feat(knowledge): 支持文件导入沉淀知识，知识图谱可视化随主题切换

- 后端新增 /api/knowledge/ingest/file：上传 md/txt/pdf/word/ppt/excel，转 Markdown 后走 wiki-capture LLM 蒸馏为陈述式知识笔记，失败回退逐字草稿 - service.capture_file + 文档专用蒸馏提示词，按主题拆分 1~4 页 - 知识图谱导出 HTML 支持 ?theme=light|dark，布局稳定后冻结，按度数缩放节点，悬停/点击聚焦邻居 - 前端知识库页新增「导入文件」对话框与 ingestKnowledgeFile API - 智能体问答页与简介侧边栏 UI 优化；批量人物蒸馏脚本提取正文逻辑修正 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-11 10:25:27 +08:00
1 parent 17bb3715d1
commit 3845d5090b
@@ -44,7 +44,7 @@ except ImportError:
 # ════════════════════════════════════════════════════════════════════════
 #  只改这一行：你的线上服务地址（不带结尾斜杠）
 # ════════════════════════════════════════════════════════════════════════
-BASE_URL = "http://localhost:8001"
+BASE_URL = "http://47.94.209.59:2026/"
 # ════════════════════════════════════════════════════════════════════════
@@ -57,7 +57,7 @@ DEPTH = "full"                  # full 完整 / fast 精简
 HERE = Path(__file__).resolve().parent
 OUTPUT_DIR = HERE / "output"
-PEOPLE_FILE_DEFAULT = HERE / "people.xlsx"
+PEOPLE_FILE_DEFAULT = HERE / "people.example.csv"
 # 执行时间窗：23:00 ~ 次日 08:00（跨午夜）
 WIN_START = dtime(23, 0)
@@ -260,35 +260,63 @@ class DeerFlowClient:
        return "timeout"
    def fetch_result_text(self, thread_id: str, run_id: str) -> str | None:
-        """抓取该 run 的最终 AI 回复文本（由 py 保存为 md）。"""
+        """抓取该 thread 的最终 AI 回复文本（由 py 保存为 md）。
        注意：本部署的 `/runs/{rid}/messages`、`/messages`、`/events` 端点都返回空
        （事件库按登录用户过滤，后台 worker 写入时未带 user_id → 读不到）。
        可靠来源是 LangGraph 检查点状态 `/api/threads/{tid}/state` → values.messages，
        其中每条消息形如 {"type": "human"|"ai"|"tool", "content": <str | 内容块列表>, ...}。
        取最后一条有正文的 ai 消息即可。
        """
        try:
-            r = self.s.get(f"{self.base}/api/threads/{thread_id}/runs/{run_id}/messages",
+            r = self.s.get(f"{self.base}/api/threads/{thread_id}/state",
-                           headers=self._headers(), params={"limit": 200}, timeout=HTTP_TIMEOUT)
+                           headers=self._headers(), timeout=HTTP_TIMEOUT)
-            if r.status_code == 200:
+            if r.status_code != 200:
-                data = r.json().get("data", [])
+                print(f"    取回复返回 {r.status_code}：{r.text[:200]}")
-                for msg in reversed(data):
+                return None
-                    if msg.get("event_type") == "ai_message" or msg.get("type") == "ai":
+            messages = (r.json().get("values") or {}).get("messages") or []
-                        txt = _extract_text(msg)
+            # 从后往前找最后一条「有正文」的 AI 回复（跳过只含工具调用的中间消息）
-                        if txt and txt.strip():
+            for msg in reversed(messages):
-                            return txt
+                if not isinstance(msg, dict) or msg.get("type") != "ai":
                    continue
                txt = _extract_text(msg)
                if txt and txt.strip():
                    return txt
        except requests.RequestException as e:
            print(f"    取回复出错：{e}")
        return None
-def _extract_text(msg: dict) -> str:
+def _extract_text(payload) -> str:
-    c = msg.get("content") or msg.get("text") or ""
+    """从一条消息的 content 里提取纯文本。
    payload 可能是：
      - LangChain 消息的 model_dump 字典（正文在 payload["content"]）
      - 直接的字符串
      - 内容块列表（[{"type":"text","text":"..."}, ...]）
    """
    if payload is None:
        return ""
    # 若是整条消息的 model_dump，正文在其 content 字段
    if isinstance(payload, dict):
        c = payload.get("content", payload.get("text", ""))
    else:
        c = payload
    if isinstance(c, str):
        return c
    if isinstance(c, list):
        parts = []
        for b in c:
            if isinstance(b, dict):
-                parts.append(b.get("text") or b.get("content") or "")
+                # 只取文本块，跳过 tool_use / thinking 等非文本块
-            else:
+                if b.get("type") in (None, "text", "text_block"):
-                parts.append(str(b))
+                    parts.append(b.get("text") or b.get("content") or "")
                elif b.get("text"):
                    parts.append(b["text"])
            elif isinstance(b, str):
                parts.append(b)
        return "\n".join(p for p in parts if p)
-    return str(c)
+    return str(c) if c else ""
 def _clean_markdown(text: str) -> str:
@@ -2,35 +2,31 @@
 import {
  BotIcon,
  CheckIcon,
  InfoIcon,
  MessageCircleQuestionIcon,
  PanelRightCloseIcon,
  PanelRightOpenIcon,
  PencilIcon,
  PlusIcon,
  SparklesIcon,
  XIcon,
 } from "lucide-react";
-import { useEffect, useMemo, useState } from "react";
+import { useMemo, useState } from "react";
 import { toast } from "sonner";
 import { Button } from "@/components/ui/button";
 import { Input } from "@/components/ui/input";
 import { SkillDetailDialog } from "@/components/workspace/skills/skill-detail-dialog";
 import { Tooltip } from "@/components/workspace/tooltip";
 import { type Agent } from "@/core/agents";
 import { useUpdateAgent } from "@/core/agents/hooks";
 import { getStoredAuth } from "@/core/auth";
 import { useSkills } from "@/core/skills/hooks";
 import { desensitize } from "@/lib/desensitize";
 import { cn } from "@/lib/utils";
 /**
- * Collapsible right-hand panel on the agent chat page that surfaces the agent's
+ * Collapsible right-hand "智能体简介" panel on the agent chat page. It is a
- * profile (name / description / skills) plus a list of frequently-asked
+ * read-only window onto the agent's profile — avatar, name, slogan/description,
- * questions ("常用问题"). Clicking a question sends it as a message. The agent's
+ * the admin-authored SOUL.md as a long-form blurb, the skill whitelist, and the
- * owner (or an admin) can edit the question list inline.
+ * admin-configured common questions surfaced as quick-ask entries. Clicking a
 * question sends it as a message.
 *
 * Editing the common questions lives in the "编辑智能体" dialog (agent-card), NOT
 * here — this panel never offers an edit affordance or an admin hint.
 */
 export function AgentInfoSidebar({
  agent,
@@ -49,20 +45,12 @@ export function AgentInfoSidebar({
  const [collapsed, setCollapsed] = useState(false);
  const [detailSkillName, setDetailSkillName] = useState<string | null>(null);
  const { skills } = useSkills();
  const updateAgent = useUpdateAgent();
  const displayName = desensitize(agent?.name ?? agentName);
  const description = agent?.description
    ? desensitize(agent.description)
    : undefined;
-
+  const soul = agent?.soul?.trim() ? desensitize(agent.soul) : undefined;
  // Owner / admin gate for inline editing of the common-questions list.
  const storedAuth = useMemo(() => getStoredAuth(), []);
  const canEdit = useMemo(() => {
    if (!agent) return false;
    if (storedAuth?.system_role === "admin") return true;
    return agent.user_id != null && agent.user_id === storedAuth?.user_id;
  }, [agent, storedAuth]);
  // Map a stored skill name to its Chinese display label (falls back to name).
  const skillLabel = useMemo(() => {
@@ -78,45 +66,9 @@ export function AgentInfoSidebar({
    [agent?.common_questions],
  );
  // --- Inline editing state ---
  const [editing, setEditing] = useState(false);
  const [drafts, setDrafts] = useState<string[]>([]);
  const startEditing = () => {
    setDrafts(questions.length > 0 ? [...questions] : [""]);
    setEditing(true);
  };
  const cancelEditing = () => {
    setEditing(false);
    setDrafts([]);
  };
  const handleSave = async () => {
    if (!agent) return;
    const cleaned = drafts.map((q) => q.trim()).filter((q) => q.length > 0);
    try {
      await updateAgent.mutateAsync({
        id: agent.id,
        request: { common_questions: cleaned },
      });
      toast.success("常用问题已保存");
      setEditing(false);
      setDrafts([]);
    } catch (error) {
      toast.error(error instanceof Error ? error.message : String(error));
    }
  };
  // Leaving edit mode whenever the panel collapses keeps the state tidy.
  useEffect(() => {
    if (collapsed && editing) cancelEditing();
    // eslint-disable-next-line react-hooks/exhaustive-deps
  }, [collapsed]);
  if (collapsed) {
    return (
-      <div className="flex shrink-0 flex-col items-center border-l pt-14">
+      <div className="flex shrink-0 flex-col items-center border-l pt-3">
        <Tooltip content="智能体简介">
          <Button
            variant="ghost"
@@ -132,8 +84,9 @@ export function AgentInfoSidebar({
  }
  return (
-    <aside className="bg-card/40 flex w-72 shrink-0 flex-col border-l pt-12">
+    <aside className="bg-card/40 hidden h-full w-[340px] shrink-0 flex-col border-l lg:flex">
-      <div className="flex items-center justify-between border-b px-3 py-2">
+      {/* Header — same height as the chat header so the two columns line up. */}
      <div className="flex h-12 shrink-0 items-center justify-between border-b px-4">
        <span className="text-sm font-semibold">智能体简介</span>
        <Tooltip content="收起">
          <Button
@@ -147,125 +100,66 @@ export function AgentInfoSidebar({
        </Tooltip>
      </div>
-      <div className="min-h-0 flex-1 space-y-5 overflow-y-auto p-4">
+      <div className="min-h-0 flex-1 overflow-y-auto">
        {/* Identity */}
-        <div className="flex flex-col items-center gap-2 text-center">
+        <div className="flex flex-col items-center gap-2 px-6 pb-6 pt-7 text-center">
-          <div className="bg-primary/10 flex h-12 w-12 items-center justify-center rounded-full">
+          <div className="bg-primary/10 ring-primary/15 flex h-16 w-16 items-center justify-center rounded-2xl ring-1">
-            <BotIcon className="text-primary h-6 w-6" />
+            <BotIcon className="text-primary h-8 w-8" />
          </div>
-          <div className="text-base font-bold" title={displayName}>
+          <div className="text-lg font-bold" title={displayName}>
            {displayName}
          </div>
          {description && (
-            <p className="text-muted-foreground text-xs leading-relaxed">
+            <p className="text-muted-foreground text-sm leading-relaxed">
              {description}
            </p>
          )}
        </div>
        {/* Soul — the agent's long-form personality blurb. */}
        {soul && (
          <section className="space-y-3 border-t px-6 py-5">
            <h4 className="text-foreground text-sm font-semibold">Soul</h4>
            <p className="text-muted-foreground text-sm leading-relaxed whitespace-pre-wrap">
              {soul}
            </p>
          </section>
        )}
        {/* Skills */}
        {agent?.skills && agent.skills.length > 0 && (
-          <div className="space-y-2">
+          <section className="space-y-3 border-t px-6 py-5">
-            <div className="text-muted-foreground flex items-center gap-1.5 text-xs font-medium">
+            <h4 className="text-foreground flex items-center gap-1.5 text-sm font-semibold">
              <SparklesIcon className="h-3.5 w-3.5" />
              技能
-            </div>
+            </h4>
-            <div className="flex flex-wrap gap-1.5">
+            <div className="flex flex-wrap gap-2">
              {agent.skills.map((name) => (
                <button
                  key={name}
                  type="button"
                  onClick={() => setDetailSkillName(name)}
                  title="查看技能详情"
-                  className="border-border bg-background hover:bg-accent inline-flex items-center gap-1 rounded-full border px-2 py-0.5 text-xs transition-colors"
+                  className="border-border bg-background hover:bg-accent inline-flex items-center gap-1 rounded-full border px-2.5 py-1 text-xs transition-colors"
                >
-                  <span className="max-w-[150px] truncate">
+                  <span className="max-w-[180px] truncate">
                    {skillLabel(name)}
                  </span>
                  <InfoIcon className="text-muted-foreground h-3 w-3 shrink-0" />
                </button>
              ))}
            </div>
-          </div>
+          </section>
        )}
-        {/* Common questions */}
+        {/* Common questions — read-only quick-ask entries. */}
-        <div className="space-y-2">
+        {questions.length > 0 && (
-          <div className="flex items-center justify-between">
+          <section className="space-y-3 border-t px-6 py-5">
-            <div className="text-muted-foreground flex items-center gap-1.5 text-xs font-medium">
+            <h4 className="text-foreground flex items-center gap-1.5 text-sm font-semibold">
              <MessageCircleQuestionIcon className="h-3.5 w-3.5" />
-              常用问题
+              推荐问题
-            </div>
+            </h4>
-            {canEdit && !editing && (
+            <div className="flex flex-col gap-2">
              <Tooltip content="编辑常用问题">
                <Button
                  variant="ghost"
                  size="icon-sm"
                  onClick={startEditing}
                  aria-label="编辑常用问题"
                >
                  <PencilIcon className="h-3.5 w-3.5" />
                </Button>
              </Tooltip>
            )}
          </div>
          {editing ? (
            <div className="space-y-2">
              {drafts.map((value, index) => (
                <div key={index} className="flex items-center gap-1">
                  <Input
                    value={value}
                    placeholder={`问题 ${index + 1}`}
                    onChange={(e) => {
                      const next = [...drafts];
                      next[index] = e.currentTarget.value;
                      setDrafts(next);
                    }}
                    className="h-8 text-xs"
                  />
                  <Button
                    variant="ghost"
                    size="icon-sm"
                    onClick={() =>
                      setDrafts(drafts.filter((_, i) => i !== index))
                    }
                    aria-label="删除"
                  >
                    <XIcon className="h-3.5 w-3.5" />
                  </Button>
                </div>
              ))}
              <Button
                variant="outline"
                size="sm"
                className="w-full"
                onClick={() => setDrafts([...drafts, ""])}
              >
                <PlusIcon className="h-3.5 w-3.5" /> 添加问题
              </Button>
              <div className="flex gap-2 pt-1">
                <Button
                  size="sm"
                  className="flex-1"
                  onClick={() => void handleSave()}
                  disabled={updateAgent.isPending}
                >
                  <CheckIcon className="h-3.5 w-3.5" /> 保存
                </Button>
                <Button
                  variant="outline"
                  size="sm"
                  className="flex-1"
                  onClick={cancelEditing}
                  disabled={updateAgent.isPending}
                >
                  取消
                </Button>
              </div>
            </div>
          ) : questions.length > 0 ? (
            <div className="flex flex-col gap-1.5">
              {questions.map((question, index) => (
                <button
                  key={index}
@@ -274,20 +168,16 @@ export function AgentInfoSidebar({
                  onClick={() => onAskQuestion(question)}
                  title={question}
                  className={cn(
-                    "border-border bg-background hover:bg-accent w-full rounded-md border px-2.5 py-1.5 text-left text-xs transition-colors",
+                    "border-border/60 bg-background/60 hover:bg-accent hover:border-border w-full rounded-xl border px-3 py-2.5 text-left text-sm leading-relaxed transition-colors",
                    "disabled:cursor-not-allowed disabled:opacity-50",
                  )}
                >
-                  {question}
+                  {desensitize(question)}
                </button>
              ))}
            </div>
-          ) : (
+          </section>
-            <p className="text-muted-foreground text-xs">
+        )}
              {canEdit ? "还没有常用问题，点击上方编辑添加。" : "暂无常用问题。"}
            </p>
          )}
        </div>
      </div>
      <SkillDetailDialog
@@ -41,14 +41,14 @@ export function AgentWelcome({
        className,
      )}
    >
-      <div className="bg-primary/10 ring-primary/15 flex h-16 w-16 items-center justify-center rounded-2xl ring-1">
+      <div className="bg-primary/10 ring-primary/15 mb-2 flex h-[72px] w-[72px] items-center justify-center rounded-3xl ring-1">
-        <BotIcon className="text-primary h-8 w-8" />
+        <BotIcon className="text-primary h-9 w-9" />
      </div>
-      <div className="text-2xl font-bold tracking-tight">
+      <div className="text-3xl font-bold tracking-tight">
        Hi，我是{displayName}
      </div>
      {description && (
-        <p className="text-muted-foreground max-w-md text-sm leading-relaxed">
+        <p className="text-muted-foreground max-w-xl text-base leading-relaxed">
          {description}
        </p>
      )}
@@ -8,6 +8,7 @@ import {
  LockIcon,
  MessageSquareIcon,
  PinIcon,
  PlusIcon,
  SearchIcon,
  ShieldIcon,
  SparklesIcon,
@@ -16,6 +17,7 @@ import {
  TagsIcon,
  Trash2Icon,
  UserIcon,
  XIcon,
 } from "lucide-react";
 import { useRouter } from "next/navigation";
 import {
@@ -207,6 +209,12 @@ export function AgentCard({ agent, layout = "card", onPublisherClick }: AgentCar
  const [editName, setEditName] = useState(agent.name);
  const [editDescription, setEditDescription] = useState(agent.description ?? "");
  const [editSoul, setEditSoul] = useState(agent.soul ?? "");
  // Common questions (常用问题) are authored here in the edit dialog and read
  // back read-only on the agent chat page. Keep one trailing blank row so there
  // is always an empty input to type the next question into.
  const [editCommonQuestions, setEditCommonQuestions] = useState<string[]>(
    agent.common_questions ?? [],
  );
  const [editPublished, setEditPublished] = useState(agent.published);
  const [editIsPrivate, setEditIsPrivate] = useState(agent.is_private);
  const [selectedSkills, setSelectedSkills] = useState<string[]>(
@@ -250,8 +258,10 @@ export function AgentCard({ agent, layout = "card", onPublisherClick }: AgentCar
    setEditPublished(agent.published);
    setEditIsPrivate(agent.is_private);
    setSelectedSkills(agent.skills ?? []);
    setEditCommonQuestions(agent.common_questions ?? []);
    setSkillSearch("");
  }, [
    agent.common_questions,
    agent.description,
    agent.is_private,
    agent.name,
@@ -269,6 +279,7 @@ export function AgentCard({ agent, layout = "card", onPublisherClick }: AgentCar
    // include `soul`) keep working.
    if (agentDetail) {
      setEditSoul(agentDetail.soul ?? "");
      setEditCommonQuestions(agentDetail.common_questions ?? []);
    } else {
      setEditSoul(agent.soul ?? "");
    }
@@ -345,6 +356,9 @@ export function AgentCard({ agent, layout = "card", onPublisherClick }: AgentCar
          published: editIsPrivate ? false : editPublished,
          is_private: editIsPrivate,
          skills: selectedSkills,
          common_questions: editCommonQuestions
            .map((q) => q.trim())
            .filter((q) => q.length > 0),
        },
      });
      toast.success("智能体已更新");
@@ -831,7 +845,7 @@ export function AgentCard({ agent, layout = "card", onPublisherClick }: AgentCar
          <DialogHeader>
            <DialogTitle>编辑智能体:{desensitize(agent.name)}</DialogTitle>
            <DialogDescription>
-              可以修改名称、描述、技能白名单、SOUL 内容与发布状态。
+              可以修改名称、描述、技能白名单、SOUL 内容、常用问题与发布状态。
            </DialogDescription>
          </DialogHeader>
          <div className="space-y-4 py-2">
@@ -935,6 +949,52 @@ export function AgentCard({ agent, layout = "card", onPublisherClick }: AgentCar
                className="min-h-40 font-mono text-xs"
              />
            </div>
            <div className="space-y-2">
              <label className="text-sm font-medium">常用问题</label>
              <p className="text-muted-foreground text-xs">
                这些问题会在该智能体的首页与简介栏作为推荐问题展示，点击即可一键提问。
              </p>
              <div className="space-y-2">
                {editCommonQuestions.map((value, index) => (
                  <div key={index} className="flex items-center gap-1.5">
                    <Input
                      value={value}
                      placeholder={`问题 ${index + 1}`}
                      onChange={(e) => {
                        const next = [...editCommonQuestions];
                        next[index] = e.currentTarget.value;
                        setEditCommonQuestions(next);
                      }}
                      className="h-9 text-sm"
                    />
                    <Button
                      type="button"
                      variant="ghost"
                      size="icon-sm"
                      onClick={() =>
                        setEditCommonQuestions(
                          editCommonQuestions.filter((_, i) => i !== index),
                        )
                      }
                      aria-label="删除问题"
                    >
                      <XIcon className="size-4" />
                    </Button>
                  </div>
                ))}
                <Button
                  type="button"
                  variant="outline"
                  size="sm"
                  className="w-full"
                  onClick={() =>
                    setEditCommonQuestions([...editCommonQuestions, ""])
                  }
                >
                  <PlusIcon className="size-3.5" /> 添加问题
                </Button>
              </div>
            </div>
            <div className="flex items-center justify-between rounded-md border p-3">
              <div>
                <p className="text-sm font-medium">公开发布</p>
@@ -127,6 +127,30 @@ export async function ingestThreadsBatch(payload: BatchIngestPayload = {}) {
  );
 }
 export interface IngestFileResult {
  note: KnowledgeNote;
  created: boolean;
  notes: KnowledgeNote[];
  llm_fallback: boolean;
 }
 /** Import a file (md/txt/pdf/word/ppt/excel) into the KB as wiki note(s). */
 export async function ingestKnowledgeFile(
  file: File,
  opts: { title?: string; tags?: string; status?: string; model_name?: string | null } = {},
 ) {
  const form = new FormData();
  form.append("file", file);
  if (opts.title) form.append("title", opts.title);
  if (opts.tags) form.append("tags", opts.tags);
  if (opts.status) form.append("status", opts.status);
  if (opts.model_name) form.append("model_name", opts.model_name);
  // No Content-Type header — the browser sets the multipart boundary itself.
  return parseResponse<IngestFileResult>(
    await apiFetch(`${baseUrl()}/ingest/file`, { method: "POST", body: form }),
  );
 }
 /** Resolve `[[wikilink]]` targets to note ids / vault pages. */
 export async function resolveWikilinks(targets: string[]) {
  const res = await parseResponse<{ resolved: WikilinkResolutionMap }>(
@@ -11,6 +11,7 @@ import {
  exportKnowledgeGraph,
  fetchVaultPage,
  getKnowledgeNote,
  ingestKnowledgeFile,
  ingestThread,
  ingestThreadsBatch,
  listDuplicates,
@@ -106,6 +107,16 @@ export function useKnowledgeActions() {
      mutationFn: ingestThreadsBatch,
      onSuccess: invalidate,
    }),
    ingestFile: useMutation({
      mutationFn: ({
        file,
        opts,
      }: {
        file: File;
        opts?: Parameters<typeof ingestKnowledgeFile>[1];
      }) => ingestKnowledgeFile(file, opts),
      onSuccess: invalidate,
    }),
    exportGraph: useMutation({ mutationFn: exportKnowledgeGraph }),
    merge: useMutation({
      mutationFn: ({ primaryId, duplicateIds }: { primaryId: string; duplicateIds: string[] }) =>
@@ -13,11 +13,7 @@ import { ArtifactTrigger } from "@/components/workspace/artifacts";
 import { ChatBox, useThreadChat } from "@/components/workspace/chats";
 import { ExportTrigger } from "@/components/workspace/export-trigger";
 import { InputBox } from "@/components/workspace/input-box";
-import {
+import { MessageList } from "@/components/workspace/messages";
  MessageList,
  MESSAGE_LIST_DEFAULT_PADDING_BOTTOM,
  MESSAGE_LIST_FOLLOWUPS_EXTRA_PADDING_BOTTOM,
 } from "@/components/workspace/messages";
 import { ThreadContext } from "@/components/workspace/messages/context";
 import { ThreadTitle } from "@/components/workspace/thread-title";
 import { TodoList } from "@/components/workspace/todo-list";
@@ -32,7 +28,6 @@ import { useThreadStream } from "@/core/threads/hooks";
 import { textOfMessage } from "@/core/threads/utils";
 import { env } from "@/env";
 import { desensitize } from "@/lib/desensitize";
 import { cn } from "@/lib/utils";
 export default function AgentChatPage() {
  const routeBase = useRouteBase();
@@ -163,146 +158,156 @@ export default function AgentChatPage() {
    await thread.stop();
  }, [thread]);
  const messageListPaddingBottom = showFollowups
    ? MESSAGE_LIST_DEFAULT_PADDING_BOTTOM +
      MESSAGE_LIST_FOLLOWUPS_EXTRA_PADDING_BOTTOM
    : undefined;
  const isLandingState = isNewThread && !hasStartedConversation;
  const isDemoMode = env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true";
  const status = thread.error
    ? "error"
    : thread.isLoading
      ? "streaming"
      : "ready";
  return (
    <ThreadContext.Provider value={{ thread }}>
      <ChatBox threadId={threadId}>
-        <div className="relative flex size-full min-h-0 justify-between">
+        {/* Root: fixed-height horizontal split. The left main column owns the
-          <header
+            chat (home / conversation) and the input; the right sidebar is a
-            className={cn(
+            separate flex sibling, so nothing in the main column can ever bleed
-              "absolute top-0 right-0 left-0 z-30 flex h-12 shrink-0 items-center gap-2 border-b px-4",
+            over it. */}
-              isLandingState
+        <div className="flex size-full min-h-0 overflow-hidden">
-                ? "border-transparent bg-transparent"
+          {/* ── Left: main conversation column ───────────────────────────── */}
-                : "bg-card/90 border-border/70 shadow-sm backdrop-blur-md",
+          <main className="flex min-h-0 min-w-0 flex-1 flex-col">
-            )}
+            {/* Header — in normal flow (not absolute), fixed height. */}
-          >
+            <header className="bg-card/90 border-border/70 flex h-12 shrink-0 items-center gap-2 border-b px-4 backdrop-blur-md">
-            {/* Agent badge */}
+              <div className="flex shrink-0 items-center gap-1.5 rounded-md border px-2 py-1">
-            <div className="flex shrink-0 items-center gap-1.5 rounded-md border px-2 py-1">
+                <BotIcon className="text-primary h-3.5 w-3.5" />
-              <BotIcon className="text-primary h-3.5 w-3.5" />
+                <span
-              <span
+                  className="max-w-[200px] truncate text-xs font-medium"
-                className="max-w-[200px] truncate text-xs font-medium"
+                  title={agentDisplayName}
                title={agentDisplayName}
              >
                {agentDisplayName}
              </span>
            </div>
            <div className="flex w-full items-center text-sm font-medium">
              <ThreadTitle threadId={threadId} thread={thread} />
            </div>
            <div className="mr-4 flex items-center">
              <Tooltip content={t.agents.newChat}>
                <Button
                  size="sm"
                  variant="secondary"
                  onClick={() => {
                    router.push(`/page/workspace/agents/${agent_id}/chats/new`);
                  }}
                >
-                  <PlusSquare /> {t.agents.newChat}
+                  {agentDisplayName}
-                </Button>
+                </span>
-              </Tooltip>
+              </div>
              <TokenUsageIndicator
                enabled={tokenUsageEnabled}
                messages={thread.messages}
              />
              <ExportTrigger threadId={threadId} />
              <ArtifactTrigger />
            </div>
          </header>
-          <main className="flex min-h-0 max-w-full grow flex-col">
+              <div className="flex min-w-0 flex-1 items-center text-sm font-medium">
-            <div className="flex size-full justify-center">
+                <ThreadTitle threadId={threadId} thread={thread} />
-              <MessageList
+              </div>
                className={cn("size-full", !isLandingState && "pt-10")}
                threadId={threadId}
                thread={thread}
                paddingBottom={messageListPaddingBottom}
                tokenUsageEnabled={tokenUsageEnabled}
                onClarificationSubmit={handleClarificationSubmit}
                onEditResubmit={(text) => handleSubmit({ text, files: [] })}
              />
            </div>
-            <div className="absolute right-0 bottom-0 left-0 z-30 flex justify-center px-4">
+              <div className="flex items-center">
-              <div
+                <Tooltip content={t.agents.newChat}>
-                className={cn(
+                  <Button
-                  "relative w-full",
+                    size="sm"
-                  isLandingState && "-translate-y-[calc(50vh-96px)]",
+                    variant="secondary"
-                  isLandingState
+                    onClick={() => {
-                    ? "max-w-(--container-width-md)"
+                      router.push(
-                    : "max-w-(--container-width-lg)",
+                        `/page/workspace/agents/${agent_id}/chats/new`,
-                )}
+                      );
-              >
+                    }}
-                <div className="absolute -top-4 right-0 left-0 z-0">
+                  >
-                  <div className="absolute right-0 bottom-0 left-0">
+                    <PlusSquare /> {t.agents.newChat}
-                    <TodoList
+                  </Button>
-                      className="bg-background/5"
+                </Tooltip>
-                      todos={thread.values.todos ?? []}
+                <TokenUsageIndicator
-                      hidden={
+                  enabled={tokenUsageEnabled}
-                        !thread.values.todos || thread.values.todos.length === 0
+                  messages={thread.messages}
-                      }
+                />
-                    />
+                <ExportTrigger threadId={threadId} />
-                  </div>
+                <ArtifactTrigger />
-                </div>
+              </div>
            </header>
-                <div className="w-full -translate-y-4">
+            {isLandingState ? (
              /* ── home: centered hero + suggested questions + input ──────
                 Everything lives inside the scrollable main column. No fixed,
                 no absolute, no viewport centering — so the avatar can't touch
                 the header and the input can't cover the sidebar. */
              <div className="flex min-h-0 flex-1 flex-col items-center overflow-y-auto px-6 pb-10 pt-16 sm:pt-24">
                <AgentWelcome
                  agent={agent}
                  agentName={agentDisplayName}
                  onAskQuestion={(text) => handleSubmit({ text, files: [] })}
                  disabled={isDemoMode}
                  className="mb-7"
                />
                <div className="w-full max-w-(--container-width-md)">
                  <InputBox
                    className="w-full"
-                    isNewThread={isLandingState}
+                    isNewThread
                    threadId={threadId}
                    assistantId={agent_id}
-                    autoFocus={isLandingState}
+                    autoFocus
-                    status={
+                    status={status}
                      thread.error
                        ? "error"
                        : thread.isLoading
                          ? "streaming"
                          : "ready"
                    }
                    context={settings.context}
-                    extraHeader={
+                    disabled={isDemoMode}
-                      isLandingState && (
+                    onContextChange={(context) =>
-                        <AgentWelcome
+                      setSettings("context", context)
                          agent={agent}
                          agentName={agentDisplayName}
                          onAskQuestion={(text) =>
                            handleSubmit({ text, files: [] })
                          }
                          disabled={
                            env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true"
                          }
                        />
                      )
                    }
                    disabled={env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true"}
                    onContextChange={(context) => setSettings("context", context)}
                    onFollowupsVisibilityChange={setShowFollowups}
                    onSubmit={handleSubmit}
                    onStop={handleStop}
                  />
                  {isDemoMode && (
                    <div className="text-muted-foreground/67 mt-3 w-full text-center text-xs">
                      {t.common.notAvailableInDemoMode}
                    </div>
                  )}
                </div>
                {env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true" && (
                  <div className="text-muted-foreground/67 w-full translate-y-12 text-center text-xs">
                    {t.common.notAvailableInDemoMode}
                  </div>
                )}
              </div>
-            </div>
+            ) : (
              /* ── conversation (active / history): messages scroll, input
                 docked at the bottom of the main column only. */
              <div className="flex min-h-0 flex-1 flex-col">
                <MessageList
                  className="min-h-0 flex-1"
                  threadId={threadId}
                  thread={thread}
                  paddingBottom={showFollowups ? 96 : 24}
                  tokenUsageEnabled={tokenUsageEnabled}
                  onClarificationSubmit={handleClarificationSubmit}
                  onEditResubmit={(text) => handleSubmit({ text, files: [] })}
                />
                <div className="from-background pointer-events-none shrink-0 bg-gradient-to-t to-transparent px-4 pb-4 pt-2">
                  <div className="pointer-events-auto mx-auto w-full max-w-(--container-width-lg)">
                    <TodoList
                      className="bg-background/5 mb-2"
                      todos={thread.values.todos ?? []}
                      hidden={
                        !thread.values.todos ||
                        thread.values.todos.length === 0
                      }
                    />
                    <InputBox
                      className="w-full"
                      isNewThread={false}
                      threadId={threadId}
                      assistantId={agent_id}
                      status={status}
                      context={settings.context}
                      disabled={isDemoMode}
                      onContextChange={(context) =>
                        setSettings("context", context)
                      }
                      onFollowupsVisibilityChange={setShowFollowups}
                      onSubmit={handleSubmit}
                      onStop={handleStop}
                    />
                    {isDemoMode && (
                      <div className="text-muted-foreground/67 mt-2 w-full text-center text-xs">
                        {t.common.notAvailableInDemoMode}
                      </div>
                    )}
                  </div>
                </div>
              </div>
            )}
          </main>
          {/* ── Right: read-only agent profile sidebar ───────────────────── */}
          <AgentInfoSidebar
            agent={agent}
            agentName={agentDisplayName}
-            disabled={
+            disabled={thread.isLoading || isDemoMode}
              thread.isLoading ||
              env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true"
            }
            onAskQuestion={(text) => handleSubmit({ text, files: [] })}
          />
        </div>
@@ -11,6 +11,7 @@ import {
  Search,
  Sparkles,
  Trash2,
  Upload,
  X,
 } from "lucide-react";
 import { useEffect, useMemo, useState } from "react";
@@ -323,6 +324,119 @@ function BatchImportDialog({
  );
 }
 function ImportFileDialog({
  open,
  onOpenChange,
 }: {
  open: boolean;
  onOpenChange: (v: boolean) => void;
 }) {
  const { ingestFile } = useKnowledgeActions();
  const navigate = useNavigate();
  const [file, setFile] = useState<File | null>(null);
  const [title, setTitle] = useState("");
  const [tags, setTags] = useState("");
  const [model, setModel] = useState<string | null>(null);
  const reset = () => {
    setFile(null);
    setTitle("");
    setTags("");
    setModel(null);
  };
  const handleImport = async () => {
    if (!file) {
      toast.error("请选择文件");
      return;
    }
    try {
      const result = await ingestFile.mutateAsync({
        file,
        opts: {
          title: title.trim() || undefined,
          tags: tags.trim() || undefined,
          status: "approved",
          model_name: model,
        },
      });
      const count = result.notes?.length ?? 1;
      if (result.llm_fallback) {
        // The model produced nothing usable — the file was stored verbatim as a
        // draft instead of distilled into a wiki note.
        toast.warning(
          `已导入 ${count} 条（大模型异常，改用规则抽取并存为草稿）`,
        );
      } else {
        toast.success(`已从文件生成 ${count} 条知识`);
      }
      onOpenChange(false);
      reset();
      if (result.note?.id) {
        navigate(`/page/workspace/knowledge/${result.note.id}`);
      }
    } catch (error) {
      toast.error(error instanceof Error ? error.message : "文件导入失败");
    }
  };
  return (
    <Dialog open={open} onOpenChange={onOpenChange}>
      <DialogContent className="max-w-md">
        <DialogHeader>
          <DialogTitle>导入文件生成 Wiki</DialogTitle>
          <DialogDescription>
            上传文档（Markdown / TXT / PDF / Word / PPT / Excel），自动提炼为知识库 wiki 词条并写入 vault。
          </DialogDescription>
        </DialogHeader>
        <div className="flex flex-col gap-4">
          <label className="flex flex-col gap-1.5 text-sm">
            选择文件
            <Input
              type="file"
              accept=".md,.markdown,.txt,.pdf,.doc,.docx,.ppt,.pptx,.xls,.xlsx"
              onChange={(e) => setFile(e.target.files?.[0] ?? null)}
              className="cursor-pointer"
            />
            {file ? (
              <span className="text-muted-foreground truncate text-xs">
                {file.name} · {(file.size / 1024).toFixed(0)} KB
              </span>
            ) : null}
          </label>
          <Input
            placeholder="标题（可选，留空则由模型生成）"
            value={title}
            onChange={(e) => setTitle(e.target.value)}
          />
          <Input
            placeholder="标签，逗号分隔（可选）"
            value={tags}
            onChange={(e) => setTags(e.target.value)}
          />
          <label className="flex items-center justify-between gap-2 text-sm">
            提炼大模型
            <ModelNameSelect
              value={model}
              onChange={setModel}
              disabled={ingestFile.isPending}
              triggerClassName="h-9 w-[11rem]"
            />
          </label>
        </div>
        <DialogFooter>
          <Button variant="outline" onClick={() => onOpenChange(false)}>
            取消
          </Button>
          <Button onClick={() => void handleImport()} disabled={ingestFile.isPending || !file}>
            {ingestFile.isPending ? "导入中..." : "导入并生成"}
          </Button>
        </DialogFooter>
      </DialogContent>
    </Dialog>
  );
 }
 function DedupDialog({
  open,
  onOpenChange,
@@ -698,6 +812,7 @@ export default function KnowledgeBasePage() {
  const [status, setStatus] = useState("all");
  const [createOpen, setCreateOpen] = useState(false);
  const [batchOpen, setBatchOpen] = useState(false);
  const [importOpen, setImportOpen] = useState(false);
  const [dedupOpen, setDedupOpen] = useState(false);
  const params = useMemo(
@@ -752,6 +867,9 @@ export default function KnowledgeBasePage() {
          </SelectContent>
        </Select>
        <div className="ml-auto flex items-center gap-2">
          <Button variant="outline" size="sm" onClick={() => setImportOpen(true)}>
            <Upload className="size-4" /> 导入文件
          </Button>
          <Button variant="outline" size="sm" onClick={() => setBatchOpen(true)}>
            <RefreshCw className="size-4" /> 批量导入
          </Button>
@@ -814,6 +932,7 @@ export default function KnowledgeBasePage() {
      </div>
      <CreateNoteDialog open={createOpen} onOpenChange={setCreateOpen} />
      <ImportFileDialog open={importOpen} onOpenChange={setImportOpen} />
      <BatchImportDialog open={batchOpen} onOpenChange={setBatchOpen} />
      <DedupDialog open={dedupOpen} onOpenChange={setDedupOpen} />
    </div>
@@ -4,13 +4,17 @@ import { useNavigate } from "react-router-dom";
 import { toast } from "sonner";
 import { Button } from "@/components/ui/button";
 import { useTheme } from "@/contexts/ThemeContext";
 import { knowledgeExportFileUrl } from "@/core/knowledge/api";
 import { useKnowledgeActions } from "@/core/knowledge/hooks";
 export default function KnowledgeGraphPage() {
  const navigate = useNavigate();
  const { theme } = useTheme();
  const { exportGraph } = useKnowledgeActions();
-  const [src, setSrc] = useState<string | null>(null);
+  // Keep the served base URL (without the theme) so a theme toggle can re-skin
  // the iframe without regenerating the graph on the backend.
  const [baseSrc, setBaseSrc] = useState<string | null>(null);
  const [stats, setStats] = useState<{ nodes: number; edges: number } | null>(null);
  const regenerate = useCallback(async () => {
@@ -18,7 +22,7 @@ export default function KnowledgeGraphPage() {
      const result = await exportGraph.mutateAsync();
      setStats(result.stats);
      // Cache-bust the iframe so it reflects the freshly generated graph.
-      setSrc(`${knowledgeExportFileUrl("graph.html")}?t=${Date.now()}`);
+      setBaseSrc(`${knowledgeExportFileUrl("graph.html")}?t=${Date.now()}`);
    } catch (error) {
      toast.error(error instanceof Error ? error.message : "生成图谱失败");
    }
@@ -29,6 +33,10 @@ export default function KnowledgeGraphPage() {
    void regenerate();
  }, [regenerate]);
  // The graph HTML lives in an iframe and can't read the app's CSS theme, so we
  // pass the active day/night mode via a query param; toggling re-renders it.
  const src = baseSrc ? `${baseSrc}&theme=${theme}` : null;
  return (
    <div className="flex size-full min-h-0 flex-col">
      <header className="flex items-center gap-2 border-b p-3">
@@ -250,7 +250,7 @@ FastAPI application on port 8001 with health check at `GET /health`. Set `GATEWA
 | **Scheduled Tasks** (`/api/scheduled-tasks`) | Per-user cron-like agent tasks. `GET/POST /` - list/create owned tasks; `PATCH/DELETE /{id}` - update/delete (owner); `POST /{id}/{pause,resume,trigger}`; `GET /{id}/runs`, `GET /runs/{rid}`, run-file preview/edit/download; `GET /runs/{rid}/messages` - agent messages for the run's underlying agent run (used to inspect a stuck/running run; authorized via `_load_run`); `GET /runs/{rid}/html` - generated HTML document for an `html_page` run; `DELETE /runs/{rid}` - owner-scoped, with an admin fallback so admins can delete any user's run; publish/subscribe under `/{id}/{publish,unpublish,subscribe}` and `GET /published`. **Admin (cross-user):** `GET /admin/all` - every task; `PATCH/DELETE /admin/{id}` - edit/delete any task; `POST /admin/{id}/trigger`; `GET /admin/{id}/runs`. Admin routes require `system_role == "admin"`. |
 | **HTML Page Favorites** (`/api/html-page-favorites`) | Bookmarked generated HTML pages, owner-scoped. `GET /` - list; `POST /` `{page_id, title?, description?, tags?}` - bookmark a `scheduled_html_pages` row (extracts a reusable style/layout summary via GLM5 at favorite time); a page can only be favorited once per user (`DuplicateFavoriteError` → HTTP 409). `GET/DELETE /{id}` - read/delete (the create-task reference picker deletes favorites here). A favorite can be selected as a style reference when creating a new `html_page` task. |
 | **Public Scheduled Tasks** (`/api/public/scheduled-tasks`) | **Unauthenticated** mirror for embedding. Adds `GET /runs/{rid}/html` and `GET /{task_id}/latest-html` for the `html_page` preview; the run result keeps `result.html` (only file paths are redacted). |
-| **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). **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 "已改用规则抽取". The "保存到知识库" 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/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); `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). Backed by the `deerflow.knowledge` module (see below). |
+| **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). **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 "已改用规则抽取". The "保存到知识库" 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); `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). Backed by the `deerflow.knowledge` module (see below). |
 Proxied through nginx: `/api/langgraph/*` → LangGraph, all other `/api/*` → Gateway.
@@ -290,7 +290,7 @@ Self-contained product knowledge base. **All knowledge capability lives in this
 - **DB mirror** — tables `knowledge_notes` / `knowledge_sources` / `knowledge_tags` / `knowledge_note_tags` (`knowledge/models.py`, registered in `persistence/models/__init__.py`, auto-created by `Base.metadata.create_all`; portable types `PortableLongText`/`BeijingDateTime`). Powers listing/filter/search/audit. Global/shared — no `user_id` column; `created_by`/`updated_by` are audit-only (resolved via `get_effective_user_id()`).
 - **Markdown vault** — obsidian-wiki compatible, default `{$DEER_FLOW_HOME}/data/knowledge/obsidian-vault`. `ObsidianWikiAdapter` (`obsidian_adapter.py`) writes wiki-capture frontmatter+body, and after **every** write syncs `index.md` / `log.md` (CAPTURE/INGEST/UPDATE/ARCHIVE/EXPORT) / `hot.md` / `.manifest.json` (source-hash dedup for `skip_existing`). `markdown_vault.py` handles frontmatter build/parse, slugging, wikilink extraction and **path-traversal-proof** resolution.
-**Module layout:** `models.py` (ORM: notes/sources/tags/note_tags + embeddings/versions/entities/relations) · `repository.py` (DB only, no LLM) · `schemas.py` (NoteDraft/SourceDraft DTOs) · `skill_templates.py` · `markdown_vault.py` · `manifest.py` · `extractor.py` (rule-based fallback) · `llm_extractor.py` (**default**: distills declarative knowledge per wiki-capture, structured JSON incl. entities/relations; falls back to `extractor.py`) · `sources.py` · `exporter.py` (`graph.json`/`graph.graphml`/`cypher.txt` + self-contained vanilla-JS `graph.html`; entity nodes + relation edges) · `chunking.py` + `embeddings.py` (OpenAI-compatible embedding client, keyword fallback) + `search.py` (keyword/vector/hybrid) · `sensitive.py` (secret/PII redaction) · `dedup.py` (Jaccard + hash dedup) · `auto_ingest.py` (background queue/worker) · `obsidian_adapter.py` · `service.py` (`KnowledgeService` orchestrator — the only thing the router touches). Tests: `tests/test_knowledge.py` (20 cases). Frontend: `frontend-web/src/core/knowledge/*` + `pages/KnowledgeBasePage.tsx` / `KnowledgeGraphPage.tsx` + chat `knowledge-save-trigger.tsx` / `knowledge-rag-toggle.tsx`; spec at `frontend-web/docs/product-knowledge-base-dev.md`.
+**Module layout:** `models.py` (ORM: notes/sources/tags/note_tags + embeddings/versions/entities/relations) · `repository.py` (DB only, no LLM) · `schemas.py` (NoteDraft/SourceDraft DTOs) · `skill_templates.py` · `markdown_vault.py` · `manifest.py` · `extractor.py` (rule-based fallback) · `llm_extractor.py` (**default**: distills declarative knowledge per wiki-capture, structured JSON incl. entities/relations; falls back to `extractor.py`) · `sources.py` · `exporter.py` (`graph.json`/`graph.graphml`/`cypher.txt` + self-contained vanilla-JS `graph.html`; entity nodes + relation edges. **`graph.html` is theme-aware** — it reads `?theme=light|dark` from its own URL since the embedding iframe can't inherit the app's CSS; `KnowledgeGraphPage.tsx` appends the active day/night mode and re-skins on toggle. The layout cools down and **freezes** so dense graphs stay clickable, node radius scales with degree, and hovering/clicking a node focuses it + its direct neighbours while dimming the rest + a detail panel — taming heavy node/edge clutter) · `chunking.py` + `embeddings.py` (OpenAI-compatible embedding client, keyword fallback) + `search.py` (keyword/vector/hybrid) · `sensitive.py` (secret/PII redaction) · `dedup.py` (Jaccard + hash dedup) · `auto_ingest.py` (background queue/worker) · `obsidian_adapter.py` · `service.py` (`KnowledgeService` orchestrator — the only thing the router touches; capture entry points `capture_thread` / `capture_search` / `capture_file` / `create_manual_note`, all converging on `_persist_draft`). Tests: `tests/test_knowledge.py` (20 cases). Frontend: `frontend-web/src/core/knowledge/*` + `pages/KnowledgeBasePage.tsx` / `KnowledgeGraphPage.tsx` + chat `knowledge-save-trigger.tsx` / `knowledge-rag-toggle.tsx`; spec at `frontend-web/docs/product-knowledge-base-dev.md`.
 **Wikilinks & multi-note capture** (`knowledge.{related_notes_enabled,related_notes_limit,multi_note_enabled}`, all default-on; `project_name` defaults to `zncm`):
 - **Navigable `[[wikilinks]]`** — `service.resolve_wikilink(s)` maps a `[[target]]` to a knowledge note (by id → `vault_path` → title) or a vault meta page (`read_vault_page`, path-traversal-proof), else `missing`. `markdown_vault.normalize_wikilink_target` canonicalizes targets (drops `|alias`, slashes, `.md`). The frontend `MarkdownRenderer` renders non-numeric `[[...]]` as clickable links from the resolver map (numeric `[[123]]` stay citation badges); note links navigate, vault links open a `VaultPageDialog`, missing links are greyed.
@@ -13,9 +13,12 @@ from __future__ import annotations
 import logging
 import mimetypes
 import re
 import tempfile
 from pathlib import Path
 from typing import Any
-from fastapi import APIRouter, BackgroundTasks, HTTPException, Request
+from fastapi import APIRouter, BackgroundTasks, File, Form, HTTPException, Request, UploadFile
 from fastapi.responses import FileResponse
 from pydantic import BaseModel, Field
@@ -26,6 +29,12 @@ from deerflow.knowledge.service import EmptyThreadError
 from deerflow.runtime import serialize_channel_values
 from deerflow.runtime.references import build_reference_batches
 from deerflow.runtime.user_context import get_effective_user_id
 from deerflow.utils.file_conversion import CONVERTIBLE_EXTENSIONS, convert_file_to_markdown
 # Plain-text/markdown files are read directly; binary documents are converted.
 _TEXT_EXTENSIONS = {".md", ".markdown", ".txt", ".text", ""}
 # Bound the in-memory read so a knowledge import can't OOM the gateway.
 _MAX_IMPORT_BYTES = 25 * 1024 * 1024
 logger = logging.getLogger(__name__)
 router = APIRouter(prefix="/api/knowledge", tags=["knowledge"])
@@ -299,6 +308,80 @@ async def ingest_threads_batch(body: BatchIngestRequest, request: Request) -> di
    return {"ok": True, "processed": len(items), "created": created, "skipped": skipped, "failed": failed, "llm_fallback": llm_fallback, "items": items}
 async def _extract_upload_text(file: UploadFile) -> tuple[str, str]:
    """Read an uploaded file and return ``(filename, markdown_text)``.
    Plain-text/markdown is decoded directly; PDF/Office documents are converted
    to Markdown via the shared converter. Raises ``HTTPException`` on empty /
    oversized / unsupported / unparseable files.
    """
    name = file.filename or "document"
    ext = Path(name).suffix.lower()
    raw = await file.read()
    if not raw:
        raise HTTPException(status_code=400, detail="文件为空")
    if len(raw) > _MAX_IMPORT_BYTES:
        raise HTTPException(status_code=413, detail=f"文件过大，最大支持 {_MAX_IMPORT_BYTES // (1024 * 1024)}MB")
    if ext in _TEXT_EXTENSIONS:
        text = raw.decode("utf-8", errors="ignore")
    elif ext in CONVERTIBLE_EXTENSIONS:
        # Convert in an isolated temp dir; a fixed safe name avoids path issues
        # while preserving the extension so the converter detects the type.
        with tempfile.TemporaryDirectory() as tmp:
            tmp_path = Path(tmp) / f"import{ext}"
            tmp_path.write_bytes(raw)
            md_path = await convert_file_to_markdown(tmp_path)
            if md_path is None:
                raise HTTPException(status_code=422, detail=f"无法解析文件：{name}")
            text = md_path.read_text(encoding="utf-8", errors="ignore")
    else:
        raise HTTPException(status_code=415, detail=f"不支持的文件类型：{ext or '未知'}（支持 md/txt/pdf/word/ppt/excel）")
    if not text.strip():
        raise HTTPException(status_code=422, detail="文件内容为空或无法提取文本")
    return name, text
@router.post("/ingest/file")
@require_auth
 async def ingest_file(
    request: Request,
    file: UploadFile = File(...),
    title: str | None = Form(default=None),
    tags: str | None = Form(default=None),
    status: str = Form(default="approved"),
    model_name: str | None = Form(default=None),
 ) -> dict[str, Any]:
    """Import an uploaded file into the knowledge base as wiki note(s).
    Converts the file to Markdown, distills it via the wiki-capture LLM pipeline
    (same as thread capture), and writes the resulting declarative note(s) into
    the shared vault. ``tags`` is a comma/space-separated string.
    """
    service = get_knowledge_service(request)
    name, text = await _extract_upload_text(file)
    tag_list = [t for t in re.split(r"[,，\s]+", tags or "") if t]
    try:
        result = await service.capture_file(
            content_md=text,
            filename=name,
            title=(title or None),
            tags=tag_list,
            status=status,
            created_by=get_effective_user_id(),
            model_name=(model_name or None),
        )
    except EmptyThreadError:
        raise HTTPException(status_code=422, detail="文件内容无可沉淀的知识")
    return {
        "note": result["note"],
        "created": result["created"],
        "notes": result.get("notes", [result["note"]]),
        "llm_fallback": result.get("llm_fallback", False),
    }
@router.post("/ingest/search")
@require_auth
 async def ingest_search(body: IngestSearchRequest, request: Request) -> dict[str, Any]:
@@ -135,7 +135,15 @@ def to_cypher(graph: dict[str, Any]) -> str:
 def to_html(graph: dict[str, Any]) -> str:
-    """Self-contained force-directed graph (canvas + vanilla JS, no CDN)."""
+    """Self-contained, theme-aware force-directed graph (canvas + vanilla JS, no CDN).
    The page reads ``?theme=light|dark`` from its own URL so the embedding iframe
    can stay in sync with the app's day/night mode (an iframe cannot inherit the
    parent's CSS). The layout settles and then **freezes** so a dense graph stops
    drifting and stays clickable; node size scales with degree; and hovering or
    clicking a node focuses it + its direct neighbours while dimming everything
    else, which cuts through heavy node/edge clutter.
    """
    data_json = json.dumps(graph, ensure_ascii=False)
    return _HTML_TEMPLATE.replace("__GRAPH_DATA__", data_json)
@@ -178,50 +186,246 @@ _HTML_TEMPLATE = """<!DOCTYPE html>
 <meta name="viewport" content="width=device-width, initial-scale=1"/>
 <title>Knowledge Graph</title>
 <style>
-  html,body{margin:0;height:100%;background:#0b1020;color:#e7ecff;font-family:system-ui,Segoe UI,Arial,sans-serif;overflow:hidden}
+  :root{
-  #hud{position:fixed;top:10px;left:12px;font-size:12px;opacity:.8;z-index:2}
+    --bg:#0b1020; --fg:#e7ecff; --sub:rgba(231,236,255,.78);
-  #tip{position:fixed;padding:4px 8px;background:#111a36;border:1px solid #2a3a66;border-radius:4px;font-size:12px;pointer-events:none;display:none;z-index:3}
+    --panel:rgba(17,26,54,.92); --panel-border:#2a3a66;
-  canvas{display:block}
+  }
-  #empty{position:fixed;inset:0;display:flex;align-items:center;justify-content:center;opacity:.6}
+  html.light{
    --bg:#f6f8fc; --fg:#1f2433; --sub:rgba(31,36,51,.72);
    --panel:rgba(255,255,255,.94); --panel-border:#d7deec;
  }
  html,body{margin:0;height:100%;background:var(--bg);color:var(--fg);font-family:system-ui,Segoe UI,Arial,sans-serif;overflow:hidden}
  canvas{display:block;cursor:grab}
  canvas.grabbing{cursor:grabbing}
  .card{position:fixed;background:var(--panel);border:1px solid var(--panel-border);border-radius:8px;font-size:12px;z-index:3;backdrop-filter:blur(6px)}
  #hud{top:10px;left:12px;padding:6px 10px;color:var(--sub);z-index:2}
  #legend{top:10px;right:12px;padding:8px 10px;display:flex;flex-direction:column;gap:6px}
  #legend .row{display:flex;align-items:center;gap:6px;color:var(--sub)}
  #legend .dot{width:10px;height:10px;border-radius:50%}
  #tip{padding:4px 8px;pointer-events:none;display:none}
  #panel{left:12px;bottom:12px;max-width:300px;padding:12px 14px;display:none}
  #panel h3{margin:0 0 6px;font-size:14px;line-height:1.3;word-break:break-word}
  #panel .meta{color:var(--sub);margin-bottom:8px}
  #panel .nb{display:flex;flex-wrap:wrap;gap:5px;max-height:120px;overflow:auto}
  #panel .nb span{padding:2px 7px;border:1px solid var(--panel-border);border-radius:999px;line-height:1.4;max-width:100%;overflow:hidden;text-overflow:ellipsis;white-space:nowrap}
  #panel .close{position:absolute;top:8px;right:10px;cursor:pointer;color:var(--sub);font-size:14px}
  #reset{bottom:12px;right:12px;padding:7px 12px;cursor:pointer;color:var(--fg);user-select:none}
  #reset:hover{filter:brightness(1.1)}
  #empty{position:fixed;inset:0;display:flex;align-items:center;justify-content:center;opacity:.55}
 </style>
 </head>
 <body>
-<div id="hud"></div>
+<div id="hud" class="card"></div>
-<div id="tip"></div>
+<div id="legend" class="card">
  <div class="row"><span class="dot" id="lg-note"></span>知识笔记</div>
  <div class="row"><span class="dot" id="lg-entity"></span>实体</div>
 </div>
 <div id="tip" class="card"></div>
 <div id="panel" class="card"><span class="close" id="panel-close">×</span><h3></h3><div class="meta"></div><div class="nb"></div></div>
 <div id="reset" class="card">重置视图</div>
 <canvas id="c"></canvas>
 <script>
 const GRAPH = __GRAPH_DATA__;
 // Theme is supplied by the embedding iframe (it can't read the parent's CSS).
 const THEME = (new URLSearchParams(location.search).get('theme') === 'light') ? 'light' : 'dark';
 const PAL = {
  dark:  {note:'#5b8cff', entity:'#ffb454', label:'rgba(231,236,255,.92)', edge:[140,165,255], halo:'rgba(11,16,32,.55)'},
  light: {note:'#2f6df6', entity:'#d97706', label:'rgba(31,36,51,.92)',   edge:[70,110,200],  halo:'rgba(255,255,255,.65)'},
 }[THEME];
 document.documentElement.classList.toggle('light', THEME === 'light');
 document.getElementById('lg-note').style.background = PAL.note;
 document.getElementById('lg-entity').style.background = PAL.entity;
 const canvas = document.getElementById('c'), ctx = canvas.getContext('2d');
 const hud = document.getElementById('hud'), tip = document.getElementById('tip');
-let W=0,H=0;
+const panel = document.getElementById('panel');
-function resize(){W=canvas.width=innerWidth;H=canvas.height=innerHeight;}
+let W=0,H=0,DPR=Math.min(window.devicePixelRatio||1,2);
-addEventListener('resize',resize);resize();
+function resize(){W=innerWidth;H=innerHeight;canvas.width=W*DPR;canvas.height=H*DPR;canvas.style.width=W+'px';canvas.style.height=H+'px';}
 addEventListener('resize',()=>{resize();bump();});resize();
 hud.textContent = GRAPH.nodes.length + ' 个知识节点 · ' + GRAPH.edges.length + ' 条关系';
-if(!GRAPH.nodes.length){document.body.insertAdjacentHTML('beforeend','<div id=\"empty\">暂无知识图谱数据</div>');}
+if(!GRAPH.nodes.length){document.body.insertAdjacentHTML('beforeend','<div id="empty">暂无知识图谱数据</div>');}
-const idx={};GRAPH.nodes.forEach((n,i)=>{idx[n.id]=n;n.x=W/2+Math.cos(i)*200*Math.random()+(Math.random()-.5)*200;n.y=H/2+Math.sin(i)*200*Math.random()+(Math.random()-.5)*200;n.vx=0;n.vy=0;});
+
-const edges=GRAPH.edges.map(e=>({s:idx[e.source],t:idx[e.target],w:e.w||e.weight||1})).filter(e=>e.s&&e.t);
+// --- index, adjacency, degree, node sizing -------------------------------
-let cam={x:0,y:0,k:1},drag=null,pan=null;
+const idx={}, adj={};
-function step(){
+GRAPH.nodes.forEach(n=>{idx[n.id]=n;adj[n.id]=new Set();});
-  for(const n of GRAPH.nodes){for(const m of GRAPH.nodes){if(n===m)continue;let dx=n.x-m.x,dy=n.y-m.y,d2=dx*dx+dy*dy+0.01,f=1200/d2;n.vx+=dx*f*0.0006;n.vy+=dy*f*0.0006;}}
+const edges=[];
-  for(const e of edges){let dx=e.t.x-e.s.x,dy=e.t.y-e.s.y,d=Math.sqrt(dx*dx+dy*dy)||1,f=(d-110)*0.01;e.s.vx+=dx/d*f;e.s.vy+=dy/d*f;e.t.vx-=dx/d*f;e.t.vy-=dy/d*f;}
+for(const e of GRAPH.edges){
-  for(const n of GRAPH.nodes){n.vx+=(W/2-n.x)*0.0008;n.vy+=(H/2-n.y)*0.0008;n.x+=n.vx*=0.85;n.y+=n.vy*=0.85;}
+  const s=idx[e.source], t=idx[e.target];
  if(!s||!t||s===t) continue;
  edges.push({s,t,w:e.weight||e.w||1,label:e.label||''});
  adj[e.source].add(e.target); adj[e.target].add(e.source);
 }
-function draw(){
+const N=GRAPH.nodes.length;
-  ctx.setTransform(cam.k,0,0,cam.k,cam.x,cam.y);ctx.clearRect(-cam.x/cam.k,-cam.y/cam.k,W/cam.k,H/cam.k);
+GRAPH.nodes.forEach((n,i)=>{
-  ctx.strokeStyle='rgba(120,150,255,.25)';
+  n.deg=adj[n.id].size;
-  for(const e of edges){ctx.lineWidth=e.w*0.6;ctx.beginPath();ctx.moveTo(e.s.x,e.s.y);ctx.lineTo(e.t.x,e.t.y);ctx.stroke();}
+  n.r=4.5+Math.min(11,Math.sqrt(n.deg)*2.4);      // hubs are visibly bigger → easier to hit
-  for(const n of GRAPH.nodes){const r=6;ctx.fillStyle='#5b8cff';ctx.beginPath();ctx.arc(n.x,n.y,r,0,7);ctx.fill();
+  const a=i*2.399963, rad=18*Math.sqrt(i);         // phyllotaxis spread = no initial overlap
-    ctx.fillStyle='rgba(231,236,255,.85)';ctx.font='11px system-ui';ctx.fillText((n.label||'').slice(0,18),n.x+9,n.y+3);}
+  n.x=Math.cos(a)*rad; n.y=Math.sin(a)*rad; n.vx=0; n.vy=0;
 });
 // "Hub" nodes keep their label even when zoomed out; the rest declutter.
 const degs=GRAPH.nodes.map(n=>n.deg).sort((a,b)=>b-a);
 const HUB=Math.max(3,(degs[Math.floor(N*0.08)]||3));
 // --- force layout that cools down and FREEZES (frozen graph = clickable) --
 const REP=9000, LINK=92, CENTER=0.0016;
 let alpha=1, drag=null;
 function physics(){
  for(let i=0;i<N;i++){
    const n=GRAPH.nodes[i];
    for(let j=i+1;j<N;j++){
      const m=GRAPH.nodes[j];
      let dx=n.x-m.x,dy=n.y-m.y,d2=dx*dx+dy*dy+0.01,f=REP/d2;
      let fx=dx*f,fy=dy*f; n.vx+=fx;n.vy+=fy;m.vx-=fx;m.vy-=fy;
    }
  }
  for(const e of edges){
    let dx=e.t.x-e.s.x,dy=e.t.y-e.s.y,d=Math.hypot(dx,dy)||1,f=(d-LINK)*0.02;
    e.s.vx+=dx/d*f;e.s.vy+=dy/d*f;e.t.vx-=dx/d*f;e.t.vy-=dy/d*f;
  }
  for(const n of GRAPH.nodes){
    if(n===drag){n.vx=n.vy=0;continue;}
    n.vx-=n.x*CENTER; n.vy-=n.y*CENTER;
    n.x+=(n.vx*=0.82)*alpha; n.y+=(n.vy*=0.82)*alpha;
  }
  alpha*=0.985;
 }
-function loop(){step();draw();requestAnimationFrame(loop);}loop();
+
 // --- camera / fit-to-view -------------------------------------------------
 let cam={x:0,y:0,k:1};
 function toWorld(x,y){return {x:(x-cam.x)/cam.k,y:(y-cam.y)/cam.k};}
-canvas.addEventListener('mousedown',ev=>{const p=toWorld(ev.clientX,ev.clientY);let hit=null;
+function fitView(){
-  for(const n of GRAPH.nodes){if((n.x-p.x)**2+(n.y-p.y)**2<100){hit=n;break;}}if(hit)drag=hit;else pan={x:ev.clientX,y:ev.clientY,cx:cam.x,cy:cam.y};});
+  if(!N){return;}
-addEventListener('mousemove',ev=>{const p=toWorld(ev.clientX,ev.clientY);if(drag){drag.x=p.x;drag.y=p.y;drag.vx=drag.vy=0;}else if(pan){cam.x=pan.cx+ev.clientX-pan.x;cam.y=pan.cy+ev.clientY-pan.y;}
+  let a=1e9,b=1e9,c=-1e9,d=-1e9;
-  let hov=null;for(const n of GRAPH.nodes){if((n.x-p.x)**2+(n.y-p.y)**2<100){hov=n;break;}}
+  for(const n of GRAPH.nodes){a=Math.min(a,n.x);b=Math.min(b,n.y);c=Math.max(c,n.x);d=Math.max(d,n.y);}
-  if(hov){tip.style.display='block';tip.style.left=(ev.clientX+12)+'px';tip.style.top=(ev.clientY+12)+'px';tip.textContent=hov.label;}else{tip.style.display='none';}});
+  const gw=Math.max(c-a,1),gh=Math.max(d-b,1),pad=90;
-addEventListener('mouseup',()=>{drag=null;pan=null;});
+  cam.k=Math.max(0.12,Math.min(2.2,Math.min((W-pad)/gw,(H-pad)/gh)));
-canvas.addEventListener('wheel',ev=>{ev.preventDefault();const s=ev.deltaY<0?1.1:0.9;cam.k*=s;cam.x=ev.clientX-(ev.clientX-cam.x)*s;cam.y=ev.clientY-(ev.clientY-cam.y)*s;},{passive:false});
+  cam.x=W/2-((a+c)/2)*cam.k; cam.y=H/2-((b+d)/2)*cam.k;
 }
 let fitted=false;
 function bump(){alpha=Math.max(alpha,0.35);} // re-warm the sim on interaction
 // --- focus / hover state --------------------------------------------------
 let hoverNode=null, focusNode=null;
 function active(){return focusNode||hoverNode;}
 function neighbors(n){return n?adj[n.id]:null;}
 function draw(){
  ctx.setTransform(DPR,0,0,DPR,0,0);
  ctx.clearRect(0,0,W,H);
  ctx.translate(cam.x,cam.y); ctx.scale(cam.k,cam.k);
  const act=active(), nb=neighbors(act), zoomed=cam.k>1.35;
  const [er,eg,eb]=PAL.edge;
  // edges: dim by default; when a node is focused, only its edges stay bright.
  for(const e of edges){
    const lit = act && (e.s===act||e.t===act);
    const op  = act ? (lit?0.9:0.05) : Math.min(0.5,0.12+e.w*0.05);
    ctx.strokeStyle='rgba('+er+','+eg+','+eb+','+op+')';
    ctx.lineWidth=(lit?1.6:0.8)*Math.max(0.6,e.w*0.55)/Math.sqrt(cam.k);
    ctx.beginPath();ctx.moveTo(e.s.x,e.s.y);ctx.lineTo(e.t.x,e.t.y);ctx.stroke();
  }
  // nodes
  for(const n of GRAPH.nodes){
    const dim = act && n!==act && !(nb&&nb.has(n.id));
    ctx.globalAlpha = dim?0.22:1;
    ctx.fillStyle = n.type==='entity'?PAL.entity:PAL.note;
    ctx.beginPath();ctx.arc(n.x,n.y,n.r,0,6.2832);ctx.fill();
    if(n===act){ctx.lineWidth=2/cam.k;ctx.strokeStyle=PAL.label;ctx.stroke();}
    ctx.globalAlpha=1;
  }
  // labels: only for focus/neighbors, hubs, or when zoomed in — kills clutter.
  ctx.textBaseline='middle';
  for(const n of GRAPH.nodes){
    const show = act ? (n===act||(nb&&nb.has(n.id))) : (zoomed||n.deg>=HUB);
    if(!show) continue;
    const txt=(n.label||'').slice(0,20);
    if(!txt) continue;
    ctx.font=(n===act?'bold ':'')+(11/cam.k)+'px system-ui';
    const tx=n.x+n.r+4/cam.k, ty=n.y;
    ctx.lineWidth=3/cam.k; ctx.strokeStyle=PAL.halo;
    ctx.strokeText(txt,tx,ty);
    ctx.fillStyle=PAL.label; ctx.fillText(txt,tx,ty);
  }
 }
 function loop(){
  if(alpha>0.02 || drag){physics();} else if(!fitted){fitView();fitted=true;}
  draw();
  requestAnimationFrame(loop);
 }
 // Pre-settle a few iterations so the first paint is already roughly laid out.
 for(let i=0;i<60;i++)physics();
 fitView();
 loop();
 // --- picking & interaction ------------------------------------------------
 function pick(p){
  let best=null,bd=1e9;
  for(const n of GRAPH.nodes){
    const dx=n.x-p.x,dy=n.y-p.y,d=dx*dx+dy*dy, hit=(n.r+8/cam.k);
    if(d<hit*hit && d<bd){bd=d;best=n;}
  }
  return best;
 }
 let pan=null, downXY=null, moved=false;
 canvas.addEventListener('mousedown',ev=>{
  const p=toWorld(ev.clientX,ev.clientY), hit=pick(p);
  downXY={x:ev.clientX,y:ev.clientY,hit}; moved=false;
  if(hit){drag=hit;} else {pan={x:ev.clientX,y:ev.clientY,cx:cam.x,cy:cam.y};}
  canvas.classList.add('grabbing');
 });
 addEventListener('mousemove',ev=>{
  const p=toWorld(ev.clientX,ev.clientY);
  if(downXY && (Math.abs(ev.clientX-downXY.x)>3||Math.abs(ev.clientY-downXY.y)>3)) moved=true;
  if(drag){drag.x=p.x;drag.y=p.y;drag.vx=drag.vy=0;bump();}
  else if(pan){cam.x=pan.cx+ev.clientX-pan.x;cam.y=pan.cy+ev.clientY-pan.y;}
  hoverNode=drag||pan?hoverNode:pick(p);
  if(hoverNode && !drag && !pan){
    tip.style.display='block';
    tip.style.left=Math.min(ev.clientX+14,W-220)+'px';
    tip.style.top=(ev.clientY+14)+'px';
    tip.textContent=hoverNode.label||'';
  } else { tip.style.display='none'; }
 });
 addEventListener('mouseup',ev=>{
  if(downXY && !moved){ // a click, not a drag → toggle focus / detail panel
    focusNode = (downXY.hit && downXY.hit!==focusNode) ? downXY.hit : null;
    renderPanel();
  }
  drag=null;pan=null;downXY=null;canvas.classList.remove('grabbing');
 });
 canvas.addEventListener('wheel',ev=>{
  ev.preventDefault();
  const s=ev.deltaY<0?1.12:0.89;
  const nk=Math.max(0.08,Math.min(6,cam.k*s)), r=nk/cam.k;
  cam.x=ev.clientX-(ev.clientX-cam.x)*r; cam.y=ev.clientY-(ev.clientY-cam.y)*r; cam.k=nk;
 },{passive:false});
 // --- detail panel ---------------------------------------------------------
 const TYPE_LABEL={note:'知识笔记',entity:'实体'};
 function renderPanel(){
  if(!focusNode){panel.style.display='none';return;}
  const n=focusNode;
  panel.querySelector('h3').textContent=n.label||n.id;
  const cat=n.category?' · '+n.category:'';
  panel.querySelector('.meta').textContent=(TYPE_LABEL[n.type]||n.type||'节点')+cat+' · '+n.deg+' 条关系';
  const nb=panel.querySelector('.nb'); nb.innerHTML='';
  let count=0;
  for(const id of adj[n.id]){
    if(count++>=24)break;
    const m=idx[id]; if(!m)continue;
    const s=document.createElement('span'); s.textContent=m.label||id;
    s.title=m.label||id;
    s.style.cursor='pointer';
    s.onclick=()=>{focusNode=m;renderPanel();};
    nb.appendChild(s);
  }
  if(!adj[n.id].size){const s=document.createElement('span');s.textContent='（无关联）';s.style.opacity=.6;nb.appendChild(s);}
  panel.style.display='block';
 }
 document.getElementById('panel-close').onclick=()=>{focusNode=null;renderPanel();};
 document.getElementById('reset').onclick=()=>{focusNode=null;renderPanel();fitView();};
 </script>
 </body>
 </html>"""
@@ -84,6 +84,46 @@ references（外部来源汇总）、decision（架构/设计决策）、journal
 }"""
 _DOC_SYSTEM_PROMPT = """\
 你是知识库整理专家，遵循 obsidian-wiki 的 wiki-capture 规范，把一篇**文档**提炼成\
 **陈述式知识（declarative knowledge）**，而不是照抄原文。
 要求：
 - 只保留高价值内容：核心结论、关键事实、定义、流程、数据、决策与其依据。
 - 丢弃：目录、页眉页脚、版权声明、重复的样板文字、无意义的排版噪声。
 - 用自己的话重组为结构化知识，不要逐段复制原文。
 - 推断内容用 ^[inferred] 标记，不确定/冲突用 ^[ambiguous] 标记。
 - 分类 category 取值之一：synthesis（分析/方案/结论）、concepts（概念/框架）、\
 references（外部来源汇总）、decision（架构/设计决策）、journal（纪要）。
 - 用中文输出。
 一篇文档可能只讲一个主题，也可能覆盖多个相互独立的主题。请把它拆成 1~4 页知识：
 - 默认只产出 **1 页**；只有当文档明确包含**多个彼此独立、可各自成文**的主题时才拆成多页。
 - 每一页聚焦单一主题，标题与 summary 必须彼此区分。
 - 文档没有可沉淀的知识时返回空的 notes 数组。
 只输出一个 JSON 对象，不要任何额外文字或 Markdown 代码块，结构与对话提炼一致：
 {
  "should_ingest": true,
  "reason": "为什么值得/不值得沉淀",
  "notes": [
    {
      "title": "简洁的知识标题（不超过 40 字）",
      "summary": "1-2 句话概括这页知识",
      "category": "synthesis",
      "context": "文档背景或适用场景，1-3 句",
      "findings": ["结论/要点（陈述式，可含 ^[inferred]）", "..."],
      "reasoning": "为什么成立、取舍、不确定性",
      "implications": ["后续建议/风险/下一步", "..."],
      "tags": ["标签1", "标签2"],
      "entities": [{"name": "实体名", "type": "technology|concept|person|org|product|other"}],
      "relations": [{"from": "实体A", "to": "实体B", "type": "uses|relates_to|part_of|depends_on"}],
      "confidence": 0.0
    }
  ]
 }"""
 def _build_transcript(turns: list[dict[str, str]], sources: list[SourceDraft], *, max_chars: int) -> str:
    parts: list[str] = []
    for i, t in enumerate(turns, 1):
@@ -171,21 +211,27 @@ def _notes_from_data(data: dict[str, Any]) -> list[dict[str, Any]]:
 def _build_note_draft(
    note_data: dict[str, Any],
    *,
-    thread_id: str,
+    source_type: str,
-    thread_title: str | None,
+    source_id: str | None,
-    turns: list[dict[str, str]],
+    source_key: str,
    fallback_title: str,
    title_override: str | None,
    tags: list[str] | None,
    project_name: str | None,
    sources: list[SourceDraft],
    source_key_suffix: str = "",
 ) -> NoteDraft:
-    """Render one note dict into a :class:`NoteDraft`."""
+    """Render one note dict into a :class:`NoteDraft`.
    Source-agnostic: the caller supplies ``source_type`` / ``source_id`` /
    ``source_key`` and a ``fallback_title`` (used when neither the user override
    nor the LLM produced a usable title), so both thread and document capture
    share one renderer.
    """
    category = str(note_data.get("category") or "synthesis").strip().lower()
    if category not in _VALID_CATEGORIES:
        category = "synthesis"
-    final_title = (title_override or "").strip() or str(note_data.get("title") or "").strip() or extractor._auto_title(thread_title, turns)
+    final_title = (title_override or "").strip() or str(note_data.get("title") or "").strip() or fallback_title
    summary = str(note_data.get("summary") or "").strip()
    related = extractor.related_links(project_name)
    body = _render_body(note_data, final_title, related, sources)
@@ -210,15 +256,15 @@ def _build_note_draft(
        summary=summary or final_title,
        content_md=body,
        category=category,
-        source_type="thread",
+        source_type=source_type,
-        source_id=thread_id,
+        source_id=source_id,
        tags=base_tags,
        confidence=max(0.0, min(confidence, 1.0)),
        related=related,
        sources=sources,
        entities=[e for e in entities if isinstance(e, dict) and e.get("name")],
        relations=[r for r in relations if isinstance(r, dict) and r.get("from") and r.get("to")],
-        source_key=f"thread:{thread_id}{source_key_suffix}",
+        source_key=source_key,
    )
@@ -293,6 +339,7 @@ async def extract_thread_llm_multi(
    else:
        note_dicts = note_dicts[: max(1, max_notes)]
    fallback_title = extractor._auto_title(thread_title, turns)
    drafts: list[NoteDraft] = []
    for i, nd in enumerate(note_dicts):
        # The user-supplied title override only applies to a single-note result;
@@ -302,14 +349,100 @@ async def extract_thread_llm_multi(
        drafts.append(
            _build_note_draft(
                nd,
-                thread_id=thread_id,
+                source_type="thread",
-                thread_title=thread_title,
+                source_id=thread_id,
-                turns=turns,
+                source_key=f"thread:{thread_id}{suffix}",
                fallback_title=fallback_title,
                title_override=override,
                tags=tags,
                project_name=project_name,
                sources=sources,
            )
        )
    return drafts
 async def extract_document_llm_multi(
    text: str,
    *,
    doc_id: str,
    doc_title: str | None = None,
    title: str | None = None,
    tags: list[str] | None = None,
    project_name: str | None = "zncm",
    sources: list[SourceDraft] | None = None,
    model_name: str | None = None,
    max_input_chars: int = 12000,
    allow_multi: bool = True,
    max_notes: int = 4,
 ) -> list[NoteDraft]:
    """Distill an imported **document** into one *or several* knowledge notes.
    Mirrors :func:`extract_thread_llm_multi` but takes raw document text (already
    converted to Markdown/plain text) instead of a conversation. Returns ``[]``
    when the LLM path fails (callers fall back to a verbatim note); raises
    :class:`LLMRejectedIngest` when the model deliberately judges the document
    worthless. Resulting notes carry ``source_type="file"``.
    """
    text = (text or "").strip()
    if not text:
        return []
    sources = sources or []
    try:
        from langchain_core.messages import HumanMessage, SystemMessage
        from deerflow.models import create_chat_model
        model = create_chat_model(name=model_name or None, thinking_enabled=False)
        body = text if len(text) <= max_input_chars else text[:max_input_chars] + "\n…（已截断）"
        header = f"文档标题：{doc_title}\n\n" if doc_title else ""
        prompt = [
            SystemMessage(content=_DOC_SYSTEM_PROMPT + "\n\n" + WIKI_CAPTURE_GUIDANCE),
            HumanMessage(content=f"以下是一篇文档，请按规范提炼为知识 JSON：\n\n{header}{body}"),
        ]
        response = await model.ainvoke(prompt)
        raw = response.content if isinstance(response.content, str) else str(response.content)
        data = _parse_json(raw)
    except Exception:
        logger.exception("[knowledge] document %s — LLM extraction call failed; using rule-based fallback", doc_id)
        return []
    if not data:
        logger.warning("[knowledge] document %s — LLM returned no parsable JSON; using rule-based fallback", doc_id)
        return []
    note_dicts = _notes_from_data(data)
    if not note_dicts:
        reason = str(data.get("reason") or "")[:200]
        if _is_falsey(data.get("should_ingest")):
            logger.warning("[knowledge] document %s SKIPPED — model judged not worth ingesting: %s", doc_id, reason)
            raise LLMRejectedIngest(reason or "no knowledge value")
        logger.warning(
            "[knowledge] document %s — LLM produced no notes (should_ingest=%s, reason=%r); using rule-based fallback",
            doc_id,
            data.get("should_ingest"),
            reason,
        )
        return []
    note_dicts = note_dicts[:1] if not allow_multi else note_dicts[: max(1, max_notes)]
    fallback_title = (doc_title or title or "文档知识").strip() or "文档知识"
    drafts: list[NoteDraft] = []
    for i, nd in enumerate(note_dicts):
        override = title if (len(note_dicts) == 1) else None
        suffix = "" if len(note_dicts) == 1 else f"#{i}"
        drafts.append(
            _build_note_draft(
                nd,
                source_type="file",
                source_id=doc_id,
                source_key=f"file:{doc_id}{suffix}",
                fallback_title=fallback_title,
                title_override=override,
                tags=tags,
                project_name=project_name,
                sources=sources,
                source_key_suffix=suffix,
            )
        )
    return drafts
@@ -394,6 +394,129 @@ class KnowledgeService:
        )
        return await self._persist_draft(draft, created_by=created_by)
    def _verbatim_file_draft(self, body: str, filename: str, *, title: str | None, tags: list[str] | None, doc_id: str) -> NoteDraft:
        """Build a verbatim fallback note from a file when LLM distillation fails.
        Lands as a ``draft`` (like the thread fallback) since it is the raw
        document, not distilled knowledge.
        """
        base_tags = list(tags or [])
        for default in (self.project_name, "knowledge-base"):
            if default and default not in base_tags:
                base_tags.append(default)
        name = (title or Path(filename).stem or "文档知识").strip() or "文档知识"
        summary = next((ln.strip() for ln in body.splitlines() if ln.strip()), name)[:280]
        return NoteDraft(
            title=name,
            summary=summary,
            content_md=body,
            category="references",
            source_type="file",
            source_id=doc_id,
            status="draft",
            tags=base_tags,
            confidence=0.4,
            related=extractor.related_links(self.project_name),
            source_key=f"file:{doc_id}",
        )
    async def capture_file(
        self,
        *,
        content_md: str,
        filename: str,
        title: str | None = None,
        tags: list[str] | None = None,
        status: str = "approved",
        created_by: str | None = None,
        model_name: str | None = None,
        skip_existing: bool = False,
    ) -> dict[str, Any]:
        """Import a file (already converted to Markdown/text) into knowledge notes.
        Runs the same wiki-capture LLM distillation as thread capture, so an
        uploaded document becomes one or more declarative wiki notes in the vault.
        Falls back to a verbatim ``draft`` note when the LLM is disabled or returns
        nothing usable. Returns ``{"note", "created", "notes", "llm_fallback"}``;
        raises :class:`EmptyThreadError` when there is nothing to keep.
        """
        import hashlib
        text = (content_md or "").strip()
        if not text:
            raise EmptyThreadError(f"File {filename} is empty")
        # Strip any frontmatter the document carries; the vault writer adds its own.
        _, parsed = MarkdownVault.parse(text)
        body = (parsed or text).strip()
        if not body:
            raise EmptyThreadError(f"File {filename} has no body content")
        # Stable id from name + size so re-importing the same file can be skipped.
        doc_id = hashlib.sha1(f"{filename}:{len(body)}".encode("utf-8")).hexdigest()[:16]
        logger.info(
            "[knowledge] importing file '%s' (chars=%d, doc_id=%s, llm_extract=%s, skip_existing=%s)",
            filename,
            len(body),
            doc_id,
            self.config.llm_extract_enabled,
            skip_existing,
        )
        if skip_existing:
            existing = await self.repo.find_by_source("file", doc_id)
            if existing:
                logger.info("[knowledge] file '%s' already imported (note %s); skipping", filename, existing.get("id"))
                return {"note": existing, "created": False, "notes": [existing], "llm_fallback": False}
        drafts: list[NoteDraft] = []
        llm_fallback = False
        if self.config.llm_extract_enabled:
            try:
                drafts = await llm_extractor.extract_document_llm_multi(
                    body,
                    doc_id=doc_id,
                    doc_title=title or Path(filename).stem,
                    title=title,
                    tags=tags,
                    project_name=self.project_name,
                    model_name=model_name or self.config.extract_model_name,
                    max_input_chars=self.config.extract_max_input_chars,
                    allow_multi=self.config.multi_note_enabled,
                )
            except llm_extractor.LLMRejectedIngest as exc:
                raise EmptyThreadError(f"File {filename} judged not worth ingesting: {exc}") from exc
            if not drafts:
                llm_fallback = True
        if not drafts:
            drafts = [self._verbatim_file_draft(body, filename, title=title, tags=tags, doc_id=doc_id)]
        effective_status = status
        if llm_fallback and normalize_status(status) == "approved":
            effective_status = "draft"
        normalized = normalize_status(effective_status)
        for draft in drafts:
            draft.status = normalized
        # Cross-link sibling notes split from the same document (resolved by title
        # once all are persisted), mirroring multi-note thread capture.
        if len(drafts) > 1:
            for i, draft in enumerate(drafts):
                siblings = [f"[[{o.title}]]" for j, o in enumerate(drafts) if j != i and o.title]
                if siblings:
                    draft.content_md = _inject_related_notes(draft.content_md, siblings)
                    draft.related = list(dict.fromkeys([*siblings, *draft.related]))
        notes = [await self._persist_draft(draft, created_by=created_by) for draft in drafts]
        logger.info(
            "[knowledge] file '%s' imported → %d note(s) [%s], status=%s, llm_fallback=%s",
            filename,
            len(notes),
            ", ".join(n.get("title", "") for n in notes),
            normalized,
            llm_fallback,
        )
        return {"note": notes[0], "created": True, "notes": notes, "llm_fallback": llm_fallback}
    # -- CRUD -------------------------------------------------------------
    async def list_notes(
        self,