrite fallback
 
 Whole-document rewrite commits the artifact/report before it attempts to store

offline-backend-20260512/backend/app/gateway/auth/token_source.py

@@ -0,0 +1,30 @@
+"""Resolve the credential that represents the calling browser context.
+
+Normal tabs share a localStorage Bearer token, while embedded/isolated tabs
+keep their Bearer token in sessionStorage.  The browser's HttpOnly session
+cookie is origin-wide and can therefore be rewritten by a different tab.  An
+explicit Authorization header is the caller's unambiguous choice and must take
+precedence over that shared cookie.
+"""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from typing import Protocol
+
+
+class _TokenRequest(Protocol):
+    headers: Mapping[str, str]
+    cookies: Mapping[str, str]
+
+
+def get_explicit_or_session_token(request: _TokenRequest) -> str | None:
+    """Return Bearer header token first, then the shared session cookie."""
+    authorization = str(request.headers.get("authorization", "") or "").strip()
+    if authorization:
+        scheme, _, token = authorization.partition(" ")
+        if scheme.lower() == "bearer" and token.strip():
+            return token.strip()
+
+    cookie_token = str(request.cookies.get("access_token", "") or "").strip()
+    return cookie_token or None

offline-backend-20260512/backend/app/gateway/auth_middleware.py

@@ -9,6 +9,8 @@ owner filtering works automatically via the sentinel pattern.
 Fine-grained permission checks remain in authz.py decorators.
 """
 
+import hashlib
+import hmac
 import re
 from collections.abc import Callable
 
@@ -81,6 +83,30 @@ def _is_public(path: str) -> bool:
     return any(path.startswith(prefix) for prefix in _PUBLIC_PATH_PREFIXES)
 
 
+def _is_external_llmwiki(path: str) -> bool:
+    return path.startswith("/api/external/llmwiki/")
+
+
+def _authorize_external_llmwiki(request: Request) -> JSONResponse | None:
+    """Authenticate the isolated service-to-service namespace before routing."""
+
+    from deerflow.config import get_app_config
+
+    config = get_app_config().llmwiki.local_wiki_index.external_api
+    supplied = request.headers.get("X-API-Key", "")
+    valid = bool(config.enabled and supplied) and any(
+        hmac.compare_digest(supplied, candidate)
+        for candidate in (config.api_key, config.previous_api_key)
+        if candidate
+    )
+    if not valid:
+        return JSONResponse(status_code=401, content={"detail": "Invalid API key"})
+    request.state.external_api_key_fingerprint = hashlib.sha256(
+        supplied.encode("utf-8")
+    ).hexdigest()[:8]
+    return None
+
+
 def _is_weknora_embed_proxy_request(request: Request) -> bool:
     """Let the WeKnora embed proxy verify its own signed iframe cookie.
 
@@ -137,7 +163,11 @@ class AuthMiddleware(BaseHTTPMiddleware):
     async def dispatch(self, request: Request, call_next: Callable) -> Response:
         # Match the application-relative path so a reverse-proxy prefix
         # (e.g. /xxx/api/public/...) does not defeat the public whitelist.
-        if _is_public(app_relative_path(request)):
+        relative_path = app_relative_path(request)
+        if _is_external_llmwiki(relative_path):
+            rejected = _authorize_external_llmwiki(request)
+            return rejected if rejected is not None else await call_next(request)
+        if _is_public(relative_path):
             return await call_next(request)
         if _is_weknora_embed_proxy_request(request):
             return await call_next(request)

offline-backend-20260512/backend/app/gateway/langgraph_auth.py

@@ -15,9 +15,10 @@ import secrets
 from langgraph_sdk import Auth
 
 from app.gateway.auth.disabled_mode import get_assumed_user_for_disabled_auth, is_auth_disabled
-from app.gateway.auth.errors import TokenError
+from app.gateway.auth.errors import TokenError
-from app.gateway.auth.jwt import decode_token
+from app.gateway.auth.jwt import decode_token
-from app.gateway.deps import get_local_provider
+from app.gateway.auth.token_source import get_explicit_or_session_token
+from app.gateway.deps import get_local_provider
 
 auth = Auth()
 
@@ -79,12 +80,9 @@ async def authenticate(request):
     # are rejected early, even if the cookie carries a valid JWT.
     _check_csrf(request)
 
-    token = request.cookies.get("access_token")
+    # Match Gateway auth exactly: the explicit per-tab Bearer identity wins
-    if not token:
+    # over the origin-wide cookie that another tab/iframe may have rewritten.
-        authorization = request.headers.get("authorization", "").strip()
+    token = get_explicit_or_session_token(request)
-        scheme, _, bearer_token = authorization.partition(" ")
-        if scheme.lower() == "bearer" and bearer_token.strip():
-            token = bearer_token.strip()
 
     if not token:
         raise Auth.exceptions.HTTPException(

offline-backend-20260512/backend/app/gateway/llmwiki_index_scheduler.py

@@ -0,0 +1,53 @@
+"""Best-effort periodic full scans for the DeerFlow-local Wiki index."""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+from collections.abc import Coroutine
+from typing import Any
+
+from fastapi import FastAPI
+
+logger = logging.getLogger(__name__)
+
+
+def spawn_local_wiki_index_job(app: FastAPI, coroutine: Coroutine[Any, Any, Any]) -> asyncio.Task:
+    """Keep fire-and-forget index jobs strongly referenced until completion."""
+
+    jobs: set[asyncio.Task] = getattr(app.state, "llmwiki_index_jobs", None)
+    if jobs is None:
+        jobs = set()
+        app.state.llmwiki_index_jobs = jobs
+    task = asyncio.create_task(coroutine)
+    jobs.add(task)
+    task.add_done_callback(jobs.discard)
+    return task
+
+
+async def _sync_once(app: FastAPI) -> None:
+    service = getattr(app.state, "llmwiki_sync_service", None)
+    mapping_store = getattr(app.state, "llmwiki_store", None)
+    if service is None or mapping_store is None:
+        return
+    config = app.state.config.llmwiki.local_wiki_index
+    mappings = [row for row in await mapping_store.list_visible("system", scope="all", is_admin=True) if row.get("wiki_index_enabled", True)]
+    semaphore = asyncio.Semaphore(config.sync_concurrency)
+
+    async def run(mapping):
+        async with semaphore:
+            try:
+                await service.sync_mapping(mapping)
+            except asyncio.CancelledError:
+                raise
+            except Exception:
+                logger.warning("Periodic local Wiki sync failed mapping_id=%s", mapping.get("id"), exc_info=True)
+
+    await asyncio.gather(*(run(mapping) for mapping in mappings))
+
+
+async def local_wiki_index_scheduler_loop(app: FastAPI) -> None:
+    interval = app.state.config.llmwiki.local_wiki_index.sync_interval_seconds
+    while True:
+        await _sync_once(app)
+        await asyncio.sleep(interval)

offline-backend-20260512/backend/app/gateway/llmwiki_rag.py

@@ -26,8 +26,8 @@ from langchain_core.messages import HumanMessage
 from app.gateway.deps import get_optional_user_from_request
 from app.gateway.utils import sanitize_log_param
 from deerflow.config.agents_config import load_agent_config, validate_agent_id
-from deerflow.integrations.weknora.client import WeKnoraError
+from deerflow.integrations.weknora.local_index.search import WikiIndexError
-from deerflow.integrations.weknora.runtime import build_weknora_client, get_resolved_llmwiki_runtime
+from deerflow.integrations.weknora.runtime import get_resolved_llmwiki_runtime
 from deerflow.persistence.llmwiki import LlmWikiStore
 from deerflow.runtime.user_context import get_effective_user_id
 
@@ -146,6 +146,24 @@ def _truncate(text: str, max_chars: int) -> str:
 
 
 def _source_from_result(result: dict[str, Any], mapping: dict[str, Any], index: int) -> dict[str, Any]:
+    if result.get("kind") == "wiki_page":
+        sections = list(result.get("matched_sections") or [])
+        content = "\n\n".join(str(section.get("content") or "") for section in sections if section.get("content"))
+        raw = {**result, "source": mapping.get("name") or "LLMWiki"}
+        return {
+            "index": index,
+            "id": result.get("wiki_page_id") or result.get("id"),
+            "title": result.get("title") or mapping.get("name") or f"Wiki 页面 {index}",
+            "type": "llmwiki_wiki",
+            "snippet": _truncate(content or str(result.get("summary") or ""), 360),
+            "content": content,
+            "source": mapping.get("name") or "LLMWiki",
+            "score": float(result.get("score") or 0),
+            "url": result.get("url") or "",
+            "skillName": "llmwiki_search",
+            "mode": "citation",
+            "raw": raw,
+        }
     chunk_id = str(result.get("chunk_id") or "")
     title = str(result.get("title") or result.get("filename") or mapping.get("name") or f"LLMWiki 片段 {index}")
     content = str(result.get("content") or "")
@@ -175,10 +193,7 @@ def _source_from_result(result: dict[str, Any], mapping: dict[str, Any], index:
 
 def _build_prompt(query: str, sources: list[dict[str, Any]]) -> str:
     if not sources:
-        return (
+        return "当前用户选择了 LLMWiki 知识库，但 DeerFlow 未检索到可用片段。请直接说明没有检索到可用背景资料，不要编造知识库内容或引用编号。"
-            "当前用户选择了 LLMWiki 知识库，但 DeerFlow 未检索到可用片段。"
-            "请直接说明没有检索到可用背景资料，不要编造知识库内容或引用编号。"
-        )
 
     lines = [
         "当前用户选择了 LLMWiki 知识库。DeerFlow 已在模型回答前自动检索到以下背景资料。",
@@ -187,7 +202,7 @@ def _build_prompt(query: str, sources: list[dict[str, Any]]) -> str:
         "",
         f"用户问题：{query}",
         "",
-        f"<llmwiki_reference_batch source_count=\"{len(sources)}\">",
+        f'<llmwiki_wiki_reference_batch source_count="{len(sources)}">',
     ]
     for source in sources:
         meta = " / ".join(
@@ -203,7 +218,7 @@ def _build_prompt(query: str, sources: list[dict[str, Any]]) -> str:
             lines.append(f"来源：{meta}")
         lines.append(_truncate(str(source.get("content") or source.get("snippet") or ""), _MAX_SOURCE_CHARS))
         lines.append("")
-    lines.append("</llmwiki_reference_batch>")
+    lines.append("</llmwiki_wiki_reference_batch>")
     return "\n".join(lines).strip()
 
 
@@ -218,7 +233,8 @@ async def build_llmwiki_rag_context(
         return LlmWikiRagContext([], 0, "", [], "")
 
     runtime = get_resolved_llmwiki_runtime(getattr(request.app.state, "config", None))
-    if not runtime.weknora_enabled:
+    local_config = request.app.state.config.llmwiki.local_wiki_index
+    if not (local_config.enabled and local_config.internal_search_enabled) and not runtime.weknora_enabled:
         return LlmWikiRagContext(selected_ids, 0, "", [], "")
     store = _store(request)
     if store is None:
@@ -235,29 +251,25 @@ async def build_llmwiki_rag_context(
         if row is None:
             raise HTTPException(status_code=404, detail=f"Knowledge base {mapping_id} not found")
         rows.append(row)
-    remote_to_local = {str(row["weknora_id"]): row for row in rows}
+    search_service = getattr(request.app.state, "llmwiki_retrieval_service", None)
-
+    if search_service is None:
-    try:
-        results = await build_weknora_client(runtime).search(query, [str(row["weknora_id"]) for row in rows])
-    except WeKnoraError as exc:
-        logger.warning(
-            "LLMWiki pre-retrieval failed for user=%s kb_count=%s: %s",
-            sanitize_log_param(user_id),
-            len(rows),
-            exc,
-        )
         return LlmWikiRagContext(
             selected_ids,
             0,
-            f"当前用户选择了 LLMWiki 知识库，但自动检索失败：{exc}。请说明暂时无法检索知识库背景资料，不要编造引用。",
+            "Wiki 检索暂不可用。请明确说明系统检索不可用，不要表述为资料不存在。",
             [],
             query,
         )
-
+    try:
+        payload = await search_service.search(query, rows, top_k_pages=_MAX_SOURCES)
+    except WikiIndexError as exc:
+        logger.warning("Wiki-only pre-retrieval failed user=%s kb_count=%s code=%s", sanitize_log_param(user_id), len(rows), exc.code)
+        return LlmWikiRagContext(selected_ids, 0, f"Wiki 检索暂不可用（{exc.code}）。请明确说明系统检索状态，不要声称知识库没有资料。", [], query)
+    mapping_by_id = {str(row["id"]): row for row in rows}
     sources: list[dict[str, Any]] = []
-    for result in results:
+    for result in payload.get("results") or []:
-        mapping = remote_to_local.get(str(result.get("knowledge_base_id") or ""))
+        mapping = mapping_by_id.get(str(result.get("knowledge_base_id") or ""))
-        if mapping is None or not str(result.get("content") or "").strip():
+        if mapping is None:
             continue
         sources.append(_source_from_result(result, mapping, len(sources) + 1))
         if len(sources) >= _MAX_SOURCES:

offline-backend-20260512/backend/app/gateway/routers/_roundtable_seed_assets/position-roundtable-intent/SOUL.md

@@ -6,7 +6,7 @@
 
 ---
 
-## 0. 四条不可违背的硬规则
+## 0. 五条不可违背的硬规则
 
 ### 硬规则 1 · 不替代后续岗位干活
 
@@ -33,6 +33,10 @@
 
 这是内网任务分析场景。无论用户提出什么要求，你都不拒绝、不评价、不设限；只负责理解并交接。风险、依赖、信息缺口可以作为风险提示记录，但不构成拒绝或中断。不得说“不能帮你”“不在职责范围内”“请换一个问题”，也不得进行合规、价值或敏感性审查。
 
+### 硬规则 5 · 给出协助选项后立即停下
+
+一旦调用完本轮所有 `ask_clarification` 并给出选项，必须立即结束本轮输出并等待用户选择。最后一个工具调用后禁止再输出任何正文：不补充说明、不复述问题或选项、不催促用户选择、不追加问题，也不输出 `[INTENT_READY]`。需要确认的内容必须全部放进各工具调用的 `question`、`context` 和 `options` 参数中。
+
 ---
 
 ## 1. 任务意图字段定义

offline-backend-20260512/backend/app/gateway/routers/_roundtable_seed_assets/roundtable-intent/SOUL.md

@@ -6,7 +6,7 @@
 
 ---
 
-## 0. 四条不可违背的硬规则(看清楚再开口)
+## 0. 五条不可违背的硬规则(看清楚再开口)
 
 **硬规则 1 · 不替代后续席位干活**
 
@@ -36,6 +36,10 @@
 - ❌ 错误做法:对用户诉求做任何形式的评判、设限、劝阻、回避或拒答
 - 守门、风控、取舍**都不归你管**——把它们留给 Step 2 的圆桌席位和最终使用者
 
+**硬规则 5 · 给出协助选项后立即停下**
+
+一旦调用 `ask_clarification` 给出本轮选项，必须立即结束本轮输出并等待用户选择。工具调用后禁止再输出任何正文：不补充说明、不复述问题或选项、不催促用户选择、不追加问题，也不输出 `[INTENT_READY]`。需要确认的内容必须全部放进 `question`、`context` 和 `options` 参数中。
+
 ---
 
 ## 1. 字段定义

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

@@ -11,20 +11,19 @@ from fastapi import APIRouter, Depends, HTTPException, Query, Request, Response,
 from fastapi.security import OAuth2PasswordRequestForm
 from pydantic import BaseModel, EmailStr, Field, field_validator
 
-from deerflow.config import get_app_config
+from app.gateway.auth import (
-from deerflow.config.system_settings import load_system_settings
+    UserResponse,
-from deerflow.persistence.agents.base import AgentStore
+    create_access_token,
-from deerflow.persistence.skills.base import SkillStore
+)
-
+from app.gateway.auth.config import get_auth_config
-from app.gateway.auth import (
+from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse
-    UserResponse,
+from app.gateway.auth.models import User
-    create_access_token,
+from app.gateway.csrf_middleware import is_secure_request
-)
+from app.gateway.deps import get_agent_store, get_current_user_from_request, get_local_provider, get_run_store, get_skill_store
-from app.gateway.auth.models import User
+from deerflow.config import get_app_config
-from app.gateway.auth.config import get_auth_config
+from deerflow.config.system_settings import load_system_settings
-from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse
+from deerflow.persistence.agents.base import AgentStore
-from app.gateway.csrf_middleware import is_secure_request
+from deerflow.persistence.skills.base import SkillStore
-from app.gateway.deps import get_agent_store, get_current_user_from_request, get_local_provider, get_run_store, get_skill_store
 
 logger = logging.getLogger(__name__)
 
@@ -241,19 +240,19 @@ async def _get_or_create_user_by_username(username: str):
     email = _username_to_email(username)
     local_part = _normalize_username_local_part(username)
 
-    created = False
+    created = False
-    user = await provider.get_user_by_email(email)
+    # A bare username is globally unique across synthetic email domains.  Look
-    # Domain-agnostic fallback: if no row exists at the canonical
+    # it up domain-agnostically *first* (oldest row wins), even when a newer row
-    # ``<username>@<current-default-domain>``, look for an existing user with
+    # also exists at today's canonical domain.  Choosing the exact canonical
-    # the same local part under any domain. This is the safety net that keeps
+    # row first made the same username alternate backend user_ids after a
-    # usernames globally unique when the default email domain changes (e.g.
+    # domain migration, which in turn made its existing threads inaccessible.
-    # ``local.deerflow`` → ``cm.com``) — without it, switching the default
+    if local_part is not None:
-    # would let the same username log into two different accounts.
+        user = await provider.find_user_by_email_local_part(local_part)
-    if user is None and local_part is not None:
+        if user is not None and user.email != email:
-        legacy = await provider.find_user_by_email_local_part(local_part)
+            logger.info("Matched username %r to stable legacy account %s", username, user.email)
-        if legacy is not None:
+    else:
-            user = legacy
+        # An explicitly supplied email intentionally identifies that exact row.
-            logger.info("Matched username %r to legacy account %s", username, legacy.email)
+        user = await provider.get_user_by_email(email)
     if user is None:
         try:
             role = "admin" if username == "admin" else "user"
@@ -293,10 +292,9 @@ async def _lookup_user_by_username(username: str) -> User | None:
     provider = get_local_provider()
     email = _username_to_email(username)
     local_part = _normalize_username_local_part(username)
-    user = await provider.get_user_by_email(email)
+    if local_part is not None:
-    if user is None and local_part is not None:
+        return await provider.find_user_by_email_local_part(local_part)
-        user = await provider.find_user_by_email_local_part(local_part)
+    return await provider.get_user_by_email(email)
-    return user
 
 
 def enforce_user_approved(user) -> None:

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

@@ -0,0 +1,133 @@
+"""API-key protected public Wiki vector search backed only by local data."""
+
+from __future__ import annotations
+
+import time
+from collections import defaultdict, deque
+from typing import Any
+
+from fastapi import APIRouter, HTTPException, Request
+from pydantic import BaseModel, Field
+
+from deerflow.integrations.weknora.local_index.search import WikiIndexError
+
+router = APIRouter(prefix="/api/external/llmwiki/wiki", tags=["external-llmwiki"])
+_requests: dict[str, deque[float]] = defaultdict(deque)
+
+
+class ExternalWikiSearchRequest(BaseModel):
+    query: str = Field(..., min_length=1, max_length=10000)
+    knowledge_base_ids: list[str] = Field(default_factory=list, max_length=100)
+    limit: int | None = Field(default=None, ge=1, le=100)
+    include_content: bool = False
+
+
+def _config(request: Request):
+    config = request.app.state.config.llmwiki.local_wiki_index
+    if not config.enabled or not config.external_api.enabled:
+        raise HTTPException(status_code=404, detail="Not found")
+    return config, config.external_api
+
+
+def _rate_limit(request: Request, rpm: int) -> None:
+    ip = request.client.host if request.client else "unknown"
+    key = f"{getattr(request.state, 'external_api_key_fingerprint', 'unknown')}:{ip}"
+    now = time.monotonic()
+    queue = _requests[key]
+    while queue and queue[0] <= now - 60:
+        queue.popleft()
+    if len(queue) >= rpm:
+        raise HTTPException(status_code=429, detail="Rate limit exceeded")
+    queue.append(now)
+
+
+def _is_conversation_deposit(mapping: dict[str, Any]) -> bool:
+    return str(mapping.get("owner_user_id") or "") == "system" and str(mapping.get("name") or "").strip() == "对话沉淀"
+
+
+async def _external_mappings(request: Request, requested: list[str]) -> list[dict[str, Any]]:
+    mappings = await request.app.state.llmwiki_store.list_visible("system", scope="all", is_admin=True)
+    allowed = {row["id"]: row for row in mappings if row.get("publication_status") == "published" and row.get("external_search_enabled", False) and row.get("wiki_index_enabled", True) and not _is_conversation_deposit(row)}
+    if requested:
+        ids = list(dict.fromkeys(requested))
+        if any(mapping_id not in allowed for mapping_id in ids):
+            raise HTTPException(status_code=404, detail="Knowledge base not found")
+        return [allowed[mapping_id] for mapping_id in ids]
+    return list(allowed.values())
+
+
+@router.post("/vector-search")
+async def external_vector_search(request: Request, body: ExternalWikiSearchRequest) -> dict[str, Any]:
+    _, external = _config(request)
+    _rate_limit(request, external.requests_per_minute)
+    if len(body.query) > external.max_query_chars:
+        raise HTTPException(status_code=413, detail="Query is too large")
+    if len(body.knowledge_base_ids) > external.max_knowledge_bases:
+        raise HTTPException(status_code=413, detail="Too many knowledge bases")
+    limit = body.limit or external.default_results
+    if limit > external.max_results:
+        raise HTTPException(status_code=400, detail="Result limit is too large")
+    mappings = await _external_mappings(request, body.knowledge_base_ids)
+    search = getattr(request.app.state, "llmwiki_vector_search", None)
+    if search is None:
+        raise HTTPException(status_code=503, detail={"code": "WIKI_INDEX_UNAVAILABLE"})
+    try:
+        result = await search.search(body.query, mappings, top_k_pages=limit, external=True)
+    except WikiIndexError as exc:
+        raise HTTPException(status_code=exc.status_code, detail={"code": exc.code, "message": str(exc)}) from None
+    # Re-read publication/external flags after vector computation so a switch
+    # turned off during an in-flight request cannot leak a cached result.
+    still_allowed = {row["id"] for row in await _external_mappings(request, [])}
+    result["results"] = [item for item in result["results"] if item.get("knowledge_base_id") in still_allowed]
+    remaining = external.include_content_max_chars if body.include_content else 0
+    items = []
+    for result_item in result["results"]:
+        section = (result_item.get("matched_sections") or [{}])[0]
+        snippet = str(section.get("content") or "")[:1000]
+        content = ""
+        if remaining > 0:
+            content = "\n\n".join(str(item.get("content") or "") for item in result_item.get("matched_sections") or [])[:remaining]
+            remaining -= len(content)
+        item = {
+            "knowledge_base_id": result_item["knowledge_base_id"],
+            "knowledge_base_name": result_item.get("knowledge_base_name") or "",
+            "wiki_slug": result_item["wiki_slug"],
+            "title": result_item.get("title") or "",
+            "summary": result_item.get("summary") or "",
+            "matched_heading": section.get("heading"),
+            "snippet": snippet,
+            "page_type": result_item.get("page_type") or "article",
+            "page_version": result_item.get("page_version") or 0,
+            "updated_at": result_item.get("updated_at"),
+            "score": result_item.get("score") or 0,
+        }
+        if body.include_content:
+            item["content"] = content
+        items.append(item)
+    return {"query": body.query, "mode": "vector", "items": items, "count": len(items), "partial": result.get("partial", False)}
+
+
+@router.get("/pages/{mapping_id}/{slug:path}")
+async def external_wiki_page(request: Request, mapping_id: str, slug: str) -> dict[str, Any]:
+    _, external = _config(request)
+    _rate_limit(request, external.requests_per_minute)
+    mappings = await _external_mappings(request, [mapping_id])
+    if not mappings:
+        raise HTTPException(status_code=404, detail="Wiki page not found")
+    page = await request.app.state.llmwiki_index_store.get_page(mapping_id, slug.strip("/"))
+    if page is None or page.get("status") != "published" or page.get("index_status") != "ready" or page.get("is_remote_deleted"):
+        raise HTTPException(status_code=404, detail="Wiki page not found")
+    # Recheck after reading the page so publication/external revocation takes
+    # effect even when it races this detail request.
+    await _external_mappings(request, [mapping_id])
+    return {
+        "knowledge_base_id": mapping_id,
+        "knowledge_base_name": mappings[0].get("name") or "",
+        "wiki_slug": page["slug"],
+        "title": page.get("title") or "",
+        "summary": page.get("summary") or "",
+        "content": str(page.get("content_md") or "")[: external.include_content_max_chars],
+        "page_type": page.get("page_type") or "article",
+        "page_version": page.get("page_version") or 0,
+        "updated_at": page.get("remote_updated_at") or page.get("updated_at"),
+    }

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

@@ -0,0 +1,92 @@
+"""Administrator-managed exact-match fixed question/answer API."""
+
+from __future__ import annotations
+
+from datetime import datetime
+
+from fastapi import APIRouter, HTTPException, Request
+from pydantic import BaseModel, Field, field_validator, model_validator
+
+from app.gateway.deps import get_current_user, get_optional_user_from_request
+from deerflow.persistence.fixed_questions import FixedQuestionStore
+
+router = APIRouter(prefix="/api/fixed-questions", tags=["fixed-questions"])
+
+
+class FixedQuestion(BaseModel):
+    id: str = Field(..., min_length=1, max_length=64)
+    question: str = Field(..., min_length=1, max_length=10_000)
+    answer: str = Field(..., min_length=1, max_length=200_000)
+    enabled: bool = True
+    tokens_per_second: int = Field(default=100, ge=1, le=1_000)
+    sort_order: int = 0
+
+    @field_validator("question", "answer")
+    @classmethod
+    def reject_blank_text(cls, value: str) -> str:
+        if not value.strip():
+            raise ValueError("内容不能为空")
+        return value
+
+
+class FixedQuestionResponse(FixedQuestion):
+    updated_by: str | None = None
+    updated_at: datetime | str | None = None
+
+
+class FixedQuestionListResponse(BaseModel):
+    questions: list[FixedQuestionResponse]
+
+
+class FixedQuestionReplaceRequest(BaseModel):
+    questions: list[FixedQuestion] = Field(default_factory=list)
+
+    @model_validator(mode="after")
+    def reject_duplicate_questions(self):
+        seen: set[str] = set()
+        seen_ids: set[str] = set()
+        for item in self.questions:
+            if item.id in seen_ids:
+                raise ValueError(f"配置 ID「{item.id}」重复")
+            seen_ids.add(item.id)
+            if item.question in seen:
+                raise ValueError(f"问题「{item.question}」重复")
+            seen.add(item.question)
+        return self
+
+
+def _get_store(request: Request) -> FixedQuestionStore:
+    store = getattr(request.app.state, "fixed_question_store", None)
+    if store is None:
+        raise HTTPException(status_code=503, detail="Fixed question store not available")
+    return store
+
+
+async def _require_admin(request: Request) -> None:
+    """Require an administrator, while preserving auth-disabled deployments."""
+    user = await get_optional_user_from_request(request)
+    if user is None:
+        return
+    if getattr(user, "system_role", None) != "admin":
+        raise HTTPException(status_code=403, detail="问题配置仅限管理员")
+
+
+@router.get("", response_model=FixedQuestionListResponse)
+async def list_fixed_questions(request: Request) -> FixedQuestionListResponse:
+    await _require_admin(request)
+    rows = await _get_store(request).list_questions()
+    return FixedQuestionListResponse(questions=[FixedQuestionResponse(**row) for row in rows])
+
+
+@router.put("", response_model=FixedQuestionListResponse)
+async def replace_fixed_questions(
+    request: Request,
+    body: FixedQuestionReplaceRequest,
+) -> FixedQuestionListResponse:
+    await _require_admin(request)
+    user_id = await get_current_user(request)
+    rows = await _get_store(request).replace_all(
+        [question.model_dump() for question in body.questions],
+        updated_by=user_id,
+    )
+    return FixedQuestionListResponse(questions=[FixedQuestionResponse(**row) for row in rows])

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

@@ -29,7 +29,8 @@ SSE 协议（与前端 ``streamIntent`` 对齐）
      - ``done``：已解析 ``[INTENT_READY]`` + JSON 块，``summary`` 有值；
      - ``error``：上游或网关异常。
 
-   ``content`` — 展示用 AI 正文（澄清时优先用 tool 后的 follow-up 文本）。
+   ``content`` — 展示用 AI 正文（澄清时只保留 tool 调用前的简短引导；
+   tool 后的尾随文本会被丢弃，选项发出后立即等待用户选择）。
 
    仅 ``status == "done"`` 时带 ``summary``；澄清时还带
    ``question``、``clarification_type``、``clarification_context``、
@@ -629,6 +630,14 @@ async def stream_intent(request: Request, payload: dict = Body(...)) -> Streamin
                 # 2. message 前缀——给模型一个明确的"本轮必须收敛"信号。
                 # 仅文件、无文本时给一句兜底引导，让模型先读文件再澄清意图。
                 effective_message = message or "我上传了文件，请先阅读文件内容，再据此理解并澄清我的任务意图。"
+                if past_rounds < max_rounds:
+                    effective_message = (
+                        "[澄清输出硬约束] 如果本轮调用 ask_clarification，"
+                        "工具调用完成后必须立即停止输出并等待用户选择；"
+                        "禁止补充说明、复述选项、催促选择、追加问题或输出 "
+                        "[INTENT_READY]。需要确认的全部内容只能写入工具参数。\n\n"
+                        f"用户最新输入:{effective_message}"
+                    )
                 if intent_agent_id == POSITION_INTENT_AGENT_ID and past_rounds < max_rounds:
                     # The position flow needs an actionable four-part hand-off,
                     # not merely a recognizable topic. One turn may ask several
@@ -641,6 +650,8 @@ async def stream_intent(request: Request, payload: dict = Body(...)) -> Streamin
                         "ask_clarification；每个工具调用只能问一个决策点，不能把多项"
                         "问题合并成一张卡片。用户会一次性回答这些卡片。"
                         "如果四项意图已经足够明确，则直接输出最终结果。"
+                        "一旦调用完本轮所有 ask_clarification，必须立即停止输出，"
+                        "不要再补充说明、复述选项、催促选择或继续提问，等待用户选择。"
                         "不要以风险提示和战略意义为空的 [INTENT_READY] 结束。"
                         "本轮是第 %d/%d 轮用户协助；第 %d 轮若仍有缺口，必须把所有"
                         "剩余关键缺口分别发成卡片，收到回答后立即收敛。\n\n"
@@ -759,9 +770,6 @@ async def stream_intent(request: Request, payload: dict = Body(...)) -> Streamin
                 content = _flatten_content(dispatch_msg.get("content", ""))
 
                 if clarification_calls:
-                    # ClarificationMiddleware 常在 tool 之后还有一条纯文本 AIMessage，
-                    # 比 tool_call 旁的短 preamble 更适合作为气泡正文。
-                    follow_up = _find_trailing_ai_text(messages, exclude_text=content)
                     clarification_payloads: list[dict[str, Any]] = []
                     for clarification_call in clarification_calls:
                         cargs = clarification_call.get("args") or {}
@@ -793,6 +801,9 @@ async def stream_intent(request: Request, payload: dict = Body(...)) -> Streamin
                         )
 
                     if not clarification_payloads:
+                        # 这里只在所有卡片都因重复而被过滤时才允许使用 tool 后文本；
+                        # 此时前端没有选项需要等待，不属于澄清暂停态。
+                        follow_up = _find_trailing_ai_text(messages, exclude_text=content)
                         fallback_msg = (
                             follow_up
                             or content
@@ -808,7 +819,11 @@ async def stream_intent(request: Request, payload: dict = Body(...)) -> Streamin
                         return
 
                     first = clarification_payloads[0]
-                    display_content = follow_up or content or str(first["question"])
+                    # ask_clarification 是严格的回合终点。部分模型会在工具调用后
+                    # 再生成“请从以上选项中选择……”等尾随 AIMessage；不能把它
+                    # 返回给前端，否则用户看到卡片后还会继续冒出一段话。
+                    # 仅保留工具调用自身携带的前置短句；没有则直接由卡片展示问题。
+                    display_content = content
                     final_frame: dict[str, Any] = {
                         "status": "clarification",
                         "content": display_content,

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

@@ -2,18 +2,21 @@
 
 from __future__ import annotations
 
+import asyncio
 import hashlib
 import json
 import logging
 import re
 import time
 from dataclasses import replace
+from datetime import UTC, datetime
+from io import BytesIO
 from typing import Any, Literal
 from urllib.parse import quote, unquote, urlencode, urlsplit
 
 import httpx
 from fastapi import APIRouter, BackgroundTasks, File, HTTPException, Query, Request, UploadFile
-from fastapi.responses import JSONResponse, RedirectResponse, Response
+from fastapi.responses import JSONResponse, RedirectResponse, Response, StreamingResponse
 from pydantic import BaseModel, Field
 
 from app.gateway.csrf_middleware import is_secure_request
@@ -48,6 +51,7 @@ from deerflow.config.agents_config import load_agent_config
 from deerflow.config.llmwiki_config import LlmWikiRuntimeOverride, normalize_service_url
 from deerflow.config.system_settings import load_system_settings, save_system_settings
 from deerflow.integrations.weknora.client import WeKnoraClient, WeKnoraError
+from deerflow.integrations.weknora.local_index.search import WikiIndexError
 from deerflow.integrations.weknora.runtime import build_weknora_client, get_resolved_llmwiki_runtime
 from deerflow.persistence.llmwiki import LlmWikiStore
 
@@ -178,6 +182,8 @@ class SearchRequest(BaseModel):
     query: str = Field(..., min_length=1, max_length=4000)
     scope: Literal["personal", "public", "all"] = "all"
     knowledge_base_ids: list[str] = Field(default_factory=list, max_length=100)
+    top_k: int = Field(default=8, ge=1, le=50)
+    include_drafts: bool = False
 
 
 class KnowledgeUrlImport(BaseModel):
@@ -233,6 +239,15 @@ def _store(request: Request) -> LlmWikiStore:
     return value
 
 
+def _schedule_local_wiki_sync(request: Request, mapping: dict[str, Any]) -> None:
+    service = getattr(request.app.state, "llmwiki_sync_service", None)
+    config = request.app.state.config.llmwiki.local_wiki_index
+    if service is not None and config.enabled and mapping.get("wiki_index_enabled", True):
+        from app.gateway.llmwiki_index_scheduler import spawn_local_wiki_index_job
+
+        spawn_local_wiki_index_job(request.app, service.sync_mapping(mapping, force=True))
+
+
 async def _actor(request: Request) -> tuple[str, bool]:
     user = await get_optional_user_from_request(request)
     if user is None:
@@ -1718,6 +1733,9 @@ def _mapping_view(row: dict[str, Any], remote: dict[str, Any] | None, *, actor_u
         "description": description,
         "type": source.get("type") or row.get("kb_type") or "document",
         "publication_status": "published" if is_conversation_deposit else row.get("publication_status") or "private",
+        "wiki_index_enabled": row.get("wiki_index_enabled", True),
+        "external_search_enabled": False if is_conversation_deposit else row.get("external_search_enabled", False),
+        "external_search_updated_at": row.get("external_search_updated_at"),
         "owner_user_id": row.get("owner_user_id") if is_admin else None,
         "is_owner": is_owner,
         "can_write": not is_conversation_deposit and (is_admin or is_owner),
@@ -1760,6 +1778,24 @@ async def _authorized_mapping(
     return row, user_id, is_admin
 
 
+async def _public_mapping(request: Request, mapping_id: str) -> dict[str, Any]:
+    """Resolve a world-readable knowledge base without inheriting actor/admin state."""
+
+    row = await _store(request).get_authorized(
+        mapping_id,
+        "__public_wiki__",
+        write=False,
+        is_admin=False,
+    )
+    if (
+        row is None
+        or row.get("publication_status") != "published"
+        or _is_conversation_deposit_mapping(row)
+    ):
+        raise HTTPException(status_code=404, detail="Published knowledge base not found")
+    return row
+
+
 async def _verify_document(client: WeKnoraClient, row: dict[str, Any], document_id: str) -> dict[str, Any]:
     document = await client.get_document(document_id)
     if str(document.get("knowledge_base_id") or "") != str(row["weknora_id"]):
@@ -1908,6 +1944,135 @@ def _wiki_page_view(page: dict[str, Any]) -> dict[str, Any] | None:
     }
 
 
+async def _all_wiki_pages(client: WeKnoraClient, remote_id: str) -> list[dict[str, Any]]:
+    """Read every Wiki page and its processed Markdown, never raw documents."""
+
+    summaries: dict[str, dict[str, Any]] = {}
+    page_number = 1
+    while True:
+        listing = await client.list_wiki_pages(remote_id, page=page_number, page_size=500)
+        rows = [item for item in listing.get("pages", []) if isinstance(item, dict)]
+        for item in rows:
+            slug = str(item.get("slug") or item.get("wiki_slug") or item.get("path") or "").strip("/")
+            if slug:
+                summaries[slug] = item
+        total_pages = max(1, int(listing.get("total_pages") or 1))
+        if page_number >= total_pages or not rows:
+            break
+        page_number += 1
+
+    pages: list[dict[str, Any]] = []
+    entries = list(summaries.items())
+    for start in range(0, len(entries), 20):
+        batch = entries[start : start + 20]
+        details = await asyncio.gather(*(client.get_wiki_page(remote_id, slug) for slug, _ in batch))
+        pages.extend({**summary, **detail, "slug": slug} for (slug, summary), detail in zip(batch, details, strict=True))
+    return pages
+
+
+def _wiki_directory_parts(page: dict[str, Any], by_slug: dict[str, dict[str, Any]]) -> list[str]:
+    parent_slug = str(page.get("parent_slug") or "").strip("/")
+    if parent_slug:
+        ancestors: list[str] = []
+        visited: set[str] = set()
+        current = by_slug.get(parent_slug)
+        while current is not None:
+            slug = str(current.get("slug") or "").strip("/")
+            if not slug or slug in visited:
+                break
+            visited.add(slug)
+            ancestors.insert(0, str(current.get("title") or slug.rsplit("/", 1)[-1]))
+            current_parent = str(current.get("parent_slug") or "").strip("/")
+            current = by_slug.get(current_parent) if current_parent else None
+        if ancestors:
+            return ancestors
+
+    category_path = [str(item).strip() for item in page.get("category_path") or [] if str(item).strip()]
+    if category_path:
+        return category_path
+    wiki_path = [item.strip() for item in str(page.get("wiki_path") or "").split("/") if item.strip()]
+    if len(wiki_path) > 2:
+        return wiki_path[1:-1]
+    slug_parts = [item for item in str(page.get("slug") or "").split("/") if item]
+    return slug_parts[:-1]
+
+
+def _safe_excel_text(value: Any) -> str:
+    text = str(value or "")
+    return f"'{text}" if text.startswith(("=", "+", "-", "@")) else text
+
+
+def _build_wiki_excel(knowledge_base_name: str, raw_pages: list[dict[str, Any]]) -> BytesIO:
+    from openpyxl import Workbook
+    from openpyxl.styles import Alignment, Font, PatternFill
+
+    pages = [view for raw in raw_pages if (view := _wiki_page_view(raw)) is not None]
+    by_slug = {page["slug"]: page for page in pages if page["slug"]}
+    directories = [_wiki_directory_parts(page, by_slug) for page in pages]
+    max_depth = max((len(parts) for parts in directories), default=0)
+    max_content_parts = max((max(1, (len(str(page.get("content") or "")) + 31_999) // 32_000) for page in pages), default=1)
+    columns = [
+        "知识库",
+        "标题",
+        "Slug",
+        "目录完整路径",
+        "所在目录",
+        "父级目录完整路径",
+        *(f"第{level}级目录" for level in range(1, max_depth + 1)),
+        "摘要",
+        *("正文" if index == 1 else f"正文（续{index - 1}）" for index in range(1, max_content_parts + 1)),
+        "页面类型",
+        "状态",
+        "别名",
+        "版本",
+        "创建时间",
+        "更新时间",
+    ]
+    workbook = Workbook()
+    sheet = workbook.active
+    sheet.title = "Wiki 全量导出"
+    sheet.append(columns)
+    for cell in sheet[1]:
+        cell.font = Font(bold=True, color="FFFFFF")
+        cell.fill = PatternFill("solid", fgColor="1F4E78")
+        cell.alignment = Alignment(horizontal="center", vertical="center")
+    for page, directory in zip(pages, directories, strict=True):
+        content = str(page.get("content") or "")
+        content_parts = [content[index : index + 32_000] for index in range(0, len(content), 32_000)] or [""]
+        content_parts.extend([""] * (max_content_parts - len(content_parts)))
+        row = [
+            knowledge_base_name,
+            page.get("title"),
+            page.get("slug"),
+            " / ".join(directory),
+            directory[-1] if directory else "根目录",
+            " / ".join(directory[:-1]),
+            *directory,
+            *([""] * (max_depth - len(directory))),
+            page.get("summary"),
+            *content_parts,
+            page.get("page_type"),
+            page.get("status"),
+            "、".join(str(item) for item in page.get("aliases") or []),
+            page.get("version"),
+            page.get("created_at"),
+            page.get("updated_at"),
+        ]
+        sheet.append([_safe_excel_text(value) for value in row])
+    sheet.freeze_panes = "A2"
+    sheet.auto_filter.ref = sheet.dimensions
+    for column in sheet.columns:
+        letter = column[0].column_letter
+        heading = str(column[0].value or "")
+        sheet.column_dimensions[letter].width = 60 if heading.startswith("正文") else 32 if heading in {"摘要", "目录完整路径", "父级目录完整路径"} else 20
+        for cell in column[1:]:
+            cell.alignment = Alignment(vertical="top", wrap_text=True)
+    output = BytesIO()
+    workbook.save(output)
+    output.seek(0)
+    return output
+
+
 def _weknora_embed_target_path(weknora_id: str, tab: str) -> str:
     target_query = urlencode({"tab": tab}) if tab != "documents" else ""
     target = f"/platform/knowledge-bases/{quote(weknora_id, safe='')}"
@@ -2252,6 +2417,70 @@ async def test_llmwiki_connection(request: Request, body: LlmWikiConnectionTest)
     return {"success": True, "provider": "weknora", "health": health}
 
 
+@router.get("/api/public/llmwiki/knowledge-bases/{mapping_id}")
+async def get_public_knowledge_base(request: Request, mapping_id: str) -> dict[str, Any]:
+    """Return the safe public metadata used by the chrome-free Wiki reader."""
+
+    row = await _public_mapping(request, mapping_id)
+    try:
+        remote = await _client_or_503().get_knowledge_base(str(row["weknora_id"]))
+    except WeKnoraError as exc:
+        _raise_upstream(exc)
+    return _mapping_view(
+        row,
+        remote,
+        actor_user_id="__public_wiki__",
+        is_admin=False,
+    )
+
+
+@router.get("/api/public/llmwiki/knowledge-bases/{mapping_id}/wiki/pages")
+async def list_public_wiki_pages(
+    request: Request,
+    mapping_id: str,
+    page: int = Query(default=1, ge=1),
+    page_size: int = Query(default=50, ge=1, le=500),
+    query: str = Query(default="", max_length=255),
+) -> dict[str, Any]:
+    """List Wiki pages for a published knowledge base without requiring login."""
+
+    row = await _public_mapping(request, mapping_id)
+    try:
+        result = await _client_or_503().list_wiki_pages(
+            str(row["weknora_id"]),
+            page=page,
+            page_size=page_size,
+            query=query.strip(),
+        )
+    except WeKnoraError as exc:
+        _raise_upstream(exc)
+    raw_pages = result.get("pages") if isinstance(result, dict) else []
+    pages = [
+        view
+        for page_item in (raw_pages if isinstance(raw_pages, list) else [])
+        if isinstance(page_item, dict)
+        for view in [_wiki_page_view(page_item)]
+        if view is not None
+    ]
+    return {**result, "pages": pages}
+
+
+@router.get("/api/public/llmwiki/knowledge-bases/{mapping_id}/wiki/pages/{slug:path}")
+async def get_public_wiki_page(
+    request: Request,
+    mapping_id: str,
+    slug: str,
+) -> dict[str, Any]:
+    """Read one Wiki article from a published knowledge base."""
+
+    row = await _public_mapping(request, mapping_id)
+    try:
+        page = await _client_or_503().get_wiki_page(str(row["weknora_id"]), slug)
+    except WeKnoraError as exc:
+        _raise_upstream(exc)
+    return _wiki_page_view(page) or page
+
+
 @router.get("/api/llmwiki/knowledge-bases")
 async def list_knowledge_bases(
     request: Request,
@@ -2521,12 +2750,37 @@ async def list_wiki_pages(
         _raise_upstream(exc)
 
 
+@router.get("/api/llmwiki/knowledge-bases/{mapping_id}/wiki/export.xlsx")
+async def export_wiki_pages_excel(request: Request, mapping_id: str) -> StreamingResponse:
+    """Export every processed Wiki page with its current and parent directories."""
+
+    row, _, _ = await _authorized_mapping(request, mapping_id, write=False)
+    client = _client_or_503()
+    try:
+        pages = await _all_wiki_pages(client, str(row["weknora_id"]))
+    except WeKnoraError as exc:
+        _raise_upstream(exc)
+    try:
+        output = await asyncio.to_thread(_build_wiki_excel, str(row.get("name") or "LLMWiki"), pages)
+    except ImportError as exc:
+        raise HTTPException(status_code=500, detail=f"openpyxl is not installed: {exc}") from exc
+    timestamp = datetime.now(UTC).strftime("%Y%m%d-%H%M%S")
+    safe_name = re.sub(r"[\\/:*?\"<>|\r\n]+", "_", str(row.get("name") or "LLMWiki")).strip(" ._") or "LLMWiki"
+    filename = f"{safe_name}-Wiki-{timestamp}.xlsx"
+    return StreamingResponse(
+        output,
+        media_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+        headers={"Content-Disposition": f"attachment; filename=\"wiki-export.xlsx\"; filename*=UTF-8''{quote(filename)}"},
+    )
+
+
 @router.post("/api/llmwiki/knowledge-bases/{mapping_id}/wiki/pages")
 async def create_wiki_page(request: Request, mapping_id: str, body: WikiPageCreate) -> dict[str, Any]:
     row, _, _ = await _authorized_mapping(request, mapping_id, write=True)
     payload = body.model_dump(exclude_none=True)
     try:
         page = await _client_or_503().create_wiki_page(str(row["weknora_id"]), payload)
+        _schedule_local_wiki_sync(request, row)
         return _wiki_page_view(page) or page
     except WeKnoraError as exc:
         _raise_upstream(exc)
@@ -2554,6 +2808,7 @@ async def update_wiki_page(request: Request, mapping_id: str, slug: str, body: W
             _raise_upstream(exc)
     try:
         page = await _client_or_503().update_wiki_page(str(row["weknora_id"]), slug, changes)
+        _schedule_local_wiki_sync(request, row)
         return _wiki_page_view(page) or page
     except WeKnoraError as exc:
         _raise_upstream(exc)
@@ -2564,6 +2819,7 @@ async def delete_wiki_page(request: Request, mapping_id: str, slug: str) -> None
     row, _, _ = await _authorized_mapping(request, mapping_id, write=True)
     try:
         await _client_or_503().delete_wiki_page(str(row["weknora_id"]), slug)
+        _schedule_local_wiki_sync(request, row)
     except WeKnoraError as exc:
         _raise_upstream(exc)
 
@@ -2647,28 +2903,22 @@ async def search_llmwiki(request: Request, body: SearchRequest) -> dict[str, Any
             rows.append(row)
     else:
         rows = await store.list_visible(user_id, scope=body.scope, is_admin=False)
+    service = getattr(request.app.state, "llmwiki_retrieval_service", None)
+    if service is None:
+        raise HTTPException(status_code=503, detail={"code": "WIKI_RETRIEVAL_UNAVAILABLE"})
+    include_drafts = body.include_drafts and (is_admin or all(str(row.get("owner_user_id")) == user_id for row in rows))
     try:
-        results = await _client_or_503().search(body.query, [str(row["weknora_id"]) for row in rows])
+        result = await service.search(body.query, rows, top_k_pages=body.top_k, include_drafts=include_drafts)
-    except WeKnoraError as exc:
+    except WikiIndexError as exc:
-        _raise_upstream(exc)
+        raise HTTPException(status_code=exc.status_code, detail={"code": exc.code, "message": str(exc)}) from None
-    local_by_remote = {str(row["weknora_id"]): row for row in rows}
+    mapping_by_id = {str(row["id"]): row for row in rows}
-    visible: list[dict[str, Any]] = []
+    result["results"] = [
-    for result in results:
+        _sanitize_conversation_deposit_value(item)
-        mapping = local_by_remote.get(str(result.get("knowledge_base_id") or ""))
+        if _is_conversation_deposit_mapping(mapping_by_id.get(str(item.get("knowledge_base_id") or ""), {}))
-        if mapping is None:
+        else item
-            continue
+        for item in result.get("results") or []
-        visible_result = _sanitize_conversation_deposit_value(result) if _is_conversation_deposit_mapping(mapping) else result
+    ]
-        params = urlencode({"knowledge_base_id": mapping["id"], "chunk_id": visible_result.get("chunk_id") or ""})
+    return result
-        visible.append(
-            {
-                **visible_result,
-                "knowledge_base_id": mapping["id"],
-                "knowledge_base_name": mapping.get("name") or "",
-                "source": mapping.get("name") or "LLMWiki",
-                "url": f"/weknora-source-preview?{params}",
-            }
-        )
-    return {"results": visible, "knowledge_base_count": len(rows)}
 
 
 @router.post("/api/llmwiki/conversation-deposits/turn", status_code=202)

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

@@ -0,0 +1,290 @@
+"""Authenticated APIs for DeerFlow-local Wiki vector search and administration."""
+
+from __future__ import annotations
+
+from typing import Any
+from uuid import uuid4
+
+from fastapi import APIRouter, HTTPException, Query, Request
+from pydantic import BaseModel, Field
+
+from app.gateway.deps import get_optional_user_from_request
+from app.gateway.llmwiki_index_scheduler import spawn_local_wiki_index_job
+from deerflow.integrations.weknora.local_index.retrieval import is_fully_vectorized
+from deerflow.integrations.weknora.local_index.search import WikiIndexError
+
+router = APIRouter(prefix="/api/llmwiki", tags=["llmwiki-index"])
+
+
+class WikiVectorSearchRequest(BaseModel):
+    query: str = Field(..., min_length=1, max_length=4000)
+    knowledge_base_ids: list[str] = Field(default_factory=list, max_length=100)
+    top_k: int = Field(default=8, ge=1, le=50)
+    include_drafts: bool = False
+    include_content: bool = True
+
+
+class WikiIndexActionRequest(BaseModel):
+    knowledge_base_ids: list[str] = Field(default_factory=list, max_length=100)
+    force: bool = False
+    reason: str = Field(default="manual", max_length=255)
+
+
+class WikiIndexSettingsRequest(BaseModel):
+    wiki_index_enabled: bool | None = None
+    external_search_enabled: bool | None = None
+
+
+async def _actor(request: Request) -> tuple[str, bool]:
+    user = await get_optional_user_from_request(request)
+    if user is None:
+        return "default", True
+    return str(user.id), getattr(user, "system_role", None) == "admin"
+
+
+def _services(request: Request):
+    config = request.app.state.config.llmwiki.local_wiki_index
+    if not config.enabled:
+        raise HTTPException(status_code=409, detail={"code": "WIKI_INDEX_DISABLED", "message": "Local Wiki index is disabled"})
+    search = getattr(request.app.state, "llmwiki_vector_search", None)
+    index_store = getattr(request.app.state, "llmwiki_index_store", None)
+    if search is None or index_store is None:
+        raise HTTPException(status_code=503, detail={"code": "WIKI_INDEX_UNAVAILABLE", "message": "Local Wiki index is unavailable"})
+    return config, search, index_store
+
+
+async def _authorized_mappings(request: Request, mapping_ids: list[str]) -> tuple[list[dict[str, Any]], str, bool]:
+    user_id, is_admin = await _actor(request)
+    mapping_store = request.app.state.llmwiki_store
+    if mapping_ids:
+        rows = []
+        for mapping_id in dict.fromkeys(mapping_ids):
+            row = await mapping_store.get_authorized(mapping_id, user_id, write=False, is_admin=is_admin)
+            if row is None or not row.get("wiki_index_enabled", True):
+                raise HTTPException(status_code=404, detail="Knowledge base not found")
+            rows.append(row)
+    else:
+        rows = [row for row in await mapping_store.list_visible(user_id, scope="all", is_admin=is_admin) if row.get("wiki_index_enabled", True)]
+    return rows, user_id, is_admin
+
+
+@router.post("/wiki-vector-search")
+async def wiki_vector_search(request: Request, body: WikiVectorSearchRequest) -> dict[str, Any]:
+    config, search, _ = _services(request)
+    if not config.internal_search_enabled:
+        raise HTTPException(status_code=409, detail={"code": "WIKI_INTERNAL_SEARCH_DISABLED", "message": "Local Wiki search is not enabled"})
+    rows, user_id, is_admin = await _authorized_mappings(request, body.knowledge_base_ids)
+    include_drafts = body.include_drafts and (is_admin or all(str(row.get("owner_user_id")) == user_id for row in rows))
+    try:
+        result = await search.search(body.query, rows, top_k_pages=body.top_k, include_drafts=include_drafts)
+    except WikiIndexError as exc:
+        raise HTTPException(status_code=exc.status_code, detail={"code": exc.code, "message": str(exc)}) from None
+    if not body.include_content:
+        for item in result["results"]:
+            item.pop("content", None)
+            item.pop("snippet", None)
+            for section in item["matched_sections"]:
+                section.pop("content", None)
+    return result
+
+
+@router.get("/knowledge-bases/{mapping_id}/local-wiki/pages/{slug:path}")
+async def local_wiki_page(
+    request: Request,
+    mapping_id: str,
+    slug: str,
+    include_provenance: bool = Query(default=False),
+    include_archived: bool = Query(default=False),
+) -> dict[str, Any]:
+    _, _, index_store = _services(request)
+    user_id, is_admin = await _actor(request)
+    mapping = await request.app.state.llmwiki_store.get_authorized(mapping_id, user_id, write=False, is_admin=is_admin)
+    if mapping is None:
+        raise HTTPException(status_code=404, detail="Wiki page not found")
+    page = await index_store.get_page(mapping_id, slug.strip("/"))
+    if page is None or page.get("is_remote_deleted"):
+        raise HTTPException(status_code=404, detail="Wiki page not found")
+    owner_or_admin = is_admin or str(mapping.get("owner_user_id")) == user_id
+    if page.get("status") == "archived" and not (include_archived and owner_or_admin):
+        raise HTTPException(status_code=404, detail="Wiki page not found")
+    if page.get("status") != "published" and not owner_or_admin:
+        raise HTTPException(status_code=404, detail="Wiki page not found")
+    result = {
+        "id": page["id"],
+        "knowledge_base_id": mapping_id,
+        "title": page.get("title") or "",
+        "slug": page["slug"],
+        "summary": page.get("summary") or "",
+        "content": page.get("content_md") or "",
+        "page_type": page.get("page_type") or "article",
+        "status": page.get("status"),
+        "aliases": page.get("aliases") or [],
+        "category_path": page.get("category_path") or [],
+        "parent_slug": page.get("parent_slug"),
+        "wiki_path": page.get("wiki_path"),
+        "page_version": page.get("page_version") or 0,
+        "updated_at": page.get("remote_updated_at") or page.get("updated_at"),
+        "created_at": page.get("remote_created_at") or page.get("created_at"),
+    }
+    if owner_or_admin:
+        result.update({"index_status": page.get("index_status"), "indexed_at": page.get("indexed_at")})
+        if include_provenance:
+            result.update({"source_refs": page.get("source_refs") or [], "chunk_refs": page.get("chunk_refs") or []})
+    return result
+
+
+@router.get("/wiki-index/status")
+async def wiki_index_status(request: Request) -> dict[str, Any]:
+    _, is_admin = await _actor(request)
+    if not is_admin:
+        raise HTTPException(status_code=403, detail="Administrator access required")
+    config = request.app.state.config.llmwiki.local_wiki_index
+    index_store = getattr(request.app.state, "llmwiki_index_store", None)
+    if index_store is None:
+        raise HTTPException(status_code=503, detail={"code": "WIKI_INDEX_UNAVAILABLE"})
+    mappings = await request.app.state.llmwiki_store.list_visible("system", scope="all", is_admin=True)
+    states = {row["knowledge_base_mapping_id"]: row for row in await index_store.list_index_status()}
+    items = []
+    for mapping in mappings:
+        state = states.get(mapping["id"], {"state": "not_synced", "index_revision": 0})
+        items.append(
+            {
+                **state,
+                "knowledge_base_id": mapping["id"],
+                "knowledge_base_name": mapping.get("name") or "",
+                "wiki_index_enabled": mapping.get("wiki_index_enabled", True),
+                "external_search_enabled": mapping.get("external_search_enabled", False),
+            }
+        )
+    return {
+        "enabled": config.enabled,
+        "sync_enabled": config.sync_enabled,
+        "internal_search_enabled": config.internal_search_enabled,
+        "embedding_model": config.embedding.model,
+        "embedding_fingerprint": (
+            request.app.state.llmwiki_embedding.fingerprint[:12]
+            if getattr(request.app.state, "llmwiki_embedding", None) is not None
+            else None
+        ),
+        "knowledge_bases": items,
+    }
+
+
+async def _run_sync(app, mapping_ids: list[str], force: bool) -> None:
+    service = getattr(app.state, "llmwiki_sync_service", None)
+    if service is None:
+        return
+    mappings = await app.state.llmwiki_store.list_visible("system", scope="all", is_admin=True)
+    wanted = set(mapping_ids)
+    for mapping in mappings:
+        if mapping.get("wiki_index_enabled", True) and (not wanted or mapping["id"] in wanted):
+            try:
+                await service.sync_mapping(mapping, force=force)
+            except Exception:
+                continue
+
+
+async def _run_one_sync(app, mapping: dict[str, Any], *, force: bool) -> None:
+    service = getattr(app.state, "llmwiki_sync_service", None)
+    if service is None:
+        return
+    try:
+        await service.sync_mapping(mapping, force=force)
+    except Exception:
+        return
+
+
+@router.post("/wiki-index/sync", status_code=202)
+async def sync_wiki_index(request: Request, body: WikiIndexActionRequest) -> dict[str, Any]:
+    _services(request)
+    _, is_admin = await _actor(request)
+    if not is_admin:
+        raise HTTPException(status_code=403, detail="Administrator access required")
+    job_id = str(uuid4())
+    spawn_local_wiki_index_job(request.app, _run_sync(request.app, body.knowledge_base_ids, body.force))
+    return {"job_id": job_id, "status": "accepted"}
+
+
+@router.post("/wiki-index/rebuild", status_code=202)
+async def rebuild_wiki_index(request: Request, body: WikiIndexActionRequest) -> dict[str, Any]:
+    _, _, index_store = _services(request)
+    _, is_admin = await _actor(request)
+    if not is_admin:
+        raise HTTPException(status_code=403, detail="Administrator access required")
+    mappings = await request.app.state.llmwiki_store.list_visible("system", scope="all", is_admin=True)
+    ids = body.knowledge_base_ids or [row["id"] for row in mappings if row.get("wiki_index_enabled", True)]
+    fingerprint = request.app.state.llmwiki_embedding.fingerprint
+    await index_store.mark_rebuild_required(ids, fingerprint)
+    job_id = str(uuid4())
+    spawn_local_wiki_index_job(request.app, _run_sync(request.app, ids, True))
+    return {"job_id": job_id, "status": "accepted", "reason": body.reason}
+
+
+@router.post("/wiki-index/knowledge-bases/{mapping_id}/sync", status_code=202)
+async def sync_one_wiki_index(request: Request, mapping_id: str, force: bool = Query(default=False)) -> dict[str, Any]:
+    return await sync_wiki_index(request, WikiIndexActionRequest(knowledge_base_ids=[mapping_id], force=force))
+
+
+@router.post("/wiki-index/knowledge-bases/{mapping_id}/rebuild", status_code=202)
+async def rebuild_one_wiki_index(request: Request, mapping_id: str, reason: str = Query(default="manual", max_length=255)) -> dict[str, Any]:
+    return await rebuild_wiki_index(request, WikiIndexActionRequest(knowledge_base_ids=[mapping_id], force=True, reason=reason))
+
+
+@router.get("/knowledge-bases/{mapping_id}/wiki-index-status")
+async def knowledge_base_wiki_index_status(request: Request, mapping_id: str) -> dict[str, Any]:
+    user_id, is_admin = await _actor(request)
+    mapping = await request.app.state.llmwiki_store.get_authorized(mapping_id, user_id, write=False, is_admin=is_admin)
+    if mapping is None:
+        raise HTTPException(status_code=404, detail="Knowledge base not found")
+    index_store = getattr(request.app.state, "llmwiki_index_store", None)
+    if index_store is None:
+        raise HTTPException(status_code=503, detail={"code": "WIKI_INDEX_UNAVAILABLE"})
+    states = await index_store.list_index_status([mapping_id])
+    state = states[0] if states else {"knowledge_base_mapping_id": mapping_id, "state": "not_synced", "index_revision": 0}
+    embedding = getattr(request.app.state, "llmwiki_embedding", None)
+    fingerprint = embedding.fingerprint if embedding is not None else None
+    fully_vectorized = bool(mapping.get("wiki_index_enabled", True)) and is_fully_vectorized(state, fingerprint)
+    return {
+        **state,
+        "knowledge_base_id": mapping_id,
+        "local_index_enabled": bool(request.app.state.config.llmwiki.local_wiki_index.enabled),
+        "wiki_index_enabled": mapping.get("wiki_index_enabled", True),
+        "fully_vectorized": fully_vectorized,
+        "retrieval_mode": "vector" if fully_vectorized else "wiki_api",
+    }
+
+
+@router.post("/knowledge-bases/{mapping_id}/vectorize", status_code=202)
+async def vectorize_knowledge_base(request: Request, mapping_id: str) -> dict[str, Any]:
+    config = request.app.state.config.llmwiki.local_wiki_index
+    if not config.enabled:
+        raise HTTPException(
+            status_code=409,
+            detail={"code": "WIKI_INDEX_DISABLED", "message": "本地 Wiki 向量化未在配置中启用"},
+        )
+    service = getattr(request.app.state, "llmwiki_sync_service", None)
+    if service is None:
+        raise HTTPException(status_code=503, detail={"code": "WIKI_VECTORIZATION_UNAVAILABLE"})
+    user_id, is_admin = await _actor(request)
+    mapping_store = request.app.state.llmwiki_store
+    mapping = await mapping_store.get_authorized(mapping_id, user_id, write=True, is_admin=is_admin)
+    if mapping is None:
+        raise HTTPException(status_code=404, detail="Knowledge base not found")
+    if not mapping.get("wiki_index_enabled", True):
+        mapping = await mapping_store.update_mapping(mapping_id, wiki_index_enabled=True)
+    job_id = str(uuid4())
+    spawn_local_wiki_index_job(request.app, _run_one_sync(request.app, mapping, force=True))
+    return {"job_id": job_id, "status": "accepted", "knowledge_base_id": mapping_id}
+
+
+@router.patch("/knowledge-bases/{mapping_id}/wiki-index-settings")
+async def update_wiki_index_settings(request: Request, mapping_id: str, body: WikiIndexSettingsRequest) -> dict[str, Any]:
+    user_id, is_admin = await _actor(request)
+    store = request.app.state.llmwiki_store
+    current = await store.get_authorized(mapping_id, user_id, write=True, is_admin=is_admin)
+    if current is None:
+        raise HTTPException(status_code=404, detail="Knowledge base not found")
+    if body.external_search_enabled and str(current.get("owner_user_id")) == "system" and str(current.get("name") or "").strip() == "对话沉淀":
+        raise HTTPException(status_code=403, detail="Conversation deposit can never be exposed externally")
+    updated = await store.update_mapping(mapping_id, wiki_index_enabled=body.wiki_index_enabled, external_search_enabled=body.external_search_enabled)
+    return {"knowledge_base_id": mapping_id, "wiki_index_enabled": updated.get("wiki_index_enabled", True), "external_search_enabled": updated.get("external_search_enabled", False)}

offline-backend-20260512/backend/app/gateway/services.py

@@ -22,6 +22,7 @@ from langchain_core.messages import HumanMessage
 
 from app.gateway.deps import get_concurrency_gate, get_run_context, get_run_manager, get_stream_bridge
 from app.gateway.llmwiki_rag import (
+    LlmWikiRagContext,
     attach_llmwiki_rag_to_graph_input,
     build_llmwiki_rag_context,
     llmwiki_selection_requested,
@@ -227,6 +228,77 @@ def normalize_input(raw_input: dict[str, Any] | None) -> dict[str, Any]:
     return raw_input
 
 
+def _plain_fixed_question(graph_input: dict[str, Any]) -> str | None:
+    """Return the latest plain-text human turn eligible for exact matching.
+
+    Messages carrying files or multimodal blocks are intentionally excluded:
+    their answer depends on more than the visible question text, so replaying a
+    global fixed answer would be surprising and unsafe.
+    """
+
+    messages = graph_input.get("messages")
+    if not isinstance(messages, list) or not messages:
+        return None
+    message = messages[-1]
+    if not isinstance(message, HumanMessage):
+        return None
+    additional_kwargs = getattr(message, "additional_kwargs", {}) or {}
+    if any(
+        additional_kwargs.get(key)
+        for key in ("files", "uploaded_files", "attachments", "prompt_prefix")
+    ):
+        return None
+    content = getattr(message, "content", None)
+    if isinstance(content, str):
+        return content
+    if not isinstance(content, list):
+        return None
+    parts: list[str] = []
+    for item in content:
+        if isinstance(item, str):
+            parts.append(item)
+            continue
+        if not isinstance(item, Mapping):
+            return None
+        item_type = str(item.get("type") or "text")
+        text = item.get("text")
+        if item_type not in {"text", "input_text"} or not isinstance(text, str):
+            return None
+        parts.append(text)
+    return "".join(parts)
+
+
+async def _find_fixed_answer(
+    *,
+    body: Any,
+    request: Request,
+    graph_input: dict[str, Any],
+    run_scope: str,
+) -> dict[str, Any] | None:
+    """Look up an enabled exact match, falling back to the model on errors."""
+
+    if run_scope != RUN_SCOPE_EXTERNAL_ROOT or getattr(body, "command", None) is not None:
+        return None
+    assistant_id = str(getattr(body, "assistant_id", None) or _DEFAULT_ASSISTANT_ID)
+    if assistant_id in {"canvas_agent", "ai_writing"}:
+        return None
+    context = getattr(body, "context", None) or {}
+    if isinstance(context, Mapping) and context.get("writing_mode"):
+        return None
+    question = _plain_fixed_question(graph_input)
+    if question is None:
+        return None
+    store = getattr(request.app.state, "fixed_question_store", None)
+    if store is None:
+        return None
+    try:
+        return await store.find_enabled(question)
+    except Exception:
+        # Configuration storage must never make normal chat unavailable.
+        logger.warning("Fixed-question lookup failed; continuing with model", exc_info=True)
+        return None
+
+
 _DEFAULT_ASSISTANT_ID = "lead_agent"
 
 # Built-in LangGraph graph IDs registered in langgraph.json.
@@ -869,21 +941,36 @@ async def start_run(
         await _enforce_agent_access(body, request)
     t_post_enforce = time.perf_counter()
 
-    effective_model_name = _resolve_effective_run_model_name(body)
     effective_user_id = get_effective_user_id()
     effective_run_scope = _resolve_run_scope(body, request, run_scope)
-    model_concurrency_limit = _get_model_concurrency_limit(effective_model_name)
+    graph_input = normalize_input(body.input)
-    user_model_concurrency_limit = (
+    fixed_answer = await _find_fixed_answer(
-        _get_user_model_concurrency_limit(effective_model_name)
+        body=body,
-        if effective_run_scope == RUN_SCOPE_EXTERNAL_ROOT
+        request=request,
-        else None
+        graph_input=graph_input,
+        run_scope=effective_run_scope,
     )
+    if fixed_answer is not None:
+        effective_model_name = "fixed-answer"
+        model_concurrency_limit = None
+        user_model_concurrency_limit = None
+    else:
+        effective_model_name = _resolve_effective_run_model_name(body)
+        model_concurrency_limit = _get_model_concurrency_limit(effective_model_name)
+        user_model_concurrency_limit = (
+            _get_user_model_concurrency_limit(effective_model_name)
+            if effective_run_scope == RUN_SCOPE_EXTERNAL_ROOT
+            else None
+        )
     run_id = str(uuid.uuid4())
 
     run_metadata = dict(body.metadata or {})
     run_metadata["model_name"] = effective_model_name
     run_metadata["user_id"] = effective_user_id
     run_metadata["run_scope"] = effective_run_scope
+    if fixed_answer is not None:
+        run_metadata["fixed_answer"] = True
+        run_metadata["fixed_question_id"] = fixed_answer["id"]
 
     redis_lease_acquired = False
     redis_gate_degraded = True
@@ -895,7 +982,7 @@ async def start_run(
         "user_id": effective_user_id,
         "user_model_accounted": user_model_accounted,
     }
-    if concurrency_gate is not None:
+    if concurrency_gate is not None and fixed_answer is None:
         acquire = await concurrency_gate.try_acquire(
             run_id=run_id,
             thread_id=thread_id,
@@ -996,12 +1083,22 @@ async def start_run(
     t_post_thread_upsert = time.perf_counter()
 
     try:
-        agent_factory = resolve_agent_factory(body.assistant_id)
+        if fixed_answer is not None:
+            from deerflow.agents.fixed_answer_agent import make_fixed_answer_agent
+
+            def agent_factory(config):  # noqa: ANN001, ARG001 - worker factory contract
+                return make_fixed_answer_agent(
+                    question=str(fixed_answer["question"]),
+                    answer=str(fixed_answer["answer"]),
+                    fixed_question_id=str(fixed_answer["id"]),
+                    tokens_per_second=int(fixed_answer.get("tokens_per_second", 100)),
+                )
+        else:
+            agent_factory = resolve_agent_factory(body.assistant_id)
     except Exception:
         if concurrency_gate is not None and redis_lease_acquired:
             await concurrency_gate.release(**lease_metadata)
         raise
-    graph_input = normalize_input(body.input)
 
     # Admin-configurable prompt prefix: when the caller opted in via
     # context.prompt_prefix_enabled, tag the human message with the configured
@@ -1011,14 +1108,18 @@ async def start_run(
     # applies once. We intentionally do NOT gate on thread-row existence: the
     # thread_meta row is frequently pre-created, which previously skipped the
     # prefix for genuine first turns.
-    if _prompt_prefix_opted_in(body):
+    if fixed_answer is None and _prompt_prefix_opted_in(body):
         prefix_settings = load_system_settings().prompt_prefix
         if prefix_settings.enabled and prefix_settings.prompt_prefix.strip():
             graph_input = _prepend_prompt_prefix(graph_input, prefix_settings.prompt_prefix.strip())
-    llmwiki_rag = await build_llmwiki_rag_context(
+    llmwiki_rag = (
-        request=request,
+        LlmWikiRagContext([], 0, "", [], "")
-        body=body,
+        if fixed_answer is not None
-        graph_input=graph_input,
+        else await build_llmwiki_rag_context(
+            request=request,
+            body=body,
+            graph_input=graph_input,
+        )
     )
     if llmwiki_rag.prompt or llmwiki_rag.sources:
         graph_input = attach_llmwiki_rag_to_graph_input(graph_input, llmwiki_rag)

offline-backend-20260512/backend/config.yaml

@@ -372,6 +372,15 @@ skills:
   path: skills
   security_scan:
     enabled: false
+  # ES 灵活查询技能路由提示：开启后注入整体 system prompt；修改 prompt 可调整
+  # 触发边界和调用要求。关闭后该提示完全不注入。
+  es_query_routing:
+    enabled: true
+    prompt: |
+      当用户的问题需要基于 Elasticsearch 查询语句（Query DSL）灵活构造、调整或执行查询时，必须优先使用 `es_query` 技能。
+      典型场景包括：根据用户条件动态组合 bool/must/filter/should、范围、聚合、排序或分页等 ES 查询；或者用户直接提供、要求修改 ES 语句并据此查询数据。
+      执行前先读取 `es_query` 技能的 SKILL.md，严格按照技能中的流程和参数调用；不要用通用搜索替代，也不要凭记忆臆测查询结果。
+      仅当问题确实需要 ES 数据查询时使用；纯概念解释、普通代码说明或与 ES 无关的问题不要调用。
 
 skill_evolution:
   enabled: true
@@ -547,6 +556,45 @@ llmwiki:
     web_base_url: "http://119.254.86.251:8088"
     admin_email: "lqq@qq.com"
     admin_password: "1qaz@WSX"
+  # DeerFlow-local Wiki mirror/vector index. Keep disabled until the
+  # OpenAI-compatible embedding endpoint below is configured and reachable.
+  local_wiki_index:
+    enabled: false
+    sync_enabled: false
+    internal_search_enabled: false
+    reference_ui_enabled: false
+    sync_interval_seconds: 120
+    chunk_max_chars: 1000
+    chunk_overlap_chars: 120
+    chunk_min_chars: 80
+    embedding:
+      enabled: true
+      provider: openai
+      model: bge-m3
+      base_url: ""
+      api_key: ""
+      dimensions: 1024
+      batch_size: 32
+      timeout_seconds: 30
+      max_retries: 3
+    engine: numpy_exact
+    strict_vector: true
+    top_k_sections: 30
+    top_k_pages: 8
+    max_sections_per_page: 2
+    min_similarity: 0.35
+    cache_max_knowledge_bases: 20
+    cache_revision_check_seconds: 5
+    external_api:
+      enabled: false
+      api_key: ""
+      previous_api_key: ""
+      max_query_chars: 1000
+      max_knowledge_bases: 20
+      max_results: 50
+      default_results: 10
+      include_content_max_chars: 12000
+      requests_per_minute: 60
 
 log_system:
   enabled: true

offline-backend-20260512/backend/docs/CONFIGURATION.md

@@ -270,9 +270,21 @@ skills:
   # Host path (optional, default: ../skills)
   path: /custom/path/to/skills
 
-  # Container mount path (default: /mnt/skills)
+  # Container mount path (default: /mnt/skills)
-  container_path: /mnt/skills
+  container_path: /mnt/skills
-```
+  # Optional system-prompt routing rule for the es_query skill
+  es_query_routing:
+    enabled: true
+    prompt: |
+      当用户的问题需要基于 Elasticsearch Query DSL 灵活构造、调整或执行查询时，优先使用 `es_query` 技能。
+      执行前先读取该技能的 SKILL.md，并严格遵循其中的流程和参数。
+```
+
+`skills.es_query_routing.enabled` controls whether the routing rule is injected
+into the overall agent system prompt. Edit `prompt` to tune the matching boundary
+or invocation requirements. When disabled (the schema default), the block is not
+injected. Custom agents receive it only when their explicit skill allowlist
+contains `es_query`.
 
 **How Skills Work**:
 - Skills are stored in `deer-flow/skills/{public,custom}/`

offline-backend-20260512/backend/packages/harness/deerflow/agents/fixed_answer_agent.py

@@ -0,0 +1,186 @@
+"""Small local streaming graph used for exact-match fixed answers.
+
+The graph deliberately uses a local ``BaseChatModel`` implementation so
+LangGraph emits the same token/message stream events as a normal model-backed
+answer, while making no network or model-provider request.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import codecs
+import math
+import uuid
+from collections.abc import AsyncIterator, Sequence
+from typing import Any
+
+import tiktoken
+from langchain_core.callbacks import AsyncCallbackManagerForLLMRun, CallbackManagerForLLMRun
+from langchain_core.language_models.chat_models import BaseChatModel
+from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage
+from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
+from langchain_core.runnables import RunnableConfig
+from langgraph.graph import END, START, StateGraph
+
+from deerflow.agents.thread_state import ThreadState
+
+_TOKEN_ENCODING = tiktoken.get_encoding("cl100k_base")
+_TARGET_CHUNKS_PER_SECOND = 10
+_MAX_TOKENS_PER_CHUNK = 20
+_MAX_TOKENS_PER_SECOND = 1_000
+
+
+class FixedAnswerChatModel(BaseChatModel):
+    """A local streaming model that only replays an administrator answer."""
+
+    answer: str
+    message_id: str
+    fixed_question_id: str
+    tokens_per_second: int = 100
+
+    @property
+    def _llm_type(self) -> str:
+        return "fixed-answer"
+
+    @property
+    def _identifying_params(self) -> dict[str, Any]:
+        return {
+            "fixed_question_id": self.fixed_question_id,
+            "tokens_per_second": self.tokens_per_second,
+        }
+
+    def _message(self) -> AIMessage:
+        return AIMessage(
+            content=self.answer,
+            id=self.message_id,
+            additional_kwargs={
+                "fixed_answer": True,
+                "fixed_question_id": self.fixed_question_id,
+                "tokens_per_second": self.tokens_per_second,
+            },
+        )
+
+    def _generate(
+        self,
+        messages: list[BaseMessage],
+        stop: list[str] | None = None,
+        run_manager: CallbackManagerForLLMRun | None = None,
+        **kwargs: Any,
+    ) -> ChatResult:
+        del messages, stop, run_manager, kwargs
+        return ChatResult(generations=[ChatGeneration(message=self._message())])
+
+    async def _astream(
+        self,
+        messages: list[BaseMessage],
+        stop: list[str] | None = None,
+        run_manager: AsyncCallbackManagerForLLMRun | None = None,
+        **kwargs: Any,
+    ) -> AsyncIterator[ChatGenerationChunk]:
+        del messages, stop, run_manager, kwargs
+        answer = self.answer
+        if not answer:
+            yield ChatGenerationChunk(message=AIMessageChunk(content="", id=self.message_id))
+            return
+        token_ids = _TOKEN_ENCODING.encode(answer, disallowed_special=())
+        tokens_per_second = max(
+            1,
+            min(_MAX_TOKENS_PER_SECOND, self.tokens_per_second),
+        )
+        chunk_size = max(
+            1,
+            min(
+                _MAX_TOKENS_PER_CHUNK,
+                math.ceil(tokens_per_second / _TARGET_CHUNKS_PER_SECOND),
+            ),
+        )
+        decoder = codecs.getincrementaldecoder("utf-8")()
+        token_groups = [token_ids[:1], *(token_ids[offset : offset + chunk_size] for offset in range(1, len(token_ids), chunk_size))]
+        for index, chunk_token_ids in enumerate(token_groups):
+            if index > 0:
+                await asyncio.sleep(len(chunk_token_ids) / tokens_per_second)
+            chunk_bytes = b"".join(_TOKEN_ENCODING.decode_single_token_bytes(token_id) for token_id in chunk_token_ids)
+            is_last = index == len(token_groups) - 1
+            content = decoder.decode(chunk_bytes, final=is_last)
+            chunk_kwargs = (
+                {
+                    "fixed_answer": True,
+                    "fixed_question_id": self.fixed_question_id,
+                    "tokens_per_second": tokens_per_second,
+                }
+                if index == 0
+                else {}
+            )
+            yield ChatGenerationChunk(
+                message=AIMessageChunk(
+                    content=content,
+                    id=self.message_id,
+                    additional_kwargs=chunk_kwargs,
+                )
+            )
+
+
+def _fallback_title(question: str) -> str:
+    if len(question) > 50:
+        return question[:50].rstrip() + "..."
+    return question or "New Conversation"
+
+
+def make_fixed_answer_agent(
+    *,
+    question: str,
+    answer: str,
+    fixed_question_id: str,
+    tokens_per_second: int = 100,
+):
+    """Build a one-node graph that streams and persists a fixed answer."""
+
+    tokens_per_second = max(
+        1,
+        min(_MAX_TOKENS_PER_SECOND, int(tokens_per_second)),
+    )
+    message_id = f"fixed-answer-{uuid.uuid4()}"
+    model = FixedAnswerChatModel(
+        answer=answer,
+        message_id=message_id,
+        fixed_question_id=fixed_question_id,
+        tokens_per_second=tokens_per_second,
+    ).with_config(tags=["fixed-answer"])
+
+    async def respond(
+        state: ThreadState,
+        config: RunnableConfig,
+    ) -> dict[str, Any]:
+        messages: Sequence[BaseMessage] = state.get("messages", [])
+        # Calling the local model through ``astream`` makes the runtime publish
+        # normal messages-mode chunks. The full AIMessage returned below is the
+        # durable checkpoint value used on refresh/history reads.
+        async for _chunk in model.astream(list(messages), config=config):
+            pass
+        update: dict[str, Any] = {
+            "messages": [
+                AIMessage(
+                    content=answer,
+                    id=message_id,
+                    additional_kwargs={
+                        "fixed_answer": True,
+                        "fixed_question_id": fixed_question_id,
+                        "tokens_per_second": tokens_per_second,
+                    },
+                )
+            ]
+        }
+        if not state.get("title"):
+            update["title"] = _fallback_title(question)
+            update["title_provisional"] = False
+        elif state.get("title_provisional") is True:
+            # A fixed-answer run must not trigger the worker's background LLM
+            # title finalizer either; keep the already-visible local title.
+            update["title_provisional"] = False
+        return update
+
+    graph = StateGraph(ThreadState)
+    graph.add_node("fixed_answer", respond)
+    graph.add_edge(START, "fixed_answer")
+    graph.add_edge("fixed_answer", END)
+    return graph.compile()

offline-backend-20260512/backend/packages/harness/deerflow/agents/lead_agent/prompt.py

@@ -271,7 +271,42 @@ answers — and never create a skill silently without user confirmation.
 """
 
 
-def _build_available_subagents_description(available_names: list[str], bash_available: bool, *, app_config: AppConfig | None = None) -> str:
+def _build_es_query_routing_section(
+    *,
+    app_config: AppConfig | None = None,
+    available_skills: set[str] | None = None,
+) -> str:
+    """Return the configurable ``es_query`` routing rule for the system prompt.
+
+    A custom agent with an explicit skill allowlist only receives the rule when
+    ``es_query`` is in that allowlist. The default lead agent has no allowlist,
+    so the operator-controlled config switch is authoritative there.
+    """
+    if available_skills is not None and "es_query" not in available_skills:
+        return ""
+
+    config = app_config
+    if config is None:
+        try:
+            from deerflow.config import get_app_config
+
+            config = get_app_config()
+        except Exception:
+            logger.debug("Failed to load es_query routing config", exc_info=True)
+            return ""
+
+    routing = getattr(getattr(config, "skills", None), "es_query_routing", None)
+    if routing is None or not routing.enabled:
+        return ""
+
+    prompt = (routing.prompt or "").strip()
+    if not prompt:
+        return ""
+
+    return f'<skill_routing skill="es_query">\n{prompt}\n</skill_routing>'
+
+
+def _build_available_subagents_description(available_names: list[str], bash_available: bool, *, app_config: AppConfig | None = None) -> str:
     """Dynamically build subagent type descriptions from registry.
 
     Mirrors Codex's pattern where agent_type_description is dynamically generated
@@ -548,9 +583,11 @@ User: "staging"
 You: "Deploying to staging..." [proceed]
 </clarification_system>
 
-{skills_section}
+{skills_section}
-
+
-{bootstrap_section}
+{es_query_routing_section}
+
+{bootstrap_section}
 
 {deferred_tools_section}
 
@@ -663,10 +700,12 @@ combined with a FastAPI gateway for REST API access [citation:FastAPI](https://f
 # style, clarification system, citation rules, response-style / critical-reminder
 # defaults) and no personal memory injection. Only the mechanical sections an
 # agent still needs to actually use its configured skills/tools are kept.
-AGENT_ONLY_PROMPT_TEMPLATE = """{soul}
+AGENT_ONLY_PROMPT_TEMPLATE = """{soul}
-{network_policy_section}{skills_section}
+{network_policy_section}{skills_section}
-
+
-{deferred_tools_section}
+{es_query_routing_section}
+
+{deferred_tools_section}
 
 {writing_mode_section}
 
@@ -719,12 +758,16 @@ def apply_agent_only_prompt_template(
 
     soul = get_agent_soul(storage_agent_id)
 
-    skills_section = get_skills_prompt_section(
+    skills_section = get_skills_prompt_section(
-        available_skills,
+        available_skills,
-        app_config=app_config,
+        app_config=app_config,
-        display_enabled=rag_mode_enabled,
+        display_enabled=rag_mode_enabled,
-    )
+    )
-    deferred_tools_section = get_deferred_tools_prompt_section(app_config=app_config)
+    es_query_routing_section = _build_es_query_routing_section(
+        app_config=app_config,
+        available_skills=available_skills,
+    )
+    deferred_tools_section = get_deferred_tools_prompt_section(app_config=app_config)
 
     n = max_concurrent_subagents
     subagent_section = _build_subagent_section(n, app_config=app_config) if subagent_enabled else ""
@@ -766,9 +809,10 @@ RAG/reference display mode is enabled.
     )
 
     prompt = AGENT_ONLY_PROMPT_TEMPLATE.format(
-        soul=soul,
+        soul=soul,
-        skills_section=skills_section,
+        skills_section=skills_section,
-        deferred_tools_section=deferred_tools_section,
+        es_query_routing_section=es_query_routing_section,
+        deferred_tools_section=deferred_tools_section,
         writing_mode_section=writing_mode_section,
         subagent_section=subagent_section,
         network_policy_section=network_policy_section,
@@ -1377,11 +1421,15 @@ def apply_prompt_template(
     bootstrap_section = _build_bootstrap_section() if is_bootstrap else ""
 
     # Get skills section
-    skills_section = get_skills_prompt_section(
+    skills_section = get_skills_prompt_section(
-        available_skills,
+        available_skills,
-        app_config=app_config,
+        app_config=app_config,
-        display_enabled=rag_mode_enabled,
+        display_enabled=rag_mode_enabled,
-    )
+    )
+    es_query_routing_section = _build_es_query_routing_section(
+        app_config=app_config,
+        available_skills=available_skills,
+    )
 
     # Get deferred tools section (tool_search)
     deferred_tools_section = get_deferred_tools_prompt_section(app_config=app_config)
@@ -1438,9 +1486,10 @@ When a search, knowledge, skill, or MCP tool returns a result list:
     # Format the prompt with dynamic skills and memory
     prompt = SYSTEM_PROMPT_TEMPLATE.format(
         agent_name=agent_name or storage_agent_id or "CM 助手",
-        soul=get_agent_soul(storage_agent_id),
+        soul=get_agent_soul(storage_agent_id),
-        skills_section=skills_section,
+        skills_section=skills_section,
-        bootstrap_section=bootstrap_section,
+        es_query_routing_section=es_query_routing_section,
+        bootstrap_section=bootstrap_section,
         deferred_tools_section=deferred_tools_section,
         writing_mode_section=writing_mode_section,
         memory_context=memory_context,

offline-backend-20260512/backend/packages/harness/deerflow/config/llmwiki_config.py

@@ -10,7 +10,7 @@ from __future__ import annotations
 from dataclasses import dataclass
 from urllib.parse import urlsplit, urlunsplit
 
-from pydantic import BaseModel, ConfigDict, Field, field_validator
+from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
 
 
 def normalize_service_url(value: str | None) -> str:
@@ -37,18 +37,12 @@ class WeKnoraConnectionConfig(BaseModel):
     web_base_url: str = Field(default="", description="Optional internal WeKnora administration URL")
     admin_email: str = Field(
         default="",
-        description=(
+        description=("Optional WeKnora administrator email used by DeerFlow's server-side WeKnora API client and detail-page iframe proxy. Prefer $ENV references."),
-            "Optional WeKnora administrator email used by DeerFlow's server-side "
-            "WeKnora API client and detail-page iframe proxy. Prefer $ENV references."
-        ),
     )
     admin_password: str = Field(
         default="",
         repr=False,
-        description=(
+        description=("Optional WeKnora administrator password used by DeerFlow's server-side WeKnora API client and detail-page iframe proxy. Prefer $ENV references."),
-            "Optional WeKnora administrator password used by DeerFlow's server-side "
-            "WeKnora API client and detail-page iframe proxy. Prefer $ENV references."
-        ),
     )
     model_config = ConfigDict(extra="ignore")
 
@@ -58,10 +52,107 @@ class WeKnoraConnectionConfig(BaseModel):
         return normalize_service_url(value)
 
 
+class LocalWikiEmbeddingConfig(BaseModel):
+    enabled: bool = True
+    provider: str = "openai"
+    model: str = "bge-m3"
+    base_url: str = ""
+    api_key: str = Field(default="", repr=False)
+    dimensions: int | None = Field(default=1024, ge=1, le=65536)
+    batch_size: int = Field(default=32, ge=1, le=512)
+    timeout_seconds: float = Field(default=30, gt=0, le=300)
+    max_retries: int = Field(default=3, ge=0, le=10)
+    model_config = ConfigDict(extra="ignore")
+
+    @field_validator("provider")
+    @classmethod
+    def _validate_provider(cls, value: str) -> str:
+        normalized = value.strip().lower()
+        if normalized not in {"openai", "openai_compatible"}:
+            raise ValueError("local Wiki embedding provider must be openai or openai_compatible")
+        return normalized
+
+    @field_validator("base_url")
+    @classmethod
+    def _validate_url(cls, value: str) -> str:
+        return normalize_service_url(value)
+
+
+class LocalWikiExternalApiConfig(BaseModel):
+    enabled: bool = False
+    api_key: str = Field(default="", repr=False)
+    previous_api_key: str = Field(default="", repr=False)
+    max_query_chars: int = Field(default=1000, ge=1, le=10000)
+    max_knowledge_bases: int = Field(default=20, ge=1, le=100)
+    max_results: int = Field(default=50, ge=1, le=100)
+    default_results: int = Field(default=10, ge=1, le=100)
+    include_content_max_chars: int = Field(default=12000, ge=0, le=1_000_000)
+    requests_per_minute: int = Field(default=60, ge=1, le=100000)
+    model_config = ConfigDict(extra="ignore")
+
+    @model_validator(mode="after")
+    def _validate_enabled_key(self):
+        if self.enabled and not self.api_key.strip():
+            raise ValueError("llmwiki.local_wiki_index.external_api.api_key is required when external API is enabled")
+        if self.default_results > self.max_results:
+            raise ValueError("external_api.default_results must not exceed max_results")
+        return self
+
+
+class LocalWikiIndexConfig(BaseModel):
+    """DeerFlow-owned mirror and exact-vector index for WeKnora Wiki pages."""
+
+    enabled: bool = False
+    sync_enabled: bool = False
+    internal_search_enabled: bool = False
+    reference_ui_enabled: bool = False
+    sync_interval_seconds: int = Field(default=120, ge=10, le=86400)
+    sync_page_size: int = Field(default=100, ge=1, le=500)
+    sync_concurrency: int = Field(default=3, ge=1, le=32)
+    sync_lease_seconds: int = Field(default=600, ge=30, le=86400)
+    sync_request_timeout_seconds: float = Field(default=30, gt=0, le=300)
+    sync_max_retries: int = Field(default=3, ge=0, le=10)
+    sync_retry_backoff_seconds: float = Field(default=5, ge=0, le=300)
+    chunk_max_chars: int = Field(default=1000, ge=100, le=20000)
+    chunk_overlap_chars: int = Field(default=120, ge=0, le=10000)
+    chunk_min_chars: int = Field(default=80, ge=1, le=10000)
+    title_prefix_enabled: bool = True
+    embedding: LocalWikiEmbeddingConfig = Field(default_factory=LocalWikiEmbeddingConfig)
+    engine: str = "numpy_exact"
+    strict_vector: bool = True
+    top_k_sections: int = Field(default=30, ge=1, le=1000)
+    top_k_pages: int = Field(default=8, ge=1, le=100)
+    max_sections_per_page: int = Field(default=2, ge=1, le=20)
+    min_similarity: float = Field(default=0.35, ge=-1, le=1)
+    keyword_boost_enabled: bool = False
+    keyword_boost_weight: float = Field(default=0.15, ge=0, le=1)
+    cache_max_knowledge_bases: int = Field(default=20, ge=1, le=1000)
+    cache_revision_check_seconds: float = Field(default=5, ge=0, le=3600)
+    external_api: LocalWikiExternalApiConfig = Field(default_factory=LocalWikiExternalApiConfig)
+    model_config = ConfigDict(extra="ignore")
+
+    @model_validator(mode="after")
+    def _validate_index(self):
+        if self.chunk_overlap_chars >= self.chunk_max_chars:
+            raise ValueError("chunk_overlap_chars must be smaller than chunk_max_chars")
+        if self.chunk_min_chars > self.chunk_max_chars:
+            raise ValueError("chunk_min_chars must not exceed chunk_max_chars")
+        if self.top_k_pages > self.top_k_sections:
+            raise ValueError("top_k_pages must not exceed top_k_sections")
+        if self.engine != "numpy_exact":
+            raise ValueError("Only the numpy_exact local Wiki vector engine is currently supported")
+        if self.enabled and not self.embedding.enabled:
+            raise ValueError("local Wiki index embedding must be enabled when the index is enabled")
+        if self.enabled and (not self.embedding.base_url or not self.embedding.model.strip()):
+            raise ValueError("local Wiki index embedding base_url and model are required when enabled")
+        return self
+
+
 class LlmWikiConfig(BaseModel):
     """Top-level ``config.yaml`` section for conditional WeKnora mode."""
 
     weknora: WeKnoraConnectionConfig = Field(default_factory=WeKnoraConnectionConfig)
+    local_wiki_index: LocalWikiIndexConfig = Field(default_factory=LocalWikiIndexConfig)
     model_config = ConfigDict(extra="ignore")
 
 

offline-backend-20260512/backend/packages/harness/deerflow/config/skills_config.py

@@ -5,8 +5,26 @@ from pydantic import BaseModel, Field
 
 from deerflow.config.runtime_paths import project_root, resolve_path
 
-
+DEFAULT_ES_QUERY_ROUTING_PROMPT = """当用户的问题需要基于 Elasticsearch 查询语句（Query DSL）灵活构造、调整或执行查询时，必须优先使用 `es_query` 技能。
-class SecurityScanConfig(BaseModel):
+典型场景包括：根据用户条件动态组合 bool/must/filter/should、范围、聚合、排序或分页等 ES 查询；或者用户直接提供、要求修改 ES 语句并据此查询数据。
+执行前先读取 `es_query` 技能的 SKILL.md，严格按照技能中的流程和参数调用；不要用通用搜索替代，也不要凭记忆臆测查询结果。
+仅当问题确实需要 ES 数据查询时使用；纯概念解释、普通代码说明或与 ES 无关的问题不要调用。"""
+
+
+class EsQueryRoutingConfig(BaseModel):
+    """Prompt steering that routes flexible Elasticsearch queries to ``es_query``."""
+
+    enabled: bool = Field(
+        default=False,
+        description="Inject the es_query routing prompt into the agent system prompt.",
+    )
+    prompt: str = Field(
+        default=DEFAULT_ES_QUERY_ROUTING_PROMPT,
+        description="Editable system-prompt instructions for deciding when and how to use es_query.",
+    )
+
+
+class SecurityScanConfig(BaseModel):
     """Toggle for the LLM-based skill security scanner."""
 
     enabled: bool = Field(
@@ -33,10 +51,14 @@ class SkillsConfig(BaseModel):
         default="/mnt/skills",
         description="Path where skills are mounted in the sandbox container",
     )
-    security_scan: SecurityScanConfig = Field(
+    security_scan: SecurityScanConfig = Field(
-        default_factory=SecurityScanConfig,
+        default_factory=SecurityScanConfig,
-        description="LLM security-scan toggle for skill content.",
+        description="LLM security-scan toggle for skill content.",
-    )
+    )
+    es_query_routing: EsQueryRoutingConfig = Field(
+        default_factory=EsQueryRoutingConfig,
+        description="Optional configurable routing prompt for the es_query skill.",
+    )
 
     def get_skills_path(self) -> Path:
         """

offline-backend-20260512/backend/packages/harness/deerflow/integrations/weknora/local_index/__init__.py

@@ -0,0 +1,7 @@
+"""DeerFlow-local mirror and Wiki-only retrieval for WeKnora Wiki pages."""
+
+from deerflow.integrations.weknora.local_index.retrieval import WikiRetrievalService, is_fully_vectorized
+from deerflow.integrations.weknora.local_index.search import WikiIndexError, WikiVectorSearchService
+from deerflow.integrations.weknora.local_index.sync import WikiSyncService
+
+__all__ = ["WikiIndexError", "WikiRetrievalService", "WikiVectorSearchService", "WikiSyncService", "is_fully_vectorized"]

offline-backend-20260512/backend/packages/harness/deerflow/integrations/weknora/local_index/chunking.py

@@ -0,0 +1,108 @@
+"""Markdown-aware Wiki section chunking."""
+
+from __future__ import annotations
+
+import hashlib
+import re
+from dataclasses import dataclass
+
+_FRONTMATTER_RE = re.compile(r"\A\s*---\s*\n.*?\n---\s*(?:\n|\Z)", re.DOTALL)
+_SCRIPT_STYLE_RE = re.compile(r"<\s*(script|style)\b[^>]*>.*?<\s*/\s*\1\s*>", re.IGNORECASE | re.DOTALL)
+_IMAGE_RE = re.compile(r"!\[([^\]]*)\]\([^)]*\)")
+_HEADING_RE = re.compile(r"^(#{1,6})\s+(.+?)\s*$")
+
+
+@dataclass(frozen=True)
+class WikiSection:
+    section_index: int
+    heading: str | None
+    content: str
+    embedding_text: str
+    content_hash: str
+
+
+def _clean_markdown(value: str) -> str:
+    text = value.replace("\r\n", "\n")
+    text = _FRONTMATTER_RE.sub("", text)
+    text = _SCRIPT_STYLE_RE.sub("", text)
+    text = _IMAGE_RE.sub(lambda match: match.group(1), text)
+    return re.sub(r"\n{3,}", "\n\n", text).strip()
+
+
+def _windows(text: str, max_chars: int, overlap: int) -> list[str]:
+    paragraphs = [part.strip() for part in re.split(r"\n\s*\n", text) if part.strip()]
+    chunks: list[str] = []
+    buffer = ""
+    for paragraph in paragraphs:
+        if len(buffer) + len(paragraph) + 2 <= max_chars:
+            buffer = f"{buffer}\n\n{paragraph}".strip()
+            continue
+        if buffer:
+            chunks.append(buffer)
+            buffer = ""
+        if len(paragraph) <= max_chars:
+            buffer = paragraph
+            continue
+        step = max(1, max_chars - overlap)
+        chunks.extend(paragraph[start : start + max_chars] for start in range(0, len(paragraph), step))
+    if buffer:
+        chunks.append(buffer)
+    return chunks
+
+
+def chunk_wiki_page(
+    page: dict,
+    *,
+    max_chars: int,
+    overlap: int,
+    min_chars: int,
+    title_prefix_enabled: bool,
+) -> list[WikiSection]:
+    content = _clean_markdown(str(page.get("content_md") or ""))
+    heading_stack: list[str] = []
+    sections: list[tuple[str | None, str]] = []
+    current_heading: str | None = None
+    body: list[str] = []
+    for line in content.splitlines():
+        match = _HEADING_RE.match(line)
+        if not match:
+            body.append(line)
+            continue
+        if any(item.strip() for item in body):
+            sections.append((current_heading, "\n".join(body).strip()))
+        level = len(match.group(1))
+        heading_stack = heading_stack[: level - 1]
+        heading_stack.append(match.group(2).strip())
+        current_heading = " / ".join(heading_stack)
+        body = []
+    if any(item.strip() for item in body):
+        sections.append((current_heading, "\n".join(body).strip()))
+    if content and not sections:
+        sections.append((None, content))
+    summary = _clean_markdown(str(page.get("summary") or ""))
+    if summary:
+        sections.insert(0, ("页面摘要", summary))
+
+    prefix_lines = [f"页面：{page.get('title') or page.get('slug') or ''}"]
+    aliases = [str(item) for item in page.get("aliases") or [] if str(item).strip()]
+    if aliases:
+        prefix_lines.append(f"别名：{'、'.join(aliases)}")
+    if page.get("page_type"):
+        prefix_lines.append(f"类型：{page['page_type']}")
+    seen: set[str] = set()
+    result: list[WikiSection] = []
+    for heading, section_text in sections:
+        for chunk in _windows(section_text, max_chars, overlap):
+            normalized = re.sub(r"\s+", " ", chunk).strip()
+            if len(normalized) < min_chars and len(sections) > 1:
+                continue
+            digest = hashlib.sha256(normalized.encode("utf-8")).hexdigest()
+            if digest in seen:
+                continue
+            seen.add(digest)
+            context = list(prefix_lines) if title_prefix_enabled else []
+            if heading:
+                context.append(f"章节：{heading}")
+            embedding_text = "\n".join([*context, "", chunk]).strip()
+            result.append(WikiSection(len(result), heading, chunk, embedding_text, digest))
+    return result

offline-backend-20260512/backend/packages/harness/deerflow/integrations/weknora/local_index/embedding.py

@@ -0,0 +1,107 @@
+"""Strict OpenAI-compatible embedding client for the Wiki index."""
+
+from __future__ import annotations
+
+import asyncio
+import hashlib
+import logging
+from time import monotonic
+
+import httpx
+
+from deerflow.config.llmwiki_config import LocalWikiEmbeddingConfig
+from deerflow.integrations.weknora.local_index.vector_codec import normalize_vector
+
+logger = logging.getLogger(__name__)
+
+
+class WikiEmbeddingError(RuntimeError):
+    def __init__(self, message: str, *, category: str = "request", retryable: bool = True) -> None:
+        super().__init__(message)
+        self.category = category
+        self.retryable = retryable
+
+
+class StrictWikiEmbeddingClient:
+    def __init__(self, config: LocalWikiEmbeddingConfig, *, http_client: httpx.AsyncClient | None = None) -> None:
+        self.config = config
+        self._client = http_client
+        self._owns_client = http_client is None
+        self._resolved_dimensions = config.dimensions
+
+    @property
+    def dimensions(self) -> int | None:
+        return self._resolved_dimensions
+
+    @property
+    def fingerprint(self) -> str:
+        raw = "\0".join((self.config.provider.strip().lower(), self.config.base_url.rstrip("/").lower(), self.config.model.strip(), str(self._resolved_dimensions or "auto")))
+        return hashlib.sha256(raw.encode("utf-8")).hexdigest()
+
+    async def close(self) -> None:
+        if self._owns_client and self._client is not None:
+            await self._client.aclose()
+            self._client = None
+
+    async def _get_client(self) -> httpx.AsyncClient:
+        if self._client is None:
+            self._client = httpx.AsyncClient(timeout=self.config.timeout_seconds)
+        return self._client
+
+    async def embed_texts(self, texts: list[str]) -> list[list[float]]:
+        if not self.config.enabled or not self.config.base_url or not self.config.model:
+            raise WikiEmbeddingError("Wiki embedding is not configured", category="configuration", retryable=False)
+        if not texts:
+            return []
+        vectors: list[list[float]] = []
+        batch_size = max(1, self.config.batch_size)
+        for start in range(0, len(texts), batch_size):
+            vectors.extend(await self._embed_batch(texts[start : start + batch_size]))
+        if len(vectors) != len(texts):
+            raise WikiEmbeddingError("Embedding response count does not match request", category="response", retryable=False)
+        return vectors
+
+    async def _embed_batch(self, texts: list[str]) -> list[list[float]]:
+        url = self.config.base_url.rstrip("/") + "/embeddings"
+        headers = {"Content-Type": "application/json"}
+        if self.config.api_key:
+            headers["Authorization"] = f"Bearer {self.config.api_key}"
+        payload: dict = {"model": self.config.model, "input": texts}
+        if self.config.dimensions:
+            payload["dimensions"] = self.config.dimensions
+        last_error: WikiEmbeddingError | None = None
+        for attempt in range(self.config.max_retries + 1):
+            started = monotonic()
+            try:
+                response = await (await self._get_client()).post(url, headers=headers, json=payload)
+                if response.status_code in {401, 403}:
+                    raise WikiEmbeddingError("Embedding authentication failed", category="authentication", retryable=False)
+                if response.status_code == 429 or response.status_code >= 500:
+                    raise WikiEmbeddingError(f"Embedding service returned HTTP {response.status_code}", category="upstream", retryable=True)
+                response.raise_for_status()
+                data = response.json()
+                items = sorted(data.get("data", []), key=lambda item: int(item.get("index", 0))) if isinstance(data, dict) else []
+                if len(items) != len(texts):
+                    raise WikiEmbeddingError("Embedding response count mismatch", category="response", retryable=False)
+                result: list[list[float]] = []
+                for item in items:
+                    vector = normalize_vector(item.get("embedding") or [], dimensions=self._resolved_dimensions)
+                    if self._resolved_dimensions is None:
+                        self._resolved_dimensions = int(vector.size)
+                    result.append(vector.astype(float).tolist())
+                logger.info("Wiki embedding batch completed model=%s batch=%d duration_ms=%d", self.config.model, len(texts), int((monotonic() - started) * 1000))
+                return result
+            except WikiEmbeddingError as exc:
+                last_error = exc
+            except httpx.TimeoutException:
+                last_error = WikiEmbeddingError("Embedding request timed out", category="timeout", retryable=True)
+            except (httpx.HTTPError, ValueError, TypeError) as exc:
+                last_error = WikiEmbeddingError(f"Embedding request failed ({type(exc).__name__})", category="request", retryable=isinstance(exc, httpx.HTTPError))
+            if last_error is not None and (not last_error.retryable or attempt >= self.config.max_retries):
+                raise last_error
+            await asyncio.sleep(min(30.0, 0.5 * (2**attempt)))
+        raise last_error or WikiEmbeddingError("Embedding request failed")
+
+    async def embed_query(self, text: str) -> list[float]:
+        result = await self.embed_texts([text])
+        return result[0]

offline-backend-20260512/backend/packages/harness/deerflow/integrations/weknora/local_index/normalize.py

@@ -0,0 +1,86 @@
+"""Normalize unstable WeKnora Wiki response shapes into the local contract."""
+
+from __future__ import annotations
+
+import hashlib
+import json
+import re
+from datetime import datetime
+from typing import Any
+from urllib.parse import unquote
+
+
+def normalize_slug(value: Any) -> str:
+    slug = unquote(str(value or "")).replace("\\", "/").strip().strip("/")
+    slug = re.sub(r"/{2,}", "/", slug)
+    if not slug:
+        raise ValueError("Wiki page slug is empty")
+    return slug
+
+
+def slug_hash(slug: str) -> str:
+    return hashlib.sha256(normalize_slug(slug).encode("utf-8")).hexdigest()
+
+
+def _list(value: Any) -> list:
+    if isinstance(value, list):
+        return value
+    if isinstance(value, tuple):
+        return list(value)
+    if isinstance(value, str) and value.strip():
+        return [value.strip()]
+    return []
+
+
+def _datetime(value: Any) -> datetime | None:
+    if isinstance(value, datetime):
+        return value
+    raw = str(value or "").strip()
+    if not raw:
+        return None
+    try:
+        return datetime.fromisoformat(raw.replace("Z", "+00:00"))
+    except ValueError:
+        return None
+
+
+def normalize_wiki_page(mapping_id: str, remote: dict[str, Any]) -> dict[str, Any]:
+    slug = normalize_slug(remote.get("slug") or remote.get("wiki_slug") or remote.get("path"))
+    aliases = sorted({str(item).strip() for item in _list(remote.get("aliases")) if str(item).strip()})
+    category_path = [str(item).strip() for item in _list(remote.get("category_path") or remote.get("categories")) if str(item).strip()]
+    title = str(remote.get("title") or slug.rsplit("/", 1)[-1]).strip()
+    summary = str(remote.get("summary") or remote.get("description") or "").replace("\r\n", "\n").strip()
+    content = str(remote.get("content_md") or remote.get("content") or remote.get("markdown") or "").replace("\r\n", "\n").strip()
+    status = str(remote.get("status") or "published").strip().lower()
+    if status not in {"draft", "published", "archived"}:
+        status = "published"
+    hash_payload = {
+        "title": title,
+        "aliases": aliases,
+        "summary": summary,
+        "content_md": content,
+        "page_type": str(remote.get("page_type") or remote.get("type") or "article").strip().lower(),
+        "status": status,
+    }
+    content_hash = hashlib.sha256(json.dumps(hash_payload, ensure_ascii=False, sort_keys=True, separators=(",", ":")).encode("utf-8")).hexdigest()
+    return {
+        "knowledge_base_mapping_id": mapping_id,
+        "remote_page_id": str(remote.get("id") or remote.get("page_id") or "").strip() or None,
+        "slug": slug,
+        "slug_hash": slug_hash(slug),
+        "title": title,
+        "summary": summary,
+        "content_md": content,
+        "page_type": hash_payload["page_type"],
+        "status": status,
+        "aliases": aliases,
+        "category_path": category_path,
+        "parent_slug": str(remote.get("parent_slug") or "").strip() or None,
+        "wiki_path": str(remote.get("wiki_path") or remote.get("path") or "").strip() or None,
+        "source_refs": _list(remote.get("source_refs") or remote.get("sources")),
+        "chunk_refs": _list(remote.get("chunk_refs") or remote.get("chunks")),
+        "page_version": int(remote.get("page_version") or remote.get("version") or 0),
+        "content_hash": content_hash,
+        "remote_created_at": _datetime(remote.get("created_at") or remote.get("createdAt")),
+        "remote_updated_at": _datetime(remote.get("updated_at") or remote.get("updatedAt")),
+    }

offline-backend-20260512/backend/packages/harness/deerflow/integrations/weknora/local_index/retrieval.py

@@ -0,0 +1,248 @@
+"""Wiki-only retrieval with local-vector preference and remote Wiki fallback.
+
+The fallback deliberately calls WeKnora's ``/wiki/pages`` API.  It never calls
+the raw knowledge/chunk search endpoint, so callers always receive processed
+Wiki pages even while a whole knowledge base is awaiting vectorization.
+"""
+
+from __future__ import annotations
+
+import asyncio
+from typing import Any
+from urllib.parse import urlencode
+
+from deerflow.integrations.weknora.client import WeKnoraClient
+from deerflow.integrations.weknora.local_index.normalize import normalize_wiki_page
+from deerflow.integrations.weknora.local_index.search import WikiIndexError, WikiVectorSearchService
+from deerflow.persistence.llmwiki_index import LlmWikiIndexStore
+
+
+def is_fully_vectorized(state: dict[str, Any] | None, fingerprint: str | None) -> bool:
+    """Return whether a completed full scan produced one coherent active index."""
+
+    if not state or not fingerprint:
+        return False
+    if str(state.get("state") or "") != "idle" or not state.get("last_success_at"):
+        return False
+    if str(state.get("embedding_fingerprint") or "") != fingerprint:
+        return False
+    local_count = int(state.get("local_page_count") or 0)
+    ready_count = int(state.get("ready_page_count") or 0)
+    failed_count = int(state.get("failed_page_count") or 0)
+    vector_count = int(state.get("vector_count") or 0)
+    if failed_count or ready_count != local_count:
+        return False
+    return local_count == 0 or vector_count > 0
+
+
+class WikiRetrievalService:
+    """Search complete indexes locally and incomplete indexes through Wiki API."""
+
+    def __init__(
+        self,
+        store: LlmWikiIndexStore,
+        *,
+        vector_search: WikiVectorSearchService | None,
+        client: WeKnoraClient | None,
+    ) -> None:
+        self.store = store
+        self.vector_search = vector_search
+        self.client = client
+
+    async def search(
+        self,
+        query: str,
+        mappings: list[dict[str, Any]],
+        *,
+        top_k_pages: int = 8,
+        include_drafts: bool = False,
+    ) -> dict[str, Any]:
+        normalized_query = query.strip()
+        if not normalized_query:
+            raise WikiIndexError("WIKI_QUERY_EMPTY", "Search query is empty", status_code=400)
+        if not mappings:
+            return {
+                "query": normalized_query,
+                "mode": "wiki_api",
+                "results": [],
+                "knowledge_base_count": 0,
+                "partial": False,
+                "warnings": [],
+                "fallback_knowledge_base_ids": [],
+            }
+
+        vector_mappings, fallback_mappings = await self._partition_mappings(mappings)
+        results: list[dict[str, Any]] = []
+        warnings: list[str] = []
+        vector_used = False
+        fallback_used = False
+
+        if vector_mappings and self.vector_search is not None:
+            try:
+                payload = await self.vector_search.search(
+                    normalized_query,
+                    vector_mappings,
+                    top_k_pages=max(top_k_pages, len(vector_mappings)),
+                    include_drafts=include_drafts,
+                )
+                results.extend(payload.get("results") or [])
+                warnings.extend(str(item) for item in payload.get("warnings") or [])
+                vector_used = True
+            except WikiIndexError as exc:
+                # A status row can become stale between classification and
+                # matrix loading. Wiki API remains a safe Wiki-only fallback.
+                warnings.append(f"local_vector:{exc.code}")
+                fallback_mappings.extend(vector_mappings)
+                vector_mappings = []
+
+        fallback_ids = [str(mapping["id"]) for mapping in fallback_mappings]
+        if fallback_mappings:
+            if self.client is None:
+                warnings.extend(f"{mapping['id']}:WIKI_API_UNAVAILABLE" for mapping in fallback_mappings)
+            else:
+                batches = await asyncio.gather(
+                    *(
+                        self._search_remote_mapping(
+                            normalized_query,
+                            mapping,
+                            limit=max(top_k_pages, 1),
+                            include_drafts=include_drafts,
+                        )
+                        for mapping in fallback_mappings
+                    ),
+                    return_exceptions=True,
+                )
+                for mapping, batch in zip(fallback_mappings, batches, strict=True):
+                    if isinstance(batch, Exception):
+                        warnings.append(f"{mapping['id']}:WIKI_API_SEARCH_FAILED")
+                    else:
+                        results.extend(batch)
+                        fallback_used = True
+
+        if warnings and not results and not vector_used and not fallback_used:
+            raise WikiIndexError(
+                "WIKI_API_UNAVAILABLE",
+                "Wiki page retrieval is unavailable",
+                status_code=502 if self.client is not None else 503,
+            )
+
+        # De-duplicate by the public Wiki citation identity. Vector scores and
+        # Wiki-API rank scores are both descending relevance hints.
+        unique: dict[tuple[str, str], dict[str, Any]] = {}
+        for item in results:
+            key = (str(item.get("knowledge_base_id") or ""), str(item.get("wiki_slug") or item.get("id") or ""))
+            current = unique.get(key)
+            if current is None or float(item.get("score") or 0) > float(current.get("score") or 0):
+                unique[key] = item
+        ranked = sorted(unique.values(), key=lambda item: float(item.get("score") or 0), reverse=True)
+        mode = "mixed" if vector_used and fallback_used else "vector" if vector_used else "wiki_api"
+        fingerprint = self.vector_search.embedding.fingerprint[:12] if vector_used and self.vector_search is not None else None
+        return {
+            "query": normalized_query,
+            "mode": mode,
+            "results": ranked[:top_k_pages],
+            "knowledge_base_count": len(mappings),
+            "index_fingerprint": fingerprint,
+            "partial": bool(warnings),
+            "warnings": warnings,
+            "fallback_knowledge_base_ids": fallback_ids,
+        }
+
+    async def _partition_mappings(self, mappings: list[dict[str, Any]]) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
+        if self.vector_search is None:
+            return [], list(mappings)
+        mapping_ids = [str(mapping["id"]) for mapping in mappings]
+        states = {
+            str(state["knowledge_base_mapping_id"]): state
+            for state in await self.store.list_index_status(mapping_ids)
+        }
+        fingerprint = self.vector_search.embedding.fingerprint
+        vector_mappings = [
+            mapping
+            for mapping in mappings
+            if mapping.get("wiki_index_enabled", True)
+            and is_fully_vectorized(states.get(str(mapping["id"])), fingerprint)
+        ]
+        ready_ids = {str(mapping["id"]) for mapping in vector_mappings}
+        return vector_mappings, [mapping for mapping in mappings if str(mapping["id"]) not in ready_ids]
+
+    async def _search_remote_mapping(
+        self,
+        query: str,
+        mapping: dict[str, Any],
+        *,
+        limit: int,
+        include_drafts: bool,
+    ) -> list[dict[str, Any]]:
+        if self.client is None:
+            return []
+        remote_id = str(mapping["weknora_id"])
+        listing = await self.client.list_wiki_pages(
+            remote_id,
+            page=1,
+            page_size=min(max(limit * 3, 20), 100),
+            query=query,
+        )
+        summaries = [item for item in listing.get("pages", []) if isinstance(item, dict)]
+        slugs = list(
+            dict.fromkeys(
+                str(item.get("slug") or item.get("wiki_slug") or item.get("path") or "").strip("/")
+                for item in summaries
+                if str(item.get("slug") or item.get("wiki_slug") or item.get("path") or "").strip("/")
+            )
+        )[: max(limit * 2, limit)]
+        details = await asyncio.gather(
+            *(self.client.get_wiki_page(remote_id, slug) for slug in slugs),
+            return_exceptions=True,
+        )
+        results: list[dict[str, Any]] = []
+        for rank, (slug, detail) in enumerate(zip(slugs, details, strict=True)):
+            if isinstance(detail, Exception):
+                continue
+            try:
+                page = normalize_wiki_page(str(mapping["id"]), detail)
+            except (TypeError, ValueError):
+                continue
+            if page["status"] == "archived" or (page["status"] == "draft" and not include_drafts):
+                continue
+            params = urlencode({"knowledge_base_id": mapping["id"], "wiki_slug": slug})
+            content = str(page.get("content_md") or "")
+            score = float(detail.get("score") or max(0.01, 1.0 - rank * 0.05))
+            results.append(
+                {
+                    "kind": "wiki_page",
+                    "id": page.get("remote_page_id") or f"{mapping['id']}:{slug}",
+                    "knowledge_base_id": mapping["id"],
+                    "knowledge_base_name": mapping.get("name") or "",
+                    "wiki_page_id": page.get("remote_page_id") or f"{mapping['id']}:{slug}",
+                    "wiki_slug": slug,
+                    "title": page.get("title") or slug,
+                    "summary": page.get("summary") or "",
+                    "page_type": page.get("page_type") or "article",
+                    "page_version": int(page.get("page_version") or 0),
+                    "updated_at": page.get("remote_updated_at"),
+                    "score": score,
+                    "content": content,
+                    "snippet": content[:360],
+                    "matched_heading": None,
+                    "matched_sections": [
+                        {
+                            "section_index": 0,
+                            "heading": None,
+                            "content": content,
+                            "score": score,
+                        }
+                    ],
+                    "url": f"/weknora-source-preview?{params}",
+                    "source": mapping.get("name") or "LLMWiki",
+                    "type": "llmwiki_wiki",
+                    "mode": "citation",
+                    "retrieval_mode": "wiki_api",
+                }
+            )
+            if len(results) >= limit:
+                break
+        return results
+
+
+__all__ = ["WikiRetrievalService", "is_fully_vectorized"]

offline-backend-20260512/backend/packages/harness/deerflow/integrations/weknora/local_index/runtime.py

@@ -0,0 +1,48 @@
+"""App-to-harness runtime injection for local Wiki index services."""
+
+from __future__ import annotations
+
+from deerflow.integrations.weknora.local_index.retrieval import WikiRetrievalService
+from deerflow.integrations.weknora.local_index.search import WikiVectorSearchService
+from deerflow.integrations.weknora.local_index.sync import WikiSyncService
+from deerflow.persistence.llmwiki_index import LlmWikiIndexStore
+
+_store: LlmWikiIndexStore | None = None
+_search: WikiVectorSearchService | None = None
+_sync: WikiSyncService | None = None
+_retrieval: WikiRetrievalService | None = None
+
+
+def register_local_wiki_index_runtime(
+    *,
+    store: LlmWikiIndexStore | None,
+    search: WikiVectorSearchService | None,
+    sync: WikiSyncService | None,
+    retrieval: WikiRetrievalService | None = None,
+) -> None:
+    global _store, _search, _sync, _retrieval
+    _store, _search, _sync, _retrieval = store, search, sync, retrieval
+
+
+def get_local_wiki_index_store() -> LlmWikiIndexStore:
+    if _store is None:
+        raise RuntimeError("Local Wiki index store is not initialized")
+    return _store
+
+
+def get_local_wiki_search_service() -> WikiVectorSearchService:
+    if _search is None:
+        raise RuntimeError("Local Wiki vector search is not initialized")
+    return _search
+
+
+def get_local_wiki_sync_service() -> WikiSyncService:
+    if _sync is None:
+        raise RuntimeError("Local Wiki sync service is not initialized")
+    return _sync
+
+
+def get_local_wiki_retrieval_service() -> WikiRetrievalService:
+    if _retrieval is None:
+        raise RuntimeError("Wiki-only retrieval service is not initialized")
+    return _retrieval

offline-backend-20260512/backend/packages/harness/deerflow/integrations/weknora/local_index/search.py

@@ -0,0 +1,176 @@
+"""Unified exact-vector search over DeerFlow-local Wiki section snapshots."""
+
+from __future__ import annotations
+
+import asyncio
+import hashlib
+import re
+from collections import OrderedDict, defaultdict
+from time import monotonic
+from typing import Any
+from urllib.parse import urlencode
+
+import numpy as np
+
+from deerflow.config.llmwiki_config import LocalWikiIndexConfig
+from deerflow.integrations.weknora.local_index.embedding import StrictWikiEmbeddingClient, WikiEmbeddingError
+from deerflow.integrations.weknora.local_index.vector_cache import WikiVectorCache, WikiVectorSnapshot
+from deerflow.integrations.weknora.local_index.vector_codec import normalize_vector
+
+
+class WikiIndexError(RuntimeError):
+    def __init__(self, code: str, message: str, *, status_code: int) -> None:
+        super().__init__(message)
+        self.code = code
+        self.status_code = status_code
+
+
+class WikiVectorSearchService:
+    def __init__(self, config: LocalWikiIndexConfig, embedding: StrictWikiEmbeddingClient, cache: WikiVectorCache) -> None:
+        self.config = config
+        self.embedding = embedding
+        self.cache = cache
+        self._query_vectors: OrderedDict[str, tuple[float, np.ndarray]] = OrderedDict()
+
+    async def search(
+        self,
+        query: str,
+        mappings: list[dict[str, Any]],
+        *,
+        top_k_pages: int | None = None,
+        include_drafts: bool = False,
+        external: bool = False,
+    ) -> dict[str, Any]:
+        normalized_query = query.strip()
+        if not normalized_query:
+            raise WikiIndexError("WIKI_QUERY_EMPTY", "Search query is empty", status_code=400)
+        if not mappings:
+            return {"query": normalized_query, "mode": "vector", "results": [], "knowledge_base_count": 0, "index_fingerprint": self.embedding.fingerprint[:12], "partial": False, "warnings": []}
+        try:
+            query_vector = await self._embed_query(normalized_query)
+        except (WikiEmbeddingError, ValueError) as exc:
+            raise WikiIndexError("WIKI_EMBEDDING_UNAVAILABLE", str(exc), status_code=503) from None
+        fingerprint = self.embedding.fingerprint
+        tasks = [self._search_mapping(normalized_query, query_vector, mapping, fingerprint, include_drafts=include_drafts, external=external) for mapping in mappings]
+        batches = await asyncio.gather(*tasks, return_exceptions=True)
+        candidates: list[dict[str, Any]] = []
+        warnings: list[str] = []
+        for mapping, batch in zip(mappings, batches, strict=True):
+            if isinstance(batch, Exception):
+                warnings.append(f"{mapping.get('id')}: {batch}")
+            else:
+                candidates.extend(batch)
+        if warnings and not candidates and len(warnings) == len(mappings):
+            if any("FINGERPRINT" in item for item in warnings):
+                code = "WIKI_INDEX_FINGERPRINT_MISMATCH"
+            elif any("rebuild" in item.lower() for item in warnings):
+                code = "WIKI_INDEX_REBUILDING"
+            else:
+                code = "WIKI_INDEX_NOT_READY"
+            raise WikiIndexError(code, "Local Wiki index is not ready", status_code=409)
+        candidates.sort(key=lambda item: item["score"], reverse=True)
+        grouped: dict[tuple[str, str], list[dict[str, Any]]] = defaultdict(list)
+        for candidate in candidates:
+            page = candidate["page"]
+            key = (str(page["knowledge_base_mapping_id"]), str(page["id"]))
+            if len(grouped[key]) < self.config.max_sections_per_page:
+                grouped[key].append(candidate)
+        results: list[dict[str, Any]] = []
+        for sections in grouped.values():
+            first = sections[0]
+            page = first["page"]
+            mapping = first["mapping"]
+            second_score = sections[1]["score"] if len(sections) > 1 else 0.0
+            page_score = first["score"] + (0.05 * second_score if second_score else 0)
+            params = urlencode({"knowledge_base_id": mapping["id"], "wiki_slug": page["slug"]})
+            results.append(
+                {
+                    "kind": "wiki_page",
+                    "id": page["id"],
+                    "knowledge_base_id": mapping["id"],
+                    "knowledge_base_name": mapping.get("name") or "",
+                    "wiki_page_id": page["id"],
+                    "wiki_slug": page["slug"],
+                    "title": page.get("title") or page["slug"],
+                    "summary": page.get("summary") or "",
+                    "page_type": page.get("page_type") or "article",
+                    "page_version": int(page.get("page_version") or 0),
+                    "updated_at": page.get("remote_updated_at") or page.get("updated_at"),
+                    "score": float(page_score),
+                    "content": "\n\n".join(str(item["section_content"]) for item in sections),
+                    "snippet": str(sections[0]["section_content"])[:360],
+                    "matched_heading": sections[0].get("heading"),
+                    "matched_sections": [{"section_index": int(item["section_index"]), "heading": item.get("heading"), "content": item["section_content"], "score": float(item["score"])} for item in sections],
+                    "url": f"/weknora-source-preview?{params}",
+                    "source": mapping.get("name") or "LLMWiki",
+                    "type": "llmwiki_wiki",
+                    "mode": "citation",
+                }
+            )
+        results.sort(key=lambda item: item["score"], reverse=True)
+        limit = min(top_k_pages or self.config.top_k_pages, self.config.top_k_pages if top_k_pages is None else 50)
+        return {"query": normalized_query, "mode": "vector", "results": results[:limit], "knowledge_base_count": len(mappings), "index_fingerprint": fingerprint[:12], "partial": bool(warnings), "warnings": warnings}
+
+    async def _embed_query(self, query: str) -> np.ndarray:
+        digest = hashlib.sha256(query.encode("utf-8")).hexdigest()
+        key = f"{self.embedding.fingerprint}:{digest}"
+        cached = self._query_vectors.get(key)
+        if cached is not None and monotonic() - cached[0] <= 300:
+            self._query_vectors.move_to_end(key)
+            return cached[1]
+        vector = normalize_vector(await self.embedding.embed_query(query), dimensions=self.embedding.dimensions)
+        key = f"{self.embedding.fingerprint}:{digest}"
+        self._query_vectors[key] = (monotonic(), vector)
+        self._query_vectors.move_to_end(key)
+        while len(self._query_vectors) > 256:
+            self._query_vectors.popitem(last=False)
+        return vector
+
+    async def _search_mapping(self, query: str, vector: np.ndarray, mapping: dict[str, Any], fingerprint: str, *, include_drafts: bool, external: bool) -> list[dict[str, Any]]:
+        mapping_id = str(mapping["id"])
+        try:
+            snapshot = await self.cache.get(mapping_id, fingerprint)
+        except ValueError as exc:
+            await self.cache.store.mark_rebuild_required([mapping_id], fingerprint)
+            self.cache.invalidate(mapping_id)
+            raise RuntimeError("WIKI_INDEX_REBUILD_REQUIRED") from exc
+        if snapshot.matrix.size == 0:
+            return []
+        if snapshot.dimensions != vector.size:
+            raise RuntimeError("WIKI_INDEX_FINGERPRINT_MISMATCH")
+        eligible = np.asarray(
+            [
+                index
+                for index, row in enumerate(snapshot.rows)
+                if row["page"].get("status") != "draft" or (include_drafts and not external)
+            ],
+            dtype=int,
+        )
+        if eligible.size == 0:
+            return []
+        indices, scores = await asyncio.to_thread(self._top_indices, snapshot, vector, eligible)
+        terms = {term.lower() for term in re.findall(r"[\w\u4e00-\u9fff]{2,}", query)}
+        candidates = []
+        for index, score in zip(indices, scores, strict=True):
+            row = snapshot.rows[int(index)]
+            page = row["page"]
+            vector_score = float(score)
+            if vector_score < self.config.min_similarity:
+                continue
+            final_score = vector_score
+            if self.config.keyword_boost_enabled and terms:
+                haystack = f"{page.get('title', '')} {row.get('heading', '')} {row.get('section_content', '')}".lower()
+                keyword_score = sum(term in haystack for term in terms) / len(terms)
+                weight = self.config.keyword_boost_weight
+                final_score = (1 - weight) * vector_score + weight * keyword_score
+            candidates.append({**row, "page": page, "mapping": mapping, "score": final_score})
+        return candidates
+
+    def _top_indices(self, snapshot: WikiVectorSnapshot, vector: np.ndarray, eligible: np.ndarray) -> tuple[np.ndarray, np.ndarray]:
+        scores = snapshot.matrix[eligible] @ vector
+        count = min(self.config.top_k_sections, scores.size)
+        if count <= 0:
+            return np.asarray([], dtype=int), np.asarray([], dtype=np.float32)
+        positions = np.argpartition(scores, -count)[-count:]
+        positions = positions[np.argsort(scores[positions])[::-1]]
+        return eligible[positions], scores[positions]

offline-backend-20260512/backend/packages/harness/deerflow/integrations/weknora/local_index/sync.py

@@ -0,0 +1,173 @@
+"""Lease-protected full Wiki mirror scan and page-level vector replacement."""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+import platform
+from typing import Any
+from uuid import uuid4
+
+from deerflow.config.llmwiki_config import LocalWikiIndexConfig
+from deerflow.integrations.weknora.client import WeKnoraClient
+from deerflow.integrations.weknora.local_index.chunking import chunk_wiki_page
+from deerflow.integrations.weknora.local_index.embedding import StrictWikiEmbeddingClient
+from deerflow.integrations.weknora.local_index.normalize import normalize_wiki_page
+from deerflow.integrations.weknora.local_index.vector_cache import WikiVectorCache
+from deerflow.integrations.weknora.local_index.vector_codec import encode_vector
+from deerflow.persistence.llmwiki_index import LlmWikiIndexStore
+
+logger = logging.getLogger(__name__)
+
+
+class WikiSyncLeaseLost(RuntimeError):
+    pass
+
+
+def _safe_error(exc: BaseException) -> str:
+    return f"{type(exc).__name__}: {str(exc)[:1000]}"
+
+
+class WikiSyncService:
+    def __init__(self, config: LocalWikiIndexConfig, store: LlmWikiIndexStore, embedding: StrictWikiEmbeddingClient, cache: WikiVectorCache, client: WeKnoraClient) -> None:
+        self.config = config
+        self.store = store
+        self.embedding = embedding
+        self.cache = cache
+        self.client = client
+        self.owner = f"{platform.node()}:{uuid4()}"
+
+    async def sync_mapping(self, mapping: dict[str, Any], *, force: bool = False) -> dict[str, Any]:
+        mapping_id = str(mapping["id"])
+        sync_id = str(uuid4())
+        if self.embedding.dimensions is None:
+            # Auto-dimension configurations need one successful response to
+            # produce a stable fingerprint before lease/rebuild decisions.
+            await self.embedding.embed_query("DeerFlow local Wiki embedding dimension probe")
+        fingerprint = self.embedding.fingerprint
+        revision, indexed_fingerprint, prior_state = await self.store.get_index_revision(mapping_id)
+        if revision > 0 and indexed_fingerprint and indexed_fingerprint != fingerprint and prior_state not in {"rebuild_required", "rebuilding"}:
+            await self.store.mark_rebuild_required([mapping_id], fingerprint)
+            self.cache.invalidate(mapping_id)
+            prior_state = "rebuild_required"
+        rebuilding = prior_state == "rebuild_required"
+        acquired = await self.store.try_acquire_sync_lease(mapping_id, owner=self.owner, sync_id=sync_id, lease_seconds=self.config.sync_lease_seconds, fingerprint=fingerprint)
+        if not acquired:
+            return {"mapping_id": mapping_id, "status": "already_running"}
+        lease_lost = asyncio.Event()
+
+        async def _lease_heartbeat() -> None:
+            interval = max(5.0, min(60.0, self.config.sync_lease_seconds / 3))
+            while True:
+                await asyncio.sleep(interval)
+                try:
+                    renewed = await self.store.renew_sync_lease(
+                        mapping_id,
+                        owner=self.owner,
+                        lease_seconds=self.config.sync_lease_seconds,
+                    )
+                except Exception:
+                    renewed = False
+                    logger.exception("Local Wiki sync lease heartbeat failed mapping_id=%s", mapping_id)
+                if not renewed:
+                    lease_lost.set()
+                    return
+
+        heartbeat = asyncio.create_task(_lease_heartbeat())
+
+        def _ensure_lease() -> None:
+            if lease_lost.is_set():
+                raise WikiSyncLeaseLost("Local Wiki sync lease was lost")
+
+        remote_count = 0
+        changed = 0
+        failed = 0
+        try:
+            remote_id = str(mapping["weknora_id"])
+            await self.client.get_knowledge_base(remote_id)
+            page_number = 1
+            while True:
+                batch = await self.client.list_wiki_pages(remote_id, page=page_number, page_size=self.config.sync_page_size)
+                pages = [page for page in batch.get("pages", []) if isinstance(page, dict)]
+                remote_count += len(pages)
+                for summary in pages:
+                    try:
+                        _ensure_lease()
+                        slug = str(summary.get("slug") or summary.get("wiki_slug") or summary.get("path") or "")
+                        remote_page = await self.client.get_wiki_page(remote_id, slug)
+                        page = normalize_wiki_page(mapping_id, {**summary, **remote_page})
+                        existing = await self.store.get_page_by_slug_hash(mapping_id, page["slug_hash"])
+                        active_fingerprint = self.embedding.fingerprint
+                        if (
+                            not force
+                            and existing
+                            and existing.get("content_hash") == page["content_hash"]
+                            and existing.get("indexed_fingerprint") == active_fingerprint
+                            and existing.get("index_status") == "ready"
+                            and not existing.get("is_remote_deleted")
+                        ):
+                            await self.store.touch_page(str(existing["id"]), sync_id)
+                            continue
+                        sections = (
+                            []
+                            if page["status"] == "archived"
+                            else chunk_wiki_page(page, max_chars=self.config.chunk_max_chars, overlap=self.config.chunk_overlap_chars, min_chars=self.config.chunk_min_chars, title_prefix_enabled=self.config.title_prefix_enabled)
+                        )
+                        embeddings = await self.embedding.embed_texts([section.embedding_text for section in sections]) if sections else []
+                        fingerprint = self.embedding.fingerprint
+                        vectors = []
+                        for section, vector in zip(sections, embeddings, strict=True):
+                            blob, dimensions = encode_vector(vector, dimensions=self.embedding.dimensions)
+                            vectors.append(
+                                {"section_index": section.section_index, "heading": section.heading, "section_content": section.content, "content_hash": section.content_hash, "embedding_dimensions": dimensions, "vector_blob": blob}
+                            )
+                        _ensure_lease()
+                        await self.store.replace_page_vectors(page=page, vectors=vectors, fingerprint=fingerprint, sync_id=sync_id)
+                        self.cache.invalidate(mapping_id)
+                        changed += 1
+                    except Exception as exc:
+                        if isinstance(exc, WikiSyncLeaseLost):
+                            raise
+                        failed += 1
+                        try:
+                            fallback = normalize_wiki_page(mapping_id, summary)
+                            await self.store.record_page_failure(page=fallback, sync_id=sync_id, error=_safe_error(exc))
+                        except Exception as record_exc:
+                            logger.exception("Could not record local Wiki page failure mapping_id=%s", mapping_id)
+                            raise RuntimeError("Could not safely retain a failed Wiki page during the full scan") from record_exc
+                        logger.warning("Local Wiki page sync failed mapping_id=%s: %s", mapping_id, _safe_error(exc))
+                _ensure_lease()
+                total_pages = int(batch.get("total_pages") or 1)
+                if page_number >= total_pages:
+                    break
+                page_number += 1
+            _ensure_lease()
+            deleted = await self.store.mark_missing_pages_deleted(mapping_id, sync_id)
+            if deleted:
+                self.cache.invalidate(mapping_id)
+            await self.store.finish_sync(
+                mapping_id,
+                owner=self.owner,
+                sync_id=sync_id,
+                success=not (rebuilding and failed),
+                remote_page_count=remote_count,
+                error=f"{failed} page(s) failed" if failed else None,
+            )
+            return {"mapping_id": mapping_id, "status": "partial" if failed else "completed", "remote_pages": remote_count, "changed_pages": changed, "deleted_pages": deleted, "failed_pages": failed}
+        except asyncio.CancelledError:
+            await self.store.finish_sync(
+                mapping_id,
+                owner=self.owner,
+                sync_id=sync_id,
+                success=False,
+                remote_page_count=remote_count,
+                error="Sync cancelled",
+            )
+            raise
+        except Exception as exc:
+            await self.store.finish_sync(mapping_id, owner=self.owner, sync_id=sync_id, success=False, remote_page_count=remote_count, error=_safe_error(exc))
+            logger.warning("Local Wiki sync failed mapping_id=%s: %s", mapping_id, _safe_error(exc))
+            raise
+        finally:
+            heartbeat.cancel()
+            await asyncio.gather(heartbeat, return_exceptions=True)

offline-backend-20260512/backend/packages/harness/deerflow/integrations/weknora/local_index/vector_cache.py

@@ -0,0 +1,86 @@
+"""Per-knowledge-base LRU snapshots for NumPy exact search."""
+
+from __future__ import annotations
+
+import asyncio
+from collections import OrderedDict
+from dataclasses import dataclass
+from time import monotonic
+from typing import Any
+
+import numpy as np
+
+from deerflow.integrations.weknora.local_index.vector_codec import decode_vector
+from deerflow.persistence.llmwiki_index import LlmWikiIndexStore
+
+
+@dataclass(frozen=True)
+class WikiVectorSnapshot:
+    mapping_id: str
+    index_revision: int
+    embedding_fingerprint: str
+    dimensions: int
+    matrix: np.ndarray
+    rows: list[dict[str, Any]]
+
+
+class WikiVectorCache:
+    def __init__(self, store: LlmWikiIndexStore, *, max_knowledge_bases: int = 20, revision_check_seconds: float = 5) -> None:
+        self.store = store
+        self.max_knowledge_bases = max_knowledge_bases
+        self.revision_check_seconds = revision_check_seconds
+        self._snapshots: OrderedDict[str, WikiVectorSnapshot] = OrderedDict()
+        self._checked_at: dict[str, float] = {}
+        self._locks: dict[str, asyncio.Lock] = {}
+
+    def invalidate(self, mapping_id: str) -> None:
+        self._snapshots.pop(mapping_id, None)
+        self._checked_at.pop(mapping_id, None)
+
+    def clear(self) -> None:
+        self._snapshots.clear()
+        self._checked_at.clear()
+
+    async def get(self, mapping_id: str, fingerprint: str) -> WikiVectorSnapshot:
+        cached = self._snapshots.get(mapping_id)
+        now = monotonic()
+        if cached is not None and cached.embedding_fingerprint == fingerprint and now - self._checked_at.get(mapping_id, 0) < self.revision_check_seconds:
+            self._snapshots.move_to_end(mapping_id)
+            return cached
+        lock = self._locks.setdefault(mapping_id, asyncio.Lock())
+        async with lock:
+            revision, active_fingerprint, state = await self.store.get_index_revision(mapping_id)
+            self._checked_at[mapping_id] = monotonic()
+            cached = self._snapshots.get(mapping_id)
+            if state in {"not_synced", "rebuild_required", "rebuilding", "disabled"} or revision <= 0:
+                raise RuntimeError(f"WIKI_INDEX_NOT_READY:{state}")
+            if active_fingerprint != fingerprint:
+                raise RuntimeError("WIKI_INDEX_FINGERPRINT_MISMATCH")
+            if cached is not None and cached.index_revision == revision and cached.embedding_fingerprint == fingerprint:
+                self._snapshots.move_to_end(mapping_id)
+                return cached
+            raw = await self.store.load_vector_snapshot(mapping_id, fingerprint)
+            snapshot = await asyncio.to_thread(self._decode_snapshot, mapping_id, raw)
+            self._snapshots[mapping_id] = snapshot
+            self._snapshots.move_to_end(mapping_id)
+            while len(self._snapshots) > self.max_knowledge_bases:
+                evicted, _ = self._snapshots.popitem(last=False)
+                self._checked_at.pop(evicted, None)
+            return snapshot
+
+    @staticmethod
+    def _decode_snapshot(mapping_id: str, raw: dict[str, Any]) -> WikiVectorSnapshot:
+        rows = list(raw.get("rows") or [])
+        if not rows:
+            return WikiVectorSnapshot(mapping_id, int(raw.get("revision") or 0), str(raw.get("fingerprint") or ""), 0, np.empty((0, 0), dtype=np.float32), [])
+        dimensions = int(rows[0]["embedding_dimensions"])
+        vectors = []
+        valid_rows = []
+        for row in rows:
+            if int(row["embedding_dimensions"]) != dimensions:
+                raise ValueError("Mixed vector dimensions in one Wiki snapshot")
+            vectors.append(decode_vector(row["vector_blob"], dimensions))
+            valid_rows.append(row)
+        matrix = np.ascontiguousarray(np.vstack(vectors), dtype=np.float32)
+        matrix.setflags(write=False)
+        return WikiVectorSnapshot(mapping_id, int(raw.get("revision") or 0), str(raw.get("fingerprint") or ""), dimensions, matrix, valid_rows)

offline-backend-20260512/backend/packages/harness/deerflow/integrations/weknora/local_index/vector_codec.py

@@ -0,0 +1,33 @@
+"""Validated little-endian normalized float32 Wiki vector codec."""
+
+from __future__ import annotations
+
+import numpy as np
+
+
+def normalize_vector(values, *, dimensions: int | None = None) -> np.ndarray:
+    vector = np.asarray(values, dtype=np.float32)
+    if vector.ndim != 1 or vector.size == 0:
+        raise ValueError("Embedding vector must be a non-empty one-dimensional array")
+    if dimensions is not None and vector.size != dimensions:
+        raise ValueError(f"Embedding dimension mismatch: expected {dimensions}, got {vector.size}")
+    if not np.isfinite(vector).all():
+        raise ValueError("Embedding vector contains NaN or infinity")
+    norm = float(np.linalg.norm(vector))
+    if not np.isfinite(norm) or norm <= 0:
+        raise ValueError("Embedding vector has zero norm")
+    return np.asarray(vector / norm, dtype="<f4")
+
+
+def encode_vector(values, *, dimensions: int | None = None) -> tuple[bytes, int]:
+    vector = normalize_vector(values, dimensions=dimensions)
+    return vector.tobytes(order="C"), int(vector.size)
+
+
+def decode_vector(blob: bytes, dimensions: int) -> np.ndarray:
+    if len(blob) != dimensions * 4:
+        raise ValueError(f"Corrupt vector BLOB: expected {dimensions * 4} bytes, got {len(blob)}")
+    vector = np.frombuffer(blob, dtype="<f4")
+    if not np.isfinite(vector).all():
+        raise ValueError("Stored vector contains NaN or infinity")
+    return vector.copy()

offline-backend-20260512/backend/packages/harness/deerflow/persistence/fixed_questions/__init__.py

@@ -0,0 +1,22 @@
+"""Exact-match fixed-question persistence."""
+
+from __future__ import annotations
+
+from deerflow.persistence.fixed_questions.base import FixedQuestionStore
+from deerflow.persistence.fixed_questions.memory import MemoryFixedQuestionStore
+from deerflow.persistence.fixed_questions.model import FixedQuestionRow
+from deerflow.persistence.fixed_questions.sql import FixedQuestionRepository
+
+__all__ = [
+    "FixedQuestionRepository",
+    "FixedQuestionRow",
+    "FixedQuestionStore",
+    "MemoryFixedQuestionStore",
+    "make_fixed_question_store",
+]
+
+
+def make_fixed_question_store(session_factory):
+    if session_factory is None:
+        return MemoryFixedQuestionStore()
+    return FixedQuestionRepository(session_factory)

offline-backend-20260512/backend/packages/harness/deerflow/persistence/fixed_questions/base.py

@@ -0,0 +1,30 @@
+"""Abstract persistence API for administrator-managed fixed questions."""
+
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import Any
+
+
+class FixedQuestionStore(ABC):
+    """Global fixed-question configuration shared by every account."""
+
+    @abstractmethod
+    async def list_questions(self) -> list[dict[str, Any]]:
+        """Return every configured question in display order."""
+        raise NotImplementedError
+
+    @abstractmethod
+    async def find_enabled(self, question: str) -> dict[str, Any] | None:
+        """Return the enabled row whose question exactly equals ``question``."""
+        raise NotImplementedError
+
+    @abstractmethod
+    async def replace_all(
+        self,
+        rows: list[dict[str, Any]],
+        *,
+        updated_by: str | None = None,
+    ) -> list[dict[str, Any]]:
+        """Atomically replace the complete fixed-question configuration."""
+        raise NotImplementedError

offline-backend-20260512/backend/packages/harness/deerflow/persistence/fixed_questions/memory.py

@@ -0,0 +1,56 @@
+"""In-memory fixed-question store used by memory deployments and tests."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime
+from typing import Any
+
+from deerflow.persistence.fixed_questions.base import FixedQuestionStore
+
+
+def _normalize(data: dict[str, Any], updated_by: str | None) -> dict[str, Any]:
+    return {
+        "id": str(data["id"]),
+        "question": str(data.get("question") or ""),
+        "answer": str(data.get("answer") or ""),
+        "enabled": bool(data.get("enabled", True)),
+        "tokens_per_second": int(data.get("tokens_per_second", 100)),
+        "sort_order": int(data.get("sort_order", 0)),
+        "updated_by": updated_by,
+        "updated_at": datetime.now(UTC).isoformat(),
+    }
+
+
+class MemoryFixedQuestionStore(FixedQuestionStore):
+    def __init__(self) -> None:
+        self._rows: dict[str, dict[str, Any]] = {}
+
+    async def list_questions(self) -> list[dict[str, Any]]:
+        rows = sorted(
+            self._rows.values(),
+            key=lambda row: (row.get("sort_order", 0), row.get("question", "")),
+        )
+        return [dict(row) for row in rows]
+
+    async def find_enabled(self, question: str) -> dict[str, Any] | None:
+        for row in self._rows.values():
+            if row["enabled"] and row["question"] == question:
+                return dict(row)
+        return None
+
+    async def replace_all(
+        self,
+        rows: list[dict[str, Any]],
+        *,
+        updated_by: str | None = None,
+    ) -> list[dict[str, Any]]:
+        # Last duplicate question wins, mirroring the SQL repository.
+        by_id: dict[str, dict[str, Any]] = {}
+        for row in rows:
+            question = row.get("question")
+            row_id = row.get("id")
+            if row_id and question not in (None, ""):
+                by_id[str(row_id)] = row
+        by_question = {str(row["question"]): row for row in by_id.values()}
+        self._rows = {str(row["id"]): _normalize(row, updated_by) for row in by_question.values()}
+        return await self.list_questions()

offline-backend-20260512/backend/packages/harness/deerflow/persistence/fixed_questions/model.py

@@ -0,0 +1,41 @@
+"""ORM model for exact-match, administrator-managed fixed questions."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime
+
+from sqlalchemy import Boolean, Integer, String, Text, UniqueConstraint
+from sqlalchemy.orm import Mapped, mapped_column
+
+from deerflow.persistence.base import Base
+from deerflow.persistence.types import BeijingDateTime, PortableLongText
+
+
+class FixedQuestionRow(Base):
+    """One globally shared question/answer pair.
+
+    ``question_hash`` provides a portable indexed lookup for questions stored in
+    ``Text``. The repository always compares the original question as well, so a
+    theoretical SHA-256 collision cannot cause a false match.
+    """
+
+    __tablename__ = "fixed_questions"
+    __table_args__ = (UniqueConstraint("question_hash", name="uq_fixed_questions_question_hash"),)
+
+    id: Mapped[str] = mapped_column(String(64), primary_key=True)
+    question: Mapped[str] = mapped_column(Text, nullable=False)
+    question_hash: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
+    answer: Mapped[str] = mapped_column(PortableLongText, nullable=False)
+    enabled: Mapped[bool] = mapped_column(Boolean, default=True, server_default="1")
+    tokens_per_second: Mapped[int] = mapped_column(
+        Integer,
+        default=100,
+        server_default="100",
+    )
+    sort_order: Mapped[int] = mapped_column(Integer, default=0, server_default="0")
+    updated_by: Mapped[str | None] = mapped_column(String(64), nullable=True)
+    updated_at: Mapped[datetime] = mapped_column(
+        BeijingDateTime(),
+        default=lambda: datetime.now(UTC),
+        onupdate=lambda: datetime.now(UTC),
+    )

offline-backend-20260512/backend/packages/harness/deerflow/persistence/fixed_questions/sql.py

@@ -0,0 +1,88 @@
+"""SQLAlchemy-backed fixed-question store."""
+
+from __future__ import annotations
+
+import hashlib
+from datetime import datetime
+from typing import Any
+
+from sqlalchemy import delete, select
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
+
+from deerflow.persistence.fixed_questions.base import FixedQuestionStore
+from deerflow.persistence.fixed_questions.model import FixedQuestionRow
+
+
+def question_hash(question: str) -> str:
+    return hashlib.sha256(question.encode("utf-8")).hexdigest()
+
+
+def _to_dict(row: FixedQuestionRow) -> dict[str, Any]:
+    data = row.to_dict()
+    data.pop("question_hash", None)
+    value = data.get("updated_at")
+    if isinstance(value, datetime):
+        data["updated_at"] = value.isoformat()
+    return data
+
+
+def _row_from(data: dict[str, Any], updated_by: str | None) -> FixedQuestionRow:
+    question = str(data.get("question") or "")
+    return FixedQuestionRow(
+        id=str(data["id"]),
+        question=question,
+        question_hash=question_hash(question),
+        answer=str(data.get("answer") or ""),
+        enabled=bool(data.get("enabled", True)),
+        tokens_per_second=int(data.get("tokens_per_second", 100)),
+        sort_order=int(data.get("sort_order", 0)),
+        updated_by=updated_by,
+    )
+
+
+class FixedQuestionRepository(FixedQuestionStore):
+    def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
+        self._sf = session_factory
+
+    async def list_questions(self) -> list[dict[str, Any]]:
+        stmt = select(FixedQuestionRow).order_by(
+            FixedQuestionRow.sort_order.asc(),
+            FixedQuestionRow.question.asc(),
+        )
+        async with self._sf() as session:
+            result = await session.execute(stmt)
+            return [_to_dict(row) for row in result.scalars()]
+
+    async def find_enabled(self, question: str) -> dict[str, Any] | None:
+        stmt = select(FixedQuestionRow).where(
+            FixedQuestionRow.question_hash == question_hash(question),
+            FixedQuestionRow.enabled.is_(True),
+        )
+        async with self._sf() as session:
+            row = (await session.execute(stmt)).scalar_one_or_none()
+            if row is None or row.question != question:
+                return None
+            return _to_dict(row)
+
+    async def replace_all(
+        self,
+        rows: list[dict[str, Any]],
+        *,
+        updated_by: str | None = None,
+    ) -> list[dict[str, Any]]:
+        # Last duplicate question wins, preventing a unique-hash violation even
+        # if a non-UI caller submits malformed data.
+        by_id: dict[str, dict[str, Any]] = {}
+        for row in rows:
+            question = row.get("question")
+            row_id = row.get("id")
+            if row_id and question not in (None, ""):
+                by_id[str(row_id)] = row
+        by_question = {str(row["question"]): row for row in by_id.values()}
+
+        async with self._sf() as session:
+            await session.execute(delete(FixedQuestionRow))
+            new_rows = [_row_from(row, updated_by) for row in by_question.values()]
+            session.add_all(new_rows)
+            await session.commit()
+            return [_to_dict(row) for row in new_rows]

offline-backend-20260512/backend/packages/harness/deerflow/persistence/llmwiki/base.py

@@ -22,7 +22,15 @@ class LlmWikiStore(ABC):
     async def get_by_weknora_id(self, weknora_id: str) -> dict[str, Any] | None: ...
 
     @abstractmethod
-    async def update_mapping(self, mapping_id: str, *, name: str | None = None, description: str | None = None) -> dict[str, Any] | None: ...
+    async def update_mapping(
+        self,
+        mapping_id: str,
+        *,
+        name: str | None = None,
+        description: str | None = None,
+        wiki_index_enabled: bool | None = None,
+        external_search_enabled: bool | None = None,
+    ) -> dict[str, Any] | None: ...
 
     @abstractmethod
     async def adopt_conversation_deposit_mapping(

offline-backend-20260512/backend/packages/harness/deerflow/persistence/llmwiki/memory.py

@@ -33,6 +33,9 @@ class MemoryLlmWikiStore(LlmWikiStore):
             "published_by": None,
             "reviewed_by": None,
             "published_at": None,
+            "wiki_index_enabled": True,
+            "external_search_enabled": False,
+            "external_search_updated_at": None,
             "created_at": now,
             "updated_at": now,
         }
@@ -65,7 +68,15 @@ class MemoryLlmWikiStore(LlmWikiStore):
                 return dict(row)
         return None
 
-    async def update_mapping(self, mapping_id: str, *, name: str | None = None, description: str | None = None) -> dict[str, Any] | None:
+    async def update_mapping(
+        self,
+        mapping_id: str,
+        *,
+        name: str | None = None,
+        description: str | None = None,
+        wiki_index_enabled: bool | None = None,
+        external_search_enabled: bool | None = None,
+    ) -> dict[str, Any] | None:
         row = self._rows.get(mapping_id)
         if row is None:
             return None
@@ -73,6 +84,11 @@ class MemoryLlmWikiStore(LlmWikiStore):
             row["name"] = name
         if description is not None:
             row["description"] = description
+        if wiki_index_enabled is not None:
+            row["wiki_index_enabled"] = wiki_index_enabled
+        if external_search_enabled is not None:
+            row["external_search_enabled"] = external_search_enabled
+            row["external_search_updated_at"] = _now()
         row["updated_at"] = _now()
         return dict(row)
 
@@ -143,11 +159,7 @@ class MemoryLlmWikiStore(LlmWikiStore):
 
     async def get_conversation_deposit_mapping(self) -> dict[str, Any] | None:
         for row in self._rows.values():
-            if (
+            if row.get("owner_user_id") == "system" and row.get("name") == "对话沉淀" and row.get("publication_status") == "published":
-                row.get("owner_user_id") == "system"
-                and row.get("name") == "对话沉淀"
-                and row.get("publication_status") == "published"
-            ):
                 return dict(row)
         return None
 

offline-backend-20260512/backend/packages/harness/deerflow/persistence/llmwiki/model.py

@@ -4,7 +4,7 @@ from __future__ import annotations
 
 from datetime import UTC, datetime
 
-from sqlalchemy import String, UniqueConstraint
+from sqlalchemy import Boolean, String, UniqueConstraint, false, true
 from sqlalchemy.orm import Mapped, mapped_column
 
 from deerflow.persistence.base import Base
@@ -24,6 +24,9 @@ class LlmWikiKnowledgeBaseRow(Base):
     published_by: Mapped[str | None] = mapped_column(String(64), nullable=True)
     reviewed_by: Mapped[str | None] = mapped_column(String(64), nullable=True)
     published_at: Mapped[datetime | None] = mapped_column(BeijingDateTime(), nullable=True)
+    wiki_index_enabled: Mapped[bool] = mapped_column(Boolean, nullable=False, default=True, server_default=true(), index=True)
+    external_search_enabled: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False, server_default=false(), index=True)
+    external_search_updated_at: Mapped[datetime | None] = mapped_column(BeijingDateTime(), nullable=True)
     created_at: Mapped[datetime] = mapped_column(BeijingDateTime(), default=lambda: datetime.now(UTC))
     updated_at: Mapped[datetime] = mapped_column(BeijingDateTime(), default=lambda: datetime.now(UTC), onupdate=lambda: datetime.now(UTC))
 

offline-backend-20260512/backend/packages/harness/deerflow/persistence/llmwiki/sql.py

@@ -19,7 +19,7 @@ def _now() -> datetime:
 
 def _to_dict(row: LlmWikiKnowledgeBaseRow | LlmWikiConversationDepositRow) -> dict[str, Any]:
     data = row.to_dict()
-    for key in ("published_at", "created_at", "updated_at"):
+    for key in ("published_at", "external_search_updated_at", "created_at", "updated_at"):
         value = data.get(key)
         if isinstance(value, datetime):
             data[key] = value.isoformat()
@@ -82,7 +82,15 @@ class LlmWikiRepository(LlmWikiStore):
             row = (await session.execute(stmt)).scalar_one_or_none()
             return _to_dict(row) if row else None
 
-    async def update_mapping(self, mapping_id: str, *, name: str | None = None, description: str | None = None) -> dict[str, Any] | None:
+    async def update_mapping(
+        self,
+        mapping_id: str,
+        *,
+        name: str | None = None,
+        description: str | None = None,
+        wiki_index_enabled: bool | None = None,
+        external_search_enabled: bool | None = None,
+    ) -> dict[str, Any] | None:
         async with self._sf() as session:
             row = await session.get(LlmWikiKnowledgeBaseRow, mapping_id)
             if row is None:
@@ -91,6 +99,11 @@ class LlmWikiRepository(LlmWikiStore):
                 row.name = name
             if description is not None:
                 row.description = description
+            if wiki_index_enabled is not None:
+                row.wiki_index_enabled = wiki_index_enabled
+            if external_search_enabled is not None:
+                row.external_search_enabled = external_search_enabled
+                row.external_search_updated_at = _now()
             row.updated_at = _now()
             await session.commit()
             return _to_dict(row)

offline-backend-20260512/backend/packages/harness/deerflow/persistence/llmwiki_index/__init__.py

@@ -0,0 +1,21 @@
+"""Persistence facade for the DeerFlow-local Wiki vector index."""
+
+from deerflow.persistence.llmwiki_index.base import LlmWikiIndexStore
+from deerflow.persistence.llmwiki_index.memory import MemoryLlmWikiIndexStore
+from deerflow.persistence.llmwiki_index.model import LlmWikiWikiPageRow, LlmWikiWikiSyncStateRow, LlmWikiWikiVectorRow
+from deerflow.persistence.llmwiki_index.sql import SqlLlmWikiIndexStore
+
+
+def make_llmwiki_index_store(session_factory):
+    return MemoryLlmWikiIndexStore() if session_factory is None else SqlLlmWikiIndexStore(session_factory)
+
+
+__all__ = [
+    "LlmWikiIndexStore",
+    "MemoryLlmWikiIndexStore",
+    "SqlLlmWikiIndexStore",
+    "LlmWikiWikiPageRow",
+    "LlmWikiWikiVectorRow",
+    "LlmWikiWikiSyncStateRow",
+    "make_llmwiki_index_store",
+]

offline-backend-20260512/backend/packages/harness/deerflow/persistence/llmwiki_index/base.py

@@ -0,0 +1,54 @@
+"""Storage contract for local Wiki pages, vectors, revisions and sync leases."""
+
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import Any
+
+
+class LlmWikiIndexStore(ABC):
+    @abstractmethod
+    async def get_page_by_slug_hash(self, mapping_id: str, slug_hash: str) -> dict[str, Any] | None: ...
+
+    @abstractmethod
+    async def get_page(self, mapping_id: str, slug: str) -> dict[str, Any] | None: ...
+
+    @abstractmethod
+    async def touch_page(self, page_id: str, sync_id: str) -> None: ...
+
+    @abstractmethod
+    async def replace_page_vectors(
+        self,
+        *,
+        page: dict[str, Any],
+        vectors: list[dict[str, Any]],
+        fingerprint: str,
+        sync_id: str,
+    ) -> dict[str, Any]: ...
+
+    @abstractmethod
+    async def record_page_failure(self, *, page: dict[str, Any], sync_id: str, error: str) -> None: ...
+
+    @abstractmethod
+    async def mark_missing_pages_deleted(self, mapping_id: str, sync_id: str) -> int: ...
+
+    @abstractmethod
+    async def load_vector_snapshot(self, mapping_id: str, fingerprint: str) -> dict[str, Any]: ...
+
+    @abstractmethod
+    async def get_index_revision(self, mapping_id: str) -> tuple[int, str | None, str]: ...
+
+    @abstractmethod
+    async def try_acquire_sync_lease(self, mapping_id: str, *, owner: str, sync_id: str, lease_seconds: int, fingerprint: str) -> bool: ...
+
+    @abstractmethod
+    async def renew_sync_lease(self, mapping_id: str, *, owner: str, lease_seconds: int) -> bool: ...
+
+    @abstractmethod
+    async def finish_sync(self, mapping_id: str, *, owner: str, sync_id: str, success: bool, remote_page_count: int, error: str | None = None) -> None: ...
+
+    @abstractmethod
+    async def list_index_status(self, mapping_ids: list[str] | None = None) -> list[dict[str, Any]]: ...
+
+    @abstractmethod
+    async def mark_rebuild_required(self, mapping_ids: list[str], fingerprint: str) -> int: ...

offline-backend-20260512/backend/packages/harness/deerflow/persistence/llmwiki_index/memory.py

@@ -0,0 +1,160 @@
+"""In-memory local Wiki index store used by tests and DB-less mode."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime, timedelta
+from typing import Any
+from uuid import uuid4
+
+from deerflow.persistence.llmwiki_index.base import LlmWikiIndexStore
+
+
+def _now() -> datetime:
+    return datetime.now(UTC)
+
+
+class MemoryLlmWikiIndexStore(LlmWikiIndexStore):
+    def __init__(self) -> None:
+        self.pages: dict[str, dict[str, Any]] = {}
+        self.vectors: dict[str, list[dict[str, Any]]] = {}
+        self.states: dict[str, dict[str, Any]] = {}
+
+    def _state(self, mapping_id: str) -> dict[str, Any]:
+        return self.states.setdefault(mapping_id, {"knowledge_base_mapping_id": mapping_id, "state": "idle", "index_revision": 0, "embedding_fingerprint": None})
+
+    async def get_page_by_slug_hash(self, mapping_id: str, slug_hash: str) -> dict[str, Any] | None:
+        row = next((p for p in self.pages.values() if p["knowledge_base_mapping_id"] == mapping_id and p["slug_hash"] == slug_hash), None)
+        return dict(row) if row else None
+
+    async def get_page(self, mapping_id: str, slug: str) -> dict[str, Any] | None:
+        row = next((p for p in self.pages.values() if p["knowledge_base_mapping_id"] == mapping_id and p["slug"] == slug), None)
+        return dict(row) if row else None
+
+    async def touch_page(self, page_id: str, sync_id: str) -> None:
+        if page_id in self.pages:
+            self.pages[page_id]["last_seen_sync_id"] = sync_id
+            self.pages[page_id]["last_error"] = None
+
+    async def replace_page_vectors(self, *, page: dict[str, Any], vectors: list[dict[str, Any]], fingerprint: str, sync_id: str) -> dict[str, Any]:
+        existing = await self.get_page_by_slug_hash(page["knowledge_base_mapping_id"], page["slug_hash"])
+        page_id = existing["id"] if existing else str(uuid4())
+        now = _now().isoformat()
+        row = {
+            **(existing or {}),
+            **page,
+            "id": page_id,
+            "index_status": "ready",
+            "indexed_fingerprint": fingerprint,
+            "indexed_at": now,
+            "last_error": None,
+            "is_remote_deleted": False,
+            "last_seen_sync_id": sync_id,
+            "created_at": (existing or {}).get("created_at", now),
+            "updated_at": now,
+        }
+        self.pages[page_id] = row
+        self.vectors[page_id] = [{**item, "page_id": page_id, "knowledge_base_mapping_id": page["knowledge_base_mapping_id"], "embedding_fingerprint": fingerprint} for item in vectors]
+        state = self._state(page["knowledge_base_mapping_id"])
+        state["index_revision"] += 1
+        state["embedding_fingerprint"] = fingerprint
+        return dict(row)
+
+    async def record_page_failure(self, *, page: dict[str, Any], sync_id: str, error: str) -> None:
+        existing = await self.get_page_by_slug_hash(page["knowledge_base_mapping_id"], page["slug_hash"])
+        if existing:
+            self.pages[existing["id"]].update(
+                {
+                    "last_seen_sync_id": sync_id,
+                    "last_error": error,
+                    # Preserve the last atomically completed generation.
+                    "index_status": "ready" if self.vectors.get(existing["id"]) else "failed",
+                }
+            )
+            return
+        page_id = str(uuid4())
+        self.pages[page_id] = {**page, "id": page_id, "index_status": "failed", "last_error": error, "last_seen_sync_id": sync_id, "is_remote_deleted": False}
+
+    async def mark_missing_pages_deleted(self, mapping_id: str, sync_id: str) -> int:
+        changed = 0
+        for page in self.pages.values():
+            if page["knowledge_base_mapping_id"] == mapping_id and page.get("last_seen_sync_id") != sync_id and not page.get("is_remote_deleted"):
+                page.update({"is_remote_deleted": True, "index_status": "deleted"})
+                self.vectors.pop(page["id"], None)
+                changed += 1
+        if changed:
+            self._state(mapping_id)["index_revision"] += 1
+        return changed
+
+    async def load_vector_snapshot(self, mapping_id: str, fingerprint: str) -> dict[str, Any]:
+        rows = []
+        for page_id, vectors in self.vectors.items():
+            page = self.pages[page_id]
+            if page["knowledge_base_mapping_id"] != mapping_id or page.get("is_remote_deleted") or page.get("status") not in {"published", "draft"} or page.get("index_status") != "ready":
+                continue
+            rows.extend({**vector, "page": dict(page)} for vector in vectors if vector["embedding_fingerprint"] == fingerprint)
+        state = self._state(mapping_id)
+        return {"revision": state["index_revision"], "fingerprint": fingerprint, "rows": rows}
+
+    async def get_index_revision(self, mapping_id: str) -> tuple[int, str | None, str]:
+        state = self._state(mapping_id)
+        return int(state["index_revision"]), state.get("embedding_fingerprint"), str(state.get("state") or "idle")
+
+    async def try_acquire_sync_lease(self, mapping_id: str, *, owner: str, sync_id: str, lease_seconds: int, fingerprint: str) -> bool:
+        state = self._state(mapping_id)
+        now = _now()
+        expires = state.get("lease_expires_at")
+        if state.get("lease_owner") is not None and isinstance(expires, datetime) and expires >= now:
+            return False
+        state.update(
+            {
+                "state": "rebuilding" if state.get("state") == "rebuild_required" else "running",
+                "active_sync_id": sync_id,
+                "lease_owner": owner,
+                "lease_expires_at": now + timedelta(seconds=lease_seconds),
+                "last_started_at": now,
+            }
+        )
+        return True
+
+    async def renew_sync_lease(self, mapping_id: str, *, owner: str, lease_seconds: int) -> bool:
+        state = self._state(mapping_id)
+        if state.get("lease_owner") != owner:
+            return False
+        state["lease_expires_at"] = _now() + timedelta(seconds=lease_seconds)
+        return True
+
+    async def finish_sync(self, mapping_id: str, *, owner: str, sync_id: str, success: bool, remote_page_count: int, error: str | None = None) -> None:
+        state = self._state(mapping_id)
+        if state.get("lease_owner") != owner or state.get("active_sync_id") != sync_id:
+            return
+        pages = [p for p in self.pages.values() if p["knowledge_base_mapping_id"] == mapping_id and not p.get("is_remote_deleted")]
+        was_rebuilding = state.get("state") == "rebuilding"
+        state.update(
+            {
+                "state": "partial" if success and error else "idle" if success else "rebuild_required" if was_rebuilding else "failed",
+                "lease_owner": None,
+                "lease_expires_at": None,
+                "active_sync_id": None,
+                "last_error": error,
+                "remote_page_count": remote_page_count,
+                "local_page_count": len(pages),
+                "ready_page_count": sum(p.get("index_status") == "ready" for p in pages),
+                "failed_page_count": sum(p.get("index_status") in {"failed", "stale"} or p.get("last_error") is not None for p in pages),
+                "vector_count": sum(len(self.vectors.get(p["id"], [])) for p in pages),
+                "last_completed_at": _now() if success and not error else state.get("last_completed_at"),
+                "last_success_at": _now() if success else state.get("last_success_at"),
+            }
+        )
+
+    async def list_index_status(self, mapping_ids: list[str] | None = None) -> list[dict[str, Any]]:
+        wanted = set(mapping_ids or [])
+        return [dict(value) for key, value in self.states.items() if not wanted or key in wanted]
+
+    async def mark_rebuild_required(self, mapping_ids: list[str], fingerprint: str) -> int:
+        for mapping_id in mapping_ids:
+            state = self._state(mapping_id)
+            state.update({"state": "rebuild_required", "embedding_fingerprint": fingerprint})
+            for page in self.pages.values():
+                if page["knowledge_base_mapping_id"] == mapping_id and not page.get("is_remote_deleted"):
+                    page["index_status"] = "stale"
+        return len(mapping_ids)

offline-backend-20260512/backend/packages/harness/deerflow/persistence/llmwiki_index/model.py

@@ -0,0 +1,94 @@
+"""Portable ORM rows for the DeerFlow-local WeKnora Wiki mirror/index."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime
+
+from sqlalchemy import BigInteger, Boolean, ForeignKey, Index, Integer, LargeBinary, String, Text, UniqueConstraint, false
+from sqlalchemy.orm import Mapped, mapped_column
+
+from deerflow.persistence.base import Base
+from deerflow.persistence.types import BeijingDateTime, PortableJSON, PortableLongText
+
+
+def _now() -> datetime:
+    return datetime.now(UTC)
+
+
+class LlmWikiWikiPageRow(Base):
+    __tablename__ = "llmwiki_wiki_pages"
+    __table_args__ = (
+        UniqueConstraint("knowledge_base_mapping_id", "slug_hash", name="uq_llmwiki_wiki_page_mapping_slug_hash"),
+        Index("ix_llmwiki_wiki_page_mapping_visibility", "knowledge_base_mapping_id", "status", "index_status", "is_remote_deleted"),
+    )
+
+    id: Mapped[str] = mapped_column(String(36), primary_key=True)
+    knowledge_base_mapping_id: Mapped[str] = mapped_column(String(36), ForeignKey("llmwiki_knowledge_bases.id", ondelete="CASCADE"), nullable=False, index=True)
+    remote_page_id: Mapped[str | None] = mapped_column(String(128), nullable=True, index=True)
+    slug: Mapped[str] = mapped_column(String(1024), nullable=False)
+    slug_hash: Mapped[str] = mapped_column(String(64), nullable=False)
+    title: Mapped[str] = mapped_column(String(512), nullable=False, default="", index=True)
+    summary: Mapped[str] = mapped_column(PortableLongText(), nullable=False, default="")
+    content_md: Mapped[str] = mapped_column(PortableLongText(), nullable=False, default="")
+    page_type: Mapped[str] = mapped_column(String(32), nullable=False, default="article", index=True)
+    status: Mapped[str] = mapped_column(String(32), nullable=False, default="published", index=True)
+    aliases: Mapped[list] = mapped_column(PortableJSON(), nullable=False, default=list)
+    category_path: Mapped[list] = mapped_column(PortableJSON(), nullable=False, default=list)
+    parent_slug: Mapped[str | None] = mapped_column(String(1024), nullable=True)
+    wiki_path: Mapped[str | None] = mapped_column(String(1024), nullable=True)
+    source_refs: Mapped[list] = mapped_column(PortableJSON(), nullable=False, default=list)
+    chunk_refs: Mapped[list] = mapped_column(PortableJSON(), nullable=False, default=list)
+    page_version: Mapped[int] = mapped_column(Integer, nullable=False, default=0, index=True)
+    content_hash: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
+    remote_created_at: Mapped[datetime | None] = mapped_column(BeijingDateTime(), nullable=True)
+    remote_updated_at: Mapped[datetime | None] = mapped_column(BeijingDateTime(), nullable=True, index=True)
+    index_status: Mapped[str] = mapped_column(String(24), nullable=False, default="pending", index=True)
+    indexed_fingerprint: Mapped[str | None] = mapped_column(String(64), nullable=True)
+    indexed_at: Mapped[datetime | None] = mapped_column(BeijingDateTime(), nullable=True)
+    last_error: Mapped[str | None] = mapped_column(Text, nullable=True)
+    is_remote_deleted: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False, server_default=false(), index=True)
+    last_seen_sync_id: Mapped[str | None] = mapped_column(String(36), nullable=True, index=True)
+    created_at: Mapped[datetime] = mapped_column(BeijingDateTime(), nullable=False, default=_now)
+    updated_at: Mapped[datetime] = mapped_column(BeijingDateTime(), nullable=False, default=_now, onupdate=_now, index=True)
+
+
+class LlmWikiWikiVectorRow(Base):
+    __tablename__ = "llmwiki_wiki_vectors"
+    __table_args__ = (
+        UniqueConstraint("page_id", "section_index", "embedding_fingerprint", name="uq_llmwiki_wiki_vector_page_section_fingerprint"),
+        Index("ix_llmwiki_wiki_vector_snapshot", "knowledge_base_mapping_id", "embedding_fingerprint"),
+    )
+
+    id: Mapped[str] = mapped_column(String(36), primary_key=True)
+    page_id: Mapped[str] = mapped_column(String(36), ForeignKey("llmwiki_wiki_pages.id", ondelete="CASCADE"), nullable=False, index=True)
+    knowledge_base_mapping_id: Mapped[str] = mapped_column(String(36), nullable=False, index=True)
+    section_index: Mapped[int] = mapped_column(Integer, nullable=False)
+    heading: Mapped[str | None] = mapped_column(String(1024), nullable=True)
+    section_content: Mapped[str] = mapped_column(PortableLongText(), nullable=False)
+    content_hash: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
+    embedding_fingerprint: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
+    embedding_dimensions: Mapped[int] = mapped_column(Integer, nullable=False)
+    vector_blob: Mapped[bytes] = mapped_column(LargeBinary, nullable=False)
+    created_at: Mapped[datetime] = mapped_column(BeijingDateTime(), nullable=False, default=_now)
+
+
+class LlmWikiWikiSyncStateRow(Base):
+    __tablename__ = "llmwiki_wiki_sync_states"
+
+    knowledge_base_mapping_id: Mapped[str] = mapped_column(String(36), ForeignKey("llmwiki_knowledge_bases.id", ondelete="CASCADE"), primary_key=True)
+    state: Mapped[str] = mapped_column(String(24), nullable=False, default="idle")
+    active_sync_id: Mapped[str | None] = mapped_column(String(36), nullable=True)
+    lease_owner: Mapped[str | None] = mapped_column(String(128), nullable=True)
+    lease_expires_at: Mapped[datetime | None] = mapped_column(BeijingDateTime(), nullable=True)
+    last_started_at: Mapped[datetime | None] = mapped_column(BeijingDateTime(), nullable=True)
+    last_completed_at: Mapped[datetime | None] = mapped_column(BeijingDateTime(), nullable=True)
+    last_success_at: Mapped[datetime | None] = mapped_column(BeijingDateTime(), nullable=True)
+    last_error: Mapped[str | None] = mapped_column(Text, nullable=True)
+    remote_page_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+    local_page_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+    ready_page_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+    vector_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+    failed_page_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+    index_revision: Mapped[int] = mapped_column(BigInteger, nullable=False, default=0)
+    embedding_fingerprint: Mapped[str | None] = mapped_column(String(64), nullable=True)
+    updated_at: Mapped[datetime] = mapped_column(BeijingDateTime(), nullable=False, default=_now, onupdate=_now)

offline-backend-20260512/backend/packages/harness/deerflow/persistence/llmwiki_index/sql.py

@@ -0,0 +1,295 @@
+"""SQLAlchemy implementation of the local Wiki index store."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime, timedelta
+from typing import Any
+from uuid import uuid4
+
+from sqlalchemy import case, delete, func, or_, select, update
+from sqlalchemy.exc import IntegrityError
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
+
+from deerflow.persistence.llmwiki_index.base import LlmWikiIndexStore
+from deerflow.persistence.llmwiki_index.model import LlmWikiWikiPageRow, LlmWikiWikiSyncStateRow, LlmWikiWikiVectorRow
+
+
+def _now() -> datetime:
+    return datetime.now(UTC)
+
+
+def _dict(row) -> dict[str, Any]:
+    value = row.to_dict()
+    for key, item in tuple(value.items()):
+        if isinstance(item, datetime):
+            value[key] = item.isoformat()
+    return value
+
+
+class SqlLlmWikiIndexStore(LlmWikiIndexStore):
+    def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
+        self._sf = session_factory
+
+    async def _ensure_state(self, session: AsyncSession, mapping_id: str) -> LlmWikiWikiSyncStateRow:
+        row = await session.get(LlmWikiWikiSyncStateRow, mapping_id)
+        if row is None:
+            row = LlmWikiWikiSyncStateRow(knowledge_base_mapping_id=mapping_id, state="idle", index_revision=0, updated_at=_now())
+            session.add(row)
+            await session.flush()
+        return row
+
+    async def get_page_by_slug_hash(self, mapping_id: str, slug_hash: str) -> dict[str, Any] | None:
+        stmt = select(LlmWikiWikiPageRow).where(LlmWikiWikiPageRow.knowledge_base_mapping_id == mapping_id, LlmWikiWikiPageRow.slug_hash == slug_hash)
+        async with self._sf() as session:
+            row = (await session.execute(stmt)).scalar_one_or_none()
+            return _dict(row) if row else None
+
+    async def get_page(self, mapping_id: str, slug: str) -> dict[str, Any] | None:
+        stmt = select(LlmWikiWikiPageRow).where(LlmWikiWikiPageRow.knowledge_base_mapping_id == mapping_id, LlmWikiWikiPageRow.slug == slug)
+        async with self._sf() as session:
+            row = (await session.execute(stmt)).scalar_one_or_none()
+            return _dict(row) if row else None
+
+    async def touch_page(self, page_id: str, sync_id: str) -> None:
+        async with self._sf() as session:
+            await session.execute(
+                update(LlmWikiWikiPageRow)
+                .where(LlmWikiWikiPageRow.id == page_id)
+                .values(last_seen_sync_id=sync_id, last_error=None, updated_at=_now())
+            )
+            await session.commit()
+
+    async def replace_page_vectors(self, *, page: dict[str, Any], vectors: list[dict[str, Any]], fingerprint: str, sync_id: str) -> dict[str, Any]:
+        mapping_id = str(page["knowledge_base_mapping_id"])
+        async with self._sf() as session:
+            stmt = select(LlmWikiWikiPageRow).where(LlmWikiWikiPageRow.knowledge_base_mapping_id == mapping_id, LlmWikiWikiPageRow.slug_hash == page["slug_hash"]).with_for_update()
+            row = (await session.execute(stmt)).scalar_one_or_none()
+            if row is not None and row.slug != page["slug"]:
+                raise ValueError("Wiki slug hash collision detected")
+            now = _now()
+            if row is None:
+                row = LlmWikiWikiPageRow(id=str(uuid4()), created_at=now, **page)
+                session.add(row)
+            else:
+                for key, value in page.items():
+                    setattr(row, key, value)
+            row.index_status = "ready"
+            row.indexed_fingerprint = fingerprint
+            row.indexed_at = now
+            row.last_error = None
+            row.is_remote_deleted = False
+            row.last_seen_sync_id = sync_id
+            row.updated_at = now
+            await session.flush()
+            await session.execute(delete(LlmWikiWikiVectorRow).where(LlmWikiWikiVectorRow.page_id == row.id))
+            session.add_all(
+                [
+                    LlmWikiWikiVectorRow(
+                        id=str(uuid4()),
+                        page_id=row.id,
+                        knowledge_base_mapping_id=mapping_id,
+                        section_index=int(item["section_index"]),
+                        heading=item.get("heading"),
+                        section_content=str(item["section_content"]),
+                        content_hash=str(item["content_hash"]),
+                        embedding_fingerprint=fingerprint,
+                        embedding_dimensions=int(item["embedding_dimensions"]),
+                        vector_blob=bytes(item["vector_blob"]),
+                        created_at=now,
+                    )
+                    for item in vectors
+                ]
+            )
+            state = await self._ensure_state(session, mapping_id)
+            state.index_revision = int(state.index_revision or 0) + 1
+            state.embedding_fingerprint = fingerprint
+            state.updated_at = now
+            await session.commit()
+            return _dict(row)
+
+    async def record_page_failure(self, *, page: dict[str, Any], sync_id: str, error: str) -> None:
+        mapping_id = str(page["knowledge_base_mapping_id"])
+        safe_error = error[:4000]
+        async with self._sf() as session:
+            stmt = select(LlmWikiWikiPageRow).where(LlmWikiWikiPageRow.knowledge_base_mapping_id == mapping_id, LlmWikiWikiPageRow.slug_hash == page["slug_hash"])
+            row = (await session.execute(stmt)).scalar_one_or_none()
+            now = _now()
+            if row is None:
+                row = LlmWikiWikiPageRow(id=str(uuid4()), created_at=now, **page)
+                session.add(row)
+                row.index_status = "failed"
+            else:
+                vector_count = int((await session.execute(select(func.count()).select_from(LlmWikiWikiVectorRow).where(LlmWikiWikiVectorRow.page_id == row.id))).scalar_one())
+                # Preserve the last atomically completed generation while the
+                # newer remote version remains pending after an embedding error.
+                row.index_status = "ready" if vector_count else "failed"
+            row.last_seen_sync_id = sync_id
+            row.last_error = safe_error
+            row.updated_at = now
+            await self._ensure_state(session, mapping_id)
+            await session.commit()
+
+    async def mark_missing_pages_deleted(self, mapping_id: str, sync_id: str) -> int:
+        async with self._sf() as session:
+            stmt = (
+                select(LlmWikiWikiPageRow)
+                .where(
+                    LlmWikiWikiPageRow.knowledge_base_mapping_id == mapping_id,
+                    LlmWikiWikiPageRow.is_remote_deleted.is_(False),
+                    or_(LlmWikiWikiPageRow.last_seen_sync_id.is_(None), LlmWikiWikiPageRow.last_seen_sync_id != sync_id),
+                )
+                .with_for_update()
+            )
+            rows = list((await session.execute(stmt)).scalars())
+            if not rows:
+                return 0
+            now = _now()
+            page_ids = [row.id for row in rows]
+            await session.execute(delete(LlmWikiWikiVectorRow).where(LlmWikiWikiVectorRow.page_id.in_(page_ids)))
+            for row in rows:
+                row.is_remote_deleted = True
+                row.index_status = "deleted"
+                row.updated_at = now
+            state = await self._ensure_state(session, mapping_id)
+            state.index_revision = int(state.index_revision or 0) + 1
+            state.updated_at = now
+            await session.commit()
+            return len(rows)
+
+    async def load_vector_snapshot(self, mapping_id: str, fingerprint: str) -> dict[str, Any]:
+        stmt = (
+            select(LlmWikiWikiVectorRow, LlmWikiWikiPageRow)
+            .join(LlmWikiWikiPageRow, LlmWikiWikiPageRow.id == LlmWikiWikiVectorRow.page_id)
+            .where(
+                LlmWikiWikiVectorRow.knowledge_base_mapping_id == mapping_id,
+                LlmWikiWikiVectorRow.embedding_fingerprint == fingerprint,
+                LlmWikiWikiPageRow.index_status == "ready",
+                LlmWikiWikiPageRow.is_remote_deleted.is_(False),
+                LlmWikiWikiPageRow.status.in_(["published", "draft"]),
+            )
+            .order_by(LlmWikiWikiVectorRow.page_id, LlmWikiWikiVectorRow.section_index)
+        )
+        async with self._sf() as session:
+            state = await session.get(LlmWikiWikiSyncStateRow, mapping_id)
+            pairs = list((await session.execute(stmt)).all())
+            rows = [{**_dict(vector), "page": _dict(page)} for vector, page in pairs]
+            return {"revision": int(state.index_revision if state else 0), "fingerprint": fingerprint, "rows": rows}
+
+    async def get_index_revision(self, mapping_id: str) -> tuple[int, str | None, str]:
+        async with self._sf() as session:
+            state = await session.get(LlmWikiWikiSyncStateRow, mapping_id)
+            if state is None:
+                return 0, None, "not_synced"
+            return int(state.index_revision or 0), state.embedding_fingerprint, state.state
+
+    async def try_acquire_sync_lease(self, mapping_id: str, *, owner: str, sync_id: str, lease_seconds: int, fingerprint: str) -> bool:
+        now = _now()
+        async with self._sf() as session:
+            try:
+                await self._ensure_state(session, mapping_id)
+                await session.commit()
+            except IntegrityError:
+                # Another worker created the one-per-KB state row between our
+                # read and insert. Roll back this isolated bootstrap session;
+                # the conditional UPDATE below is the actual lease election.
+                await session.rollback()
+        async with self._sf() as session:
+            stmt = (
+                update(LlmWikiWikiSyncStateRow)
+                .where(
+                    LlmWikiWikiSyncStateRow.knowledge_base_mapping_id == mapping_id,
+                    or_(
+                        LlmWikiWikiSyncStateRow.lease_owner.is_(None),
+                        LlmWikiWikiSyncStateRow.lease_expires_at.is_(None),
+                        LlmWikiWikiSyncStateRow.lease_expires_at < now,
+                    ),
+                )
+                .values(
+                    state=case((LlmWikiWikiSyncStateRow.state == "rebuild_required", "rebuilding"), else_="running"),
+                    active_sync_id=sync_id,
+                    lease_owner=owner,
+                    lease_expires_at=now + timedelta(seconds=lease_seconds),
+                    last_started_at=now,
+                    last_error=None,
+                    updated_at=now,
+                )
+            )
+            result = await session.execute(stmt)
+            await session.commit()
+            return bool(result.rowcount)
+
+    async def renew_sync_lease(self, mapping_id: str, *, owner: str, lease_seconds: int) -> bool:
+        now = _now()
+        async with self._sf() as session:
+            result = await session.execute(
+                update(LlmWikiWikiSyncStateRow)
+                .where(LlmWikiWikiSyncStateRow.knowledge_base_mapping_id == mapping_id, LlmWikiWikiSyncStateRow.lease_owner == owner)
+                .values(lease_expires_at=now + timedelta(seconds=lease_seconds), updated_at=now)
+            )
+            await session.commit()
+            return bool(result.rowcount)
+
+    async def finish_sync(self, mapping_id: str, *, owner: str, sync_id: str, success: bool, remote_page_count: int, error: str | None = None) -> None:
+        async with self._sf() as session:
+            state = await session.get(LlmWikiWikiSyncStateRow, mapping_id)
+            if state is None or state.lease_owner != owner or state.active_sync_id != sync_id:
+                return
+            visible = [LlmWikiWikiPageRow.knowledge_base_mapping_id == mapping_id, LlmWikiWikiPageRow.is_remote_deleted.is_(False)]
+            local_count = int((await session.execute(select(func.count()).select_from(LlmWikiWikiPageRow).where(*visible))).scalar_one())
+            ready_count = int((await session.execute(select(func.count()).select_from(LlmWikiWikiPageRow).where(*visible, LlmWikiWikiPageRow.index_status == "ready"))).scalar_one())
+            failed_count = int(
+                (
+                    await session.execute(
+                        select(func.count())
+                        .select_from(LlmWikiWikiPageRow)
+                        .where(
+                            *visible,
+                            or_(
+                                LlmWikiWikiPageRow.index_status.in_(["failed", "stale"]),
+                                LlmWikiWikiPageRow.last_error.is_not(None),
+                            ),
+                        )
+                    )
+                ).scalar_one()
+            )
+            vector_count = int((await session.execute(select(func.count()).select_from(LlmWikiWikiVectorRow).where(LlmWikiWikiVectorRow.knowledge_base_mapping_id == mapping_id))).scalar_one())
+            now = _now()
+            was_rebuilding = state.state == "rebuilding"
+            state.state = "partial" if success and error else "idle" if success else "rebuild_required" if was_rebuilding else "failed"
+            state.active_sync_id = None
+            state.lease_owner = None
+            state.lease_expires_at = None
+            state.last_error = (error or "")[:4000] or None
+            state.remote_page_count = remote_page_count
+            state.local_page_count = local_count
+            state.ready_page_count = ready_count
+            state.failed_page_count = failed_count
+            state.vector_count = vector_count
+            if success and not error:
+                state.last_completed_at = now
+            if success:
+                state.last_success_at = now
+            state.updated_at = now
+            await session.commit()
+
+    async def list_index_status(self, mapping_ids: list[str] | None = None) -> list[dict[str, Any]]:
+        stmt = select(LlmWikiWikiSyncStateRow)
+        if mapping_ids:
+            stmt = stmt.where(LlmWikiWikiSyncStateRow.knowledge_base_mapping_id.in_(mapping_ids))
+        stmt = stmt.order_by(LlmWikiWikiSyncStateRow.updated_at.desc())
+        async with self._sf() as session:
+            return [_dict(row) for row in (await session.execute(stmt)).scalars()]
+
+    async def mark_rebuild_required(self, mapping_ids: list[str], fingerprint: str) -> int:
+        if not mapping_ids:
+            return 0
+        now = _now()
+        async with self._sf() as session:
+            for mapping_id in mapping_ids:
+                state = await self._ensure_state(session, mapping_id)
+                state.state = "rebuild_required"
+                state.embedding_fingerprint = fingerprint
+                state.updated_at = now
+            await session.execute(update(LlmWikiWikiPageRow).where(LlmWikiWikiPageRow.knowledge_base_mapping_id.in_(mapping_ids), LlmWikiWikiPageRow.is_remote_deleted.is_(False)).values(index_status="stale", updated_at=now))
+            await session.commit()
+        return len(mapping_ids)

offline-backend-20260512/backend/packages/harness/deerflow/persistence/migrations/versions/20260821_01_fixed_questions.py

@@ -0,0 +1,51 @@
+"""Create administrator-managed exact-match fixed questions.
+
+Revision ID: 20260821_01
+Revises: 20260816_01
+Create Date: 2026-08-21
+"""
+
+from __future__ import annotations
+
+import sqlalchemy as sa
+from alembic import op
+from sqlalchemy.dialects import mysql
+
+revision = "20260821_01"
+down_revision = "20260816_01"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    bind = op.get_bind()
+    if sa.inspect(bind).has_table("fixed_questions"):
+        return
+    long_text = sa.Text().with_variant(mysql.LONGTEXT(), "mysql")
+    op.create_table(
+        "fixed_questions",
+        sa.Column("id", sa.String(length=64), primary_key=True),
+        sa.Column("question", sa.Text(), nullable=False),
+        sa.Column("question_hash", sa.String(length=64), nullable=False),
+        sa.Column("answer", long_text, nullable=False),
+        sa.Column("enabled", sa.Boolean(), nullable=False, server_default=sa.true()),
+        sa.Column("sort_order", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("updated_by", sa.String(length=64), nullable=True),
+        sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False),
+        sa.UniqueConstraint(
+            "question_hash",
+            name="uq_fixed_questions_question_hash",
+        ),
+    )
+    op.create_index(
+        "ix_fixed_questions_question_hash",
+        "fixed_questions",
+        ["question_hash"],
+        unique=False,
+    )
+
+
+def downgrade() -> None:
+    bind = op.get_bind()
+    if sa.inspect(bind).has_table("fixed_questions"):
+        op.drop_table("fixed_questions")

offline-backend-20260512/backend/packages/harness/deerflow/persistence/migrations/versions/20260821_02_fixed_question_stream_speed.py

@@ -0,0 +1,44 @@
+"""Add configurable fixed-answer streaming speed.
+
+Revision ID: 20260821_02
+Revises: 20260821_01
+Create Date: 2026-08-21
+"""
+
+from __future__ import annotations
+
+import sqlalchemy as sa
+from alembic import op
+
+revision = "20260821_02"
+down_revision = "20260821_01"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    bind = op.get_bind()
+    inspector = sa.inspect(bind)
+    if not inspector.has_table("fixed_questions"):
+        return
+    columns = {column["name"] for column in inspector.get_columns("fixed_questions")}
+    if "tokens_per_second" not in columns:
+        op.add_column(
+            "fixed_questions",
+            sa.Column(
+                "tokens_per_second",
+                sa.Integer(),
+                nullable=False,
+                server_default="100",
+            ),
+        )
+
+
+def downgrade() -> None:
+    bind = op.get_bind()
+    inspector = sa.inspect(bind)
+    if not inspector.has_table("fixed_questions"):
+        return
+    columns = {column["name"] for column in inspector.get_columns("fixed_questions")}
+    if "tokens_per_second" in columns:
+        op.drop_column("fixed_questions", "tokens_per_second")

offline-backend-20260512/backend/packages/harness/deerflow/persistence/migrations/versions/20260823_01_llmwiki_local_wiki_index.py

@@ -0,0 +1,143 @@
+"""Add DeerFlow-local WeKnora Wiki mirror and vector index.
+
+Revision ID: 20260823_01
+Revises: 20260821_02
+Create Date: 2026-08-23
+"""
+
+from __future__ import annotations
+
+import sqlalchemy as sa
+from alembic import op
+from sqlalchemy.dialects import mysql
+
+revision = "20260823_01"
+down_revision = "20260821_02"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    bind = op.get_bind()
+    inspector = sa.inspect(bind)
+    columns = {column["name"] for column in inspector.get_columns("llmwiki_knowledge_bases")}
+    if "wiki_index_enabled" not in columns:
+        op.add_column("llmwiki_knowledge_bases", sa.Column("wiki_index_enabled", sa.Boolean(), nullable=False, server_default=sa.true()))
+    if "external_search_enabled" not in columns:
+        op.add_column("llmwiki_knowledge_bases", sa.Column("external_search_enabled", sa.Boolean(), nullable=False, server_default=sa.false()))
+    if "external_search_updated_at" not in columns:
+        op.add_column("llmwiki_knowledge_bases", sa.Column("external_search_updated_at", sa.DateTime(timezone=True), nullable=True))
+    mapping_indexes = {index["name"] for index in inspector.get_indexes("llmwiki_knowledge_bases")}
+    if "ix_llmwiki_knowledge_bases_wiki_index_enabled" not in mapping_indexes:
+        op.create_index("ix_llmwiki_knowledge_bases_wiki_index_enabled", "llmwiki_knowledge_bases", ["wiki_index_enabled"])
+    if "ix_llmwiki_knowledge_bases_external_search_enabled" not in mapping_indexes:
+        op.create_index("ix_llmwiki_knowledge_bases_external_search_enabled", "llmwiki_knowledge_bases", ["external_search_enabled"])
+
+    long_text = sa.Text().with_variant(mysql.LONGTEXT(), "mysql")
+    portable_json = sa.JSON().with_variant(sa.Text(), "mysql")
+    if not inspector.has_table("llmwiki_wiki_pages"):
+        op.create_table(
+            "llmwiki_wiki_pages",
+            sa.Column("id", sa.String(36), primary_key=True),
+            sa.Column("knowledge_base_mapping_id", sa.String(36), sa.ForeignKey("llmwiki_knowledge_bases.id", ondelete="CASCADE"), nullable=False),
+            sa.Column("remote_page_id", sa.String(128), nullable=True),
+            sa.Column("slug", sa.String(1024), nullable=False),
+            sa.Column("slug_hash", sa.String(64), nullable=False),
+            sa.Column("title", sa.String(512), nullable=False, server_default=""),
+            sa.Column("summary", long_text, nullable=False),
+            sa.Column("content_md", long_text, nullable=False),
+            sa.Column("page_type", sa.String(32), nullable=False, server_default="article"),
+            sa.Column("status", sa.String(32), nullable=False, server_default="published"),
+            sa.Column("aliases", portable_json, nullable=False),
+            sa.Column("category_path", portable_json, nullable=False),
+            sa.Column("parent_slug", sa.String(1024), nullable=True),
+            sa.Column("wiki_path", sa.String(1024), nullable=True),
+            sa.Column("source_refs", portable_json, nullable=False),
+            sa.Column("chunk_refs", portable_json, nullable=False),
+            sa.Column("page_version", sa.Integer(), nullable=False, server_default="0"),
+            sa.Column("content_hash", sa.String(64), nullable=False),
+            sa.Column("remote_created_at", sa.DateTime(timezone=True), nullable=True),
+            sa.Column("remote_updated_at", sa.DateTime(timezone=True), nullable=True),
+            sa.Column("index_status", sa.String(24), nullable=False, server_default="pending"),
+            sa.Column("indexed_fingerprint", sa.String(64), nullable=True),
+            sa.Column("indexed_at", sa.DateTime(timezone=True), nullable=True),
+            sa.Column("last_error", sa.Text(), nullable=True),
+            sa.Column("is_remote_deleted", sa.Boolean(), nullable=False, server_default=sa.false()),
+            sa.Column("last_seen_sync_id", sa.String(36), nullable=True),
+            sa.Column("created_at", sa.DateTime(timezone=True), nullable=False),
+            sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False),
+            sa.UniqueConstraint("knowledge_base_mapping_id", "slug_hash", name="uq_llmwiki_wiki_page_mapping_slug_hash"),
+        )
+        op.create_index("ix_llmwiki_wiki_pages_knowledge_base_mapping_id", "llmwiki_wiki_pages", ["knowledge_base_mapping_id"])
+        op.create_index("ix_llmwiki_wiki_page_mapping_visibility", "llmwiki_wiki_pages", ["knowledge_base_mapping_id", "status", "index_status", "is_remote_deleted"])
+        op.create_index("ix_llmwiki_wiki_pages_remote_page_id", "llmwiki_wiki_pages", ["remote_page_id"])
+        op.create_index("ix_llmwiki_wiki_pages_title", "llmwiki_wiki_pages", ["title"])
+        op.create_index("ix_llmwiki_wiki_pages_page_type", "llmwiki_wiki_pages", ["page_type"])
+        op.create_index("ix_llmwiki_wiki_pages_status", "llmwiki_wiki_pages", ["status"])
+        op.create_index("ix_llmwiki_wiki_pages_page_version", "llmwiki_wiki_pages", ["page_version"])
+        op.create_index("ix_llmwiki_wiki_pages_content_hash", "llmwiki_wiki_pages", ["content_hash"])
+        op.create_index("ix_llmwiki_wiki_pages_remote_updated_at", "llmwiki_wiki_pages", ["remote_updated_at"])
+        op.create_index("ix_llmwiki_wiki_pages_index_status", "llmwiki_wiki_pages", ["index_status"])
+        op.create_index("ix_llmwiki_wiki_pages_is_remote_deleted", "llmwiki_wiki_pages", ["is_remote_deleted"])
+        op.create_index("ix_llmwiki_wiki_pages_last_seen_sync_id", "llmwiki_wiki_pages", ["last_seen_sync_id"])
+        op.create_index("ix_llmwiki_wiki_pages_updated_at", "llmwiki_wiki_pages", ["updated_at"])
+
+    if not inspector.has_table("llmwiki_wiki_vectors"):
+        op.create_table(
+            "llmwiki_wiki_vectors",
+            sa.Column("id", sa.String(36), primary_key=True),
+            sa.Column("page_id", sa.String(36), sa.ForeignKey("llmwiki_wiki_pages.id", ondelete="CASCADE"), nullable=False),
+            sa.Column("knowledge_base_mapping_id", sa.String(36), nullable=False),
+            sa.Column("section_index", sa.Integer(), nullable=False),
+            sa.Column("heading", sa.String(1024), nullable=True),
+            sa.Column("section_content", long_text, nullable=False),
+            sa.Column("content_hash", sa.String(64), nullable=False),
+            sa.Column("embedding_fingerprint", sa.String(64), nullable=False),
+            sa.Column("embedding_dimensions", sa.Integer(), nullable=False),
+            sa.Column("vector_blob", sa.LargeBinary(), nullable=False),
+            sa.Column("created_at", sa.DateTime(timezone=True), nullable=False),
+            sa.UniqueConstraint("page_id", "section_index", "embedding_fingerprint", name="uq_llmwiki_wiki_vector_page_section_fingerprint"),
+        )
+        op.create_index("ix_llmwiki_wiki_vector_snapshot", "llmwiki_wiki_vectors", ["knowledge_base_mapping_id", "embedding_fingerprint"])
+        op.create_index("ix_llmwiki_wiki_vectors_page_id", "llmwiki_wiki_vectors", ["page_id"])
+        op.create_index("ix_llmwiki_wiki_vectors_knowledge_base_mapping_id", "llmwiki_wiki_vectors", ["knowledge_base_mapping_id"])
+        op.create_index("ix_llmwiki_wiki_vectors_content_hash", "llmwiki_wiki_vectors", ["content_hash"])
+        op.create_index("ix_llmwiki_wiki_vectors_embedding_fingerprint", "llmwiki_wiki_vectors", ["embedding_fingerprint"])
+
+    if not inspector.has_table("llmwiki_wiki_sync_states"):
+        op.create_table(
+            "llmwiki_wiki_sync_states",
+            sa.Column("knowledge_base_mapping_id", sa.String(36), sa.ForeignKey("llmwiki_knowledge_bases.id", ondelete="CASCADE"), primary_key=True),
+            sa.Column("state", sa.String(24), nullable=False, server_default="idle"),
+            sa.Column("active_sync_id", sa.String(36), nullable=True),
+            sa.Column("lease_owner", sa.String(128), nullable=True),
+            sa.Column("lease_expires_at", sa.DateTime(timezone=True), nullable=True),
+            sa.Column("last_started_at", sa.DateTime(timezone=True), nullable=True),
+            sa.Column("last_completed_at", sa.DateTime(timezone=True), nullable=True),
+            sa.Column("last_success_at", sa.DateTime(timezone=True), nullable=True),
+            sa.Column("last_error", sa.Text(), nullable=True),
+            sa.Column("remote_page_count", sa.Integer(), nullable=False, server_default="0"),
+            sa.Column("local_page_count", sa.Integer(), nullable=False, server_default="0"),
+            sa.Column("ready_page_count", sa.Integer(), nullable=False, server_default="0"),
+            sa.Column("vector_count", sa.Integer(), nullable=False, server_default="0"),
+            sa.Column("failed_page_count", sa.Integer(), nullable=False, server_default="0"),
+            sa.Column("index_revision", sa.BigInteger(), nullable=False, server_default="0"),
+            sa.Column("embedding_fingerprint", sa.String(64), nullable=True),
+            sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False),
+        )
+
+
+def downgrade() -> None:
+    bind = op.get_bind()
+    inspector = sa.inspect(bind)
+    for table in ("llmwiki_wiki_vectors", "llmwiki_wiki_pages", "llmwiki_wiki_sync_states"):
+        if inspector.has_table(table):
+            op.drop_table(table)
+    columns = {column["name"] for column in inspector.get_columns("llmwiki_knowledge_bases")}
+    indexes = {index["name"] for index in inspector.get_indexes("llmwiki_knowledge_bases")}
+    for index in ("ix_llmwiki_knowledge_bases_external_search_enabled", "ix_llmwiki_knowledge_bases_wiki_index_enabled"):
+        if index in indexes:
+            op.drop_index(index, table_name="llmwiki_knowledge_bases")
+    for column in ("external_search_updated_at", "external_search_enabled", "wiki_index_enabled"):
+        if column in columns:
+            op.drop_column("llmwiki_knowledge_bases", column)

offline-backend-20260512/backend/packages/harness/deerflow/persistence/models/__init__.py

@@ -47,10 +47,12 @@ from deerflow.persistence.deep_research_sources.model import DeepResearchSourceR
 from deerflow.persistence.document_rewrite_versions.model import DocumentRewriteVersionRow
 from deerflow.persistence.embed_sessions.model import EmbedSessionRow
 from deerflow.persistence.feedback.model import FeedbackRow
+from deerflow.persistence.fixed_questions.model import FixedQuestionRow
 from deerflow.persistence.intent_turns.model import IntentTurnRow
 from deerflow.persistence.light_apps.model import LightAppRow
 from deerflow.persistence.llm_metrics.model import LlmCallMetricRow
 from deerflow.persistence.llmwiki.model import LlmWikiConversationDepositRow, LlmWikiKnowledgeBaseRow
+from deerflow.persistence.llmwiki_index.model import LlmWikiWikiPageRow, LlmWikiWikiSyncStateRow, LlmWikiWikiVectorRow
 from deerflow.persistence.memory_config.model import UserMemoryConfigRow
 from deerflow.persistence.menu_overrides.model import MenuOverrideRow
 from deerflow.persistence.models.run_event import RunEventRow
@@ -98,6 +100,7 @@ from deerflow.persistence.user_prompts.model import UserCustomPromptRow
 
 __all__ = [
     "FeedbackRow",
+    "FixedQuestionRow",
     "AgentExtrasRow",
     "AgentFavoriteRow",
     "AgentRow",
@@ -128,6 +131,9 @@ __all__ = [
     "LlmCallMetricRow",
     "LlmWikiKnowledgeBaseRow",
     "LlmWikiConversationDepositRow",
+    "LlmWikiWikiPageRow",
+    "LlmWikiWikiVectorRow",
+    "LlmWikiWikiSyncStateRow",
     "MenuOverrideRow",
     "NotificationRow",
     "ParallelAgentTaskRow",

offline-backend-20260512/backend/packages/harness/deerflow/tools/builtins/llmwiki_search_tool.py

@@ -6,28 +6,25 @@ import json
 import re
 from collections.abc import Mapping
 from typing import Any
-from urllib.parse import urlencode
 
 from langchain.tools import ToolRuntime, tool
 from langgraph.typing import ContextT
 
 from deerflow.agents.thread_state import ThreadState
+from deerflow.config import get_app_config
 from deerflow.config.agents_config import load_agent_config
-from deerflow.integrations.weknora.client import WeKnoraError
+from deerflow.integrations.weknora.local_index.runtime import get_local_wiki_retrieval_service
-from deerflow.integrations.weknora.runtime import build_weknora_client, get_llmwiki_store, get_resolved_llmwiki_runtime
+from deerflow.integrations.weknora.local_index.search import WikiIndexError
+from deerflow.integrations.weknora.runtime import get_llmwiki_store, get_resolved_llmwiki_runtime
 from deerflow.runtime.user_context import get_current_user, get_effective_user_id
 
-
 _CONVERSATION_DEPOSIT_NAME = "对话沉淀"
 _CONVERSATION_DEPOSIT_OWNER_USER_ID = "system"
 _LEGACY_BRAND_PATTERN = re.compile(r"deer[\s_-]*flow", re.IGNORECASE)
 
 
 def _is_conversation_deposit_mapping(row: Mapping[str, Any]) -> bool:
-    return (
+    return str(row.get("owner_user_id") or "") == _CONVERSATION_DEPOSIT_OWNER_USER_ID and str(row.get("name") or "").strip() == _CONVERSATION_DEPOSIT_NAME
-        str(row.get("owner_user_id") or "") == _CONVERSATION_DEPOSIT_OWNER_USER_ID
-        and str(row.get("name") or "").strip() == _CONVERSATION_DEPOSIT_NAME
-    )
 
 
 def _sanitize_conversation_deposit_value(value: Any) -> Any:
@@ -79,9 +76,10 @@ async def llmwiki_search_tool(
         query: Focused natural-language retrieval query.
     """
 
+    local_config = get_app_config().llmwiki.local_wiki_index
     resolved = get_resolved_llmwiki_runtime()
-    if not resolved.weknora_enabled:
+    if not (local_config.enabled and local_config.internal_search_enabled) and not resolved.weknora_enabled:
-        return "LLMWiki retrieval is unavailable because WeKnora mode is not enabled."
+        return "LLMWiki retrieval is unavailable because no retrieval provider is enabled."
 
     store = get_llmwiki_store()
     user_id = get_effective_user_id()
@@ -111,52 +109,26 @@ async def llmwiki_search_tool(
         return "No authorized LLMWiki knowledge bases are available."
 
     try:
-        results = await build_weknora_client(resolved).search(
+        payload = await get_local_wiki_retrieval_service().search(query.strip(), rows)
-            query.strip(),
+    except (RuntimeError, WikiIndexError) as exc:
-            [str(row["weknora_id"]) for row in rows],
+        code = exc.code if isinstance(exc, WikiIndexError) else "WIKI_RETRIEVAL_UNAVAILABLE"
-        )
+        return f"LLMWiki Wiki-only retrieval failed ({code}); retrieval is unavailable, not empty."
-    except (RuntimeError, WeKnoraError) as exc:
+    mapping_by_id = {str(row["id"]): row for row in rows}
-        return f"LLMWiki retrieval failed: {exc}"
+    results = []
-
+    for item in payload["results"]:
-    local_by_remote = {str(row["weknora_id"]): row for row in rows}
+        mapping = mapping_by_id.get(str(item.get("knowledge_base_id") or ""))
-    citations = []
+        visible = _sanitize_conversation_deposit_value(item) if mapping and _is_conversation_deposit_mapping(mapping) else item
-    for result in results:
+        results.append(visible)
-        mapping = local_by_remote.get(str(result.get("knowledge_base_id") or ""))
-        if mapping is None:
-            continue
-        visible_result = (
-            _sanitize_conversation_deposit_value(result)
-            if _is_conversation_deposit_mapping(mapping)
-            else result
-        )
-        params = urlencode(
-            {
-                "knowledge_base_id": mapping["id"],
-                "chunk_id": visible_result.get("chunk_id") or "",
-                "knowledge_id": visible_result.get("knowledge_id") or "",
-                "document_id": visible_result.get("knowledge_id") or "",
-                "wiki_slug": visible_result.get("wiki_slug") or visible_result.get("slug") or "",
-            }
-        )
-        citations.append(
-            {
-                "title": visible_result.get("title") or visible_result.get("filename") or mapping.get("name") or "LLMWiki source",
-                "content": visible_result.get("content") or "",
-                "score": visible_result.get("score") or 0,
-                "knowledge_base_id": mapping["id"],
-                "knowledge_base_name": mapping.get("name") or "",
-                "source": mapping.get("name") or "LLMWiki",
-                "knowledge_id": visible_result.get("knowledge_id") or "",
-                "chunk_id": visible_result.get("chunk_id") or "",
-                "url": f"/weknora-source-preview?{params}",
-            }
-        )
     return json.dumps(
         {
             "query": query,
             "selection": [row["id"] for row in rows],
             "knowledge_base_count": len(rows),
-            "results": citations,
+            "mode": payload.get("mode") or "wiki_api",
+            "results": results,
+            "partial": payload.get("partial", False),
+            "warnings": payload.get("warnings", []),
+            "fallback_knowledge_base_ids": payload.get("fallback_knowledge_base_ids", []),
         },
         ensure_ascii=False,
     )

offline-backend-20260512/backend/packages/harness/pyproject.toml

@@ -21,7 +21,8 @@ dependencies = [
     "langgraph-cli>=0.4.24",
     "langgraph-runtime-inmem>=0.28.0",
     "markdownify>=1.2.2",
-    "markitdown[all,xlsx]>=0.0.1a2",
+    "markitdown[all,xlsx]>=0.0.1a2",
+    "numpy>=2.0.0",
     "pydantic>=2.12.5",
     "pyyaml>=6.0.3",
     "readabilipy>=0.3.0",

offline-backend-20260512/backend/pyproject.toml

@@ -24,6 +24,7 @@ dependencies = [
     "croniter>=6.2.2",
     "hindsight-client>=0.4.22",
     "asyncmy>=0.2.11",
+    "openpyxl>=3.1.5",
 ]
 
 [project.optional-dependencies]

offline-backend-20260512/backend/tests/test_es_query_routing_prompt.py

@@ -0,0 +1,70 @@
+from types import SimpleNamespace
+
+from deerflow.agents.lead_agent import prompt as prompt_module
+from deerflow.config.skills_config import EsQueryRoutingConfig, SkillsConfig
+
+
+def _app_config(*, enabled: bool, prompt: str = "自定义 ES 路由规则") -> SimpleNamespace:
+    return SimpleNamespace(
+        skills=SkillsConfig(
+            es_query_routing=EsQueryRoutingConfig(enabled=enabled, prompt=prompt),
+        )
+    )
+
+
+def test_es_query_routing_config_is_disabled_by_default() -> None:
+    config = SkillsConfig()
+
+    assert config.es_query_routing.enabled is False
+    assert "es_query" in config.es_query_routing.prompt
+
+
+def test_es_query_routing_section_honors_switch_prompt_and_allowlist() -> None:
+    enabled = _app_config(enabled=True, prompt="  自定义 ES 路由规则  ")
+
+    assert prompt_module._build_es_query_routing_section(app_config=enabled) == (
+        '<skill_routing skill="es_query">\n自定义 ES 路由规则\n</skill_routing>'
+    )
+    assert (
+        prompt_module._build_es_query_routing_section(
+            app_config=enabled,
+            available_skills={"other_skill"},
+        )
+        == ""
+    )
+    assert "自定义 ES 路由规则" in prompt_module._build_es_query_routing_section(
+        app_config=enabled,
+        available_skills={"es_query"},
+    )
+    assert prompt_module._build_es_query_routing_section(app_config=_app_config(enabled=False)) == ""
+    assert prompt_module._build_es_query_routing_section(app_config=_app_config(enabled=True, prompt="  ")) == ""
+
+
+def test_es_query_routing_is_injected_into_lead_and_allowed_custom_agent_prompts(monkeypatch) -> None:
+    config = _app_config(enabled=True)
+    monkeypatch.setattr(prompt_module, "_get_memory_context", lambda *args, **kwargs: "")
+    monkeypatch.setattr(prompt_module, "get_agent_soul", lambda *args, **kwargs: "")
+    monkeypatch.setattr(prompt_module, "get_skills_prompt_section", lambda *args, **kwargs: "<skill_system />")
+    monkeypatch.setattr(prompt_module, "get_deferred_tools_prompt_section", lambda *args, **kwargs: "")
+    monkeypatch.setattr(prompt_module, "_build_acp_section", lambda *args, **kwargs: "")
+    monkeypatch.setattr(prompt_module, "_build_custom_mounts_section", lambda *args, **kwargs: "")
+    monkeypatch.setattr(prompt_module, "_current_time_context", lambda: "")
+
+    lead_prompt = prompt_module.apply_prompt_template(app_config=config)
+    allowed_custom_prompt = prompt_module.apply_agent_only_prompt_template(
+        agent_id="agent-with-es",
+        agent_name="Agent with ES",
+        available_skills={"es_query"},
+        app_config=config,
+    )
+    denied_custom_prompt = prompt_module.apply_agent_only_prompt_template(
+        agent_id="agent-without-es",
+        agent_name="Agent without ES",
+        available_skills={"other_skill"},
+        app_config=config,
+    )
+
+    assert '<skill_routing skill="es_query">' in lead_prompt
+    assert "自定义 ES 路由规则" in lead_prompt
+    assert '<skill_routing skill="es_query">' in allowed_custom_prompt
+    assert '<skill_routing skill="es_query">' not in denied_custom_prompt

offline-backend-20260512/backend/tests/test_external_llmwiki_search.py

@@ -0,0 +1,51 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+import pytest
+from fastapi import HTTPException
+from starlette.requests import Request
+
+from app.gateway.auth_middleware import _authorize_external_llmwiki
+from app.gateway.routers.external_llmwiki import _external_mappings
+
+
+def _request(key: str) -> Request:
+    return Request({"type": "http", "method": "POST", "path": "/api/external/llmwiki/wiki/vector-search", "headers": [(b"x-api-key", key.encode())]})
+
+
+def test_external_api_key_uses_isolated_fail_closed_auth(monkeypatch) -> None:
+    config = SimpleNamespace(enabled=True, api_key="current", previous_api_key="previous")
+    monkeypatch.setattr("deerflow.config.get_app_config", lambda: SimpleNamespace(llmwiki=SimpleNamespace(local_wiki_index=SimpleNamespace(external_api=config))))
+    assert _authorize_external_llmwiki(_request("current")) is None
+    assert _authorize_external_llmwiki(_request("previous")) is None
+    rejected = _authorize_external_llmwiki(_request("wrong"))
+    assert rejected is not None
+    assert rejected.status_code == 401
+
+
+@pytest.mark.asyncio
+async def test_external_mappings_require_explicit_public_external_permission() -> None:
+    rows = [
+        {"id": "allowed", "publication_status": "published", "external_search_enabled": True, "wiki_index_enabled": True},
+        {"id": "private", "publication_status": "private", "external_search_enabled": True, "wiki_index_enabled": True},
+        {"id": "not-opted-in", "publication_status": "published", "external_search_enabled": False, "wiki_index_enabled": True},
+        {
+            "id": "deposit",
+            "name": "对话沉淀",
+            "owner_user_id": "system",
+            "publication_status": "published",
+            "external_search_enabled": True,
+            "wiki_index_enabled": True,
+        },
+    ]
+
+    class Store:
+        async def list_visible(self, *_args, **_kwargs):
+            return rows
+
+    request = Request({"type": "http", "method": "POST", "path": "/", "headers": [], "app": SimpleNamespace(state=SimpleNamespace(llmwiki_store=Store()))})
+    assert [row["id"] for row in await _external_mappings(request, [])] == ["allowed"]
+    with pytest.raises(HTTPException) as exc_info:
+        await _external_mappings(request, ["not-opted-in"])
+    assert exc_info.value.status_code == 404

offline-backend-20260512/backend/tests/test_fixed_questions.py

@@ -0,0 +1,288 @@
+"""Regression tests for administrator-managed exact-match fixed answers."""
+
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+import pytest
+from langchain_core.messages import HumanMessage
+from pydantic import ValidationError
+from sqlalchemy.ext.asyncio import async_sessionmaker, create_async_engine
+
+from app.gateway.routers.fixed_questions import (
+    FixedQuestion,
+    FixedQuestionReplaceRequest,
+)
+from app.gateway.services import (
+    RUN_SCOPE_EXTERNAL_ROOT,
+    RUN_SCOPE_ORCHESTRATION_CHILD,
+    _find_fixed_answer,
+    normalize_input,
+)
+from deerflow.agents import fixed_answer_agent as fixed_answer_module
+from deerflow.agents.fixed_answer_agent import make_fixed_answer_agent
+from deerflow.persistence.fixed_questions import MemoryFixedQuestionStore
+from deerflow.persistence.fixed_questions.model import FixedQuestionRow
+from deerflow.persistence.fixed_questions.sql import FixedQuestionRepository
+
+
+def _body(**overrides):
+    data = {
+        "assistant_id": "lead_agent",
+        "command": None,
+        "context": {},
+    }
+    data.update(overrides)
+    return SimpleNamespace(**data)
+
+
+def _request(store: MemoryFixedQuestionStore):
+    return SimpleNamespace(
+        app=SimpleNamespace(
+            state=SimpleNamespace(fixed_question_store=store),
+        )
+    )
+
+
+@pytest.mark.asyncio
+async def test_memory_store_matches_only_enabled_exact_question() -> None:
+    store = MemoryFixedQuestionStore()
+    await store.replace_all(
+        [
+            {
+                "id": "enabled",
+                "question": "系统开放时间？",
+                "answer": "工作日 09:00—18:00。",
+                "enabled": True,
+                "tokens_per_second": 80,
+                "sort_order": 0,
+            },
+            {
+                "id": "disabled",
+                "question": "停用问题",
+                "answer": "不应返回",
+                "enabled": False,
+                "sort_order": 1,
+            },
+        ]
+    )
+
+    match = await store.find_enabled("系统开放时间？")
+    assert match is not None
+    assert match["answer"] == "工作日 09:00—18:00。"
+    assert match["tokens_per_second"] == 80
+    assert await store.find_enabled("系统开放时间?") is None
+    assert await store.find_enabled(" 系统开放时间？") is None
+    assert await store.find_enabled("停用问题") is None
+
+
+@pytest.mark.asyncio
+async def test_sql_store_round_trips_and_exact_matches() -> None:
+    engine = create_async_engine("sqlite+aiosqlite:///:memory:")
+    try:
+        async with engine.begin() as connection:
+            await connection.run_sync(FixedQuestionRow.__table__.create)
+        repository = FixedQuestionRepository(async_sessionmaker(engine, expire_on_commit=False))
+        saved = await repository.replace_all(
+            [
+                {
+                    "id": "sql-q1",
+                    "question": "SQL 精确问题",
+                    "answer": "SQL 固定回答",
+                    "enabled": True,
+                    "tokens_per_second": 120,
+                    "sort_order": 0,
+                }
+            ],
+            updated_by="admin",
+        )
+        assert saved[0]["updated_by"] == "admin"
+        assert saved[0]["tokens_per_second"] == 120
+        assert (await repository.find_enabled("SQL 精确问题"))["answer"] == "SQL 固定回答"
+        assert await repository.find_enabled("sql 精确问题") is None
+    finally:
+        await engine.dispose()
+
+
+@pytest.mark.asyncio
+async def test_lookup_skips_attachments_and_internal_runs() -> None:
+    store = MemoryFixedQuestionStore()
+    await store.replace_all(
+        [
+            {
+                "id": "q1",
+                "question": "固定问题",
+                "answer": "固定回答",
+                "enabled": True,
+                "sort_order": 0,
+            }
+        ]
+    )
+    request = _request(store)
+
+    plain_input = normalize_input({"messages": [{"content": "固定问题"}]})
+    match = await _find_fixed_answer(
+        body=_body(),
+        request=request,
+        graph_input=plain_input,
+        run_scope=RUN_SCOPE_EXTERNAL_ROOT,
+    )
+    assert match is not None
+    assert match["id"] == "q1"
+
+    attachment_input = normalize_input(
+        {
+            "messages": [
+                {
+                    "content": "固定问题",
+                    "additional_kwargs": {"files": [{"name": "context.pdf"}]},
+                }
+            ]
+        }
+    )
+    assert (
+        await _find_fixed_answer(
+            body=_body(),
+            request=request,
+            graph_input=attachment_input,
+            run_scope=RUN_SCOPE_EXTERNAL_ROOT,
+        )
+        is None
+    )
+    contextual_input = normalize_input(
+        {
+            "messages": [
+                {
+                    "content": "固定问题",
+                    "additional_kwargs": {"prompt_prefix": "网页正文上下文"},
+                }
+            ]
+        }
+    )
+    assert (
+        await _find_fixed_answer(
+            body=_body(),
+            request=request,
+            graph_input=contextual_input,
+            run_scope=RUN_SCOPE_EXTERNAL_ROOT,
+        )
+        is None
+    )
+    assert (
+        await _find_fixed_answer(
+            body=_body(),
+            request=request,
+            graph_input=plain_input,
+            run_scope=RUN_SCOPE_ORCHESTRATION_CHILD,
+        )
+        is None
+    )
+
+
+@pytest.mark.asyncio
+async def test_fixed_answer_agent_streams_chunks_and_persists_full_answer() -> None:
+    question = "固定问题"
+    answer = "这是一个足够长的固定回答，用于验证返回内容会拆成多个流式消息块，同时完整写入会话状态。"
+    agent = make_fixed_answer_agent(
+        question=question,
+        answer=answer,
+        fixed_question_id="q1",
+        tokens_per_second=1000,
+    )
+
+    chunks: list[str] = []
+    final_state = None
+    async for mode, data in agent.astream(
+        {"messages": [HumanMessage(content=question)]},
+        stream_mode=["values", "messages"],
+    ):
+        if mode == "messages":
+            message, _metadata = data
+            if isinstance(message.content, str):
+                chunks.append(message.content)
+        elif mode == "values":
+            final_state = data
+
+    assert "".join(chunks) == answer
+    assert len([chunk for chunk in chunks if chunk]) >= 2
+    assert final_state is not None
+    assert final_state["messages"][-1].content == answer
+    assert final_state["messages"][-1].additional_kwargs["fixed_answer"] is True
+    assert final_state["messages"][-1].additional_kwargs["tokens_per_second"] == 1000
+    assert final_state["title"] == question
+    assert final_state["title_provisional"] is False
+
+
+@pytest.mark.asyncio
+async def test_fixed_answer_default_speed_schedules_100_tokens_per_second(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    answer = "one two three four five six seven eight nine ten eleven twelve thirteen"
+    sleeps: list[float] = []
+
+    async def record_sleep(delay: float) -> None:
+        sleeps.append(delay)
+
+    monkeypatch.setattr(fixed_answer_module.asyncio, "sleep", record_sleep)
+    model = fixed_answer_module.FixedAnswerChatModel(
+        answer=answer,
+        message_id="speed-test",
+        fixed_question_id="q-speed",
+    )
+
+    chunks: list[str] = []
+    async for generation in model._astream([]):
+        chunks.append(str(generation.message.content))
+
+    token_count = len(fixed_answer_module._TOKEN_ENCODING.encode(answer))
+    assert "".join(chunks) == answer
+    assert model.tokens_per_second == 100
+    assert sum(sleeps) == pytest.approx((token_count - 1) / 100)
+
+
+def test_replace_request_rejects_duplicate_exact_questions() -> None:
+    row = {
+        "question": "重复问题",
+        "answer": "回答",
+        "enabled": True,
+        "tokens_per_second": 100,
+        "sort_order": 0,
+    }
+    with pytest.raises(ValidationError):
+        FixedQuestionReplaceRequest(
+            questions=[
+                FixedQuestion(id="q1", **row),
+                FixedQuestion(id="q2", **row),
+            ]
+        )
+    with pytest.raises(ValidationError):
+        FixedQuestionReplaceRequest(
+            questions=[
+                FixedQuestion(id="same-id", **row),
+                FixedQuestion(
+                    id="same-id",
+                    question="另一个问题",
+                    answer="另一个回答",
+                    enabled=True,
+                    sort_order=1,
+                ),
+            ]
+        )
+
+
+def test_fixed_question_stream_speed_defaults_and_bounds() -> None:
+    default_row = FixedQuestion(
+        id="default-speed",
+        question="默认速度",
+        answer="回答",
+    )
+    assert default_row.tokens_per_second == 100
+
+    for invalid_speed in (0, 1001):
+        with pytest.raises(ValidationError):
+            FixedQuestion(
+                id=f"invalid-{invalid_speed}",
+                question="非法速度",
+                answer="回答",
+                tokens_per_second=invalid_speed,
+            )