diff --git a/.env.example b/.env.example
index 8655a6e..bae9572 100644
--- a/.env.example
+++ b/.env.example
@@ -37,6 +37,11 @@ INGEST_API_KEYS=dev-key-1
 AMAP_WEB_KEY=
 AMAP_JS_KEY=
 AMAP_SECURITY_JSCODE=
+
+# 阿里云 OCR (RecognizePassport 等), optional
+ALIYUN_OCR_ACCESS_KEY_ID=
+ALIYUN_OCR_ACCESS_KEY_SECRET=
+ALIYUN_OCR_ENDPOINT=ocr-api.cn-hangzhou.aliyuncs.com
 GAODE_CRAWLER_PATH=
 TRAVEL_KG_DATA_ROOT=./data
 TRAVEL_AGENCY_SOURCE_ROOT=./data/source/travel_agency
diff --git a/.gitignore b/.gitignore
index 882ea56..987bb7b 100644
--- a/.gitignore
+++ b/.gitignore
@@ -20,6 +20,7 @@ admin-web/tsconfig.tsbuildinfo
 # Runtime and generated local files
 logs/
 tmp/
+.codex-tmp/
 *.log
 *.pid
 app/static/admin/
diff --git a/Dockerfile b/Dockerfile
index e5ec480..c7b395a 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,5 +1,3 @@
-# syntax=docker/dockerfile:1.7
-
 FROM node:22-bookworm-slim AS admin-web-build
 
 WORKDIR /build/admin-web
diff --git a/admin-web/src/api.ts b/admin-web/src/api.ts
index fd67f64..84bf6eb 100644
--- a/admin-web/src/api.ts
+++ b/admin-web/src/api.ts
@@ -175,8 +175,26 @@ export const plazaOverview = () => api.get("/plaza/overview");
 export const plazaUsage = () => api.get("/plaza/usage");
 export const plazaAlerts = () => api.get("/plaza/alerts");
 export const plazaAmapConfig = () => api.get("/plaza/amap-config");
+export const plazaMapPois = () => api.get("/plaza/map-pois");
+export const plazaBusRoutes = () => api.get("/plaza/bus-routes");
+export const plazaMapPoiDetail = (placeId: string) =>
+  api.get(`/plaza/map-pois/${encodeURIComponent(placeId)}`);
 export const plazaUserQuery = (data: unknown) => api.post("/plaza/user-query", data);
 export const travelAssistantQuery = (data: unknown) => api.post("/travel/assistant-query", data);
+
+// ── OCR (旅行社名单录入) ──
+export const ocrPassport = (file: File) => {
+  const form = new FormData();
+  form.append("file", file);
+  return api.post("/ocr/passport", form, {
+    headers: { "Content-Type": "multipart/form-data" },
+  });
+};
+export const ocrPassportByUrl = (url: string) => {
+  const form = new FormData();
+  form.append("url", url);
+  return api.post("/ocr/passport", form);
+};
 export const graphOverview = () => api.get("/graph/overview");
 export const graphQuery = (cypher: string, limit = 200) =>
   api.post("/graph/query", { cypher, limit });
diff --git a/admin-web/src/panels/plaza/GraphCanvas.tsx b/admin-web/src/panels/plaza/GraphCanvas.tsx
index 2466aa9..c3b3c66 100644
--- a/admin-web/src/panels/plaza/GraphCanvas.tsx
+++ b/admin-web/src/panels/plaza/GraphCanvas.tsx
@@ -9,11 +9,11 @@ import * as echarts from "echarts";
 import api, { displayGraphName, getProjectContext } from "../../api";
 
 const CATEGORY_COLORS: Record<string, string> = {
-  Place: "#00D4AA", Area: "#5B8FF9", Station: "#F6BD16",
+  Place: "#00D4AA", Area: "#5B8FF9", GeoCell: "#5B8FF9", 片区: "#5B8FF9", Station: "#F6BD16",
   BusStop: "#F6BD16", MetroStation: "#1677FF", TransitStop: "#F6BD16",
   BusLine: "#9270CA",
-  地点: "#00D4AA", 景点: "#00D4AA", 美食: "#FF9D4D", 酒店: "#6DC8EC",
-  商场: "#F6BD16", 公交站: "#F6BD16", 地铁站: "#1677FF", 交通站点: "#F6BD16",
+  地点: "#00D4AA", 景点: "#1677FF", 景区: "#1677FF", 美食: "#FF5A1F", 酒店: "#722ED1",
+  交通设施: "#13A8A8", 商场: "#F6BD16", 公交站: "#F6BD16", 地铁站: "#1677FF", 交通站点: "#F6BD16",
   RouteTemplate: "#E8684A", ExperienceTag: "#6DC8EC",
   Source: "#9270CA", Evidence: "#FF99C3",
   TourProduct: "#4C6FFF", ProductDay: "#6DC8EC", RouteStop: "#F6BD16",
@@ -207,6 +207,15 @@ const FULL_GRAPH_LIMIT = 2500;
 const FULL_GRAPH_BATCH_SIZE = 1000;
 const FULL_GRAPH_BASE_CYPHER = "MATCH (n)-[r]->(m) RETURN n,r,m";
 const GENERIC_DEFAULT_CYPHER = `${FULL_GRAPH_BASE_CYPHER} LIMIT ${FULL_GRAPH_LIMIT}`;
+const LIBO_DEFAULT_CYPHER = [
+  "MATCH (n:Hotel)-[r:IN_H3_R9]->(cell:GeoCell)-[areaRel:LOCATED_IN]->(area:Area) RETURN n,r,cell,areaRel,area,null AS parentRel,null AS parent LIMIT 100",
+  "UNION",
+  "MATCH (n:FoodPlace)-[r:IN_H3_R9]->(cell:GeoCell)-[areaRel:LOCATED_IN]->(area:Area) RETURN n,r,cell,areaRel,area,null AS parentRel,null AS parent LIMIT 100",
+  "UNION",
+  "MATCH (n:TransitFacility)-[r:IN_H3_R9]->(cell:GeoCell)-[areaRel:LOCATED_IN]->(area:Area) RETURN n,r,cell,areaRel,area,null AS parentRel,null AS parent LIMIT 60",
+  "UNION",
+  "MATCH (n:ScenicSpot)-[parentRel:PART_OF_SCENIC_AREA]->(parent) MATCH (n)-[r:IN_H3_R9]->(cell:GeoCell)-[areaRel:LOCATED_IN]->(area:Area) RETURN n,r,cell,areaRel,area,parentRel,parent LIMIT 50",
+].join(" ");
 const TRAVEL_CORE_CYPHER = [
   "MATCH (p:TourProduct)-[lineStop:PRODUCT_HAS_ORDERED_STOP]->(s:RouteStop)",
   "OPTIONAL MATCH (s)-[next:ROUTE_STOP_NEXT]->(s2:RouteStop)",
@@ -342,8 +351,19 @@ function isAnyTravelGraphName(value?: any): boolean {
   return name.includes("travel") || name.includes("旅行社") || name.includes("旅游");
 }
 
+function isYunyouLiboGraphName(value?: any): boolean {
+  const name = String(value || "").toLowerCase();
+  return name.includes("yunyou_libo") || name.includes("云游荔波");
+}
+
 function defaultCypherForGraph(value?: any): string {
-  return isTravelItemGraphName(value) ? TRAVEL_ITEM_CORE_CYPHER : (isAnyTravelGraphName(value) ? TRAVEL_DEFAULT_CYPHER : GENERIC_DEFAULT_CYPHER);
+  return isYunyouLiboGraphName(value)
+    ? LIBO_DEFAULT_CYPHER
+    : isTravelItemGraphName(value)
+    ? TRAVEL_ITEM_CORE_CYPHER
+    : isAnyTravelGraphName(value)
+    ? TRAVEL_DEFAULT_CYPHER
+    : GENERIC_DEFAULT_CYPHER;
 }
 
 function modeLabel(mode?: string): string {
@@ -1355,7 +1375,25 @@ export default function GraphCanvas() {
   const currentGraphName = overview.graph_name || getProjectContext().graphName;
   const isTravelGraph = isAnyTravelGraphName(currentGraphName);
   const isTravelItemGraph = isTravelItemGraphName(currentGraphName);
-  const queryTemplates = isTravelItemGraph ? [
+  const isYunyouLiboGraph = isYunyouLiboGraphName(currentGraphName);
+  const queryTemplates = isYunyouLiboGraph ? [
+    { label: "四类业务全景", cypher: LIBO_DEFAULT_CYPHER },
+    { label: "全部关系抽样", cypher: GENERIC_DEFAULT_CYPHER },
+    { label: "酒店", cypher: "MATCH (n:Hotel) RETURN n LIMIT 150" },
+    { label: "美食", cypher: "MATCH (n:FoodPlace) RETURN n LIMIT 150" },
+    { label: "交通设施", cypher: "MATCH (n:TransitFacility) RETURN n LIMIT 150" },
+    { label: "景点", cypher: "MATCH (n:ScenicSpot) RETURN n LIMIT 120" },
+    { label: "景区", cypher: "MATCH (n:ScenicArea) RETURN n LIMIT 20" },
+    { label: "公交线路停靠", cypher: "MATCH (line:BusRoute)-[r:STOPS_AT]->(stop:BusStop) RETURN line,r,stop LIMIT 350" },
+    { label: "公交相邻站", cypher: "MATCH (a:BusStop)-[r:NEXT_STOP]->(b:BusStop) RETURN a,r,b LIMIT 320" },
+    { label: "景点归属", cypher: "MATCH (spot:ScenicSpot)-[r:PART_OF_SCENIC_AREA]->(parent) RETURN spot,r,parent LIMIT 120" },
+    { label: "POI 所在荔波县", cypher: "MATCH (poi:Place)-[r:LOCATED_IN]->(area:Area) WHERE area.adcode = '522722' RETURN poi,r,area LIMIT 300" },
+    {
+      label: "POI 所属片区",
+      cypher: "MATCH (poi:Place)-[r:IN_H3_R9]->(cell:GeoCell)-[areaRel:LOCATED_IN]->(area:Area) RETURN poi,r,cell,areaRel,area LIMIT 50",
+    },
+    { label: "行政区层级", cypher: "MATCH (child:Area)-[r:PART_OF]->(parent:Area) RETURN child,r,parent LIMIT 20" },
+  ] : isTravelItemGraph ? [
     { label: "核心业务图", cypher: TRAVEL_ITEM_CORE_CYPHER },
     { label: "固定线路骨架", cypher: TRAVEL_ITEM_ROUTE_SKELETON_CYPHER },
     { label: "景区附近酒店餐饮", cypher: TRAVEL_ITEM_NEARBY_RESOURCE_CYPHER },
@@ -1408,6 +1446,8 @@ export default function GraphCanvas() {
     ? "输入自然语言或 Cypher，例如：黄果树天星桥有哪些必付小交通和可选二消？"
     : isTravelGraph
     ? "输入自然语言或 Cypher，例如：一家5人6天想去黄果树小七孔西江梵净山，推荐什么线路？"
+    : isYunyouLiboGraph
+    ? "输入自然语言或 Cypher，例如：查询荔波县的酒店、美食、交通设施或景点"
     : "输入自然语言或 Cypher，例如：花溪公园有哪些历史事件？";
 
   const selectedTrafficInfo = selectedNode ? collectTrafficInfo(selectedNode, dataRef.current) : null;
@@ -1488,7 +1528,11 @@ export default function GraphCanvas() {
           <Space split="·" wrap>
             {resultInfo && <span style={{ color: "#52c41a", fontSize: 12 }}>{resultInfo}</span>}
             <span style={{ color: "#999", fontSize: 12 }}>
-              {isTravelGraph ? "默认展示固定线路主干；费用/规则/审计关系按需查询" : "支持自然语言和 Cypher"} · 单击看详情 · 双击展开关联 · 滚轮缩放 · 拖拽平移
+              {isTravelGraph
+                ? "默认展示固定线路主干；费用/规则/审计关系按需查询"
+                : isYunyouLiboGraph
+                ? "快速查询已按荔波县酒店、美食、交通、景点、公交和空间关系配置"
+                : "支持自然语言和 Cypher"} · 单击看详情 · 双击展开关联 · 滚轮缩放 · 拖拽平移
             </span>
           </Space>
           {queryMeta?.cypher && (
diff --git a/admin-web/src/panels/plaza/ManualIngestPanel.tsx b/admin-web/src/panels/plaza/ManualIngestPanel.tsx
index ce4f9f9..94a17aa 100644
--- a/admin-web/src/panels/plaza/ManualIngestPanel.tsx
+++ b/admin-web/src/panels/plaza/ManualIngestPanel.tsx
@@ -21,6 +21,7 @@ import {
 import {
   ArrowLeftOutlined,
   CheckCircleOutlined,
+  FileMarkdownOutlined,
   FileSearchOutlined,
   InboxOutlined,
   SearchOutlined,
@@ -122,6 +123,7 @@ type ManualTaskRow = {
   status: string;
   owner: string;
   createdAt: string;
+  markdownDocument?: string;
   error?: string;
 };
 
@@ -144,6 +146,8 @@ type ManualIngestSession = {
   taskCreatedAt: string;
   taskRecord: ManualTaskRow | null;
   result: ExtractResult | null;
+  convertedMarkdownFile?: string;
+  convertedMarkdownPath?: string;
   updatedAt: number;
 };
 
@@ -481,6 +485,32 @@ function SourceHighlighter({ text, hit }: { text: string; hit: EvidenceHit | nul
   return <div style={{ whiteSpace: "pre-wrap", lineHeight: 1.8, fontSize: 13 }}>{text}</div>;
 }
 
+function MarkdownPreview({ markdown }: { markdown: string }) {
+  if (!markdown.trim()) {
+    return <Empty image={Empty.PRESENTED_IMAGE_SIMPLE} description="暂无 Markdown 内容" />;
+  }
+  return (
+    <div className="manual-markdown-preview">
+      {markdown.split(/\r?\n/).map((line, index) => {
+        const key = `${index}-${line.slice(0, 16)}`;
+        const heading = line.match(/^(#{1,6})\s+(.+)$/);
+        if (heading) {
+          const level = Math.min(heading[1].length, 4) as 1 | 2 | 3 | 4;
+          return <Title key={key} level={level}>{heading[2]}</Title>;
+        }
+        if (!line.trim()) return <div key={key} className="manual-markdown-blank" />;
+        if (/^\s*([-*+]|\d+[.)])\s+\S/.test(line)) {
+          return <div key={key} className="manual-markdown-list-item">{line.replace(/^\s*([-*+]|\d+[.)])\s+/, "")}</div>;
+        }
+        if (line.includes("|") && line.split("|").length >= 3) {
+          return <pre key={key} className="manual-markdown-table-line">{line}</pre>;
+        }
+        return <p key={key}>{line}</p>;
+      })}
+    </div>
+  );
+}
+
 function connectedPreviewGraph(graph?: { nodes: KgRow[]; edges: KgRow[] }) {
   const allNodes = graph?.nodes || [];
   const nodeIds = new Set(allNodes.map((n) => String(n.id)));
@@ -713,6 +743,14 @@ export default function ManualIngestPanel() {
   const [taskRecord, setTaskRecord] = useState<ManualTaskRow | null>(null);
   const [hit, setHit] = useState<EvidenceHit | null>(null);
   const [sessionHydrated, setSessionHydrated] = useState(false);
+  const [fileConverting, setFileConverting] = useState(false);
+  const [convertedMarkdownFile, setConvertedMarkdownFile] = useState("");
+  const [convertedMarkdownPath, setConvertedMarkdownPath] = useState("");
+  const [markdownPreviewOpen, setMarkdownPreviewOpen] = useState(false);
+  const [markdownPreviewLoading, setMarkdownPreviewLoading] = useState(false);
+  const [markdownPreviewText, setMarkdownPreviewText] = useState("");
+  const [markdownPreviewPath, setMarkdownPreviewPath] = useState("");
+  const [markdownPreviewTab, setMarkdownPreviewTab] = useState("preview");
 
   const summary = result?.summary || {};
   const hasResult = !!result;
@@ -748,7 +786,10 @@ export default function ManualIngestPanel() {
     setTaskCreatedAt(cached.taskCreatedAt || "");
     setTaskRecord(cached.taskRecord || null);
     setResult(cached.result || null);
+    setConvertedMarkdownFile(cached.convertedMarkdownFile || "");
+    setConvertedMarkdownPath(cached.convertedMarkdownPath || "");
     setLoading(false);
+    setFileConverting(false);
     setHit(null);
     setResultOpen(false);
     setSessionHydrated(true);
@@ -815,6 +856,10 @@ export default function ManualIngestPanel() {
   };
 
   const runExtract = async () => {
+    if (fileConverting) {
+      message.info("请等待文件转换完成");
+      return;
+    }
     if (!text.trim()) {
       message.warning("请先上传或粘贴文档内容");
       return;
@@ -838,6 +883,7 @@ export default function ManualIngestPanel() {
       status: "执行中",
       owner: "111111",
       createdAt,
+      markdownDocument: convertedMarkdownFile,
     };
     setTaskCreatedAt(createdAt);
     setTaskRecord(pendingTask);
@@ -866,6 +912,8 @@ export default function ManualIngestPanel() {
       taskCreatedAt: createdAt,
       taskRecord: pendingTask,
       result: null,
+      convertedMarkdownFile,
+      convertedMarkdownPath,
       updatedAt: Date.now(),
     }, true);
     try {
@@ -908,6 +956,8 @@ export default function ManualIngestPanel() {
         taskCreatedAt: createdAt,
         taskRecord: completedTask,
         result: data,
+        convertedMarkdownFile,
+        convertedMarkdownPath,
         updatedAt: Date.now(),
       }, true);
       setResultOpen(false);
@@ -937,6 +987,8 @@ export default function ManualIngestPanel() {
         taskCreatedAt: createdAt,
         taskRecord: failedTask,
         result: null,
+        convertedMarkdownFile,
+        convertedMarkdownPath,
         updatedAt: Date.now(),
       }, true);
       message.error(errorDetail);
@@ -998,6 +1050,7 @@ export default function ManualIngestPanel() {
   const taskRows = taskRecord ? [taskRecord] : [];
   const displayTaskName = taskRecord?.name || documentName;
   const displayUploadDocument = taskRecord?.document || uploadDocument;
+  const displayMarkdownDocument = taskRecord?.markdownDocument || convertedMarkdownFile || convertedMarkdownPath;
   const displayBusinessScene = taskRecord?.businessScene || selectedScene.label;
   const displaySceneRule = taskRecord?.sceneRule || selectedScene.schema;
   const displaySegmentStrategy = taskRecord?.segmentStrategy || STRATEGY_LABELS[extractStrategy];
@@ -1008,6 +1061,9 @@ export default function ManualIngestPanel() {
   const logLines = [
     `${taskCreatedAt || new Date().toLocaleString("zh-CN", { hour12: false })}: create knowledge extraction task:${displayTaskName}`,
     `${taskCreatedAt || new Date().toLocaleString("zh-CN", { hour12: false })}: upload document:${displayUploadDocument}`,
+    displayMarkdownDocument
+      ? `${taskCreatedAt || new Date().toLocaleString("zh-CN", { hour12: false })}: markitdown markdown:${displayMarkdownDocument}`
+      : "",
     `${taskCreatedAt || new Date().toLocaleString("zh-CN", { hour12: false })}: business scene:${displayBusinessScene}`,
     `${taskCreatedAt || new Date().toLocaleString("zh-CN", { hour12: false })}: auto schema:${displaySceneRule}`,
     `${taskCreatedAt || new Date().toLocaleString("zh-CN", { hour12: false })}: knowledge llm:${displayExtractModel}`,
@@ -1115,6 +1171,8 @@ export default function ManualIngestPanel() {
       taskCreatedAt,
       taskRecord,
       result,
+      convertedMarkdownFile,
+      convertedMarkdownPath,
       updatedAt: Date.now(),
     });
   }, [
@@ -1136,6 +1194,8 @@ export default function ManualIngestPanel() {
     taskCreatedAt,
     taskRecord,
     result,
+    convertedMarkdownFile,
+    convertedMarkdownPath,
   ]);
 
   const fillSample = () => {
@@ -1157,6 +1217,11 @@ export default function ManualIngestPanel() {
     setAllowSchemaExtra(false);
     setDirectImport(false);
     setText("");
+    setConvertedMarkdownFile("");
+    setConvertedMarkdownPath("");
+    setMarkdownPreviewOpen(false);
+    setMarkdownPreviewText("");
+    setMarkdownPreviewPath("");
     setHit(null);
     setWizardStep(0);
   };
@@ -1190,8 +1255,61 @@ export default function ManualIngestPanel() {
     setBusinessScene(nextScene.scene);
   };
 
+  const convertUploadToMarkdown = async (file: File) => {
+    setFileConverting(true);
+    setHit(null);
+    const formData = new FormData();
+    formData.append("file", file);
+    try {
+      const { data } = await api.post("/manual-ingest/convert-file", formData);
+      const markdown = String(data?.markdown || "");
+      if (!markdown.trim()) {
+        message.warning("文件已上传，但未转换出可抽取文本");
+        return;
+      }
+      const filename = String(data?.filename || file.name);
+      const markdownPath = String(data?.markdown_path || "");
+      setText(markdown);
+      setSourceUrl(filename);
+      setFormat("markdown");
+      setConvertedMarkdownFile(markdownPath || `${filename}.markitdown.md`);
+      setConvertedMarkdownPath(markdownPath);
+      if (!sourceName.trim()) {
+        setSourceName(filename.replace(/\.[^.]+$/, ""));
+      }
+      message.success(`已转换为 MarkItDown Markdown，共 ${Number(data?.markdown_chars || markdown.length)} 字`);
+    } catch (err: any) {
+      message.error(err?.response?.data?.detail || err?.message || "文件转换失败");
+    } finally {
+      setFileConverting(false);
+    }
+  };
+
+  const openMarkdownPreview = async () => {
+    const path = convertedMarkdownPath || convertedMarkdownFile;
+    setMarkdownPreviewPath(path);
+    setMarkdownPreviewText(text);
+    setMarkdownPreviewTab("preview");
+    setMarkdownPreviewOpen(true);
+    if (!path) return;
+    setMarkdownPreviewLoading(true);
+    try {
+      const { data } = await api.get("/manual-ingest/markdown-preview", { params: { path } });
+      setMarkdownPreviewText(String(data?.markdown || text));
+      setMarkdownPreviewPath(String(data?.markdown_path || path));
+    } catch (err: any) {
+      message.warning(err?.response?.data?.detail || "读取 Markdown 文件失败，先显示当前文档内容");
+    } finally {
+      setMarkdownPreviewLoading(false);
+    }
+  };
+
   const nextStep = () => {
     if (wizardStep === 0) {
+      if (fileConverting) {
+        message.info("请等待文件转换完成");
+        return;
+      }
       if (!sourceName.trim()) {
         message.warning("请输入知识任务名称");
         return;
@@ -1232,22 +1350,27 @@ export default function ManualIngestPanel() {
             <label><span>*</span> 上传文件</label>
             <Upload.Dragger
               className="manual-task-uploader"
-              accept=".txt,.csv,.json,.xml,.log,.md,.pdf"
+              accept=".txt,.csv,.json,.xml,.log,.md,.markdown,.pdf,.doc,.docx,.ppt,.pptx,.xls,.xlsx,.html,.htm,.zip,.epub,.jpg,.jpeg,.png,.gif,.wav,.mp3"
               showUploadList={false}
+              disabled={fileConverting}
               beforeUpload={(file) => {
-                const reader = new FileReader();
-                reader.onload = () => {
-                  setText(String(reader.result || ""));
-                  setSourceUrl(file.name);
-                };
-                reader.readAsText(file);
-                return false;
+                void convertUploadToMarkdown(file as File);
+                return Upload.LIST_IGNORE;
               }}
             >
               <p className="ant-upload-drag-icon"><InboxOutlined /></p>
-              <p className="ant-upload-text">点击或将文件拖拽到这里上传</p>
-              <p className="ant-upload-hint">支持拓展名:txt，csv，json，xml，log，md，pdf</p>
+              <p className="ant-upload-text">{fileConverting ? "正在转换为 MarkItDown Markdown..." : "点击或将文件拖拽到这里上传"}</p>
+              <p className="ant-upload-hint">支持 PDF、Word、PPT、Excel、HTML、Markdown、CSV、JSON、XML、图片、音频和 ZIP</p>
             </Upload.Dragger>
+            {convertedMarkdownFile && (
+              <button type="button" className="manual-markdown-note" onClick={openMarkdownPreview}>
+                <FileMarkdownOutlined />
+                <Text type="secondary" ellipsis={{ tooltip: convertedMarkdownFile }}>
+                  已生成 MarkItDown 文件：{convertedMarkdownFile}
+                </Text>
+                <span>查看</span>
+              </button>
+            )}
           </div>
 
           <div className="manual-form-row">
@@ -1256,7 +1379,7 @@ export default function ManualIngestPanel() {
               value={text}
               onChange={(event) => setText(event.target.value)}
               rows={5}
-              placeholder="也可以直接粘贴文档内容"
+              placeholder="上传文件会自动转换为 MarkItDown Markdown；也可以直接粘贴文档内容"
             />
           </div>
 
@@ -1286,6 +1409,7 @@ export default function ManualIngestPanel() {
               onChange={setFormat}
               options={[
                 { value: "auto", label: "自动识别格式" },
+                { value: "markdown", label: "MarkItDown Markdown" },
                 { value: "text", label: "自由文本" },
                 { value: "csv", label: "CSV / 表格" },
                 { value: "kv", label: "键值对" },
@@ -1495,11 +1619,53 @@ export default function ManualIngestPanel() {
         </div>
       </Drawer>
 
+      <Drawer
+        title="MarkItDown Markdown 预览"
+        open={markdownPreviewOpen}
+        onClose={() => setMarkdownPreviewOpen(false)}
+        width={820}
+      >
+        <Space direction="vertical" size={12} style={{ width: "100%" }}>
+          <Alert
+            type="info"
+            showIcon
+            message={markdownPreviewPath || "当前文档内容"}
+            description={markdownPreviewLoading ? "正在读取生成的 Markdown 文件..." : `共 ${markdownPreviewText.length} 字`}
+          />
+          <Tabs
+            activeKey={markdownPreviewTab}
+            onChange={setMarkdownPreviewTab}
+            items={[
+              {
+                key: "preview",
+                label: "预览",
+                children: <MarkdownPreview markdown={markdownPreviewText} />,
+              },
+              {
+                key: "source",
+                label: "源码",
+                children: (
+                  <TextArea
+                    value={markdownPreviewText}
+                    readOnly
+                    autoSize={{ minRows: 18, maxRows: 30 }}
+                    className="manual-markdown-source"
+                  />
+                ),
+              },
+            ]}
+          />
+        </Space>
+      </Drawer>
+
       <Drawer title="查看配置" open={configOpen} onClose={() => setConfigOpen(false)} width={520}>
         <div className="manual-config-list">
           <div><Text type="secondary">任务名称</Text><strong>{displayTaskName}</strong></div>
           <div><Text type="secondary">文件类型</Text><strong>{displayFileType}</strong></div>
           <div><Text type="secondary">上传文档</Text><strong>{displayUploadDocument}</strong></div>
+          {displayMarkdownDocument && (
+            <div><Text type="secondary">MarkItDown 文件</Text><strong>{displayMarkdownDocument}</strong></div>
+          )}
           <div><Text type="secondary">业务场景</Text><strong>{displayBusinessScene}</strong></div>
           <div><Text type="secondary">场景规则</Text><strong>{displaySceneRule}</strong></div>
           <div><Text type="secondary">分段方式</Text><strong>{displaySegmentStrategy}</strong></div>
diff --git a/admin-web/src/panels/plaza/PassportOcrCard.tsx b/admin-web/src/panels/plaza/PassportOcrCard.tsx
new file mode 100644
index 0000000..5ecbed9
--- /dev/null
+++ b/admin-web/src/panels/plaza/PassportOcrCard.tsx
@@ -0,0 +1,122 @@
+import { useState } from "react";
+import {
+  Alert, Button, Card, Descriptions, Input, Space, Tag, Upload, message,
+} from "antd";
+import { IdcardOutlined, UploadOutlined } from "@ant-design/icons";
+import type { UploadFile } from "antd";
+import { ocrPassport, ocrPassportByUrl } from "../../api";
+
+type OcrResult = Record<string, any>;
+
+const PRIMARY_LABELS: Record<string, string> = {
+  name: "姓名",
+  given_name: "名 (Given Name)",
+  family_name: "姓 (Surname)",
+  sex: "性别",
+  nationality: "国籍",
+  country: "国家代码",
+  passport_no: "护照号",
+  birth_date: "出生日期",
+  date_of_birth: "出生日期",
+  expiry_date: "到期日期",
+  date_of_expiry: "到期日期",
+  issue_date: "签发日期",
+  date_of_issue: "签发日期",
+  issue_place: "签发地",
+  place_of_birth: "出生地",
+  authority: "签发机关",
+};
+
+function labelOf(key: string) {
+  return PRIMARY_LABELS[key] || key;
+}
+
+export default function PassportOcrCard() {
+  const [file, setFile] = useState<UploadFile | null>(null);
+  const [url, setUrl] = useState("");
+  const [loading, setLoading] = useState(false);
+  const [result, setResult] = useState<OcrResult | null>(null);
+  const [errorMsg, setErrorMsg] = useState<string | null>(null);
+
+  const reset = () => {
+    setResult(null);
+    setErrorMsg(null);
+  };
+
+  const submit = async () => {
+    reset();
+    if (!file && !url.trim()) {
+      message.warning("请上传护照图片或填写图片 URL");
+      return;
+    }
+    setLoading(true);
+    try {
+      const resp = file?.originFileObj
+        ? await ocrPassport(file.originFileObj as File)
+        : await ocrPassportByUrl(url.trim());
+      setResult(resp.data?.data || {});
+    } catch (err: any) {
+      const detail = err?.response?.data?.detail || err?.message || "识别失败";
+      setErrorMsg(String(detail));
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  const requestId = result?._request_id;
+  const fields = result
+    ? Object.entries(result).filter(([k]) => k !== "_request_id")
+    : [];
+
+  return (
+    <Card
+      className="travel-panel"
+      size="small"
+      title={<><IdcardOutlined /> 护照识别（旅行社名单录入）</>}
+      extra={requestId && <Tag color="blue">RequestId {String(requestId).slice(0, 12)}…</Tag>}
+    >
+      <Space direction="vertical" style={{ width: "100%" }} size="middle">
+        <Space wrap>
+          <Upload
+            beforeUpload={(f) => {
+              setFile({ uid: f.uid, name: f.name, originFileObj: f } as UploadFile);
+              return false;
+            }}
+            onRemove={() => setFile(null)}
+            fileList={file ? [file] : []}
+            maxCount={1}
+            accept="image/*"
+          >
+            <Button icon={<UploadOutlined />}>选择护照图片</Button>
+          </Upload>
+          <Input
+            placeholder="或粘贴公网图片 URL（如 OSS 链接）"
+            value={url}
+            onChange={(e) => setUrl(e.target.value)}
+            style={{ width: 340 }}
+            allowClear
+          />
+          <Button type="primary" loading={loading} onClick={submit}>
+            识别
+          </Button>
+        </Space>
+
+        {errorMsg && <Alert type="error" showIcon message="识别失败" description={errorMsg} />}
+
+        {result && (
+          fields.length ? (
+            <Descriptions size="small" bordered column={2}>
+              {fields.map(([key, value]) => (
+                <Descriptions.Item key={key} label={labelOf(key)}>
+                  {typeof value === "object" ? JSON.stringify(value) : String(value ?? "")}
+                </Descriptions.Item>
+              ))}
+            </Descriptions>
+          ) : (
+            <Alert type="warning" showIcon message="阿里云返回空结果，可能图片质量不足或非护照页" />
+          )
+        )}
+      </Space>
+    </Card>
+  );
+}
diff --git a/admin-web/src/panels/plaza/PlazaOverview.tsx b/admin-web/src/panels/plaza/PlazaOverview.tsx
index d808d02..1076e53 100644
--- a/admin-web/src/panels/plaza/PlazaOverview.tsx
+++ b/admin-web/src/panels/plaza/PlazaOverview.tsx
@@ -11,20 +11,30 @@ import {
   graphOverview,
   graphQuery,
   plazaOverview,
+  superAgentCoverage,
   type KgProjectContext,
 } from "../../api";
-import SuperAgentPanel from "./SuperAgentPanel";
+import SuperAgentPanel, { KnowledgeMap, type CoverageSnapshot } from "./SuperAgentPanel";
 
 const STATUS_COLORS: Record<string, string> = {
   active: "green", published: "blue", draft: "default", archived: "orange",
 };
 
 const GRAPH_CATEGORY_CYPHER =
-  "MATCH (n:Place) RETURN n.place_type AS place_type, n.station_type AS station_type, count(n) AS count LIMIT 200";
+  "MATCH (n:Place) WHERE size(labels(n)) = 1 "
+  + "RETURN n.place_type AS place_type, n.station_type AS station_type, count(n) AS count LIMIT 200";
 
 const LABEL_NAMES: Record<string, string> = {
   Area: "行政区",
   BusLine: "公交线路",
+  BusRoute: "公交运行方向",
+  BusStop: "公交站",
+  FoodPlace: "美食",
+  GeoCell: "空间网格",
+  Hotel: "酒店",
+  ScenicArea: "景区",
+  ScenicSpot: "景点",
+  TransitFacility: "交通设施",
   ExperienceTag: "体验标签",
   RouteTemplate: "线路模板",
   Source: "来源",
@@ -37,7 +47,9 @@ const PLACE_TYPE_NAMES: Record<string, string> = {
   hotel: "酒店",
   mall: "商场",
   poi: "其他地点",
+  recreation: "体育休闲",
   sight: "景点",
+  transit: "交通设施",
   transit_stop: "交通站点",
   walk: "漫步",
 };
@@ -58,20 +70,28 @@ export default function PlazaOverview() {
   const [data, setData] = useState<Record<string, unknown>>({});
   const [graphData, setGraphData] = useState<Record<string, unknown>>({});
   const [graphCategories, setGraphCategories] = useState<EntityCategory[]>([]);
+  const [mapCoverage, setMapCoverage] = useState<CoverageSnapshot | null>(null);
   const [projectContext, setProjectContextState] = useState<KgProjectContext>(getProjectContext());
   const navigate = useNavigate();
 
   const fetch = async () => {
     const currentContext = getProjectContext();
     const isCityProject = currentContext.graphName === DEFAULT_PROJECT_CONTEXT.graphName;
+    const isLiboProject = currentContext.graphName === "yunyou_libo"
+      || currentContext.projectId === "yunyou_libo";
+    const isKnowledgeMapProject = isCityProject || isLiboProject;
     const [plaza, graph] = await Promise.all([plazaOverview(), graphOverview()]);
-    const placeTypeRows = isCityProject
+    const placeTypeRows = isKnowledgeMapProject
       ? await graphQuery(GRAPH_CATEGORY_CYPHER).then((res) => res.data.rows || []).catch(() => [])
       : [];
+    const coverage = isLiboProject
+      ? await superAgentCoverage().then((res) => res.data).catch(() => null)
+      : null;
     setProjectContextState(currentContext);
     setData(plaza.data);
     setGraphData(graph.data);
-    setGraphCategories(isCityProject ? buildGraphCategories(graph.data, placeTypeRows) : []);
+    setGraphCategories(isKnowledgeMapProject ? buildGraphCategories(graph.data, placeTypeRows) : []);
+    setMapCoverage(coverage);
   };
 
   useEffect(() => {
@@ -84,13 +104,20 @@ export default function PlazaOverview() {
   const categories = graphCategories.length ? graphCategories : ((data.categories as Array<Record<string, any>>) || []);
   const releases = (data.graph_releases as Array<Record<string, unknown>>) || [];
   const isCityProject = projectContext.graphName === DEFAULT_PROJECT_CONTEXT.graphName;
-  const pageTitle = isCityProject ? "知识广场 · 馆藏概览" : "业务资料库 · 馆藏概览";
+  const isLiboProject = projectContext.graphName === "yunyou_libo"
+    || projectContext.projectId === "yunyou_libo";
+  const pageTitle = isCityProject
+    ? "知识广场 · 馆藏概览"
+    : isLiboProject
+      ? "知识广场 · 云游荔波馆藏概览"
+      : "业务资料库 · 馆藏概览";
 
   return (
     <div>
       <h2>{pageTitle}</h2>
 
       {isCityProject && <SuperAgentPanel />}
+      {isLiboProject && <KnowledgeMap cov={mapCoverage} scope="libo" />}
 
       {/* Stat cards */}
       <Row gutter={16} style={{ marginBottom: 24 }}>
diff --git a/admin-web/src/panels/plaza/SuperAgentPanel.tsx b/admin-web/src/panels/plaza/SuperAgentPanel.tsx
index 2e5b033..bf29554 100644
--- a/admin-web/src/panels/plaza/SuperAgentPanel.tsx
+++ b/admin-web/src/panels/plaza/SuperAgentPanel.tsx
@@ -1,15 +1,24 @@
-import { useEffect, useState, useRef, useCallback, useMemo } from "react";
+import { useEffect, useState, useRef, useCallback, useMemo, type ReactNode } from "react";
 import {
   Card, Button, Space, Tag, Progress, Timeline, message, Alert, Table, Tooltip,
+  Drawer, Descriptions, Image, Spin, Empty, Divider, Tabs,
 } from "antd";
 import {
   RobotOutlined, ThunderboltOutlined, StopOutlined, BulbOutlined,
   WarningOutlined, BookOutlined, EnvironmentOutlined,
-  FullscreenOutlined, FullscreenExitOutlined,
+  FullscreenOutlined, FullscreenExitOutlined, CompassOutlined,
+  PhoneOutlined, AimOutlined, CarOutlined, UnorderedListOutlined,
+  CoffeeOutlined, ShoppingOutlined, CheckCircleOutlined, FireOutlined,
+  CustomerServiceOutlined, AppstoreOutlined, SafetyCertificateOutlined,
+  ClearOutlined, SmileOutlined, WifiOutlined, HomeOutlined,
+  PictureOutlined, PlayCircleOutlined, LinkOutlined, SolutionOutlined,
+  StarOutlined, CommentOutlined, CrownOutlined, PayCircleOutlined,
+  CalendarOutlined,
 } from "@ant-design/icons";
 import {
   superAgentRun, superAgentLatest, superAgentGet, superAgentStop,
   superAgentCoverage, superAgentTasks, plazaAmapConfig,
+  plazaMapPois, plazaMapPoiDetail, plazaBusRoutes,
 } from "../../api";
 
 const ST: Record<string, { label: string; color: string }> = {
@@ -20,7 +29,7 @@ const ST: Record<string, { label: string; color: string }> = {
   error: { label: "失败", color: "error" },
 };
 
-type Cov = {
+export type CoverageSnapshot = {
   items: any[];
   total: number;
   grid_overall_pct?: number;
@@ -31,6 +40,1749 @@ type Cov = {
   quota_limited?: number;
 };
 
+type MapPoi = {
+  id: string;
+  gaode_poi_id: string;
+  name: string;
+  category: string;
+  categories?: string[];
+  place_type: string;
+  lng: number;
+  lat: number;
+  address: string;
+  district: string;
+  city: string;
+};
+
+type MapPoiDetail = MapPoi & {
+  graph_name: string;
+  business_subcategory: string;
+  scenic_type: string;
+  scenic_level: string;
+  parent_scenic: string;
+  scenic_grade: string;
+  visitor_value: string;
+  audit_result: string;
+  audit_confidence: string;
+  audit_basis: string;
+  audit_date: string;
+  amap_type: string;
+  typecode: string;
+  scan_hit_count: number;
+  matched_scan_types: string[];
+  province: string;
+  adcode: string;
+  business_area: string;
+  tel: string;
+  open_time: string;
+  rating: string;
+  cost: string;
+  level: string;
+  tags: string;
+  photo_urls: string[];
+  source: string;
+  source_cell_id: string;
+  source_resolution?: number | null;
+  source_scope_adcode: string;
+  first_fetched_at: string;
+  last_fetched_at: string;
+  graph_labels: string[];
+  food_enrichment: Record<string, unknown>;
+  hotel_enrichment: Record<string, unknown>;
+};
+
+type BusStop = {
+  stop_id: string;
+  name: string;
+  lng: number;
+  lat: number;
+  sequence: number;
+};
+
+type BusRoute = {
+  route_id: string;
+  line_name: string;
+  direction: string;
+  start_stop: string;
+  end_stop: string;
+  stop_count: number;
+  fare_yuan: number;
+  first_bus: string;
+  last_bus: string;
+  distance_km: number;
+  path_source: string;
+  stops: BusStop[];
+};
+
+type BusStopNetwork = Omit<BusStop, "sequence"> & {
+  routes: BusRoute[];
+};
+
+type BusPanel =
+  | { mode: "list" }
+  | { mode: "line"; lineName: string }
+  | { mode: "route"; routeId: string }
+  | { mode: "stop"; stopId: string }
+  | null;
+
+type FullscreenMode = "none" | "native" | "fallback";
+
+const POI_CATEGORY_COLORS: Record<string, string> = {
+  景点: "#1677ff",
+  美食: "#fa541c",
+  酒店: "#722ed1",
+  交通设施: "#13a8a8",
+};
+
+const DIANPING_APP_ICON_URL =
+  "https://is1-ssl.mzstatic.com/image/thumb/Purple211/v4/43/c7/74/43c7747c-2b0c-1462-1717-d6a530153bab/AppIcon-0-0-1x_U007epad-0-1-0-sRGB-85-220.png/200x200bb.png";
+
+const poiCategoryColor = (category?: string) =>
+  POI_CATEGORY_COLORS[category || ""] || "#597ef7";
+
+const BUS_LINE_COLORS = [
+  "#00a870", "#1677ff", "#722ed1", "#fa8c16",
+  "#13a8a8", "#eb2f96", "#52c41a", "#2f54eb",
+];
+
+const LIBO_BUS_LINE_COLORS: Record<string, string> = {
+  "荔波1路": "#00a870",
+  "荔波2路": "#1677ff",
+  "荔波5路": "#722ed1",
+  "荔波9路": "#fa8c16",
+  "荔波10路": "#13a8a8",
+  "荔波11路": "#eb2f96",
+  "荔波12路": "#52c41a",
+  "荔波13路": "#2f54eb",
+};
+
+const busLineColor = (lineName: string) => {
+  if (LIBO_BUS_LINE_COLORS[lineName]) return LIBO_BUS_LINE_COLORS[lineName];
+  let hash = 0;
+  for (const char of lineName) hash = (hash * 31 + char.charCodeAt(0)) >>> 0;
+  return BUS_LINE_COLORS[hash % BUS_LINE_COLORS.length];
+};
+
+const busLineShortName = (lineName: string) => lineName.replace(/^荔波/, "");
+
+const normalizeBusStopName = (value: unknown) =>
+  String(value || "")
+    .replace(/[\s()（）]/g, "")
+    .replace(/公交站$/, "")
+    .replace(/^荔波县?/, "");
+
+const poiCoordinateKey = (lng: number, lat: number) =>
+  `${Number(lng).toFixed(6)},${Number(lat).toFixed(6)}`;
+
+const poiNavigationUrl = (poi: Pick<MapPoi, "lng" | "lat" | "name">) =>
+  `https://uri.amap.com/marker?position=${poi.lng},${poi.lat}`
+  + `&name=${encodeURIComponent(poi.name)}&src=znkg&coordinate=gaode&callnative=0`;
+
+const formatPoiTime = (value?: string) => {
+  if (!value) return "";
+  const date = new Date(value);
+  return Number.isNaN(date.getTime()) ? value : date.toLocaleString("zh-CN", { hour12: false });
+};
+
+type DetailItem = {
+  key: string;
+  label: string;
+  children: ReactNode;
+  icon?: ReactNode;
+};
+
+const FOOD_FEATURE_LABELS: Array<[string, string]> = [
+  ["dianping_tags", "特色标签"],
+  ["recommended_dish_names", "推荐菜"],
+];
+
+const HOTEL_OVERVIEW_LABELS: Array<[string, string]> = [
+  ["ctrip_hotel_type", "住宿类型"],
+  ["ctrip_ranking", "榜单排名"],
+];
+
+const HOTEL_FACILITY_LABELS: Array<[string, string]> = [
+  ["ctrip_popular_facilities", "热门设施"],
+  ["facility_summary", "设施服务"],
+];
+
+const HOTEL_POLICY_LABELS: Array<[string, string]> = [
+  ["policy_summary", "酒店政策"],
+];
+
+const HOTEL_NEARBY_LABELS: Array<[string, string]> = [
+  ["nearby_place_summary", "周边地点"],
+];
+
+const ZERO_MEANS_MISSING_KEYS = new Set([
+  "dianping_rating",
+  "dianping_review_count",
+  "dianping_avg_price",
+  "group_buy_count",
+  "review_sample_count",
+  "review_sample_avg_stars",
+  "ctrip_rating",
+  "ctrip_review_count",
+  "ctrip_room_count",
+  "room_min_price",
+  "room_max_price",
+  "offer_count",
+  "offer_min_price",
+  "offer_max_price",
+  "guest_review_sample_count",
+  "guest_review_sample_avg_score",
+]);
+
+const normalizeCtripDiamondLevel = (value: unknown) => {
+  const text = String(value ?? "").trim();
+  if (!text) return "";
+  if (/^\d+(?:\.\d+)?钻$/.test(text)) return text;
+  const match = text.match(/^(\d+(?:\.\d+)?)\s+out\s+of\s+5\s+(rating|diamonds?)$/i);
+  if (!match) return "";
+  return `${match[1]}钻`;
+};
+
+const normalizeDetailValue = (key: string, value: unknown): ReactNode => {
+  if (value === undefined || value === null || value === "") return "";
+  if (ZERO_MEANS_MISSING_KEYS.has(key) && Number(value) === 0) return "";
+  if (key === "ctrip_diamond_level") return normalizeCtripDiamondLevel(value);
+  if (value === true) return "是";
+  if (value === false) return "否";
+  if (typeof value === "string" || typeof value === "number") return value;
+  return JSON.stringify(value);
+};
+
+const enrichmentDetailItems = (
+  enrichment: Record<string, unknown> | undefined,
+  labels: Array<[string, string]>,
+) => labels
+  .map(([key, label]) => {
+    const value = normalizeDetailValue(key, enrichment?.[key]);
+    return {
+      key,
+      label,
+      children: value,
+    };
+  })
+  .filter((item) => item.children !== "");
+
+const splitDetailValues = (value: ReactNode) => String(value || "")
+  .split(/\s*[|｜]\s*/)
+  .map((item) => item.trim())
+  .filter(Boolean);
+
+const DetailSection = ({
+  title,
+  items,
+  accent = "#1677ff",
+  richList = false,
+}: {
+  title: string;
+  items: DetailItem[];
+  accent?: string;
+  richList?: boolean;
+}) => {
+  if (!items.length) return null;
+  return (
+    <section
+      style={{
+        width: "100%",
+        maxWidth: "100%",
+        minWidth: 0,
+        boxSizing: "border-box",
+        overflow: "hidden",
+        padding: "15px 16px",
+        border: "1px solid #e8edf3",
+        borderRadius: 12,
+        background: "#fff",
+        boxShadow: "0 2px 8px rgba(15, 23, 42, 0.04)",
+      }}
+    >
+      <div
+        style={{
+          display: "flex",
+          alignItems: "center",
+          gap: 8,
+          marginBottom: 12,
+          color: "#101828",
+          fontSize: 15,
+          fontWeight: 700,
+        }}
+      >
+        <span style={{ width: 4, height: 16, borderRadius: 99, background: accent }} />
+        {title}
+      </div>
+      <div style={{ display: "grid", gap: richList ? 10 : 8, width: "100%", minWidth: 0 }}>
+        {items.map((item) => {
+          const values = richList ? splitDetailValues(item.children) : [];
+          return (
+            <div
+              key={item.key}
+              style={{
+                display: "grid",
+                gridTemplateColumns: richList ? "1fr" : "104px minmax(0, 1fr)",
+                gap: richList ? 6 : 12,
+                width: "100%",
+                minWidth: 0,
+                boxSizing: "border-box",
+                alignItems: "start",
+                paddingBottom: 8,
+                borderBottom: "1px dashed #eef1f5",
+              }}
+            >
+              <div style={{ minWidth: 0, color: "#667085", fontSize: 12, lineHeight: 1.65 }}>
+                {item.label}
+              </div>
+              {richList ? (
+                <div style={{ display: "flex", flexWrap: "wrap", gap: 7, minWidth: 0 }}>
+                  {values.map((value) => (
+                    <Tag
+                      key={`${item.key}-${value}`}
+                      bordered={false}
+                      style={{
+                        maxWidth: "100%",
+                        margin: 0,
+                        padding: "3px 8px",
+                        color: "#344054",
+                        background: "#f2f4f7",
+                        whiteSpace: "normal",
+                        wordBreak: "break-word",
+                        overflowWrap: "anywhere",
+                      }}
+                    >
+                      {value}
+                    </Tag>
+                  ))}
+                </div>
+              ) : (
+                <div
+                  style={{
+                    minWidth: 0,
+                    color: "#1d2939",
+                    fontSize: 13,
+                    lineHeight: 1.65,
+                    wordBreak: "break-word",
+                    overflowWrap: "anywhere",
+                  }}
+                >
+                  {item.children}
+                </div>
+              )}
+            </div>
+          );
+        })}
+      </div>
+    </section>
+  );
+};
+
+const DetailMetricStrip = ({
+  items,
+  accent = "#1677ff",
+}: {
+  items: Array<{ key: string; label: string; value: ReactNode; note?: ReactNode }>;
+  accent?: string;
+}) => {
+  const visibleItems = items.filter((item) => item.value !== "");
+  if (!visibleItems.length) return null;
+  return (
+    <div
+      style={{
+        display: "grid",
+        gridTemplateColumns: `repeat(${Math.min(visibleItems.length, 3)}, minmax(0, 1fr))`,
+        gap: 8,
+        width: "100%",
+        maxWidth: "100%",
+        minWidth: 0,
+        boxSizing: "border-box",
+      }}
+    >
+      {visibleItems.map((item) => (
+        <div
+          key={item.key}
+          style={{
+            minWidth: 0,
+            boxSizing: "border-box",
+            overflow: "hidden",
+            padding: "10px 9px",
+            border: `1px solid ${accent}22`,
+            borderRadius: 10,
+            background: `${accent}0a`,
+          }}
+        >
+          <div
+            style={{
+              color: accent,
+              fontSize: 18,
+              fontWeight: 700,
+              lineHeight: 1.25,
+              overflowWrap: "anywhere",
+            }}
+          >
+            {item.value}
+          </div>
+          <div style={{ color: "#475467", fontSize: 11, marginTop: 3 }}>{item.label}</div>
+          {item.note && (
+            <div
+              style={{
+                color: "#667085",
+                fontSize: 11,
+                marginTop: 4,
+                overflow: "hidden",
+                textOverflow: "ellipsis",
+                whiteSpace: "nowrap",
+              }}
+            >
+              {item.note}
+            </div>
+          )}
+        </div>
+      ))}
+    </div>
+  );
+};
+
+const PlatformOverviewSection = ({
+  title,
+  accent,
+  metrics,
+  items,
+  titleIcon,
+}: {
+  title: string;
+  accent: string;
+  metrics: Array<{ key: string; label: string; value: ReactNode; note?: ReactNode }>;
+  items: DetailItem[];
+  titleIcon?: ReactNode;
+}) => {
+  const hasMetrics = metrics.some((item) => item.value !== "");
+  if (!hasMetrics && !items.length) return null;
+  return (
+    <section
+      style={{
+        width: "100%",
+        maxWidth: "100%",
+        minWidth: 0,
+        boxSizing: "border-box",
+        overflow: "hidden",
+        padding: "15px 16px",
+        border: "1px solid #e8edf3",
+        borderRadius: 12,
+        background: "#fff",
+        boxShadow: "0 2px 8px rgba(15, 23, 42, 0.04)",
+      }}
+    >
+      <div
+        style={{
+          display: "flex",
+          alignItems: "center",
+          gap: 8,
+          marginBottom: 12,
+          color: "#101828",
+          fontSize: 15,
+          fontWeight: 700,
+        }}
+      >
+        {titleIcon || (
+          <span style={{ width: 4, height: 16, borderRadius: 99, background: accent }} />
+        )}
+        {title}
+      </div>
+      <DetailMetricStrip items={metrics} accent={accent} />
+      {items.length > 0 && (
+        <div
+          style={{
+            display: "grid",
+            gap: 8,
+            width: "100%",
+            minWidth: 0,
+            marginTop: hasMetrics ? 14 : 0,
+          }}
+        >
+          {items.map((item) => (
+            <div
+              key={item.key}
+              style={{
+                display: "grid",
+                gridTemplateColumns: "132px minmax(0, 1fr)",
+                gap: 12,
+                width: "100%",
+                minWidth: 0,
+                boxSizing: "border-box",
+                alignItems: "center",
+                paddingBottom: 10,
+                borderBottom: "1px dashed #eef1f5",
+              }}
+            >
+              <div
+                style={{
+                  display: "flex",
+                  alignItems: "center",
+                  gap: 8,
+                  minWidth: 0,
+                  color: "#667085",
+                  fontSize: 12,
+                  lineHeight: 1.65,
+                }}
+              >
+                {item.icon && (
+                  <span
+                    style={{
+                      display: "inline-flex",
+                      alignItems: "center",
+                      justifyContent: "center",
+                      flex: "0 0 24px",
+                      width: 24,
+                      height: 24,
+                      borderRadius: 7,
+                      color: accent,
+                      background: `${accent}0d`,
+                      fontSize: 13,
+                    }}
+                  >
+                    {item.icon}
+                  </span>
+                )}
+                {item.label}
+              </div>
+              <div
+                style={{
+                  minWidth: 0,
+                  color: "#1d2939",
+                  fontSize: 13,
+                  fontWeight: 500,
+                  lineHeight: 1.65,
+                  wordBreak: "break-word",
+                  overflowWrap: "anywhere",
+                }}
+              >
+                {item.children}
+              </div>
+            </div>
+          ))}
+        </div>
+      )}
+    </section>
+  );
+};
+
+const PolicySection = ({
+  items,
+}: {
+  items: DetailItem[];
+}) => {
+  const policies = items.flatMap((item) => splitDetailValues(item.children))
+    .map((item, index) => {
+      const separator = item.indexOf("：");
+      if (separator <= 0) {
+        return { key: `policy-${index}`, label: "说明", value: item };
+      }
+      return {
+        key: `policy-${index}`,
+        label: item.slice(0, separator).trim(),
+        value: item.slice(separator + 1).trim(),
+      };
+    })
+    .filter((item) => item.value);
+  if (!policies.length) return null;
+  return (
+    <section
+      style={{
+        width: "100%",
+        maxWidth: "100%",
+        minWidth: 0,
+        boxSizing: "border-box",
+        overflow: "hidden",
+        padding: "15px 16px",
+        border: "1px solid #e8edf3",
+        borderRadius: 12,
+        background: "#fff",
+        boxShadow: "0 2px 8px rgba(15, 23, 42, 0.04)",
+      }}
+    >
+      <div style={{ display: "flex", alignItems: "center", gap: 8, marginBottom: 12, fontSize: 15, fontWeight: 700 }}>
+        <span style={{ width: 4, height: 16, borderRadius: 99, background: "#722ed1" }} />
+        酒店政策
+      </div>
+      <div style={{ display: "grid", gap: 10, width: "100%", minWidth: 0 }}>
+        {policies.map((policy) => (
+          <div
+            key={policy.key}
+            style={{
+              display: "grid",
+              gridTemplateColumns: "86px minmax(0, 1fr)",
+              gap: 12,
+              width: "100%",
+              minWidth: 0,
+              boxSizing: "border-box",
+              paddingBottom: 10,
+              borderBottom: "1px dashed #eef1f5",
+            }}
+          >
+            <div style={{ minWidth: 0, color: "#475467", fontSize: 12, fontWeight: 600, lineHeight: 1.7 }}>
+              {policy.label}
+            </div>
+            <div
+              style={{
+                minWidth: 0,
+                color: "#344054",
+                fontSize: 13,
+                lineHeight: 1.7,
+                wordBreak: "break-word",
+                overflowWrap: "anywhere",
+              }}
+            >
+              {policy.value}
+            </div>
+          </div>
+        ))}
+      </div>
+    </section>
+  );
+};
+
+type HotelRoomOffer = {
+  offer_id?: string;
+  breakfast?: string;
+  cancellation_policy?: string;
+  confirmation_policy?: string;
+  payment_method?: string;
+  occupancy?: number;
+  original_price?: number;
+  current_price?: number;
+};
+
+type HotelRoomItem = {
+  room_id: string;
+  name: string;
+  price?: number;
+  currency?: string;
+  image_url?: string;
+  room_url?: string;
+  bed_type?: string;
+  window?: string;
+  area?: string;
+  capacity?: number;
+  smoking_policy?: string;
+  network?: string;
+  offers?: HotelRoomOffer[];
+};
+
+type HotelReviewItem = {
+  review_id: string;
+  nickname?: string;
+  review_at?: string;
+  stay_at?: string;
+  room_type?: string;
+  travel_type?: string;
+  score?: number;
+  content: string;
+  like_count?: number;
+  image_count?: number;
+};
+
+const parseJsonArray = <T,>(value: unknown): T[] => {
+  if (!value) return [];
+  try {
+    const parsed = typeof value === "string" ? JSON.parse(value) : value;
+    return Array.isArray(parsed) ? parsed as T[] : [];
+  } catch {
+    return [];
+  }
+};
+
+const splitHotelTags = (...values: unknown[]) => [
+  ...new Set(values.flatMap((value) => String(value || "")
+    .split(/\s*[|｜、,，]\s*/)
+    .map((item) => item.trim())
+    .filter(Boolean))),
+];
+
+const HotelRoomSection = ({
+  rooms,
+}: {
+  rooms: HotelRoomItem[];
+}) => (
+  <section
+    style={{
+      width: "100%",
+      maxWidth: "100%",
+      minWidth: 0,
+      boxSizing: "border-box",
+      overflow: "hidden",
+      padding: "15px 16px",
+      border: "1px solid #e8edf3",
+      borderRadius: 12,
+      background: "#fff",
+      boxShadow: "0 2px 8px rgba(15, 23, 42, 0.04)",
+    }}
+  >
+    <div
+      style={{
+        display: "flex",
+        alignItems: "center",
+        justifyContent: "space-between",
+        gap: 8,
+        marginBottom: 12,
+      }}
+    >
+      <div style={{ display: "flex", alignItems: "center", gap: 8, color: "#101828", fontSize: 15, fontWeight: 700 }}>
+        <span style={{ width: 4, height: 16, borderRadius: 99, background: "#722ed1" }} />
+        房型与价格
+      </div>
+      {rooms.length > 0 && <Tag style={{ margin: 0 }}>{rooms.length} 个房型</Tag>}
+    </div>
+    {rooms.length === 0 ? (
+      <Alert
+        type="info"
+        showIcon
+        message="房型信息待补充"
+        description="当前酒店尚未采集到可用房型、床型和售卖方案数据。"
+      />
+    ) : (
+      <div
+        style={{
+          display: "grid",
+          gap: 10,
+          width: "100%",
+          minWidth: 0,
+          maxHeight: 520,
+          overflowY: "auto",
+          paddingRight: 2,
+        }}
+      >
+        {rooms.map((room) => {
+          const bestOffer = room.offers?.find((offer) => offer.current_price);
+          const displayPrice = bestOffer?.current_price || room.price;
+          const meta = [
+            room.bed_type,
+            room.area,
+            room.window,
+            room.capacity ? `可住${room.capacity}人` : "",
+          ].filter(Boolean);
+          const policies = [
+            bestOffer?.breakfast,
+            bestOffer?.cancellation_policy,
+            bestOffer?.confirmation_policy,
+            bestOffer?.payment_method,
+          ].filter(Boolean);
+          return (
+            <article
+              key={room.room_id}
+              style={{
+                display: "grid",
+                gridTemplateColumns: room.image_url ? "96px minmax(0, 1fr)" : "minmax(0, 1fr)",
+                gap: 10,
+                alignItems: "start",
+                minWidth: 0,
+                padding: 12,
+                border: "1px solid #ebe5f7",
+                borderRadius: 10,
+                background: "#fcfaff",
+              }}
+            >
+              {room.image_url && (
+                <Image
+                  src={room.image_url}
+                  alt={`${room.name} 房间图片`}
+                  width={96}
+                  height={76}
+                  style={{
+                    display: "block",
+                    width: 96,
+                    height: 76,
+                    objectFit: "cover",
+                    borderRadius: 8,
+                  }}
+                />
+              )}
+              <div
+                style={{
+                  display: "grid",
+                  gap: 8,
+                  minWidth: 0,
+                }}
+              >
+                <div
+                  style={{
+                    display: "grid",
+                    gridTemplateColumns: "minmax(0, 1fr) auto",
+                    gap: 10,
+                    alignItems: "start",
+                    minWidth: 0,
+                  }}
+                >
+                  <div style={{ minWidth: 0 }}>
+                    <div style={{ color: "#1d2939", fontSize: 13, fontWeight: 700, lineHeight: 1.5 }}>
+                      {room.name}
+                    </div>
+                    {meta.length > 0 && (
+                      <div style={{ color: "#667085", fontSize: 11, lineHeight: 1.6, marginTop: 3 }}>
+                        {meta.join(" · ")}
+                      </div>
+                    )}
+                  </div>
+                  <div style={{ color: "#722ed1", fontSize: 16, fontWeight: 700, whiteSpace: "nowrap" }}>
+                    {displayPrice ? `¥${displayPrice} 起` : "价格待补"}
+                  </div>
+                </div>
+                {policies.length > 0 && (
+                  <div style={{ display: "flex", flexWrap: "wrap", gap: 6, minWidth: 0 }}>
+                    {policies.slice(0, 4).map((policy) => (
+                      <Tag
+                        key={policy}
+                        bordered={false}
+                        style={{
+                          flex: "0 0 auto",
+                          maxWidth: "100%",
+                          margin: 0,
+                          overflow: "hidden",
+                          textOverflow: "ellipsis",
+                          whiteSpace: "nowrap",
+                          color: "#475467",
+                          background: "#f2f4f7",
+                        }}
+                      >
+                        {policy}
+                      </Tag>
+                    ))}
+                  </div>
+                )}
+              </div>
+            </article>
+          );
+        })}
+      </div>
+    )}
+  </section>
+);
+
+const HotelReviewSection = ({
+  tags,
+  reviews,
+}: {
+  tags: string[];
+  reviews: HotelReviewItem[];
+}) => {
+  const visibleTags = tags.slice(0, 4);
+  const hiddenTags = tags.slice(4);
+  return (
+    <section
+      style={{
+        width: "100%",
+        maxWidth: "100%",
+        minWidth: 0,
+        boxSizing: "border-box",
+        overflow: "hidden",
+        padding: "15px 16px",
+        border: "1px solid #e8edf3",
+        borderRadius: 12,
+        background: "#fff",
+        boxShadow: "0 2px 8px rgba(15, 23, 42, 0.04)",
+      }}
+    >
+      <div style={{ display: "flex", alignItems: "center", gap: 8, marginBottom: 12, fontSize: 15, fontWeight: 700 }}>
+        <span style={{ width: 4, height: 16, borderRadius: 99, background: "#722ed1" }} />
+        住客评价摘要
+      </div>
+      {tags.length === 0 && reviews.length === 0 ? (
+        <Alert type="info" showIcon message="住客评价待补充" />
+      ) : (
+        <div style={{ display: "grid", gap: 12, minWidth: 0 }}>
+          {tags.length > 0 && (
+            <div
+              style={{
+                display: "grid",
+                gridTemplateColumns: "64px minmax(0, 1fr)",
+                gap: 8,
+                alignItems: "center",
+                minWidth: 0,
+              }}
+            >
+              <span style={{ color: "#667085", fontSize: 12 }}>点评标签</span>
+              <div style={{ display: "flex", gap: 6, minWidth: 0, overflow: "hidden", whiteSpace: "nowrap" }}>
+                {visibleTags.map((tag) => (
+                  <Tag key={tag} bordered={false} style={{ flex: "0 0 auto", margin: 0, color: "#722ed1", background: "#f7f1ff" }}>
+                    {tag}
+                  </Tag>
+                ))}
+                {hiddenTags.length > 0 && (
+                  <Tooltip title={tags.join("、")}>
+                    <Tag bordered={false} style={{ flex: "0 0 auto", margin: 0, cursor: "help" }}>……</Tag>
+                  </Tooltip>
+                )}
+              </div>
+            </div>
+          )}
+          {reviews.slice(0, 3).map((review) => (
+            <article
+              key={review.review_id}
+              style={{
+                display: "grid",
+                gap: 6,
+                minWidth: 0,
+                paddingTop: 10,
+                borderTop: "1px dashed #eef1f5",
+              }}
+            >
+              <div style={{ display: "flex", justifyContent: "space-between", gap: 10, minWidth: 0 }}>
+                <div style={{ minWidth: 0, color: "#344054", fontSize: 12, fontWeight: 600 }}>
+                  {review.nickname || "匿名用户"}
+                  {review.travel_type ? ` · ${review.travel_type}` : ""}
+                </div>
+                {review.score ? (
+                  <span style={{ flex: "0 0 auto", color: "#722ed1", fontSize: 12, fontWeight: 700 }}>
+                    {review.score} 分
+                  </span>
+                ) : null}
+              </div>
+              <Tooltip title={review.content}>
+                <div
+                  style={{
+                    minWidth: 0,
+                    color: "#475467",
+                    fontSize: 12,
+                    lineHeight: 1.65,
+                    display: "-webkit-box",
+                    WebkitLineClamp: 3,
+                    WebkitBoxOrient: "vertical",
+                    overflow: "hidden",
+                    cursor: "default",
+                  }}
+                >
+                  {review.content}
+                </div>
+              </Tooltip>
+              {(review.room_type || review.review_at) && (
+                <div style={{ color: "#98a2b3", fontSize: 11, lineHeight: 1.5 }}>
+                  {[review.room_type, review.review_at?.slice(0, 10)].filter(Boolean).join(" · ")}
+                </div>
+              )}
+            </article>
+          ))}
+        </div>
+      )}
+    </section>
+  );
+};
+
+type FoodGroupBuyItem = {
+  deal_id: string;
+  title: string;
+  price?: number;
+  original_price?: number;
+  discount?: string;
+  terms?: string[];
+  image_url?: string;
+};
+
+type FoodReviewItem = {
+  review_id: string;
+  nickname?: string;
+  review_at?: string;
+  rating_label?: string;
+  stars?: number;
+  content: string;
+  image_urls?: string[];
+  image_count?: number;
+};
+
+type FoodReviewTag = {
+  label: string;
+  count?: number;
+};
+
+const FoodGroupBuySection = ({
+  deals,
+}: {
+  deals: FoodGroupBuyItem[];
+}) => {
+  if (!deals.length) return null;
+  return (
+    <section
+      style={{
+        width: "100%",
+        maxWidth: "100%",
+        minWidth: 0,
+        boxSizing: "border-box",
+        overflow: "hidden",
+        padding: "15px 16px",
+        border: "1px solid #e8edf3",
+        borderRadius: 12,
+        background: "#fff",
+        boxShadow: "0 2px 8px rgba(15, 23, 42, 0.04)",
+      }}
+    >
+      <div
+        style={{
+          display: "flex",
+          alignItems: "center",
+          gap: 8,
+          marginBottom: 12,
+          color: "#101828",
+          fontSize: 15,
+          fontWeight: 700,
+        }}
+      >
+        <span
+          style={{
+            display: "inline-flex",
+            alignItems: "center",
+            justifyContent: "center",
+            width: 24,
+            height: 24,
+            borderRadius: 7,
+            color: "#fff",
+            background: "#ff4d22",
+          }}
+        >
+          <ShoppingOutlined />
+        </span>
+        团购套餐
+      </div>
+      <div
+        style={{
+          display: "grid",
+          gap: 10,
+          width: "100%",
+          minWidth: 0,
+          maxHeight: 430,
+          overflowY: "auto",
+          paddingRight: 2,
+        }}
+      >
+        {deals.map((deal) => (
+          <article
+            key={deal.deal_id}
+            style={{
+              display: "grid",
+              gridTemplateColumns: deal.image_url ? "96px minmax(0, 1fr)" : "minmax(0, 1fr)",
+              gap: 12,
+              alignItems: "stretch",
+              minWidth: 0,
+              padding: 10,
+              border: "1px solid #ffe1d8",
+              borderRadius: 10,
+              background: "#fffdfc",
+            }}
+          >
+            {deal.image_url && (
+              <Image
+                src={deal.image_url}
+                alt={`${deal.title} 图片`}
+                width={96}
+                height={90}
+                preview={false}
+                style={{
+                  display: "block",
+                  width: 96,
+                  height: 90,
+                  objectFit: "cover",
+                  borderRadius: 8,
+                }}
+              />
+            )}
+            <div
+              style={{
+                display: "grid",
+                gridTemplateRows: "auto auto 1fr",
+                gap: 7,
+                minWidth: 0,
+              }}
+            >
+              <div
+                style={{
+                  minWidth: 0,
+                  color: "#1d2939",
+                  fontSize: 13,
+                  fontWeight: 700,
+                  lineHeight: 1.5,
+                  display: "-webkit-box",
+                  WebkitLineClamp: 2,
+                  WebkitBoxOrient: "vertical",
+                  overflow: "hidden",
+                }}
+              >
+                {deal.title}
+              </div>
+              {deal.terms?.length ? (
+                <div
+                  style={{
+                    minWidth: 0,
+                    color: "#667085",
+                    fontSize: 11,
+                    lineHeight: 1.5,
+                    whiteSpace: "nowrap",
+                    overflow: "hidden",
+                    textOverflow: "ellipsis",
+                  }}
+                >
+                  {deal.terms.join(" · ")}
+                </div>
+              ) : null}
+              <div style={{ display: "flex", alignItems: "end", gap: 7, alignSelf: "end", minWidth: 0 }}>
+                {deal.price !== undefined && (
+                  <span style={{ color: "#ff4d22", fontSize: 18, fontWeight: 750, whiteSpace: "nowrap" }}>
+                    ¥{deal.price}
+                  </span>
+                )}
+                {deal.discount && (
+                  <Tag
+                    bordered
+                    style={{
+                      margin: "0 0 2px",
+                      paddingInline: 5,
+                      color: "#ff4d22",
+                      borderColor: "#ff4d22",
+                      background: "#fff",
+                      lineHeight: "18px",
+                    }}
+                  >
+                    {deal.discount}
+                  </Tag>
+                )}
+                {deal.original_price !== undefined && (
+                  <span
+                    style={{
+                      marginBottom: 3,
+                      color: "#98a2b3",
+                      fontSize: 11,
+                      textDecoration: "line-through",
+                      whiteSpace: "nowrap",
+                    }}
+                  >
+                    ¥{deal.original_price}
+                  </span>
+                )}
+              </div>
+            </div>
+          </article>
+        ))}
+      </div>
+    </section>
+  );
+};
+
+const FoodReviewSection = ({
+  tags,
+  reviews,
+}: {
+  tags: FoodReviewTag[];
+  reviews: FoodReviewItem[];
+}) => {
+  if (!tags.length && !reviews.length) return null;
+  return (
+    <section
+      style={{
+        width: "100%",
+        maxWidth: "100%",
+        minWidth: 0,
+        boxSizing: "border-box",
+        overflow: "hidden",
+        padding: "15px 16px",
+        border: "1px solid #e8edf3",
+        borderRadius: 12,
+        background: "#fff",
+        boxShadow: "0 2px 8px rgba(15, 23, 42, 0.04)",
+      }}
+    >
+      <div
+        style={{
+          display: "flex",
+          alignItems: "center",
+          gap: 8,
+          marginBottom: 12,
+          color: "#101828",
+          fontSize: 15,
+          fontWeight: 700,
+        }}
+      >
+        <span style={{ width: 4, height: 16, borderRadius: 99, background: "#fa541c" }} />
+        用户评价摘要
+      </div>
+      {tags.length > 0 && (
+        <div style={{ display: "flex", flexWrap: "wrap", gap: 7, minWidth: 0, marginBottom: 6 }}>
+          {tags.slice(0, 10).map((tag) => (
+            <Tag
+              key={tag.label}
+              bordered={false}
+              style={{
+                margin: 0,
+                padding: "4px 9px",
+                color: "#5c4033",
+                background: "#fff5f0",
+                borderRadius: 999,
+                whiteSpace: "normal",
+              }}
+            >
+              {tag.label}
+              {tag.count ? <span style={{ marginLeft: 5, color: "#98a2b3" }}>{tag.count}</span> : null}
+            </Tag>
+          ))}
+        </div>
+      )}
+      <div style={{ display: "grid", gap: 0, minWidth: 0 }}>
+        {reviews.slice(0, 5).map((review) => (
+          <article
+            key={review.review_id}
+            style={{
+              display: "grid",
+              gap: 7,
+              minWidth: 0,
+              padding: "12px 0",
+              borderTop: "1px dashed #eef1f5",
+            }}
+          >
+            <div
+              style={{
+                display: "flex",
+                justifyContent: "space-between",
+                alignItems: "center",
+                gap: 10,
+                minWidth: 0,
+              }}
+            >
+              <div
+                style={{
+                  display: "flex",
+                  alignItems: "center",
+                  gap: 7,
+                  minWidth: 0,
+                  color: "#344054",
+                  fontSize: 12,
+                  fontWeight: 650,
+                }}
+              >
+                <span
+                  style={{
+                    display: "inline-flex",
+                    alignItems: "center",
+                    justifyContent: "center",
+                    flex: "0 0 24px",
+                    width: 24,
+                    height: 24,
+                    borderRadius: "50%",
+                    color: "#fa541c",
+                    background: "#fff2e8",
+                  }}
+                >
+                  <CommentOutlined />
+                </span>
+                <span style={{ minWidth: 0, overflow: "hidden", textOverflow: "ellipsis", whiteSpace: "nowrap" }}>
+                  {review.nickname || "匿名用户"}
+                </span>
+              </div>
+              <span style={{ flex: "0 0 auto", color: "#98a2b3", fontSize: 11 }}>
+                {review.review_at}
+              </span>
+            </div>
+            {(review.rating_label || review.stars) && (
+              <div style={{ color: "#fa541c", fontSize: 11, lineHeight: 1.4 }}>
+                {[review.rating_label, review.stars ? `${review.stars} 星` : ""].filter(Boolean).join(" · ")}
+              </div>
+            )}
+            <Tooltip title={review.content}>
+              <div
+                style={{
+                  minWidth: 0,
+                  color: "#344054",
+                  fontSize: 12,
+                  lineHeight: 1.65,
+                  display: "-webkit-box",
+                  WebkitLineClamp: 4,
+                  WebkitBoxOrient: "vertical",
+                  overflow: "hidden",
+                }}
+              >
+                {review.content}
+              </div>
+            </Tooltip>
+          </article>
+        ))}
+      </div>
+    </section>
+  );
+};
+
+type NearbyPlaceItem = {
+  name: string;
+  distance: string;
+  travel_time?: string;
+};
+
+type NearbyPlaceCategory = {
+  category: string;
+  items: NearbyPlaceItem[];
+};
+
+const nearbyCategoryIcon = (category: string) => {
+  if (category === "交通") return <CarOutlined />;
+  if (category === "景点") return <EnvironmentOutlined />;
+  if (category === "美食") return <CoffeeOutlined />;
+  return <ShoppingOutlined />;
+};
+
+const parseNearbyPlaceCategories = (value: unknown): NearbyPlaceCategory[] => {
+  if (!value) return [];
+  try {
+    const parsed = typeof value === "string" ? JSON.parse(value) : value;
+    if (!parsed || typeof parsed !== "object" || Array.isArray(parsed)) return [];
+    return ["交通", "景点", "美食", "购物"].flatMap((category) => {
+      const rawItems = (parsed as Record<string, unknown>)[category];
+      if (!Array.isArray(rawItems)) return [];
+      const items = rawItems.flatMap((item) => {
+        if (!item || typeof item !== "object") return [];
+        const record = item as Record<string, unknown>;
+        const name = String(record.name || "").trim();
+        if (!name) return [];
+        return [{
+          name,
+          distance: String(record.distance || "").trim(),
+          travel_time: String(record.travel_time || "").trim(),
+        }];
+      });
+      return items.length ? [{ category, items }] : [];
+    });
+  } catch {
+    return [];
+  }
+};
+
+const NearbyCategorySection = ({
+  categories,
+}: {
+  categories: NearbyPlaceCategory[];
+}) => {
+  if (!categories.length) return null;
+  return (
+    <section
+      style={{
+        width: "100%",
+        maxWidth: "100%",
+        minWidth: 0,
+        boxSizing: "border-box",
+        overflow: "hidden",
+        padding: "15px 16px",
+        border: "1px solid #e8edf3",
+        borderRadius: 12,
+        background: "#fff",
+        boxShadow: "0 2px 8px rgba(15, 23, 42, 0.04)",
+      }}
+    >
+      <div style={{ display: "flex", alignItems: "center", gap: 8, marginBottom: 5, fontSize: 15, fontWeight: 700 }}>
+        <span style={{ width: 4, height: 16, borderRadius: 99, background: "#722ed1" }} />
+        周边地点
+      </div>
+      <Tabs
+        size="small"
+        tabBarGutter={16}
+        style={{ width: "100%", maxWidth: "100%", minWidth: 0 }}
+        items={categories.map(({ category, items }) => ({
+          key: category,
+          label: (
+            <Space size={5}>
+              {nearbyCategoryIcon(category)}
+              <span>{category}</span>
+              <span style={{ color: "#98a2b3", fontSize: 11 }}>{items.length}</span>
+            </Space>
+          ),
+          children: (
+            <div style={{ display: "grid", gap: 0, width: "100%", minWidth: 0 }}>
+              {items.map((item, index) => (
+                <div
+                  key={`${category}-${item.name}-${index}`}
+                  style={{
+                    display: "grid",
+                    gridTemplateColumns: category === "交通"
+                      ? "minmax(0, 1fr) max-content"
+                      : "minmax(0, 1fr) auto",
+                    gap: category === "交通" ? 16 : 12,
+                    width: "100%",
+                    minWidth: 0,
+                    boxSizing: "border-box",
+                    alignItems: "center",
+                    padding: "9px 0",
+                    borderBottom: index === items.length - 1 ? "none" : "1px dashed #eef1f5",
+                  }}
+                >
+                  <div
+                    style={{
+                      display: "flex",
+                      alignItems: "center",
+                      gap: 7,
+                      minWidth: 0,
+                      color: "#1d2939",
+                      fontSize: 13,
+                      lineHeight: 1.5,
+                    }}
+                  >
+                    <span style={{ color: "#722ed1", marginTop: 1 }}>{nearbyCategoryIcon(category)}</span>
+                    <span style={{ minWidth: 0, wordBreak: "break-word", overflowWrap: "anywhere" }}>
+                      {item.name}
+                    </span>
+                  </div>
+                  <div
+                    style={{
+                      maxWidth: category === "交通" ? "none" : 148,
+                      minWidth: 0,
+                      color: "#667085",
+                      fontSize: 12,
+                      lineHeight: 1.5,
+                      textAlign: "right",
+                      justifySelf: "end",
+                      whiteSpace: category === "交通" ? "nowrap" : "normal",
+                      wordBreak: category === "交通" ? "normal" : "break-word",
+                    }}
+                  >
+                    {item.distance || item.travel_time || "距离待补"}
+                  </div>
+                </div>
+              ))}
+            </div>
+          ),
+        }))}
+      />
+    </section>
+  );
+};
+
+type HotelFacilityItem = {
+  name: string;
+  fee: string;
+  description: string;
+  source_url: string;
+};
+
+type HotelFacilityCategory = {
+  category: string;
+  items: HotelFacilityItem[];
+};
+
+type HotelFacilityImage = {
+  url: string;
+  source_url: string;
+};
+
+type HotelFacilityPayload = {
+  categories: HotelFacilityCategory[];
+  images: HotelFacilityImage[];
+};
+
+const HOTEL_FACILITY_CATEGORY_ORDER = [
+  "热门设施",
+  "康体设施",
+  "交通服务",
+  "餐饮服务",
+  "娱乐活动设施",
+  "前台服务",
+  "公共区",
+  "儿童设施服务",
+  "商务服务",
+  "清洁服务",
+  "安全与安保",
+  "无障碍设施服务",
+  "网络与通讯",
+  "房型特色",
+  "设施服务",
+  "更多设施",
+];
+
+const hotelFacilityCategoryIcon = (category: string) => {
+  if (category === "热门设施") return <ThunderboltOutlined />;
+  if (category === "康体设施") return <FireOutlined />;
+  if (category === "交通服务") return <CarOutlined />;
+  if (category === "餐饮服务") return <CoffeeOutlined />;
+  if (category === "娱乐活动设施") return <PlayCircleOutlined />;
+  if (category === "前台服务") return <CustomerServiceOutlined />;
+  if (category === "公共区") return <AppstoreOutlined />;
+  if (category === "儿童设施服务") return <SmileOutlined />;
+  if (category === "商务服务") return <SolutionOutlined />;
+  if (category === "清洁服务") return <ClearOutlined />;
+  if (category === "安全与安保") return <SafetyCertificateOutlined />;
+  if (category === "网络与通讯") return <WifiOutlined />;
+  if (category === "房型特色") return <HomeOutlined />;
+  return <AppstoreOutlined />;
+};
+
+const parseHotelFacilityPayload = (value: unknown): HotelFacilityPayload => {
+  const emptyPayload = { categories: [], images: [] };
+  if (!value) return emptyPayload;
+  try {
+    const parsed = typeof value === "string" ? JSON.parse(value) : value;
+    if (!parsed || typeof parsed !== "object" || Array.isArray(parsed)) return emptyPayload;
+    const record = parsed as Record<string, unknown>;
+    const rawCategories = record.categories;
+    const categoryRecord = rawCategories && typeof rawCategories === "object" && !Array.isArray(rawCategories)
+      ? rawCategories as Record<string, unknown>
+      : {};
+    const categoryRank = new Map(
+      HOTEL_FACILITY_CATEGORY_ORDER.map((category, index) => [category, index]),
+    );
+    const categories = Object.entries(categoryRecord)
+      .flatMap(([category, rawItems]) => {
+        if (!Array.isArray(rawItems)) return [];
+        const items = rawItems.flatMap((item) => {
+          if (!item || typeof item !== "object") return [];
+          const facility = item as Record<string, unknown>;
+          const name = String(facility.name || "").trim();
+          if (!name) return [];
+          return [{
+            name,
+            fee: String(facility.fee || "").trim(),
+            description: String(facility.description || "").trim(),
+            source_url: String(facility.source_url || "").trim(),
+          }];
+        });
+        return items.length ? [{ category, items }] : [];
+      })
+      .sort((left, right) => (
+        (categoryRank.get(left.category) ?? 999) - (categoryRank.get(right.category) ?? 999)
+        || left.category.localeCompare(right.category, "zh-CN")
+      ));
+    const images = (Array.isArray(record.images) ? record.images : []).flatMap((item) => {
+      if (!item || typeof item !== "object") return [];
+      const image = item as Record<string, unknown>;
+      const url = String(image.url || "").trim();
+      if (!url) return [];
+      return [{
+        url,
+        source_url: String(image.source_url || "").trim(),
+      }];
+    });
+    return { categories, images };
+  } catch {
+    return emptyPayload;
+  }
+};
+
+const HotelFacilitySection = ({
+  payload,
+}: {
+  payload: HotelFacilityPayload;
+}) => {
+  const [activeCategory, setActiveCategory] = useState(
+    payload.categories[0]?.category || "",
+  );
+  useEffect(() => {
+    if (!payload.categories.some((item) => item.category === activeCategory)) {
+      setActiveCategory(payload.categories[0]?.category || "");
+    }
+  }, [activeCategory, payload.categories]);
+  if (!payload.categories.length) return null;
+  const totalFacilities = payload.categories.reduce((sum, item) => sum + item.items.length, 0);
+  const selectedCategory = payload.categories.find((item) => item.category === activeCategory)
+    || payload.categories[0];
+  const selectedSourceUrl = selectedCategory.items.find((item) => item.source_url)?.source_url || "";
+  return (
+    <section
+      style={{
+        width: "100%",
+        maxWidth: "100%",
+        minWidth: 0,
+        boxSizing: "border-box",
+        overflow: "hidden",
+        padding: "15px 16px",
+        border: "1px solid #e8edf3",
+        borderRadius: 12,
+        background: "#fff",
+        boxShadow: "0 2px 8px rgba(15, 23, 42, 0.04)",
+      }}
+    >
+      <div style={{ display: "flex", alignItems: "center", justifyContent: "space-between", gap: 12 }}>
+        <div style={{ display: "flex", alignItems: "center", gap: 8, fontSize: 15, fontWeight: 700 }}>
+          <span style={{ width: 4, height: 16, borderRadius: 99, background: "#722ed1" }} />
+          服务及设施
+        </div>
+        <span style={{ color: "#98a2b3", fontSize: 11 }}>
+          {payload.categories.length} 类 · {totalFacilities} 项
+        </span>
+      </div>
+
+      {payload.images.length > 0 && (
+        <div style={{ marginTop: 12 }}>
+          <div style={{ display: "flex", alignItems: "center", gap: 6, marginBottom: 8, color: "#475467", fontSize: 12 }}>
+            <PictureOutlined style={{ color: "#722ed1" }} />
+            设施实拍
+          </div>
+          <Image.PreviewGroup>
+            <div
+              style={{
+                display: "flex",
+                gap: 8,
+                width: "100%",
+                maxWidth: "100%",
+                minWidth: 0,
+                overflowX: "auto",
+                paddingBottom: 5,
+                scrollSnapType: "x mandatory",
+                WebkitOverflowScrolling: "touch",
+                scrollbarWidth: "thin",
+              }}
+            >
+              {payload.images.slice(0, 3).map((image, index) => (
+                <div
+                  key={`${image.url}-${index}`}
+                  style={{
+                    position: "relative",
+                    flex: "0 0 178px",
+                    scrollSnapAlign: "start",
+                  }}
+                >
+                  <Image
+                    src={image.url}
+                    alt={`设施实拍${index + 1}`}
+                    width="100%"
+                    height={98}
+                    style={{ objectFit: "cover", borderRadius: 8 }}
+                  />
+                  <span
+                    style={{
+                      position: "absolute",
+                      left: 6,
+                      bottom: 7,
+                      padding: "2px 6px",
+                      borderRadius: 5,
+                      background: "rgba(16,24,40,.72)",
+                      color: "#fff",
+                      fontSize: 10,
+                      pointerEvents: "none",
+                    }}
+                  >
+                    设施实拍 {index + 1}
+                  </span>
+                </div>
+              ))}
+            </div>
+          </Image.PreviewGroup>
+        </div>
+      )}
+
+      <div
+        aria-label="酒店设施分类"
+        style={{
+          display: "flex",
+          gap: 7,
+          width: "100%",
+          maxWidth: "100%",
+          minWidth: 0,
+          boxSizing: "border-box",
+          margin: "12px -2px 0",
+          padding: "0 2px 7px",
+          overflowX: "auto",
+          scrollSnapType: "x proximity",
+          WebkitOverflowScrolling: "touch",
+          scrollbarWidth: "thin",
+        }}
+      >
+        {payload.categories.map(({ category, items }) => {
+          const selected = category === selectedCategory.category;
+          return (
+            <button
+              key={category}
+              type="button"
+              onClick={() => setActiveCategory(category)}
+              aria-pressed={selected}
+              style={{
+                display: "inline-flex",
+                alignItems: "center",
+                gap: 6,
+                flex: "0 0 auto",
+                minHeight: 34,
+                padding: "7px 10px",
+                border: `1px solid ${selected ? "#722ed1" : "#e4e7ec"}`,
+                borderRadius: 9,
+                background: selected ? "#f5f0ff" : "#fff",
+                color: selected ? "#722ed1" : "#475467",
+                fontSize: 12,
+                fontWeight: selected ? 650 : 500,
+                cursor: "pointer",
+                whiteSpace: "nowrap",
+                scrollSnapAlign: "start",
+              }}
+            >
+              {hotelFacilityCategoryIcon(category)}
+              <span>{category}</span>
+              <span
+                style={{
+                  minWidth: 18,
+                  padding: "0 5px",
+                  borderRadius: 99,
+                  background: selected ? "#722ed1" : "#f2f4f7",
+                  color: selected ? "#fff" : "#667085",
+                  fontSize: 10,
+                  lineHeight: "18px",
+                  textAlign: "center",
+                }}
+              >
+                {items.length}
+              </span>
+            </button>
+          );
+        })}
+      </div>
+
+      <div style={{ display: "grid", gap: 7, marginTop: 4 }}>
+        {selectedCategory.items.map((item, index) => (
+          <div
+            key={`${selectedCategory.category}-${item.name}-${index}`}
+            style={{
+              display: "grid",
+              gridTemplateColumns: "minmax(0, 1fr) auto",
+              gap: 10,
+              alignItems: "center",
+              width: "100%",
+              minWidth: 0,
+              boxSizing: "border-box",
+              padding: "9px 10px",
+              border: "1px solid #eef1f5",
+              borderRadius: 9,
+              background: "#fafbfc",
+            }}
+          >
+            <div style={{ display: "flex", alignItems: "flex-start", gap: 7, minWidth: 0 }}>
+              <CheckCircleOutlined style={{ marginTop: 2, color: "#722ed1", flex: "0 0 auto" }} />
+              <div style={{ minWidth: 0 }}>
+                <div style={{ color: "#1d2939", fontSize: 12, lineHeight: 1.5, wordBreak: "break-word" }}>
+                  {item.name}
+                </div>
+                {item.description && (
+                  <div style={{ color: "#667085", fontSize: 10, lineHeight: 1.5, marginTop: 2 }}>
+                    {item.description}
+                  </div>
+                )}
+              </div>
+            </div>
+            {item.fee && (
+              <Tag
+                bordered={false}
+                color={item.fee === "免费" ? "success" : "default"}
+                style={{ margin: 0, fontSize: 10, whiteSpace: "nowrap" }}
+              >
+                {item.fee}
+              </Tag>
+            )}
+          </div>
+        ))}
+      </div>
+      {selectedSourceUrl && (
+        <div style={{ display: "flex", justifyContent: "flex-end", marginTop: 9 }}>
+          <Button
+            type="link"
+            size="small"
+            icon={<LinkOutlined />}
+            href={selectedSourceUrl}
+            target="_blank"
+            rel="noreferrer"
+            style={{ height: "auto", padding: 0, fontSize: 11 }}
+          >
+            查看携程设施来源
+          </Button>
+        </div>
+      )}
+    </section>
+  );
+};
+
 type AMapCtor = any;
 
 declare global {
@@ -60,7 +1812,7 @@ const loadAmapSdk = (jsKey: string, securityJsCode?: string) => {
     const script = document.createElement("script");
     script.id = "amap-js-sdk";
     script.async = true;
-    script.src = `https://webapi.amap.com/maps?v=2.0&key=${encodeURIComponent(jsKey)}&plugin=AMap.Scale,AMap.ToolBar,AMap.DistrictSearch`;
+    script.src = `https://webapi.amap.com/maps?v=2.0&key=${encodeURIComponent(jsKey)}&plugin=AMap.Scale,AMap.ToolBar,AMap.DistrictSearch,AMap.MarkerCluster,AMap.LineSearch`;
     script.onload = () => resolve(window.AMap);
     script.onerror = () => reject(new Error("高德地图脚本加载失败"));
     document.head.appendChild(script);
@@ -80,23 +1832,136 @@ const GUIZHOU_CITIES = [
   { name: "黔西南", coord: [104.9064, 25.0878] },
 ];
 
-function GuizhouKnowledgeMap({ cov }: { cov: Cov | null }) {
+export function KnowledgeMap({
+  cov,
+  scope = "guizhou",
+}: {
+  cov: CoverageSnapshot | null;
+  scope?: "guizhou" | "libo";
+}) {
   const mapRef = useRef<HTMLDivElement | null>(null);
+  const mapShellRef = useRef<HTMLDivElement | null>(null);
   const mapInstance = useRef<AMapCtor | null>(null);
+  const amapRef = useRef<AMapCtor | null>(null);
+  const clusterRef = useRef<any>(null);
+  const busOverlaysRef = useRef<any[]>([]);
+  const infoWindowRef = useRef<any>(null);
+  const poiLookupRef = useRef<Map<string, MapPoi>>(new Map());
+  const poiOpenRef = useRef<(poi: MapPoi) => void>(() => undefined);
+  const busRouteOpenRef = useRef<(route: BusRoute) => void>(() => undefined);
+  const busStopOpenRef = useRef<(stop: BusStopNetwork) => void>(() => undefined);
+  const detailRequestRef = useRef(0);
+  const busPathRequestRef = useRef(0);
   const [mapStatus, setMapStatus] = useState<"loading" | "ready" | "error">("loading");
   const [mapMessage, setMapMessage] = useState("正在加载高德地图...");
-  const [isFullscreen, setIsFullscreen] = useState(false);
+  const [fullscreenMode, setFullscreenMode] = useState<FullscreenMode>("none");
+  const [mapPois, setMapPois] = useState<MapPoi[]>([]);
+  const [selectedCategories, setSelectedCategories] = useState<string[]>([]);
+  const [poiLoading, setPoiLoading] = useState(false);
+  const [poiError, setPoiError] = useState("");
+  const [selectedPoi, setSelectedPoi] = useState<MapPoi | null>(null);
+  const [poiDetail, setPoiDetail] = useState<MapPoiDetail | null>(null);
+  const [detailLoading, setDetailLoading] = useState(false);
+  const [busRoutes, setBusRoutes] = useState<BusRoute[]>([]);
+  const [busLayerVisible, setBusLayerVisible] = useState(true);
+  const [busLoading, setBusLoading] = useState(false);
+  const [busError, setBusError] = useState("");
+  const [busPanel, setBusPanel] = useState<BusPanel>(null);
+  const [focusedBusRouteId, setFocusedBusRouteId] = useState("");
+  const [focusedBusLineName, setFocusedBusLineName] = useState("");
+  const [resolvedBusPaths, setResolvedBusPaths] = useState<Record<string, number[][]>>({});
+  const isLibo = scope === "libo";
+  const isFullscreen = fullscreenMode !== "none";
 
-  const topCats = useMemo(() => (cov?.items || []).slice(0, 4), [cov]);
+  const poiCategories = useMemo(() => {
+    const counts = new Map<string, number>();
+    mapPois.forEach((poi) => {
+      (poi.categories?.length ? poi.categories : [poi.category]).forEach((category) => {
+        counts.set(category, (counts.get(category) || 0) + 1);
+      });
+    });
+    return [...counts.entries()]
+      .map(([category, count]) => ({ category, count }))
+      .sort((a, b) => b.count - a.count || a.category.localeCompare(b.category, "zh-CN"));
+  }, [mapPois]);
+  const topCats = useMemo(
+    () => isLibo
+      ? poiCategories.slice(0, 4).map((item) => ({ cat: item.category, current: item.count }))
+      : (cov?.items || []).slice(0, 4),
+    [cov, isLibo, poiCategories],
+  );
+  const visiblePois = useMemo(
+    () => mapPois.filter((poi) => (
+      poi.categories?.length ? poi.categories : [poi.category]
+    ).some((category) => selectedCategories.includes(category))),
+    [mapPois, selectedCategories],
+  );
+  const busLines = useMemo(
+    () => [...new Set(busRoutes.map((route) => route.line_name))]
+      .sort(new Intl.Collator("zh-CN", { numeric: true }).compare),
+    [busRoutes],
+  );
+  const busStopNetwork = useMemo(() => {
+    const stops = new Map<string, BusStopNetwork>();
+    busRoutes.forEach((route) => route.stops.forEach((stop) => {
+      const existing = stops.get(stop.stop_id);
+      if (existing) {
+        existing.routes.push(route);
+      } else {
+        stops.set(stop.stop_id, {
+          stop_id: stop.stop_id,
+          name: stop.name,
+          lng: stop.lng,
+          lat: stop.lat,
+          routes: [route],
+        });
+      }
+    }));
+    return stops;
+  }, [busRoutes]);
+  const focusedBusRoute = useMemo(
+    () => busRoutes.find((route) => route.route_id === focusedBusRouteId) || null,
+    [busRoutes, focusedBusRouteId],
+  );
+  const focusedBusLineRoutes = useMemo(
+    () => busRoutes.filter((route) => route.line_name === focusedBusLineName),
+    [busRoutes, focusedBusLineName],
+  );
+  const selectedBusLineRoutes = useMemo(
+    () => (
+      busPanel?.mode === "line"
+        ? busRoutes.filter((route) => route.line_name === busPanel.lineName)
+        : []
+    ),
+    [busPanel, busRoutes],
+  );
+  const selectedBusRoute = useMemo(
+    () => (
+      busPanel?.mode === "route"
+        ? busRoutes.find((route) => route.route_id === busPanel.routeId) || null
+        : null
+    ),
+    [busPanel, busRoutes],
+  );
+  const selectedBusStop = useMemo(
+    () => (
+      busPanel?.mode === "stop"
+        ? busStopNetwork.get(busPanel.stopId) || null
+        : null
+    ),
+    [busPanel, busStopNetwork],
+  );
 
   useEffect(() => {
     const timer = window.setTimeout(() => mapInstance.current?.resize?.(), 120);
-    if (!isFullscreen) return () => window.clearTimeout(timer);
+    if (fullscreenMode === "none") return () => window.clearTimeout(timer);
 
     const prevOverflow = document.body.style.overflow;
     document.body.style.overflow = "hidden";
     const onKeyDown = (e: KeyboardEvent) => {
-      if (e.key === "Escape") setIsFullscreen(false);
+      if (e.key === "Escape" && fullscreenMode === "fallback") {
+        setFullscreenMode("none");
+      }
     };
     window.addEventListener("keydown", onKeyDown);
     return () => {
@@ -104,7 +1969,234 @@ function GuizhouKnowledgeMap({ cov }: { cov: Cov | null }) {
       window.removeEventListener("keydown", onKeyDown);
       document.body.style.overflow = prevOverflow;
     };
-  }, [isFullscreen]);
+  }, [fullscreenMode]);
+
+  useEffect(() => {
+    const onFullscreenChange = () => {
+      const isMapFullscreen = document.fullscreenElement === mapShellRef.current;
+      setFullscreenMode((current) => {
+        if (isMapFullscreen) return "native";
+        return current === "native" ? "none" : current;
+      });
+      window.setTimeout(() => mapInstance.current?.resize?.(), 120);
+    };
+    document.addEventListener("fullscreenchange", onFullscreenChange);
+    return () => document.removeEventListener("fullscreenchange", onFullscreenChange);
+  }, []);
+
+  const toggleFullscreen = useCallback(async () => {
+    if (fullscreenMode === "native") {
+      await document.exitFullscreen?.();
+      return;
+    }
+    if (fullscreenMode === "fallback") {
+      setFullscreenMode("none");
+      return;
+    }
+    const shell = mapShellRef.current;
+    if (!shell) return;
+    try {
+      if (shell.requestFullscreen) {
+        await shell.requestFullscreen();
+        setFullscreenMode("native");
+      } else {
+        setFullscreenMode("fallback");
+      }
+    } catch {
+      setFullscreenMode("fallback");
+    }
+  }, [fullscreenMode]);
+
+  useEffect(() => {
+    if (!isLibo) {
+      setMapPois([]);
+      setSelectedCategories([]);
+      return;
+    }
+    let disposed = false;
+    setPoiLoading(true);
+    setPoiError("");
+    plazaMapPois()
+      .then(({ data }) => {
+        if (disposed) return;
+        const items = (data?.items || []) as MapPoi[];
+        setMapPois(items);
+        setSelectedCategories([
+          ...new Set(items.flatMap((item) => (
+            item.categories?.length ? item.categories : [item.category]
+          ))),
+        ]);
+      })
+      .catch((error: any) => {
+        if (disposed) return;
+        setPoiError(error?.response?.data?.detail || "POI点位加载失败");
+      })
+      .finally(() => {
+        if (!disposed) setPoiLoading(false);
+      });
+    return () => {
+      disposed = true;
+    };
+  }, [isLibo]);
+
+  useEffect(() => {
+    if (!isLibo) {
+      setBusRoutes([]);
+      setResolvedBusPaths({});
+      setFocusedBusLineName("");
+      return;
+    }
+    let disposed = false;
+    setBusLoading(true);
+    setBusError("");
+    plazaBusRoutes()
+      .then(({ data }) => {
+        if (disposed) return;
+        const items = (data?.items || []) as BusRoute[];
+        setBusRoutes(items);
+        const names = [...new Set(items.map((route) => route.line_name))];
+        setFocusedBusLineName((current) => (
+          current || (names.includes("荔波1路") ? "荔波1路" : names[0] || "")
+        ));
+      })
+      .catch((error: any) => {
+        if (disposed) return;
+        setBusError(error?.response?.data?.detail || "公交线路加载失败");
+      })
+      .finally(() => {
+        if (!disposed) setBusLoading(false);
+      });
+    return () => {
+      disposed = true;
+    };
+  }, [isLibo]);
+
+  const closePoiDetail = useCallback(() => {
+    detailRequestRef.current += 1;
+    setSelectedPoi(null);
+    setPoiDetail(null);
+    setDetailLoading(false);
+    infoWindowRef.current?.close?.();
+  }, []);
+
+  const openPoi = useCallback((poi: MapPoi) => {
+    const AMap = amapRef.current;
+    const map = mapInstance.current;
+    if (!AMap || !map) return;
+
+    setSelectedPoi(poi);
+    setPoiDetail(null);
+    const requestId = detailRequestRef.current + 1;
+    detailRequestRef.current = requestId;
+    setDetailLoading(true);
+
+    const card = document.createElement("div");
+    card.style.cssText = [
+      "min-width:220px",
+      "max-width:290px",
+      "padding:12px 14px",
+      "border:1px solid #d6e4ff",
+      "border-radius:10px",
+      "background:rgba(255,255,255,.98)",
+      "box-shadow:0 10px 30px rgba(15,23,42,.18)",
+      "font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',sans-serif",
+    ].join(";");
+    const title = document.createElement("div");
+    title.textContent = poi.name;
+    title.style.cssText = "font-size:14px;font-weight:700;color:#1f2329;line-height:1.4";
+    const meta = document.createElement("div");
+    meta.textContent = `${poi.category}${poi.address ? ` · ${poi.address}` : ""}`;
+    meta.style.cssText = "margin-top:6px;font-size:12px;color:#667085;line-height:1.5";
+    const hint = document.createElement("div");
+    hint.textContent = "详细资料已在右侧面板打开";
+    hint.style.cssText = "margin-top:8px;font-size:12px;color:#1677ff";
+    card.append(title, meta, hint);
+
+    infoWindowRef.current?.close?.();
+    infoWindowRef.current = new AMap.InfoWindow({
+      isCustom: true,
+      content: card,
+      anchor: "bottom-center",
+      offset: new AMap.Pixel(0, -12),
+    });
+    infoWindowRef.current.open(map, [poi.lng, poi.lat]);
+
+    plazaMapPoiDetail(poi.id)
+      .then(({ data }) => {
+        if (detailRequestRef.current === requestId) {
+          setPoiDetail(data as MapPoiDetail);
+        }
+      })
+      .catch((error: any) => {
+        if (detailRequestRef.current === requestId) {
+          message.error(error?.response?.data?.detail || "POI详情加载失败");
+        }
+      })
+      .finally(() => {
+        if (detailRequestRef.current === requestId) {
+          setDetailLoading(false);
+        }
+      });
+  }, []);
+  poiOpenRef.current = openPoi;
+
+  const closeBusPanel = useCallback(() => {
+    setBusPanel(null);
+    setFocusedBusRouteId("");
+    infoWindowRef.current?.close?.();
+  }, []);
+
+  const openBusLine = useCallback((lineName: string) => {
+    closePoiDetail();
+    setBusLayerVisible(true);
+    setFocusedBusRouteId("");
+    setFocusedBusLineName(lineName);
+    setBusPanel({ mode: "line", lineName });
+  }, [closePoiDetail]);
+
+  const openBusRoute = useCallback((route: BusRoute) => {
+    closePoiDetail();
+    setBusLayerVisible(true);
+    setFocusedBusLineName(route.line_name);
+    setFocusedBusRouteId(route.route_id);
+    setBusPanel({ mode: "route", routeId: route.route_id });
+  }, [closePoiDetail]);
+  busRouteOpenRef.current = openBusRoute;
+
+  const openBusStop = useCallback((stop: BusStopNetwork) => {
+    const AMap = amapRef.current;
+    const map = mapInstance.current;
+    closePoiDetail();
+    setBusPanel({ mode: "stop", stopId: stop.stop_id });
+
+    if (!AMap || !map) return;
+    const card = document.createElement("div");
+    card.style.cssText = [
+      "min-width:220px",
+      "padding:12px 14px",
+      "border:1px solid #87e8de",
+      "border-radius:10px",
+      "background:rgba(255,255,255,.98)",
+      "box-shadow:0 10px 30px rgba(15,23,42,.18)",
+      "font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',sans-serif",
+    ].join(";");
+    const title = document.createElement("div");
+    title.textContent = `${stop.name}（公交站）`;
+    title.style.cssText = "font-size:14px;font-weight:700;color:#1f2329";
+    const lines = document.createElement("div");
+    lines.textContent = `途经 ${[...new Set(stop.routes.map((route) => route.line_name))].join("、")}`;
+    lines.style.cssText = "margin-top:6px;font-size:12px;color:#667085";
+    card.append(title, lines);
+    infoWindowRef.current?.close?.();
+    infoWindowRef.current = new AMap.InfoWindow({
+      isCustom: true,
+      content: card,
+      anchor: "bottom-center",
+      offset: new AMap.Pixel(0, -16),
+    });
+    infoWindowRef.current.open(map, [stop.lng, stop.lat]);
+  }, [closePoiDetail]);
+  busStopOpenRef.current = openBusStop;
 
   useEffect(() => {
     let disposed = false;
@@ -116,16 +2208,17 @@ function GuizhouKnowledgeMap({ cov }: { cov: Cov | null }) {
         const { data } = await plazaAmapConfig();
         if (!data?.configured || !data?.js_key) {
           setMapStatus("error");
-          setMapMessage("高德 JS API Key 未配置，无法加载贵州省地图。");
+          setMapMessage(`高德 JS API Key 未配置，无法加载${isLibo ? "荔波县" : "贵州省"}地图。`);
           return;
         }
         const AMap = await loadAmapSdk(data.js_key, data.security_jscode);
         if (disposed || !mapRef.current || !AMap) return;
 
+        amapRef.current = AMap;
         mapInstance.current?.destroy?.();
         const map = new AMap.Map(mapRef.current, {
-          center: [106.7135, 26.5783],
-          zoom: 7.2,
+          center: isLibo ? [107.88057, 25.402528] : [106.7135, 26.5783],
+          zoom: isLibo ? 10 : 7.2,
           viewMode: "2D",
           resizeEnable: true,
           mapStyle: "amap://styles/normal",
@@ -137,65 +2230,115 @@ function GuizhouKnowledgeMap({ cov }: { cov: Cov | null }) {
         map.addControl(new AMap.ToolBar({ position: { right: "12px", top: "56px" } }));
 
         const cityOverlays: any[] = [];
-        GUIZHOU_CITIES.forEach((city) => {
-          const active = city.active;
-          const countText = active && cov ? `${cov.total.toLocaleString()} 条` : "待接入";
-          const marker = new AMap.CircleMarker({
-            center: city.coord,
-            radius: active ? 12 : 7,
-            strokeColor: active ? "#1677ff" : "#7aa7c7",
-            strokeWeight: active ? 3 : 1,
-            strokeOpacity: active ? 0.9 : 0.55,
-            fillColor: active ? "#16a085" : "#d8ecfb",
-            fillOpacity: active ? 0.9 : 0.65,
-            zIndex: active ? 20 : 10,
+        if (!isLibo) {
+          GUIZHOU_CITIES.forEach((city) => {
+            const active = city.active;
+            const countText = active && cov ? `${cov.total.toLocaleString()} 条` : "待接入";
+            const marker = new AMap.CircleMarker({
+              center: city.coord,
+              radius: active ? 12 : 7,
+              strokeColor: active ? "#1677ff" : "#7aa7c7",
+              strokeWeight: active ? 3 : 1,
+              strokeOpacity: active ? 0.9 : 0.55,
+              fillColor: active ? "#16a085" : "#d8ecfb",
+              fillOpacity: active ? 0.9 : 0.65,
+              zIndex: active ? 20 : 10,
+            });
+            const label = new AMap.Text({
+              text: `${city.name} · ${countText}`,
+              position: city.coord,
+              anchor: "bottom-center",
+              offset: new AMap.Pixel(0, -12),
+              style: {
+                padding: "4px 8px",
+                borderRadius: "999px",
+                border: active ? "1px solid #1677ff" : "1px solid #d6e4ff",
+                background: active ? "rgba(255,255,255,0.96)" : "rgba(255,255,255,0.82)",
+                color: active ? "#1f2329" : "#6b7a90",
+                fontSize: "12px",
+                boxShadow: active ? "0 6px 16px rgba(22,119,255,0.16)" : "none",
+              },
+            });
+            cityOverlays.push(marker, label);
           });
-          const label = new AMap.Text({
-            text: `${city.name} · ${countText}`,
-            position: city.coord,
-            anchor: "bottom-center",
-            offset: new AMap.Pixel(0, -12),
-            style: {
-              padding: "4px 8px",
-              borderRadius: "999px",
-              border: active ? "1px solid #1677ff" : "1px solid #d6e4ff",
-              background: active ? "rgba(255,255,255,0.96)" : "rgba(255,255,255,0.82)",
-              color: active ? "#1f2329" : "#6b7a90",
-              fontSize: "12px",
-              boxShadow: active ? "0 6px 16px rgba(22,119,255,0.16)" : "none",
-            },
-          });
-          cityOverlays.push(marker, label);
-        });
-        map.add(cityOverlays);
+          map.add(cityOverlays);
+        }
 
         AMap.plugin("AMap.DistrictSearch", () => {
           if (disposed || !mapInstance.current) return;
           const district = new AMap.DistrictSearch({
-            level: "province",
+            level: isLibo ? "district" : "province",
             subdistrict: 0,
             extensions: "all",
           });
-          district.search("贵州省", (status: string, result: any) => {
-            if (disposed || status !== "complete") return;
-            const boundaries = result?.districtList?.[0]?.boundaries || [];
+          district.search(isLibo ? "522722" : "贵州省", (status: string, result: any) => {
+            if (disposed) return;
+            if (status !== "complete") {
+              if (isLibo) {
+                setMapStatus("error");
+                setMapMessage("荔波县行政边界查询失败，请稍后刷新重试。");
+              }
+              return;
+            }
+            const districtItem = result?.districtList?.[0];
+            const boundaries = districtItem?.boundaries || [];
+            if (!boundaries.length) {
+              if (isLibo) {
+                setMapStatus("error");
+                setMapMessage("高德未返回荔波县行政边界数据。");
+              }
+              return;
+            }
             const polygons = boundaries.map((path: any) => new AMap.Polygon({
               path,
               strokeColor: "#1677ff",
-              strokeWeight: 2,
-              strokeOpacity: 0.7,
-              fillColor: "#e6f4ff",
-              fillOpacity: 0.28,
-              zIndex: 2,
+              strokeWeight: isLibo ? 4 : 2,
+              strokeOpacity: isLibo ? 1 : 0.7,
+              fillColor: isLibo ? "#69b1ff" : "#e6f4ff",
+              fillOpacity: isLibo ? 0.18 : 0.28,
+              zIndex: isLibo ? 5 : 2,
             }));
             if (polygons.length) {
               map.add(polygons);
-              map.setFitView([...polygons, ...cityOverlays], false, [36, 28, 36, 28]);
+              if (isLibo && districtItem?.center) {
+                map.setZoomAndCenter(9.5, districtItem.center);
+              } else {
+                map.setFitView([...polygons, ...cityOverlays], false, [36, 28, 36, 28]);
+              }
+              if (isLibo && districtItem?.center) {
+                const center = districtItem.center;
+                const marker = new AMap.CircleMarker({
+                  center,
+                  radius: 10,
+                  strokeColor: "#0958d9",
+                  strokeWeight: 3,
+                  fillColor: "#16a085",
+                  fillOpacity: 0.96,
+                  zIndex: 20,
+                });
+                const label = new AMap.Text({
+                  text: `荔波县 · ${mapPois.length.toLocaleString()} 条`,
+                  position: center,
+                  anchor: "bottom-center",
+                  offset: new AMap.Pixel(0, -12),
+                  style: {
+                    padding: "5px 10px",
+                    borderRadius: "999px",
+                    border: "1px solid #1677ff",
+                    background: "rgba(255,255,255,0.96)",
+                    color: "#1f2329",
+                    fontSize: "12px",
+                    boxShadow: "0 6px 16px rgba(22,119,255,0.2)",
+                  },
+                });
+                map.add([marker, label]);
+              }
             }
+            setMapStatus("ready");
           });
         });
 
-        setMapStatus("ready");
+        if (!isLibo) setMapStatus("ready");
       } catch (e: any) {
         setMapStatus("error");
         setMapMessage(e?.message || "高德地图加载失败");
@@ -205,10 +2348,577 @@ function GuizhouKnowledgeMap({ cov }: { cov: Cov | null }) {
     boot();
     return () => {
       disposed = true;
+      if (busOverlaysRef.current.length && mapInstance.current) {
+        mapInstance.current.remove(busOverlaysRef.current);
+      }
+      busOverlaysRef.current = [];
+      clusterRef.current?.setMap?.(null);
+      clusterRef.current = null;
+      infoWindowRef.current?.close?.();
+      infoWindowRef.current = null;
       mapInstance.current?.destroy?.();
       mapInstance.current = null;
+      amapRef.current = null;
     };
-  }, [cov]);
+  }, [cov, isLibo, mapPois.length]);
+
+  useEffect(() => {
+    const AMap = amapRef.current;
+    const map = mapInstance.current;
+    if (!isLibo || mapStatus !== "ready" || !AMap || !map) return;
+
+    let disposed = false;
+    const lookup = new Map<string, MapPoi>();
+    visiblePois.forEach((poi) => {
+      const key = poiCoordinateKey(poi.lng, poi.lat);
+      if (!lookup.has(key)) lookup.set(key, poi);
+    });
+    poiLookupRef.current = lookup;
+
+    const data = visiblePois.map((poi) => ({
+      lnglat: [poi.lng, poi.lat],
+      weight: 1,
+      poi,
+    }));
+
+    AMap.plugin("AMap.MarkerCluster", () => {
+      if (disposed || mapInstance.current !== map) return;
+      clusterRef.current?.setMap?.(null);
+      clusterRef.current = null;
+      if (!data.length) return;
+
+      const renderClusterMarker = (context: any) => {
+        const count = Number(context.count || 0);
+        const size = count >= 1000 ? 52 : count >= 100 ? 46 : count >= 10 ? 40 : 34;
+        const node = document.createElement("div");
+        node.dataset.clusterCount = String(count);
+        node.textContent = count.toLocaleString();
+        node.style.cssText = [
+          `width:${size}px`,
+          `height:${size}px`,
+          `line-height:${size}px`,
+          "border-radius:50%",
+          "text-align:center",
+          "color:#fff",
+          "font-size:12px",
+          "font-weight:700",
+          "background:linear-gradient(135deg,rgba(22,119,255,.92),rgba(9,88,217,.94))",
+          "border:3px solid rgba(255,255,255,.92)",
+          "box-shadow:0 5px 18px rgba(22,119,255,.36)",
+          "cursor:pointer",
+          "user-select:none",
+        ].join(";");
+        context.marker.setOffset(new AMap.Pixel(-size / 2, -size / 2));
+        context.marker.setContent(node);
+        context.marker.on?.("click", () => {
+          const position = context.marker.getPosition?.();
+          if (!position) return;
+          const currentZoom = Number(map.getZoom?.() || 10);
+          map.setZoomAndCenter?.(Math.min(currentZoom + 2, 16), position);
+        });
+      };
+
+      const renderMarker = (context: any) => {
+        const position = context.marker.getPosition?.();
+        const lng = Number(position?.lng ?? position?.getLng?.());
+        const lat = Number(position?.lat ?? position?.getLat?.());
+        const poi = context.data?.poi
+          || poiLookupRef.current.get(poiCoordinateKey(lng, lat));
+        const color = poiCategoryColor(poi?.category);
+        const node = document.createElement("div");
+        node.dataset.poiId = poi?.id || "";
+        node.title = poi?.name || "POI";
+        node.style.cssText = [
+          "width:16px",
+          "height:16px",
+          "border-radius:50%",
+          `background:${color}`,
+          "border:3px solid #fff",
+          `box-shadow:0 2px 9px ${color}99`,
+          "cursor:pointer",
+        ].join(";");
+        context.marker.setOffset(new AMap.Pixel(-8, -8));
+        context.marker.setContent(node);
+        if (poi) {
+          context.marker.setTitle?.(poi.name);
+          context.marker.on?.("click", () => poiOpenRef.current(poi));
+        }
+      };
+
+      clusterRef.current = new AMap.MarkerCluster(map, data, {
+        gridSize: 58,
+        maxZoom: 16,
+        averageCenter: true,
+        clusterByZoomChange: true,
+        renderClusterMarker,
+        renderMarker,
+      });
+    });
+
+    return () => {
+      disposed = true;
+      clusterRef.current?.setMap?.(null);
+      clusterRef.current = null;
+    };
+  }, [isLibo, mapStatus, visiblePois]);
+
+  useEffect(() => {
+    const AMap = amapRef.current;
+    if (!isLibo || mapStatus !== "ready" || !AMap || !busRoutes.length) {
+      setResolvedBusPaths({});
+      return;
+    }
+
+    const requestId = busPathRequestRef.current + 1;
+    busPathRequestRef.current = requestId;
+    const routeGroups = new Map<string, BusRoute[]>();
+    busRoutes.forEach((route) => {
+      routeGroups.set(route.line_name, [...(routeGroups.get(route.line_name) || []), route]);
+    });
+
+    const pointToArray = (point: any): number[] | null => {
+      const lng = Number(point?.lng ?? point?.getLng?.() ?? point?.[0]);
+      const lat = Number(point?.lat ?? point?.getLat?.() ?? point?.[1]);
+      return Number.isFinite(lng) && Number.isFinite(lat) ? [lng, lat] : null;
+    };
+    const endpointName = (value: any) => (
+      value && typeof value === "object" ? value.name : value
+    );
+
+    AMap.plugin("AMap.LineSearch", async () => {
+      const pathEntries = await Promise.all(
+        [...routeGroups.entries()].map(([lineName, routes]) => (
+          new Promise<Array<[string, number[][]]>>((resolve) => {
+            const service = new AMap.LineSearch({
+              pageIndex: 1,
+              pageSize: 20,
+              city: "荔波县",
+              extensions: "all",
+            });
+            service.search(lineName, (status: string, result: any) => {
+              if (status !== "complete") {
+                resolve([]);
+                return;
+              }
+              const candidates = Array.isArray(result?.lineInfo) ? result.lineInfo : [];
+              resolve(routes.flatMap((route) => {
+                const start = normalizeBusStopName(route.start_stop);
+                const end = normalizeBusStopName(route.end_stop);
+                const best = [...candidates].sort((left, right) => {
+                  const score = (item: any) => {
+                    const itemStart = normalizeBusStopName(endpointName(item?.start_stop));
+                    const itemEnd = normalizeBusStopName(endpointName(item?.end_stop));
+                    return Number(itemStart.includes(start) || start.includes(itemStart))
+                      + Number(itemEnd.includes(end) || end.includes(itemEnd));
+                  };
+                  return score(right) - score(left);
+                })[0];
+                const path = (best?.path || []).map(pointToArray).filter(Boolean) as number[][];
+                return path.length >= 2 ? [[route.route_id, path]] : [];
+              }));
+            });
+          })
+        )),
+      );
+      if (busPathRequestRef.current !== requestId) return;
+      setResolvedBusPaths(Object.fromEntries(pathEntries.flat()));
+    });
+
+    return () => {
+      if (busPathRequestRef.current === requestId) {
+        busPathRequestRef.current += 1;
+      }
+    };
+  }, [busRoutes, isLibo, mapStatus]);
+
+  useEffect(() => {
+    const AMap = amapRef.current;
+    const map = mapInstance.current;
+    if (busOverlaysRef.current.length && map) {
+      map.remove(busOverlaysRef.current);
+    }
+    busOverlaysRef.current = [];
+    if (!isLibo || mapStatus !== "ready" || !AMap || !map || !busLayerVisible) return;
+
+    const overlays: any[] = [];
+    const focusedPolylines: any[] = [];
+    const hasRouteFocus = Boolean(focusedBusRouteId);
+    const hasLineFocus = !hasRouteFocus && Boolean(focusedBusLineName);
+    busRoutes.forEach((route) => {
+      const fallbackPath = route.stops.map((stop) => [stop.lng, stop.lat]);
+      const path = resolvedBusPaths[route.route_id] || fallbackPath;
+      if (path.length < 2) return;
+      const focused = hasRouteFocus
+        ? focusedBusRouteId === route.route_id
+        : hasLineFocus
+          ? focusedBusLineName === route.line_name
+          : true;
+      const color = busLineColor(route.line_name);
+      const polyline = new AMap.Polyline({
+        path,
+        strokeColor: color,
+        strokeWeight: focused ? 8 : 4,
+        strokeOpacity: focused ? 0.94 : 0.12,
+        borderWeight: focused ? 2 : 1,
+        outlineColor: "#ffffff",
+        lineJoin: "round",
+        lineCap: "round",
+        showDir: hasRouteFocus && focusedBusRouteId === route.route_id,
+        zIndex: focused ? 24 : 10,
+      });
+      polyline.on("click", () => busRouteOpenRef.current(route));
+      overlays.push(polyline);
+      if (focused) focusedPolylines.push(polyline);
+    });
+
+    const visibleStops = focusedBusRoute
+      ? focusedBusRoute.stops
+        .map((stop) => busStopNetwork.get(stop.stop_id))
+        .filter(Boolean) as BusStopNetwork[]
+      : focusedBusLineRoutes.length
+        ? [...new Map(
+          focusedBusLineRoutes
+            .flatMap((route) => route.stops)
+            .map((stop) => [stop.stop_id, busStopNetwork.get(stop.stop_id)]),
+        ).values()].filter(Boolean) as BusStopNetwork[]
+        : [...busStopNetwork.values()];
+    const activeBusColor = focusedBusRoute
+      ? busLineColor(focusedBusRoute.line_name)
+      : focusedBusLineName
+        ? busLineColor(focusedBusLineName)
+        : "#00a870";
+    visibleStops.forEach((stop) => {
+      const isFocused = Boolean(focusedBusRoute || focusedBusLineName);
+      const node = document.createElement("div");
+      node.dataset.busStopId = stop.stop_id;
+      node.title = `${stop.name}（公交站）`;
+      node.textContent = "BUS";
+      node.style.cssText = [
+        `width:${isFocused ? 28 : 22}px`,
+        `height:${isFocused ? 28 : 22}px`,
+        `line-height:${isFocused ? 25 : 19}px`,
+        "box-sizing:border-box",
+        "border-radius:7px 7px 9px 9px",
+        "text-align:center",
+        "color:#fff",
+        `font-size:${isFocused ? 8 : 7}px`,
+        "font-weight:800",
+        "letter-spacing:-.3px",
+        `background:${activeBusColor}`,
+        "border:2px solid rgba(255,255,255,.96)",
+        `box-shadow:0 3px 10px ${activeBusColor}66`,
+        "cursor:pointer",
+      ].join(";");
+      node.addEventListener("click", (event) => {
+        event.stopPropagation();
+        busStopOpenRef.current(stop);
+      });
+      const marker = new AMap.Marker({
+        position: [stop.lng, stop.lat],
+        content: node,
+        anchor: "bottom-center",
+        offset: new AMap.Pixel(0, -2),
+        zIndex: isFocused ? 42 : 30,
+        title: `${stop.name}（公交站）`,
+      });
+      marker.on("click", () => busStopOpenRef.current(stop));
+      const label = new AMap.Text({
+        text: `${stop.name}（公交站）`,
+        position: [stop.lng, stop.lat],
+        anchor: "bottom-left",
+        offset: new AMap.Pixel(15, -7),
+        zIndex: 45,
+        style: {
+          padding: "3px 7px",
+          borderRadius: "7px",
+          border: `1px solid ${activeBusColor}88`,
+          background: "rgba(255,255,255,.94)",
+          color: "#1f2329",
+          fontSize: "11px",
+          fontWeight: "650",
+          whiteSpace: "nowrap",
+          boxShadow: "0 3px 10px rgba(15,23,42,.1)",
+        },
+      });
+      label.on("click", () => busStopOpenRef.current(stop));
+      overlays.push(marker, label);
+    });
+
+    map.add(overlays);
+    busOverlaysRef.current = overlays;
+    if (focusedPolylines.length) {
+      window.setTimeout(() => {
+        if (mapInstance.current === map) {
+          map.setFitView(focusedPolylines, false, [70, 430, 70, 70]);
+        }
+      }, 60);
+    }
+
+    return () => {
+      if (mapInstance.current === map && overlays.length) map.remove(overlays);
+      if (busOverlaysRef.current === overlays) busOverlaysRef.current = [];
+    };
+  }, [
+    busLayerVisible,
+    busRoutes,
+    busStopNetwork,
+    focusedBusRoute,
+    focusedBusRouteId,
+    focusedBusLineName,
+    focusedBusLineRoutes,
+    isLibo,
+    mapStatus,
+    resolvedBusPaths,
+  ]);
+
+  const allCategoriesSelected = poiCategories.length > 0
+    && selectedCategories.length === poiCategories.length;
+  const toggleAllCategories = () => {
+    setSelectedCategories(allCategoriesSelected ? [] : poiCategories.map((item) => item.category));
+  };
+  const togglePoiCategory = (category: string, checked: boolean) => {
+    setSelectedCategories((current) => (
+      checked
+        ? [...new Set([...current, category])]
+        : current.filter((item) => item !== category)
+    ));
+  };
+
+  const detailItems = useMemo(() => {
+    if (!poiDetail) return [];
+    const rows = [
+      { key: "region", label: "行政区", children: [poiDetail.city, poiDetail.district].filter(Boolean).join(" · ") },
+      { key: "address", label: "地址", children: poiDetail.address },
+      { key: "business_subcategory", label: "细分类", children: poiDetail.business_subcategory },
+      { key: "tel", label: "商家电话", children: poiDetail.tel },
+      { key: "scenic_type", label: "景点类型", children: poiDetail.scenic_type },
+      { key: "scenic_level", label: "景点层级", children: poiDetail.scenic_level },
+      { key: "parent_scenic", label: "所属景区", children: poiDetail.parent_scenic },
+      { key: "scenic_grade", label: "景区等级", children: poiDetail.scenic_grade },
+      { key: "visitor_value", label: "游客价值", children: poiDetail.visitor_value },
+      { key: "open_time", label: "营业时间", children: poiDetail.open_time },
+      { key: "cost", label: "参考消费", children: poiDetail.cost },
+      { key: "business_area", label: "商圈", children: poiDetail.business_area },
+      { key: "tags", label: "标签", children: poiDetail.tags },
+    ];
+    return rows.filter((item) => Boolean(item.children));
+  }, [poiDetail]);
+  const foodOverviewItems = useMemo(() => {
+    const enrichment = poiDetail?.food_enrichment;
+    if (!enrichment?.dianping_name) return [];
+    const value = (key: string) => normalizeDetailValue(key, enrichment[key]);
+    return [
+      {
+        key: "dianping_name",
+        label: "点评店名",
+        icon: <HomeOutlined />,
+        children: value("dianping_name") || "暂无数据",
+      },
+      {
+        key: "dianping_category",
+        label: "点评分类",
+        icon: <AppstoreOutlined />,
+        children: value("dianping_category") || "暂无数据",
+      },
+      {
+        key: "dianping_rating",
+        label: "点评评分",
+        icon: <StarOutlined />,
+        children: value("dianping_rating") || "暂无数据",
+      },
+      {
+        key: "dianping_review_count",
+        label: "用户点评",
+        icon: <CommentOutlined />,
+        children: value("dianping_review_count")
+          ? `${value("dianping_review_count")} 条`
+          : "暂无数据",
+      },
+      {
+        key: "dianping_avg_price",
+        label: "人均消费",
+        icon: <PayCircleOutlined />,
+        children: value("dianping_avg_price")
+          ? `¥${value("dianping_avg_price")}`
+          : "暂无数据",
+      },
+      {
+        key: "dianping_ranking",
+        label: "榜单排名",
+        icon: <CrownOutlined />,
+        children: value("dianping_ranking") || "暂无数据",
+      },
+      {
+        key: "dianping_business_status",
+        label: "营业状态",
+        icon: <CheckCircleOutlined />,
+        children: value("dianping_business_status") || "暂无数据",
+      },
+      {
+        key: "dianping_business_hours",
+        label: "营业时间",
+        icon: <CalendarOutlined />,
+        children: value("dianping_business_hours") || "暂无数据",
+      },
+    ];
+  }, [poiDetail]);
+  const foodFeatureItems = useMemo(
+    () => enrichmentDetailItems(poiDetail?.food_enrichment, FOOD_FEATURE_LABELS),
+    [poiDetail],
+  );
+  const foodGroupBuyItems = useMemo(
+    () => parseJsonArray<FoodGroupBuyItem>(
+      poiDetail?.food_enrichment?.group_buy_items_json,
+    ),
+    [poiDetail],
+  );
+  const foodReviewPayload = useMemo(
+    () => parseJsonArray<FoodReviewItem>(
+      poiDetail?.food_enrichment?.food_review_items_json,
+    ),
+    [poiDetail],
+  );
+  const foodReviewTags = useMemo(
+    () => parseJsonArray<FoodReviewTag>(
+      poiDetail?.food_enrichment?.food_review_tags_json,
+    ),
+    [poiDetail],
+  );
+  const hotelOverviewItems = useMemo(() => {
+    const enrichment = poiDetail?.hotel_enrichment;
+    if (!enrichment) return [];
+
+    const rating = normalizeDetailValue("ctrip_rating", enrichment.ctrip_rating);
+    const ratingDescription = normalizeDetailValue(
+      "ctrip_rating_description",
+      enrichment.ctrip_rating_description,
+    );
+    const reviewCount = normalizeDetailValue("ctrip_review_count", enrichment.ctrip_review_count);
+    const diamondLevel = normalizeCtripDiamondLevel(enrichment.ctrip_diamond_level);
+    const minPrice = normalizeDetailValue("room_min_price", enrichment.room_min_price);
+    const ctripName = normalizeDetailValue("ctrip_name_cn", enrichment.ctrip_name_cn);
+    const openedYear = normalizeDetailValue("ctrip_opened_year", enrichment.ctrip_opened_year);
+    const roomCount = normalizeDetailValue("ctrip_room_count", enrichment.ctrip_room_count);
+    const secondaryItems = enrichmentDetailItems(enrichment, HOTEL_OVERVIEW_LABELS);
+
+    if (
+      ![rating, ratingDescription, reviewCount, diamondLevel, minPrice, ctripName, openedYear, roomCount]
+        .some((value) => value !== "")
+      && !secondaryItems.length
+    ) {
+      return [];
+    }
+
+    const primaryItems: DetailItem[] = [
+      {
+        key: "ctrip_name_cn",
+        label: "携程酒店名",
+        icon: <HomeOutlined />,
+        children: ctripName || "暂无数据",
+      },
+      {
+        key: "ctrip_opened_year",
+        label: "开业时间",
+        icon: <CalendarOutlined />,
+        children: openedYear ? `${openedYear} 年` : "暂无数据",
+      },
+      {
+        key: "ctrip_room_count",
+        label: "客房数量",
+        icon: <AppstoreOutlined />,
+        children: roomCount ? `${roomCount} 间` : "暂无数据",
+      },
+      {
+        key: "ctrip_diamond_level",
+        label: "酒店钻级",
+        icon: <CrownOutlined />,
+        children: diamondLevel || "暂无数据",
+      },
+      {
+        key: "ctrip_rating",
+        label: "携程评分",
+        icon: <StarOutlined />,
+        children: rating
+          ? `${rating}${ratingDescription ? ` · ${ratingDescription}` : ""}`
+          : "暂无数据",
+      },
+      {
+        key: "ctrip_review_count",
+        label: "用户点评",
+        icon: <CommentOutlined />,
+        children: reviewCount ? `${reviewCount} 条` : "暂无数据",
+      },
+      {
+        key: "room_min_price",
+        label: "参考起价",
+        icon: <PayCircleOutlined />,
+        children: minPrice ? `¥${minPrice} 起` : "暂无数据",
+      },
+    ];
+
+    return [
+      ...primaryItems,
+      ...secondaryItems,
+    ];
+  }, [poiDetail]);
+  const hotelRoomPayload = useMemo(
+    () => parseJsonArray<HotelRoomItem>(poiDetail?.hotel_enrichment?.room_items_json),
+    [poiDetail],
+  );
+  const hotelFacilityItems = useMemo(
+    () => enrichmentDetailItems(poiDetail?.hotel_enrichment, HOTEL_FACILITY_LABELS),
+    [poiDetail],
+  );
+  const hotelFacilityPayload = useMemo(
+    () => parseHotelFacilityPayload(poiDetail?.hotel_enrichment?.facility_category_items_json),
+    [poiDetail],
+  );
+  const hotelPolicyItems = useMemo(
+    () => enrichmentDetailItems(poiDetail?.hotel_enrichment, HOTEL_POLICY_LABELS),
+    [poiDetail],
+  );
+  const hotelReviewPayload = useMemo(
+    () => parseJsonArray<HotelReviewItem>(poiDetail?.hotel_enrichment?.review_items_json),
+    [poiDetail],
+  );
+  const hotelReviewTags = useMemo(
+    () => splitHotelTags(
+      poiDetail?.hotel_enrichment?.ctrip_tags,
+      poiDetail?.hotel_enrichment?.review_travel_types,
+    ),
+    [poiDetail],
+  );
+  const hotelNearbyItems = useMemo(
+    () => enrichmentDetailItems(poiDetail?.hotel_enrichment, HOTEL_NEARBY_LABELS),
+    [poiDetail],
+  );
+  const hotelNearbyCategories = useMemo(
+    () => parseNearbyPlaceCategories(poiDetail?.hotel_enrichment?.nearby_category_items_json),
+    [poiDetail],
+  );
+  const sourceDetailItems = useMemo(
+    () => {
+      if (!poiDetail) return [];
+      const sources = [
+        poiDetail.source === "amap" ? "高德地图" : poiDetail.source,
+        poiDetail.food_enrichment?.dianping_name ? "大众点评" : "",
+        poiDetail.hotel_enrichment?.ctrip_name_cn ? "携程" : "",
+      ].filter(Boolean);
+      return [
+        {
+          key: "source",
+          label: "知识来源",
+          children: [...new Set(sources)].join(" · "),
+        },
+        {
+          key: "fetched",
+          label: "最近更新",
+          children: formatPoiTime(poiDetail.last_fetched_at),
+        },
+      ].filter((item) => Boolean(item.children));
+    },
+    [poiDetail],
+  );
 
   return (
     <div
@@ -223,11 +2933,13 @@ function GuizhouKnowledgeMap({ cov }: { cov: Cov | null }) {
       <div style={{ display: "flex", alignItems: "center", justifyContent: "space-between", gap: 12, marginBottom: 10 }}>
         <Space size={8}>
           <EnvironmentOutlined style={{ color: "#1677ff" }} />
-          <b>贵州省知识地图</b>
+          <b>{isLibo ? "贵州省荔波县知识地图" : "贵州省知识地图"}</b>
           <Tag color="blue">高德 JS API</Tag>
         </Space>
         <span style={{ fontSize: 12, color: "#888" }}>
-          当前图谱：贵阳已接入 · 省域底图为后续扩展预留
+          {isLibo
+            ? "当前图谱：荔波县已接入 · 突出显示荔波县行政区域"
+            : "当前图谱：贵阳已接入 · 省域底图为后续扩展预留"}
         </span>
       </div>
 
@@ -248,20 +2960,27 @@ function GuizhouKnowledgeMap({ cov }: { cov: Cov | null }) {
             minHeight: 320,
           }}
         >
-          <div style={{ color: "#888", fontSize: 12, marginBottom: 4 }}>省域馆藏汇总</div>
+          <div style={{ color: "#888", fontSize: 12, marginBottom: 4 }}>
+            {isLibo ? "荔波县馆藏汇总" : "省域馆藏汇总"}
+          </div>
           <div style={{ fontSize: 28, fontWeight: 700, lineHeight: 1.15 }}>
-            {(cov?.total ?? 0).toLocaleString()}
+            {(isLibo ? mapPois.length : (cov?.total ?? 0)).toLocaleString()}
           </div>
           <div style={{ color: "#888", fontSize: 12, marginTop: 4 }}>
             当前已入藏知识 / POI 条目
           </div>
-          <div style={{ marginTop: 14 }}>
+          {!isLibo && <div style={{ marginTop: 14 }}>
             <Progress
               percent={cov?.grid_overall_pct ?? 0}
               size="small"
               status={(cov?.grid_overall_pct ?? 0) >= 100 ? "success" : "active"}
             />
-          </div>
+          </div>}
+          {isLibo && (
+            <div style={{ marginTop: 14 }}>
+              <Tag color="green">82 个细网格采集已完成</Tag>
+            </div>
+          )}
           <div style={{ marginTop: 14, display: "flex", flexDirection: "column", gap: 8 }}>
             {topCats.map((it) => (
               <div key={it.cat} style={{ display: "flex", alignItems: "center", justifyContent: "space-between", gap: 8 }}>
@@ -274,30 +2993,154 @@ function GuizhouKnowledgeMap({ cov }: { cov: Cov | null }) {
             ))}
           </div>
           <div style={{ marginTop: 14, color: "#888", fontSize: 12, lineHeight: 1.7 }}>
-            地图先展示贵州省边界与九市州锚点；贵阳为当前知识图谱主库，后续扩展遵义、黔东南等城市时可直接挂接同一省域画布。
+            {isLibo
+              ? "地图正常展示荔波县及周边区域，并用蓝色边界与浅蓝填充突出荔波县主体；所有 POI 均按荔波县行政区划代码 522722 过滤。"
+              : "地图先展示贵州省边界与九市州锚点；贵阳为当前知识图谱主库，后续扩展遵义、黔东南等城市时可直接挂接同一省域画布。"}
           </div>
         </div>}
 
         <div
+          ref={mapShellRef}
           style={{
-            position: isFullscreen ? "fixed" : "relative",
-            inset: isFullscreen ? 16 : undefined,
+            position: fullscreenMode === "fallback" ? "fixed" : "relative",
+            inset: fullscreenMode === "fallback" ? 0 : undefined,
             zIndex: isFullscreen ? 2000 : undefined,
-            minHeight: isFullscreen ? "calc(100vh - 32px)" : 320,
-            height: isFullscreen ? "calc(100vh - 32px)" : undefined,
-            borderRadius: isFullscreen ? 12 : 8,
+            width: isFullscreen ? "100vw" : undefined,
+            minHeight: isFullscreen ? "100dvh" : 320,
+            height: isFullscreen ? "100dvh" : undefined,
+            borderRadius: isFullscreen ? 0 : 8,
             overflow: "hidden",
-            border: "1px solid #edf2f7",
+            border: isFullscreen ? "none" : "1px solid #edf2f7",
             background: "#fff",
-            boxShadow: isFullscreen ? "0 18px 60px rgba(15, 23, 42, 0.32)" : undefined,
+            boxShadow: fullscreenMode === "fallback" ? "0 18px 60px rgba(15, 23, 42, 0.32)" : undefined,
           }}
         >
           <div ref={mapRef} style={{ width: "100%", height: isFullscreen ? "100%" : 320 }} />
+          {isLibo && (
+            <div
+              style={{
+                position: "absolute",
+                left: 12,
+                top: 12,
+                zIndex: 32,
+                width: isFullscreen ? 520 : "min(520px, calc(100% - 150px))",
+                maxWidth: "calc(100% - 150px)",
+                padding: "10px 12px",
+                border: "1px solid rgba(145,202,255,.9)",
+                borderRadius: 10,
+                background: "rgba(255,255,255,.94)",
+                boxShadow: "0 8px 24px rgba(15,23,42,.14)",
+                backdropFilter: "blur(8px)",
+              }}
+            >
+              <div style={{ display: "flex", alignItems: "center", justifyContent: "space-between", gap: 10 }}>
+                <Space size={6}>
+                  <AimOutlined style={{ color: "#1677ff" }} />
+                  <b style={{ fontSize: 13 }}>荔波POI图层</b>
+                  <Tag color="blue" style={{ marginInlineEnd: 0 }}>
+                    {visiblePois.length.toLocaleString()} / {mapPois.length.toLocaleString()}
+                  </Tag>
+                </Space>
+                {poiLoading && <Spin size="small" />}
+              </div>
+              {poiError ? (
+                <div style={{ color: "#cf1322", fontSize: 12, marginTop: 8 }}>{poiError}</div>
+              ) : (
+                <div style={{ display: "flex", flexWrap: "wrap", gap: 6, marginTop: 8 }}>
+                  <Tag.CheckableTag
+                    checked={allCategoriesSelected}
+                    onChange={toggleAllCategories}
+                    style={{ marginInlineEnd: 0 }}
+                  >
+                    全部
+                  </Tag.CheckableTag>
+                  {poiCategories.map(({ category, count }) => {
+                    const checked = selectedCategories.includes(category);
+                    const color = poiCategoryColor(category);
+                    return (
+                      <Tag.CheckableTag
+                        key={category}
+                        checked={checked}
+                        onChange={(nextChecked) => togglePoiCategory(category, nextChecked)}
+                        style={{
+                          marginInlineEnd: 0,
+                          border: `1px solid ${checked ? color : "#d9d9d9"}`,
+                          color: checked ? "#fff" : "#475467",
+                          background: checked ? color : "rgba(255,255,255,.84)",
+                        }}
+                      >
+                        {category} {count}
+                      </Tag.CheckableTag>
+                    );
+                  })}
+                </div>
+              )}
+              <Divider style={{ margin: "10px 0 8px" }} />
+              <div style={{ display: "flex", alignItems: "center", justifyContent: "space-between", gap: 8 }}>
+                <Space size={6} wrap>
+                  <Tag.CheckableTag
+                    checked={busLayerVisible}
+                    onChange={(checked) => setBusLayerVisible(checked)}
+                    style={{
+                      marginInlineEnd: 0,
+                      border: `1px solid ${busLayerVisible ? "#00a870" : "#d9d9d9"}`,
+                      color: busLayerVisible ? "#fff" : "#475467",
+                      background: busLayerVisible ? "#00a870" : "rgba(255,255,255,.84)",
+                    }}
+                  >
+                    <CarOutlined /> 公交图层
+                  </Tag.CheckableTag>
+                  {busLoading && <Spin size="small" />}
+                </Space>
+                <Button
+                  size="small"
+                  icon={<UnorderedListOutlined />}
+                  disabled={!busRoutes.length}
+                  onClick={() => {
+                    closePoiDetail();
+                    setFocusedBusRouteId("");
+                    setBusPanel({ mode: "list" });
+                  }}
+                >
+                  线路列表
+                </Button>
+              </div>
+              <div style={{ display: "flex", flexWrap: "wrap", gap: 6, marginTop: 8 }}>
+                {busLines.map((lineName) => {
+                  const color = busLineColor(lineName);
+                  const checked = focusedBusLineName === lineName;
+                  return (
+                    <Tooltip key={lineName} title={`显示${lineName}公交路线`}>
+                      <Tag.CheckableTag
+                        checked={checked}
+                        onChange={() => openBusLine(lineName)}
+                        style={{
+                          marginInlineEnd: 0,
+                          minWidth: 48,
+                          textAlign: "center",
+                          border: `1px solid ${color}`,
+                          color: checked ? "#fff" : color,
+                          background: checked ? color : `${color}12`,
+                          fontWeight: 700,
+                          boxShadow: checked ? `0 4px 12px ${color}44` : "none",
+                        }}
+                      >
+                        {busLineShortName(lineName)}
+                      </Tag.CheckableTag>
+                    </Tooltip>
+                  );
+                })}
+              </div>
+              {busError && (
+                <div style={{ color: "#cf1322", fontSize: 12, marginTop: 6 }}>{busError}</div>
+              )}
+            </div>
+          )}
           <Tooltip title={isFullscreen ? "退出全屏" : "全屏展示地图"}>
             <Button
               size="small"
               icon={isFullscreen ? <FullscreenExitOutlined /> : <FullscreenOutlined />}
-              onClick={() => setIsFullscreen((v) => !v)}
+              onClick={toggleFullscreen}
               style={{
                 position: "absolute",
                 right: 12,
@@ -325,6 +3168,436 @@ function GuizhouKnowledgeMap({ cov }: { cov: Cov | null }) {
               {mapMessage}
             </div>
           )}
+          <Drawer
+            title={selectedPoi ? (
+              <Space size={8}>
+                <span
+                  style={{
+                    width: 10,
+                    height: 10,
+                    borderRadius: 99,
+                    background: poiCategoryColor(selectedPoi.category),
+                    display: "inline-block",
+                  }}
+                />
+                <span>{selectedPoi.name}</span>
+              </Space>
+            ) : "POI详情"}
+            placement="right"
+            width={460}
+            open={Boolean(selectedPoi)}
+            onClose={closePoiDetail}
+            getContainer={false}
+            mask={false}
+            rootStyle={{ position: "absolute", zIndex: 60 }}
+            styles={{
+              header: { padding: "14px 18px", borderBottom: "1px solid #eef1f5" },
+              body: {
+                padding: 14,
+                overflowY: "auto",
+                overflowX: "hidden",
+                background: "#f5f7fa",
+              },
+            }}
+          >
+            {detailLoading && !poiDetail ? (
+              <div style={{ minHeight: 220, display: "grid", placeItems: "center" }}>
+                <Spin tip="正在读取图谱详情..." />
+              </div>
+            ) : poiDetail ? (
+              <div style={{ display: "grid", gap: 12, width: "100%", minWidth: 0 }}>
+                <div style={{ display: "flex", alignItems: "center", flexWrap: "wrap", gap: 7 }}>
+                  <Tag color={poiCategoryColor(poiDetail.category)} style={{ margin: 0 }}>
+                    {poiDetail.category}
+                  </Tag>
+                  {poiDetail.rating && (
+                    <Tag color="gold" style={{ margin: 0 }}>高德评分 {poiDetail.rating}</Tag>
+                  )}
+                  {poiDetail.cost && <Tag style={{ margin: 0 }}>参考消费 {poiDetail.cost}</Tag>}
+                  {poiDetail.business_subcategory && (
+                    <Tag bordered={false} style={{ margin: 0, color: "#475467", background: "#eef2f6" }}>
+                      {poiDetail.business_subcategory}
+                    </Tag>
+                  )}
+                </div>
+
+                {poiDetail.photo_urls?.length > 0 && (
+                  <section
+                    style={{
+                      width: "100%",
+                      maxWidth: "100%",
+                      minWidth: 0,
+                      boxSizing: "border-box",
+                      overflow: "hidden",
+                      padding: 8,
+                      border: "1px solid #e8edf3",
+                      borderRadius: 12,
+                      background: "#fff",
+                    }}
+                  >
+                    <Image.PreviewGroup>
+                      <div
+                        style={{
+                          display: "grid",
+                          gridTemplateColumns: "repeat(3, minmax(0, 1fr))",
+                          gap: 8,
+                          width: "100%",
+                          minWidth: 0,
+                          overflow: "hidden",
+                        }}
+                      >
+                        {poiDetail.photo_urls.slice(0, 3).map((url, index) => (
+                          <div key={`${url}-${index}`} style={{ minWidth: 0, overflow: "hidden" }}>
+                            <Image
+                              src={url}
+                              alt={`${poiDetail.name} 图片${index + 1}`}
+                              width="100%"
+                              height={92}
+                              style={{ display: "block", objectFit: "cover", borderRadius: 8 }}
+                              fallback="data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='160' height='100'%3E%3Crect width='100%25' height='100%25' fill='%23f2f4f7'/%3E%3Ctext x='50%25' y='52%25' text-anchor='middle' fill='%2398a2b3' font-size='12'%3E暂无图片%3C/text%3E%3C/svg%3E"
+                            />
+                          </div>
+                        ))}
+                      </div>
+                    </Image.PreviewGroup>
+                  </section>
+                )}
+
+                <DetailSection
+                  title="基础信息"
+                  items={detailItems}
+                  accent={poiCategoryColor(poiDetail.category)}
+                />
+
+                <PlatformOverviewSection
+                  title="大众点评信息"
+                  accent="#fa541c"
+                  metrics={[]}
+                  items={foodOverviewItems}
+                  titleIcon={(
+                    <img
+                      src={DIANPING_APP_ICON_URL}
+                      alt="大众点评"
+                      width={24}
+                      height={24}
+                      style={{ display: "block", width: 24, height: 24, borderRadius: 7 }}
+                    />
+                  )}
+                />
+                <DetailSection
+                  title="特色与推荐"
+                  items={foodFeatureItems}
+                  accent="#fa541c"
+                  richList
+                />
+                <FoodGroupBuySection deals={foodGroupBuyItems} />
+                <FoodReviewSection
+                  tags={foodReviewTags}
+                  reviews={foodReviewPayload}
+                />
+
+                <PlatformOverviewSection
+                  title="携程酒店信息"
+                  accent="#722ed1"
+                  metrics={[]}
+                  items={hotelOverviewItems}
+                />
+                {poiDetail.graph_labels?.includes("Hotel") && (
+                  <HotelRoomSection rooms={hotelRoomPayload} />
+                )}
+                {hotelFacilityPayload.categories.length > 0 ? (
+                  <HotelFacilitySection payload={hotelFacilityPayload} />
+                ) : (
+                  <DetailSection
+                    title="服务及设施"
+                    items={hotelFacilityItems}
+                    accent="#722ed1"
+                    richList
+                  />
+                )}
+                <PolicySection items={hotelPolicyItems} />
+                {hotelNearbyCategories.length > 0 ? (
+                  <NearbyCategorySection categories={hotelNearbyCategories} />
+                ) : (
+                  <DetailSection
+                    title="周边地点"
+                    items={hotelNearbyItems}
+                    accent="#722ed1"
+                    richList
+                  />
+                )}
+                {poiDetail.graph_labels?.includes("Hotel") && (
+                  <HotelReviewSection
+                    tags={hotelReviewTags}
+                    reviews={hotelReviewPayload}
+                  />
+                )}
+                <DetailSection
+                  title="数据来源"
+                  items={sourceDetailItems}
+                  accent="#98a2b3"
+                />
+
+                <div
+                  style={{
+                    position: "sticky",
+                    bottom: -14,
+                    margin: "0 -14px -14px",
+                    padding: "12px 14px",
+                    borderTop: "1px solid #e4e7ec",
+                    background: "rgba(255,255,255,.96)",
+                    backdropFilter: "blur(10px)",
+                    zIndex: 2,
+                  }}
+                >
+                  <Space wrap>
+                  <Button
+                    type="primary"
+                    icon={<CompassOutlined />}
+                    href={poiNavigationUrl(poiDetail)}
+                    target="_blank"
+                    rel="noreferrer"
+                  >
+                    高德地图查看
+                  </Button>
+                  {poiDetail.tel && (
+                    <Button icon={<PhoneOutlined />} href={`tel:${poiDetail.tel}`}>
+                      拨打电话
+                    </Button>
+                  )}
+                  {typeof poiDetail.food_enrichment?.dianping_url === "string"
+                    && poiDetail.food_enrichment.dianping_url && (
+                    <Button
+                      href={poiDetail.food_enrichment.dianping_url}
+                      target="_blank"
+                      rel="noreferrer"
+                    >
+                      大众点评详情
+                    </Button>
+                  )}
+                  {typeof poiDetail.hotel_enrichment?.ctrip_url === "string"
+                    && poiDetail.hotel_enrichment.ctrip_url && (
+                    <Button
+                      href={poiDetail.hotel_enrichment.ctrip_url}
+                      target="_blank"
+                      rel="noreferrer"
+                    >
+                      携程详情
+                    </Button>
+                  )}
+                  </Space>
+                </div>
+              </div>
+            ) : (
+              <Empty image={Empty.PRESENTED_IMAGE_SIMPLE} description="暂无可展示详情" />
+            )}
+          </Drawer>
+          <Drawer
+            title={busPanel?.mode === "route" && selectedBusRoute
+              ? `${selectedBusRoute.line_name} · ${selectedBusRoute.direction}`
+              : busPanel?.mode === "line"
+                ? `${busPanel.lineName}公交路线`
+              : busPanel?.mode === "stop" && selectedBusStop
+                ? `${selectedBusStop.name}（公交站）`
+                : "荔波公交线路"}
+            placement="left"
+            width={420}
+            open={Boolean(busPanel)}
+            onClose={closeBusPanel}
+            getContainer={false}
+            mask={false}
+            rootStyle={{ position: "absolute", zIndex: 61 }}
+            styles={{ body: { padding: 16, overflowY: "auto" } }}
+          >
+            {busPanel?.mode === "list" && (
+              <>
+                <Alert
+                  type="success"
+                  showIcon
+                  message="选择需要查看的公交路线"
+                  description="每条路线使用独立颜色；点击运行方向后可查看班次、票价、里程和完整站序。"
+                  style={{ marginBottom: 14 }}
+                />
+                <div style={{ display: "flex", flexDirection: "column", gap: 10 }}>
+                  {busLines.map((lineName) => {
+                    const directions = busRoutes.filter((route) => route.line_name === lineName);
+                    const color = busLineColor(lineName);
+                    return (
+                      <div
+                        key={lineName}
+                        style={{
+                          border: "1px solid #edf2f7",
+                          borderLeft: `5px solid ${color}`,
+                          borderRadius: 10,
+                          padding: "10px 12px",
+                          background: "#fff",
+                        }}
+                      >
+                        <b>{lineName}</b>
+                        <div style={{ display: "flex", flexDirection: "column", gap: 6, marginTop: 8 }}>
+                          {directions.map((route) => (
+                            <Button
+                              key={route.route_id}
+                              type="text"
+                              block
+                              onClick={() => openBusRoute(route)}
+                              style={{
+                                height: "auto",
+                                padding: "7px 8px",
+                                textAlign: "left",
+                                whiteSpace: "normal",
+                                border: "1px solid #f0f0f0",
+                              }}
+                            >
+                              <div style={{ width: "100%" }}>
+                                <div style={{ fontSize: 13, color: "#1f2329" }}>{route.direction}</div>
+                                <div style={{ marginTop: 3, fontSize: 12, color: "#667085" }}>
+                                  {route.stop_count} 站 · {route.distance_km} 公里 · {route.fare_yuan} 元
+                                </div>
+                              </div>
+                            </Button>
+                          ))}
+                        </div>
+                      </div>
+                    );
+                  })}
+                </div>
+              </>
+            )}
+
+            {busPanel?.mode === "line" && selectedBusLineRoutes.length > 0 && (
+              <>
+                <Alert
+                  type="info"
+                  showIcon
+                  message={`地图已突出显示${busPanel.lineName}`}
+                  description="两个运行方向使用相同线路颜色，公交站名称显示在站牌右侧。"
+                  style={{ marginBottom: 14 }}
+                />
+                <div style={{ display: "flex", flexDirection: "column", gap: 10 }}>
+                  {selectedBusLineRoutes.map((route) => (
+                    <Button
+                      key={route.route_id}
+                      block
+                      onClick={() => openBusRoute(route)}
+                      style={{
+                        height: "auto",
+                        padding: "12px 14px",
+                        textAlign: "left",
+                        whiteSpace: "normal",
+                        borderLeft: `5px solid ${busLineColor(route.line_name)}`,
+                      }}
+                    >
+                      <div style={{ width: "100%" }}>
+                        <div style={{ fontWeight: 700, color: "#1f2329" }}>{route.direction}</div>
+                        <div style={{ color: "#667085", fontSize: 12, marginTop: 5 }}>
+                          {route.stop_count} 站 · {route.distance_km} 公里 · {route.fare_yuan} 元
+                        </div>
+                        <div style={{ color: "#667085", fontSize: 12, marginTop: 2 }}>
+                          首班 {route.first_bus} · 末班 {route.last_bus}
+                        </div>
+                      </div>
+                    </Button>
+                  ))}
+                </div>
+              </>
+            )}
+
+            {busPanel?.mode === "route" && selectedBusRoute && (
+              <>
+                <Space wrap style={{ marginBottom: 12 }}>
+                  <Tag color={busLineColor(selectedBusRoute.line_name)}>{selectedBusRoute.line_name}</Tag>
+                  <Tag color="green">
+                    {resolvedBusPaths[selectedBusRoute.route_id] ? "高德道路轨迹" : "站序连线"}
+                  </Tag>
+                  <Tag>{selectedBusRoute.stop_count} 站</Tag>
+                </Space>
+                <Descriptions
+                  size="small"
+                  column={1}
+                  colon={false}
+                  labelStyle={{ width: 86, color: "#667085" }}
+                  items={[
+                    { key: "direction", label: "运行方向", children: selectedBusRoute.direction },
+                    { key: "time", label: "运营时间", children: `${selectedBusRoute.first_bus}－${selectedBusRoute.last_bus}` },
+                    { key: "fare", label: "票价", children: `${selectedBusRoute.fare_yuan} 元` },
+                    { key: "distance", label: "线路里程", children: `${selectedBusRoute.distance_km} 公里` },
+                    { key: "source", label: "图谱来源", children: "荔波城区公交_高德数据.xlsx" },
+                  ]}
+                />
+                <Divider orientation="left" plain>途经站点</Divider>
+                <Timeline
+                  items={selectedBusRoute.stops.map((stop, index) => ({
+                    color: index === 0 || index === selectedBusRoute.stops.length - 1
+                      ? busLineColor(selectedBusRoute.line_name)
+                      : "green",
+                    children: (
+                      <Button
+                        type="link"
+                        size="small"
+                        onClick={() => {
+                          const networkStop = busStopNetwork.get(stop.stop_id);
+                          if (networkStop) openBusStop(networkStop);
+                        }}
+                        style={{ padding: 0, height: "auto", color: "#1f2329" }}
+                      >
+                        {String(stop.sequence).padStart(2, "0")} · {stop.name}
+                      </Button>
+                    ),
+                  }))}
+                />
+              </>
+            )}
+
+            {busPanel?.mode === "stop" && selectedBusStop && (
+              <>
+                <Alert
+                  type="info"
+                  showIcon
+                  message="已录入知识图谱的公交站"
+                  description={`坐标 ${selectedBusStop.lng}, ${selectedBusStop.lat}`}
+                  style={{ marginBottom: 14 }}
+                />
+                <Divider orientation="left" plain>途经线路</Divider>
+                <div style={{ display: "flex", flexDirection: "column", gap: 8 }}>
+                  {selectedBusStop.routes.map((route) => (
+                    <Button
+                      key={`${route.route_id}-${selectedBusStop.stop_id}`}
+                      block
+                      onClick={() => openBusRoute(route)}
+                      style={{ height: "auto", padding: "9px 12px", textAlign: "left", whiteSpace: "normal" }}
+                    >
+                      <div style={{ width: "100%" }}>
+                        <Space size={6}>
+                          <span
+                            style={{
+                              width: 9,
+                              height: 9,
+                              borderRadius: 99,
+                              background: busLineColor(route.line_name),
+                              display: "inline-block",
+                            }}
+                          />
+                          <b>{route.line_name}</b>
+                        </Space>
+                        <div style={{ color: "#667085", fontSize: 12, marginTop: 3 }}>{route.direction}</div>
+                      </div>
+                    </Button>
+                  ))}
+                </div>
+                <Divider />
+                <Button
+                  type="primary"
+                  icon={<CompassOutlined />}
+                  href={poiNavigationUrl(selectedBusStop)}
+                  target="_blank"
+                  rel="noreferrer"
+                >
+                  高德地图查看
+                </Button>
+              </>
+            )}
+          </Drawer>
         </div>
       </div>
     </div>
@@ -333,7 +3606,7 @@ function GuizhouKnowledgeMap({ cov }: { cov: Cov | null }) {
 
 export default function SuperAgentPanel() {
   const [run, setRun] = useState<Record<string, any> | null>(null);
-  const [cov, setCov] = useState<Cov | null>(null);
+  const [cov, setCov] = useState<CoverageSnapshot | null>(null);
   const [tasks, setTasks] = useState<any[]>([]);
   const [busy, setBusy] = useState(false);
   const timer = useRef<ReturnType<typeof setInterval> | null>(null);
@@ -536,7 +3809,7 @@ export default function SuperAgentPanel() {
         </div>
       )}
 
-      <GuizhouKnowledgeMap cov={cov} />
+      <KnowledgeMap cov={cov} />
 
       {escalatedCats.length > 0 && (
         <Alert
diff --git a/admin-web/src/panels/plaza/TravelAgencyAssistantPanel.tsx b/admin-web/src/panels/plaza/TravelAgencyAssistantPanel.tsx
index ac5f6d4..b52a845 100644
--- a/admin-web/src/panels/plaza/TravelAgencyAssistantPanel.tsx
+++ b/admin-web/src/panels/plaza/TravelAgencyAssistantPanel.tsx
@@ -14,6 +14,7 @@ import {
   ThunderboltOutlined,
 } from "@ant-design/icons";
 import { travelAssistantQuery } from "../../api";
+import PassportOcrCard from "./PassportOcrCard";
 
 const { Paragraph, Text, Title } = Typography;
 const { TextArea } = Input;
@@ -134,7 +135,7 @@ export default function TravelAgencyAssistantPanel() {
   const [payload, setPayload] = useState<AssistantPayload | null>(null);
   const [returnState, setReturnState] = useState<{ question: string; payload: AssistantPayload } | null>(null);
   const [loading, setLoading] = useState(false);
-  const [useLlm, setUseLlm] = useState(false);
+  const [useLlm] = useState(true);
 
   const run = async (value = question, options: { preservePrevious?: boolean } = {}) => {
     const text = value.trim();
@@ -163,7 +164,7 @@ export default function TravelAgencyAssistantPanel() {
           <h2>客服行程方案助手</h2>
           <Space wrap>
             <Tag color="green">旅行社资料库</Tag>
-            <Tag color="blue">规则快速解析</Tag>
+            <Tag color="blue">LLM 图查询</Tag>
             <Tag color="purple">知识图谱检索</Tag>
             {payload?.trace?.plan_candidates !== undefined && (
               <Tag color="cyan">候选方案 {payload.trace.plan_candidates}</Tag>
@@ -180,6 +181,10 @@ export default function TravelAgencyAssistantPanel() {
 
       <AgentTestConsole payload={payload} />
 
+      <div style={{ marginBottom: 16 }}>
+        <PassportOcrCard />
+      </div>
+
       <Row gutter={16} align="stretch">
         <Col xs={24} xl={7}>
           <Card className="travel-panel" title={<><SendOutlined /> 客户咨询</>} size="small">
@@ -191,9 +196,9 @@ export default function TravelAgencyAssistantPanel() {
             />
             <div className="travel-llm-toggle">
               <Space>
-                <Switch size="small" checked={useLlm} onChange={setUseLlm} />
-                <Text type="secondary">大模型意图解析</Text>
-                <Tag color={useLlm ? "blue" : "default"}>{useLlm ? "已开启" : "默认关闭"}</Tag>
+                <Switch size="small" checked={useLlm} disabled />
+                <Text type="secondary">大模型图查询</Text>
+                <Tag color="blue">固定启用</Tag>
               </Space>
             </div>
             <Button
@@ -317,8 +322,8 @@ function AgentTestConsole({ payload }: { payload: AssistantPayload | null }) {
     : [
       { name: "接收问题", status: "ready", detail: "客服输入或客服系统 API 传入客户原话。" },
       { name: "意图解析", status: "ready", detail: "抽取人数、天数、景点、酒店、用车和预算。" },
-      { name: "图谱召回", status: "ready", detail: "按线路、景点、酒店、餐饮、车辆、费用规则查询。" },
-      { name: "排序/组合", status: "ready", detail: "返回固定线路或可替换资源池。" },
+      { name: "图谱召回", status: "ready", detail: "LLM 生成 Cypher 后执行 FalkorDB 只读查询。" },
+      { name: "答案组织", status: "ready", detail: "基于图查询证据组织客服话术、风险边界和追问。" },
       { name: "证据边界", status: "ready", detail: "输出核价、余位、不可承诺项和追问。" },
     ];
   const summary = trace.quality_summary || {};
diff --git a/admin-web/src/panels/plaza/UserExperiencePanel.tsx b/admin-web/src/panels/plaza/UserExperiencePanel.tsx
index 7e9ff40..fffeee8 100644
--- a/admin-web/src/panels/plaza/UserExperiencePanel.tsx
+++ b/admin-web/src/panels/plaza/UserExperiencePanel.tsx
@@ -366,7 +366,7 @@ export default function UserExperiencePanel() {
           trace,
           plans: data?.plans || [],
           follow_up_questions: data?.follow_up_questions || [],
-          risk_notes: warnings,
+          risk_notes: Array.isArray(data?.risk_notes) && data.risk_notes.length ? data.risk_notes : warnings,
         });
         setActiveId("");
         return;
diff --git a/admin-web/src/panels/system/AgentSettings.tsx b/admin-web/src/panels/system/AgentSettings.tsx
index ba86e88..eea77e4 100644
--- a/admin-web/src/panels/system/AgentSettings.tsx
+++ b/admin-web/src/panels/system/AgentSettings.tsx
@@ -1,11 +1,11 @@
 import { useEffect, useState, useCallback } from "react";
 import {
   Card, Form, Input, InputNumber, Switch, Button, message, Row, Col,
-  Spin, Tag, Space, Divider, Tooltip,
+  Spin, Tag, Space, Divider, Tooltip, Alert,
 } from "antd";
 import {
   SaveOutlined, RobotOutlined, EyeOutlined, ThunderboltOutlined,
-  EditOutlined, UpOutlined, PlusOutlined, DeleteOutlined,
+  EditOutlined, UpOutlined, PlusOutlined, DeleteOutlined, CopyOutlined,
 } from "@ant-design/icons";
 import { Select } from "antd";
 
@@ -28,6 +28,19 @@ type DistillModel = {
 };
 type Config = {
   global: { base_url: string; model: string; api_key: string; timeout: number };
+  api_access: {
+    api_keys: string;
+    default_graph: string;
+    default_use_llm: boolean;
+    default_llm_fusion: boolean;
+    qa_llm: {
+      base_url: string;
+      model: string;
+      api_key: string;
+      timeout: number;
+      max_tokens?: number | null;
+    };
+  };
   thresholds: { audit_hit: number; audit_gap: number; aligner_auto_merge: number };
   agents: Record<string, AgentCfg>;
   distill: {
@@ -70,6 +83,55 @@ export default function AgentSettings() {
 
   const setGlobal = (k: string, v: any) =>
     setCfg((c) => c && ({ ...c, global: { ...c.global, [k]: v } }));
+  const setApiAccess = (k: string, v: any) =>
+    setCfg((c) => {
+      if (!c) return c;
+      const current = c.api_access || {
+        api_keys: "",
+        default_graph: "baixinghui_travel_agency",
+        default_use_llm: true,
+        default_llm_fusion: true,
+        qa_llm: {
+          base_url: "",
+          model: "deepseek-chat",
+          api_key: "",
+          timeout: 30,
+          max_tokens: 1600,
+        },
+      };
+      return { ...c, api_access: { ...current, [k]: v } };
+    });
+  const setQaLlm = (k: string, v: any) =>
+    setCfg((c) => {
+      if (!c) return c;
+      const current = c.api_access || {
+        api_keys: "",
+        default_graph: "baixinghui_travel_agency",
+        default_use_llm: true,
+        default_llm_fusion: true,
+        qa_llm: {
+          base_url: "",
+          model: "deepseek-chat",
+          api_key: "",
+          timeout: 30,
+          max_tokens: 1600,
+        },
+      };
+      const qaLlm = current.qa_llm || {
+        base_url: "",
+        model: "deepseek-chat",
+        api_key: "",
+        timeout: 30,
+        max_tokens: 1600,
+      };
+      return {
+        ...c,
+        api_access: {
+          ...current,
+          qa_llm: { ...qaLlm, [k]: v },
+        },
+      };
+    });
   const setThreshold = (k: string, v: any) =>
     setCfg((c) => c && ({ ...c, thresholds: { ...c.thresholds, [k]: v } }));
   const setAgent = (key: string, k: string, v: any) =>
@@ -176,6 +238,92 @@ export default function AgentSettings() {
   }
 
   const labelStyle = { fontSize: 13, color: "#666", marginBottom: 4 };
+  const apiOrigin = typeof window !== "undefined" ? window.location.origin : "";
+  const openApiPath = "/v1/openapi/knowledge-qa/query";
+  const compatApiPath = "/v1/admin/travel/customer-service-query";
+  const openApiUrl = `${apiOrigin}${openApiPath}`;
+  const compatApiUrl = `${apiOrigin}${compatApiPath}`;
+  const authHeaderExample = "X-KG-API-Key: <由管理员提供的接口 Key>";
+  const requestExample = `{
+  "request_id": "crm-msg-20260610-0001",
+  "question": "黄小西三日游多少钱？",
+  "graph_name": "baixinghui_travel_agency",
+  "session_id": "customer-session-001",
+  "channel": "online_service",
+  "customer_id": "customer-001",
+  "use_llm": true,
+  "llm_fusion": true
+}`;
+  const curlExample = `curl ${openApiUrl} \\
+  -H 'Content-Type: application/json' \\
+  -H '${authHeaderExample}' \\
+  -d '${requestExample}'`;
+  const responseExample = `{
+  "request_id": "crm-msg-20260610-0001",
+  "trace_id": "trc_xxx",
+  "graph_name": "baixinghui_travel_agency",
+  "customer_reply": "可直接发给客户的话术",
+  "answer": "完整问答结果",
+  "knowledge": {
+    "plans": [],
+    "evidence": []
+  },
+  "risk_notes": [],
+  "trace": {
+    "latency_ms": 24875,
+    "response_mode": "llm_graph_qa"
+  }
+}`;
+  const fallbackCopyText = (text: string) => {
+    const textarea = document.createElement("textarea");
+    textarea.value = text;
+    textarea.setAttribute("readonly", "true");
+    textarea.style.position = "fixed";
+    textarea.style.left = "-9999px";
+    textarea.style.top = "0";
+    textarea.style.opacity = "0";
+    document.body.appendChild(textarea);
+    textarea.focus();
+    textarea.select();
+    textarea.setSelectionRange(0, textarea.value.length);
+    let copied = false;
+    try {
+      copied = document.execCommand("copy");
+    } catch {
+      copied = false;
+    } finally {
+      document.body.removeChild(textarea);
+    }
+    return copied;
+  };
+  const copyText = async (text: string, successText = "已复制") => {
+    try {
+      if (navigator.clipboard && window.isSecureContext) {
+        await navigator.clipboard.writeText(text);
+        message.success(successText);
+        return;
+      }
+      if (fallbackCopyText(text)) {
+        message.success(successText);
+        return;
+      }
+      await navigator.clipboard.writeText(text);
+      message.success(successText);
+    } catch {
+      message.error("浏览器禁止自动复制，请手动选中文本后复制");
+    }
+  };
+  const codeBlockStyle = {
+    margin: 0,
+    padding: 12,
+    background: "#f7f8fa",
+    border: "1px solid #e8e8e8",
+    borderRadius: 6,
+    fontSize: 12,
+    lineHeight: 1.6,
+    whiteSpace: "pre-wrap" as const,
+    wordBreak: "break-word" as const,
+  };
 
   return (
     <div style={{ maxWidth: "100%", paddingRight: 8,
@@ -189,6 +337,9 @@ export default function AgentSettings() {
 
       {/* Global LLM */}
       <Card size="small" title="全局 LLM 配置" style={{ marginBottom: 16 }}>
+        <p style={{ color: "#999", fontSize: 12, marginTop: 0 }}>
+          这里配置客服问答、LLM 图查询、意图解析和话术融合默认使用的大模型。模型服务需要兼容 OpenAI Chat Completions。
+        </p>
         <Row gutter={16}>
           <Col span={18}>
             <div style={labelStyle}>基础 URL</div>
@@ -740,7 +891,244 @@ export default function AgentSettings() {
         })}
       </Row>
 
-      <div style={{ textAlign: "right", marginTop: 8, order: 3 }}>
+      <Card
+        size="small"
+        title="外部图谱问答 API"
+        style={{ marginTop: 8, marginBottom: 16, order: 4 }}
+        extra={
+          <Space size={6}>
+            <Tag color="green">正式开放</Tag>
+            <Tag color="blue">Key 鉴权</Tag>
+          </Space>
+        }
+      >
+        <p style={{ color: "#999", fontSize: 12, marginTop: 0 }}>
+          给第三方客服系统、CRM 或小程序调用百姓惠知识图谱问答时使用。调用方传入用户自然语言问题，接口返回可直接回复客户的话术和图谱证据。请求头必须带
+          <code style={{ margin: "0 4px" }}>X-KG-API-Key</code>
+          ，服务端会用这里保存的 Key 校验，并优先使用本块的问答 LLM 模型生成客服话术。
+        </p>
+        <Row gutter={16}>
+          <Col span={12}>
+            <div style={labelStyle}>正式开放接口（给第三方使用）</div>
+            <Space.Compact style={{ width: "100%" }}>
+              <Input value={openApiUrl} readOnly />
+              <Button icon={<CopyOutlined />} onClick={() => copyText(openApiUrl, "接口地址已复制")}>
+                复制
+              </Button>
+            </Space.Compact>
+          </Col>
+          <Col span={12}>
+            <div style={labelStyle}>认证请求头</div>
+            <Space.Compact style={{ width: "100%" }}>
+              <Input value={authHeaderExample} readOnly />
+              <Button icon={<CopyOutlined />} onClick={() => copyText(authHeaderExample, "请求头已复制")}>
+                复制
+              </Button>
+            </Space.Compact>
+            <div style={{ color: "#999", fontSize: 12, marginTop: 4 }}>
+              这里的 <code>API Key</code> 由管理员提供；不是问答模型 API Key，也不会在页面明文展示。
+            </div>
+          </Col>
+        </Row>
+        <Row gutter={16} style={{ marginTop: 12 }}>
+          <Col span={8}>
+            <div style={labelStyle}>接口协议</div>
+            <Input value="POST + JSON / UTF-8" readOnly />
+          </Col>
+          <Col span={8}>
+            <div style={labelStyle}>支持的鉴权方式</div>
+            <Input value="X-KG-API-Key / X-API-Key / Bearer" readOnly />
+          </Col>
+          <Col span={8}>
+            <div style={labelStyle}>超时建议</div>
+            <Input value="第三方建议设置 90-180 秒" readOnly />
+          </Col>
+        </Row>
+        <Row gutter={16} style={{ marginTop: 12 }}>
+          <Col span={12}>
+            <div style={labelStyle}>兼容旧接口（已有系统可继续用）</div>
+            <Input value={compatApiUrl} readOnly />
+          </Col>
+          <Col span={12}>
+            <div style={labelStyle}>第三方系统主要读取</div>
+            <Input value="customer_reply；trace_id 用于排查；knowledge.evidence 用于证据展示" readOnly />
+          </Col>
+        </Row>
+        <div style={{ marginTop: 12, padding: 12, background: "#fafafa", border: "1px solid #f0f0f0", borderRadius: 6 }}>
+          <div style={{ fontWeight: 600, marginBottom: 8 }}>第三方接入流程</div>
+          <ol style={{ margin: 0, paddingLeft: 18, color: "#666", fontSize: 13, lineHeight: 1.8 }}>
+            <li>在下面填写一个或多个 API Key，点击页面右上角或底部“保存配置”。</li>
+            <li>把“正式开放接口”和 API Key 发给第三方系统，第三方用 POST JSON 调用。</li>
+            <li>第三方请求体至少传 <code>question</code>；建议同时传 <code>request_id</code>、<code>session_id</code>、<code>channel</code> 方便排查。</li>
+            <li>第三方优先使用返回里的 <code>customer_reply</code> 展示给客服或客户；需要审计时保存 <code>trace_id</code> 和 <code>knowledge.evidence</code>。</li>
+          </ol>
+        </div>
+        <Row gutter={16} style={{ marginTop: 12 }}>
+          <Col span={12}>
+            <div style={labelStyle}>默认查询图谱（请求未传 graph_name 时使用）</div>
+            <Input
+              value={cfg.api_access?.default_graph || "baixinghui_travel_agency"}
+              onChange={(e) => setApiAccess("default_graph", e.target.value)}
+              placeholder="baixinghui_travel_agency"
+            />
+            <div style={{ color: "#999", fontSize: 12, marginTop: 4 }}>
+              第三方可在请求体传 <code>graph_name</code> 覆盖默认图谱；兼容 <code>knowledge_graph</code>、<code>kg</code>、<code>graph</code>。
+            </div>
+          </Col>
+          <Col span={12}>
+            <div style={labelStyle}>默认 LLM 策略</div>
+            <Space wrap>
+              <Space size={6}>
+                <Switch
+                  size="small"
+                  checked={cfg.api_access?.default_use_llm ?? true}
+                  onChange={(v) => setApiAccess("default_use_llm", v)}
+                />
+                <span style={{ fontSize: 13 }}>意图解析</span>
+              </Space>
+              <Space size={6}>
+                <Switch
+                  size="small"
+                  checked={cfg.api_access?.default_llm_fusion ?? true}
+                  onChange={(v) => setApiAccess("default_llm_fusion", v)}
+                />
+                <span style={{ fontSize: 13 }}>客服话术融合</span>
+              </Space>
+            </Space>
+          </Col>
+        </Row>
+        <Divider orientation="left" style={{ marginTop: 18 }}>
+          第三方调用示例
+        </Divider>
+        <Row gutter={16}>
+          <Col span={12}>
+            <Space style={{ display: "flex", justifyContent: "space-between", marginBottom: 6 }}>
+              <div style={labelStyle}>请求 JSON</div>
+              <Button size="small" icon={<CopyOutlined />} onClick={() => copyText(requestExample, "请求 JSON 已复制")}>
+                复制
+              </Button>
+            </Space>
+            <pre style={codeBlockStyle}>{requestExample}</pre>
+          </Col>
+          <Col span={12}>
+            <Space style={{ display: "flex", justifyContent: "space-between", marginBottom: 6 }}>
+              <div style={labelStyle}>curl 联调命令</div>
+              <Button size="small" icon={<CopyOutlined />} onClick={() => copyText(curlExample, "curl 示例已复制")}>
+                复制
+              </Button>
+            </Space>
+            <pre style={codeBlockStyle}>{curlExample}</pre>
+          </Col>
+        </Row>
+        <Divider orientation="left" style={{ marginTop: 18 }}>
+          请求字段说明
+        </Divider>
+        <div style={{ display: "grid", gridTemplateColumns: "170px 90px 1fr", rowGap: 8, columnGap: 12, fontSize: 13 }}>
+          <strong>字段</strong><strong>是否必填</strong><strong>说明</strong>
+          <code>question</code><Tag color="red">必填</Tag><span>用户或客服输入的自然语言问题，例如“黄小西三日游多少钱”。兼容 <code>text</code>、<code>query</code>。</span>
+          <code>request_id</code><Tag>可选</Tag><span>第三方系统请求 ID，用于幂等排查和日志关联；不传时服务端自动生成。</span>
+          <code>session_id</code><Tag>可选</Tag><span>客服会话 ID，便于把多轮咨询归到同一个会话。</span>
+          <code>channel</code><Tag>可选</Tag><span>来源渠道，例如 <code>web</code>、<code>wechat</code>、<code>online_service</code>。</span>
+          <code>customer_id</code><Tag>可选</Tag><span>第三方客户 ID；也兼容 <code>external_user_id</code>。</span>
+          <code>graph_name</code><Tag>可选</Tag><span>指定查询图谱；不传时使用上方默认图谱。兼容 <code>knowledge_graph</code>、<code>kg</code>、<code>graph</code>。</span>
+          <code>use_llm</code><Tag>可选</Tag><span>是否启用 LLM 图查询和意图理解，默认跟随本页开关。</span>
+          <code>llm_fusion</code><Tag>可选</Tag><span>是否让 LLM 基于图谱证据组织客服话术，默认跟随本页开关。</span>
+        </div>
+        <Divider orientation="left" style={{ marginTop: 18 }}>
+          返回字段说明
+        </Divider>
+        <Row gutter={16}>
+          <Col span={12}>
+            <div style={{ display: "grid", gridTemplateColumns: "140px 1fr", rowGap: 8, columnGap: 12, fontSize: 13 }}>
+              <strong>customer_reply</strong><span>客服可直接发送给客户的简洁话术。</span>
+              <strong>answer</strong><span>完整回答，适合后台查看。</span>
+              <strong>knowledge.plans</strong><span>命中的线路、方案或证据卡片。</span>
+              <strong>knowledge.evidence</strong><span>图谱证据，适合质检和溯源。</span>
+              <strong>risk_notes</strong><span>不可直接承诺、需要二次核实的事项。</span>
+              <strong>trace_id</strong><span>排查问题时给后台技术人员定位链路。</span>
+            </div>
+          </Col>
+          <Col span={12}>
+            <pre style={codeBlockStyle}>{responseExample}</pre>
+          </Col>
+        </Row>
+        <Divider orientation="left" style={{ marginTop: 18 }}>
+          常见错误码
+        </Divider>
+        <Row gutter={16}>
+          <Col span={6}><Tag color="red">401</Tag> API Key 缺失或无效</Col>
+          <Col span={6}><Tag color="orange">400</Tag> 未传 question</Col>
+          <Col span={6}><Tag color="gold">502</Tag> 图查询或 LLM 调用失败</Col>
+          <Col span={6}><Tag color="blue">503</Tag> 后台未配置 API Key</Col>
+        </Row>
+        <Divider orientation="left" style={{ marginTop: 18 }}>
+          问答环节 LLM 模型
+        </Divider>
+        <p style={{ color: "#999", fontSize: 12, marginTop: -8 }}>
+          这组模型只服务外部客服问答和话术融合。填写后优先使用这里；留空则继承上方全局 LLM 配置。这里的 API Key 是大模型服务 Key，不是第三方访问接口用的 API Key。
+        </p>
+        <Row gutter={16}>
+          <Col span={12}>
+            <div style={labelStyle}>基础 URL</div>
+            <Input
+              value={cfg.api_access?.qa_llm?.base_url || ""}
+              onChange={(e) => setQaLlm("base_url", e.target.value)}
+              placeholder={cfg.global.base_url || "https://api.deepseek.com/v1"}
+            />
+          </Col>
+          <Col span={12}>
+            <div style={labelStyle}>模型 ID</div>
+            <Input
+              value={cfg.api_access?.qa_llm?.model || ""}
+              onChange={(e) => setQaLlm("model", e.target.value)}
+              placeholder={cfg.global.model || "deepseek-chat"}
+            />
+          </Col>
+        </Row>
+        <Row gutter={16} style={{ marginTop: 12 }}>
+          <Col span={12}>
+            <div style={labelStyle}>超时 (秒)</div>
+            <InputNumber
+              min={5}
+              max={300}
+              style={{ width: "100%" }}
+              value={cfg.api_access?.qa_llm?.timeout ?? 30}
+              onChange={(v) => setQaLlm("timeout", v ?? 30)}
+            />
+          </Col>
+          <Col span={12}>
+            <div style={labelStyle}>最大输出 tokens（数值，不是 API Key）</div>
+            <InputNumber
+              min={256}
+              max={200000}
+              step={512}
+              style={{ width: "100%" }}
+              value={cfg.api_access?.qa_llm?.max_tokens ?? 1600}
+              placeholder="如 2048 / 8192 / 131072"
+              onChange={(v) => setQaLlm("max_tokens", v ?? 1600)}
+            />
+          </Col>
+        </Row>
+        <Row gutter={16} style={{ marginTop: 12 }}>
+          <Col span={24}>
+            <div style={labelStyle}>问答模型 API Key（大模型服务 Key，留空继承全局）</div>
+            <Input.Password
+              value={cfg.api_access?.qa_llm?.api_key || ""}
+              onChange={(e) => setQaLlm("api_key", e.target.value)}
+              placeholder="如 sk-...；留空则使用全局 LLM API Key"
+              autoComplete="new-password"
+            />
+          </Col>
+        </Row>
+        <Alert
+          type="info"
+          showIcon
+          style={{ marginTop: 8 }}
+          message="区分两个 Key：上面的“接口访问 API Key”发给第三方系统；这里的“问答模型 API Key”只用于本系统调用大模型，不应提供给第三方。"
+        />
+      </Card>
+
+      <div style={{ textAlign: "right", marginTop: 8, order: 5 }}>
         <Button type="primary" icon={<SaveOutlined />} loading={saving} onClick={save}>
           保存配置
         </Button>
diff --git a/admin-web/src/styles.css b/admin-web/src/styles.css
index 3a922c4..b77dac6 100644
--- a/admin-web/src/styles.css
+++ b/admin-web/src/styles.css
@@ -1204,6 +1204,97 @@ body { margin: 0; font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Ro
   font-size: 14px;
 }
 
+.manual-markdown-note {
+  display: flex;
+  align-items: center;
+  gap: 8px;
+  width: 100%;
+  min-width: 0;
+  margin-top: 10px;
+  padding: 9px 12px;
+  border: 1px solid #d9e7ff;
+  border-radius: 8px;
+  background: #f6faff;
+  color: inherit;
+  cursor: pointer;
+  text-align: left;
+  transition: border-color .2s ease, background .2s ease;
+}
+
+.manual-markdown-note:hover {
+  border-color: #91caff;
+  background: #eef6ff;
+}
+
+.manual-markdown-note .anticon {
+  flex: 0 0 auto;
+  color: #1677ff;
+  font-size: 16px;
+}
+
+.manual-markdown-note .ant-typography {
+  flex: 1 1 auto;
+  min-width: 0;
+}
+
+.manual-markdown-note > span:last-child {
+  flex: 0 0 auto;
+  color: #1677ff;
+  font-size: 13px;
+  font-weight: 600;
+}
+
+.manual-markdown-preview {
+  min-height: 360px;
+  padding: 18px 20px;
+  border: 1px solid #edf0f5;
+  border-radius: 8px;
+  background: #fff;
+  color: #1f2937;
+  line-height: 1.75;
+}
+
+.manual-markdown-preview h1,
+.manual-markdown-preview h2,
+.manual-markdown-preview h3,
+.manual-markdown-preview h4 {
+  margin: 14px 0 8px;
+}
+
+.manual-markdown-preview p {
+  margin: 0 0 8px;
+}
+
+.manual-markdown-blank {
+  height: 10px;
+}
+
+.manual-markdown-list-item {
+  position: relative;
+  margin-bottom: 6px;
+  padding-left: 18px;
+}
+
+.manual-markdown-list-item::before {
+  position: absolute;
+  left: 4px;
+  content: "•";
+  color: #1677ff;
+}
+
+.manual-markdown-table-line,
+.manual-markdown-source {
+  font-family: ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", monospace;
+}
+
+.manual-markdown-table-line {
+  overflow-x: auto;
+  margin: 0 0 6px;
+  padding: 6px 8px;
+  border-radius: 6px;
+  background: #f8fafc;
+}
+
 .manual-preview-box {
   padding: 18px 20px;
   border: 1px solid #edf0f5;
diff --git a/app/aliyun_ocr.py b/app/aliyun_ocr.py
new file mode 100644
index 0000000..781c902
--- /dev/null
+++ b/app/aliyun_ocr.py
@@ -0,0 +1,114 @@
+"""阿里云 OCR 客户端封装（ocr-api 2021-07-07）。
+
+只关注当前需要的能力——RecognizePassport（护照识别）。
+其它证件接口（身份证、行驶证…）按需扩展即可，签名/客户端复用 _build_client。
+
+配置项 (app.config.settings):
+- aliyun_ocr_access_key_id
+- aliyun_ocr_access_key_secret
+- aliyun_ocr_endpoint  (默认 ocr-api.cn-hangzhou.aliyuncs.com)
+"""
+from __future__ import annotations
+
+import json
+from functools import lru_cache
+from io import BytesIO
+from typing import Any
+
+from app.config import settings
+
+
+class OcrConfigError(RuntimeError):
+    """AK/SK 未配置等可恢复错误，路由层应返回 503。"""
+
+
+class OcrCallError(RuntimeError):
+    """阿里云返回非 200 或网络异常等运行期错误。"""
+
+
+@lru_cache(maxsize=1)
+def _build_client():  # 延迟导入 SDK，缺包时给出明确提示
+    try:
+        from alibabacloud_ocr_api20210707.client import Client
+        from alibabacloud_tea_openapi.models import Config
+    except ImportError as exc:  # noqa: BLE001
+        raise OcrConfigError(
+            "未安装阿里云 OCR SDK，请执行: pip install alibabacloud_ocr_api20210707"
+        ) from exc
+
+    ak = settings.aliyun_ocr_access_key_id.strip()
+    sk = settings.aliyun_ocr_access_key_secret.strip()
+    endpoint = settings.aliyun_ocr_endpoint.strip() or "ocr-api.cn-hangzhou.aliyuncs.com"
+    if not ak or not sk:
+        raise OcrConfigError(
+            "阿里云 OCR 未配置：请在 .env 设置 ALIYUN_OCR_ACCESS_KEY_ID / ALIYUN_OCR_ACCESS_KEY_SECRET"
+        )
+    config = Config(access_key_id=ak, access_key_secret=sk)
+    config.endpoint = endpoint
+    return Client(config)
+
+
+def _parse_data(body: Any) -> dict[str, Any]:
+    """RecognizePassport 返回 body.data 是一段 JSON 字符串，统一解析为 dict。"""
+    raw = getattr(body, "data", None)
+    if raw is None and isinstance(body, dict):
+        raw = body.get("Data") or body.get("data")
+    if raw is None:
+        return {}
+    if isinstance(raw, (dict, list)):
+        return raw  # type: ignore[return-value]
+    try:
+        return json.loads(raw)
+    except (TypeError, ValueError):
+        return {"raw": str(raw)}
+
+
+def recognize_passport(
+    *,
+    image_bytes: bytes | None = None,
+    image_url: str | None = None,
+) -> dict[str, Any]:
+    """识别护照。image_bytes / image_url 至少传一个。
+
+    返回结构（与控制台字段一致，常见字段示例）:
+        {
+            "name": "...",                # 姓名
+            "sex": "M",
+            "country": "CHN",
+            "passport_no": "E12345678",
+            "date_of_birth": "1990-01-01",
+            "date_of_expiry": "2030-01-01",
+            "place_of_birth": "...",
+            ...其它字段透传...
+            "_request_id": "...",         # 便于在阿里云后台溯源
+        }
+    """
+    if not image_bytes and not image_url:
+        raise ValueError("recognize_passport 需要 image_bytes 或 image_url")
+
+    from alibabacloud_ocr_api20210707.models import RecognizePassportRequest
+    from alibabacloud_tea_util.models import RuntimeOptions
+
+    client = _build_client()
+    req_kwargs: dict[str, Any] = {}
+    if image_bytes is not None:
+        req_kwargs["body"] = BytesIO(image_bytes)
+    if image_url:
+        req_kwargs["url"] = image_url
+    request = RecognizePassportRequest(**req_kwargs)
+
+    try:
+        response = client.recognize_passport_with_options(request, RuntimeOptions())
+    except OcrConfigError:
+        raise
+    except Exception as exc:  # noqa: BLE001
+        raise OcrCallError(f"调用阿里云 OCR 失败: {exc}") from exc
+
+    body = getattr(response, "body", response)
+    data = _parse_data(body)
+    request_id = getattr(body, "request_id", None) or (
+        body.get("RequestId") if isinstance(body, dict) else None
+    )
+    if request_id and isinstance(data, dict):
+        data.setdefault("_request_id", request_id)
+    return data
diff --git a/app/api/__init__.py b/app/api/__init__.py
index 71816b4..cba1a80 100644
--- a/app/api/__init__.py
+++ b/app/api/__init__.py
@@ -1,4 +1,4 @@
-"""API router aggregation — all /v1/admin/* routes."""
+"""API router aggregation."""
 from fastapi import APIRouter
 
 from app.api.source_profiles import router as source_profiles_router
@@ -18,9 +18,12 @@ from app.api.publish_jobs import router as publish_jobs_router
 from app.api.graph import router as graph_router
 from app.api.evidence import router as evidence_router
 from app.api.manual_ingest import router as manual_ingest_router
+from app.api.ocr import router as ocr_router
+from app.api.travel_assistant import public_router as travel_assistant_public_router
 from app.api.travel_assistant import router as travel_assistant_router
 
 api_router = APIRouter(prefix="/v1/admin")
+openapi_router = APIRouter(prefix="/v1/openapi")
 
 # Auth
 from app.api.auth import router as auth_router  # noqa: E402
@@ -61,6 +64,7 @@ api_router.include_router(graph_router, tags=["graph"])
 api_router.include_router(evidence_router, tags=["evidence"])
 api_router.include_router(manual_ingest_router, tags=["manual-ingest"])
 api_router.include_router(travel_assistant_router, tags=["travel-assistant"])
+api_router.include_router(ocr_router, tags=["ocr"])
 
 # Agent call logs
 from app.api.agent_call_logs import router as agent_call_logs_router  # noqa: E402
@@ -91,3 +95,6 @@ api_router.include_router(agent_settings_router, tags=["agent-settings"])
 from app.api.super_agent import router as super_agent_router  # noqa: E402
 
 api_router.include_router(super_agent_router, tags=["super-agent"])
+
+# Third-party integration APIs
+openapi_router.include_router(travel_assistant_public_router, tags=["openapi-knowledge-qa"])
diff --git a/app/api/doc_restructure.py b/app/api/doc_restructure.py
new file mode 100644
index 0000000..2ecdd34
--- /dev/null
+++ b/app/api/doc_restructure.py
@@ -0,0 +1,320 @@
+"""文档 MD 的 ②结构化重排 + ③事实级校验（供 8765 上传转换后调用）。
+
+来自 doc-eval 压测验证过的逻辑，纯函数、无外部副作用：
+  · restructure_md(md)  把"忠实转换"的宽表 MD 折叠成「每产品一节 + 干净明细表」的结构化 MD
+  · validate(src, out)  事实级校验：数字保真(幻觉)、按产品价格不串位、内容不被删减、业务规则
+"""
+from __future__ import annotations
+
+import re
+from collections import Counter, defaultdict
+
+NUM = re.compile(r"\d+(?:\.\d+)?")
+
+
+def _clean(s: str) -> str:
+    s = (s or "").replace("<br>", " ")
+    s = re.sub(r"\s+", " ", s).strip()
+    n = len(s)
+    if n > 20:  # 折叠"整串精确对折重复"（源 Excel 合并单元格常存双份）
+        for mid in range(n // 2 - 2, n // 2 + 3):
+            if 0 < mid < n:
+                left, right = s[:mid].strip(), s[mid:].strip()
+                if left and len(left) > 10 and left == right:
+                    return left
+    return s
+
+
+def parse_blocks(md: str):
+    lines = md.splitlines()
+    blocks, i, n, buf = [], 0, len(lines), []
+
+    def flush():
+        if buf:
+            for para in re.split(r"\n\s*\n", "\n".join(buf)):
+                if para.strip():
+                    blocks.append(("text", para.strip()))
+            buf.clear()
+
+    def is_row(s):
+        return s.strip().startswith("|") and s.count("|") >= 2
+
+    def is_sep(s):
+        return bool(re.match(r"^\s*\|[\s:|-]+\|\s*$", s)) and "-" in s
+
+    while i < n:
+        if is_row(lines[i]) and i + 1 < n and is_sep(lines[i + 1]):
+            flush()
+            header = [c.strip() for c in lines[i].strip().strip("|").split("|")]
+            j, rows = i + 2, []
+            while j < n and is_row(lines[j]) and not is_sep(lines[j]):
+                row = [c.strip() for c in lines[j].strip().strip("|").split("|")]
+                rows.append((row + [""] * len(header))[: len(header)])
+                j += 1
+            blocks.append(("table", header, rows))
+            i = j
+        else:
+            buf.append(lines[i])
+            i += 1
+    flush()
+    return blocks
+
+
+def classify_columns(header, rows):
+    n, doc, keys, data = len(rows), [], [], []
+    for c in range(len(header)):
+        vals = [r[c] for r in rows]
+        nonempty = [v for v in vals if v]
+        if not nonempty:
+            continue
+        distinct = len(set(nonempty))
+        changes = sum(1 for k in range(1, n) if vals[k] != vals[k - 1])
+        if distinct <= 1:
+            doc.append(c)
+        elif n >= 4 and changes <= max(1, int(n * 0.45)):
+            keys.append(c)
+        else:
+            data.append(c)
+    return doc, keys, data
+
+
+def _restructure_table(header, rows):
+    doc, keys, data = classify_columns(header, rows)
+    docmeta = {}
+    for c in doc:
+        v = next((r[c] for r in rows if r[c]), "")
+        if v:
+            docmeta[_clean(header[c])] = _clean(v)
+    if not keys or not data:
+        keep = [c for c in range(len(header)) if any(r[c] for r in rows)]
+        out = ["| " + " | ".join(_clean(header[c]) for c in keep) + " |",
+               "| " + " | ".join("---" for _ in keep) + " |"]
+        out += ["| " + " | ".join(r[c] for c in keep) + " |" for r in rows]
+        return docmeta, ["\n".join(out)]
+    title_col = max(keys, key=lambda c: len({r[c] for r in rows if r[c]}))
+    attr_keys = [c for c in keys if c != title_col]
+    sections, cur_key, grp = [], object(), []
+
+    def emit(group):
+        if not group:
+            return
+        seg = [f"## {_clean(group[0][title_col]) or '(未命名)'}"]
+        for c in attr_keys:
+            v = _clean(group[0][c])
+            if v:
+                seg.append(f"- {_clean(header[c])}: {v}")
+        seg.append("")
+        seg.append("| " + " | ".join(_clean(header[c]) for c in data) + " |")
+        seg.append("| " + " | ".join("---" for _ in data) + " |")
+        for r in group:
+            seg.append("| " + " | ".join(_clean(r[c]) for c in data) + " |")
+        sections.append("\n".join(seg))
+
+    for r in rows:
+        kt = tuple(r[c] for c in keys)
+        if kt != cur_key:
+            emit(grp)
+            grp, cur_key = [], kt
+        grp.append(r)
+    emit(grp)
+    return docmeta, sections
+
+
+def restructure_md(md: str, source: str = "") -> str:
+    blocks = parse_blocks(md)
+    docmeta, body, seen, title = {}, [], set(), ""
+    for blk in blocks:
+        if blk[0] == "text":
+            para = blk[1]
+            key = re.sub(r"\s+", "", para)
+            if key in seen:
+                continue
+            seen.add(key)
+            if not title and not para.startswith(("#", "|")):
+                title = para.split("\n")[0]
+                if "\n" not in para:
+                    continue
+            if re.fullmatch(r"##\s*Sheet\d+\s*", para):
+                continue
+            body.append(("text", para))
+        else:
+            dm, secs = _restructure_table(blk[1], blk[2])
+            docmeta.update(dm)
+            body.append(("secs", secs))
+    out = ["## 基本信息", ""]
+    if source:
+        out.append(f"- 来源文件: {source}")
+    for k, v in docmeta.items():
+        out.append(f"- {k}: {v}")
+    out.append("")
+    if title:
+        out.append(f"# {title}\n")
+    for kind, val in body:
+        if kind == "text" and not val.startswith("#"):
+            out.append(val + "\n")
+        elif kind == "text":
+            out.append(val + "\n")
+        else:
+            out.extend(s + "\n" for s in val)
+    return "\n".join(out).strip() + "\n"
+
+
+# ---------- ②-LLM 语义结构化（类型自适应，用于行程单/复杂件；价格表走免费确定性）----------
+STRUCTURE_PROMPT = """你是旅游 ToB 文档结构化助手。把下面从源文件转出的原始 Markdown，重排成"结构化科学 MD"，供后期 LLM 检索入库。
+
+【先判断文档类型，套用对应结构】
+· 报价单/价目表：顶部「## 基本信息」表(供应商/有效期/出发地/币种)；每个产品一个 `## 产品：<名称>` 小节(拼团类型/起订人数/景区小交通费/退费政策等)；价格用「房型 | 成人价 | 儿童价 | 单房差」表；通用规则、参考酒店各自独立小节。
+· 行程单：顶部「## 基本信息」表(产品名/天数/车型/出发地)；按天分 `## D1 <当天路线>`、`## D2 …` 小节，每天完整保留 行程详情/餐食(早中晚)/住宿/交通；费用包含、费用不含、购物场所、预订须知、温馨提示 各自独立小节。
+· 资源表(酒店/车辆/餐厅)：每个资源一个小节 + 属性。
+· 其它：用标题分层、表格如实保留。
+
+【铁律，违反即事故】
+1. 完整保留原文每一条信息、逐条照搬——严禁摘要、严禁概括、严禁删减合并、严禁省略。这是入库用的全量数据；输出篇幅应与原文相当。
+2. 所有数值/价格/日期/时间/电话严格来自原文，一字不改、不新增、不计算、不脑补；看不清就原样抄。
+3. 可纠正明显的"表头误标"(如"车型"列内容其实是"N人拼小团"→改标「拼团类型」)，但只改标签、不改数值。
+4. 元数据用可见的「## 基本信息」表，不要 YAML frontmatter。
+只输出 MD，不要任何解释。"""
+
+
+def resolve_llm_key() -> str | None:
+    """LLM key 解析顺序：环境变量 LLM_API_KEY / DEEPSEEK_API_KEY → ~/.ark_key 文件。"""
+    import os
+    k = os.environ.get("LLM_API_KEY") or os.environ.get("DEEPSEEK_API_KEY")
+    if k:
+        return k.strip()
+    try:
+        with open(os.path.expanduser("~/.ark_key")) as f:
+            return f.read().strip() or None
+    except Exception:
+        return None
+
+
+def structure_llm(md: str, api_key: str) -> str:
+    """调 LLM(默认火山豆包，可用 LLM_BASE_URL/LLM_MODEL 覆盖)做类型自适应结构化，带重试退避。"""
+    import os
+    import time
+    import requests
+    base_url = os.environ.get("LLM_BASE_URL", "https://ark.cn-beijing.volces.com/api/v3")
+    model = os.environ.get("LLM_MODEL", "doubao-seed-2-0-lite-260428")
+    payload = {"model": model, "temperature": 0,
+               "messages": [{"role": "system", "content": STRUCTURE_PROMPT},
+                            {"role": "user", "content": md}]}
+    last = None
+    for attempt in range(4):
+        try:
+            r = requests.post(f"{base_url}/chat/completions",
+                              headers={"Authorization": f"Bearer {api_key}"},
+                              json=payload, timeout=180)
+            r.raise_for_status()
+            return r.json()["choices"][0]["message"]["content"]
+        except requests.exceptions.RequestException as e:
+            last = e
+            if attempt < 3:
+                time.sleep(2 * (attempt + 1))
+    raise last
+
+
+# ---------- ③ 事实级校验 ----------
+def _wide_product_numbers(md: str) -> dict:
+    out = defaultdict(set)
+    for blk in parse_blocks(md):
+        if blk[0] != "table":
+            continue
+        header, rows = blk[1], blk[2]
+        _doc, keys, _data = classify_columns(header, rows)
+        if not keys:
+            continue
+        tcol = max(keys, key=lambda c: len({r[c] for r in rows if r[c]}))
+        for r in rows:
+            for cell in r:
+                out[_clean(r[tcol])].update(NUM.findall(cell))
+    return out
+
+
+def _section_numbers(md: str) -> dict:
+    out, cur = defaultdict(set), None
+    for line in md.splitlines():
+        m = re.match(r"^##\s+(?:产品[:：])?\s*(.+)$", line)
+        if m:
+            cur = _clean(m.group(1))
+        elif cur and line.count("|") >= 2:
+            out[cur].update(NUM.findall(line))
+    return out
+
+
+def _has_price_table(md: str) -> bool:
+    for blk in parse_blocks(md):
+        if blk[0] != "table":
+            continue
+        _doc, keys, data = classify_columns(blk[1], blk[2])
+        if keys and len(data) >= 2:
+            vals = [r[c] for r in blk[2] for c in data]
+            nums = [float(v) for v in vals if re.fullmatch(r"\d+(?:\.\d+)?", v)]
+            if nums and sum(x >= 100 for x in nums) >= len(nums) * 0.5:
+                return True
+    return False
+
+
+def _strip_fm(md: str) -> str:
+    m = re.match(r"^---\n.*?\n---\n", md, re.S)
+    return md[m.end():] if m else md
+
+
+def validate(src_md: str, out_md: str) -> dict:
+    out_body = _strip_fm(out_md)
+    # 去掉"来源文件"行（文件名里的日期是元数据、不是业务数据，不参与数字校验）
+    out_body = "\n".join(l for l in out_body.splitlines() if not l.lstrip().startswith("- 来源文件"))
+    src_nums, out_nums = Counter(NUM.findall(src_md)), Counter(NUM.findall(out_body))
+    invented = {n: c for n, c in (out_nums - src_nums).items() if n not in src_nums}
+
+    misassigned: dict = {}
+    if _has_price_table(src_md):
+        src_by = _wide_product_numbers(src_md)
+        for prod, nums in _section_numbers(out_md).items():
+            match = next((src_by[k] for k in src_by if k and (k in prod or prod in k)), None)
+            if match is None:
+                continue
+            bad = {n for n in (nums - match) if float(n) >= 100 and not 1900 <= float(n) <= 2099}
+            if bad:
+                misassigned[prod] = sorted(bad)
+        shared = {n for n, c in Counter(n for ns in misassigned.values() for n in ns).items()
+                  if c >= max(3, int(len(misassigned) * 0.5))}
+        misassigned = {p: [n for n in ns if n not in shared]
+                       for p, ns in misassigned.items() if [n for n in ns if n not in shared]}
+
+    def _prose(md):
+        return sum(len(re.sub(r"\s", "", l)) for l in md.splitlines() if l.count("|") < 2)
+
+    sp, op = _prose(src_md), _prose(out_body)
+    content_loss = f"②正文{op}字 / ①{sp}字，疑似删减" if (sp > 300 and op < sp * 0.5) else None
+
+    warn = []
+    for line in out_md.splitlines():
+        if line.count("|") >= 3:
+            cells = [c.strip() for c in line.strip("|").split("|")]
+            nums = [c for c in cells if re.fullmatch(r"\d+(?:\.\d+)?", c)]
+            if len(nums) >= 2 and float(nums[0]) < float(nums[1]):
+                warn.append(f"成人价<儿童价? {line.strip()[:50]}")
+    return {
+        "passed": not invented and not misassigned and not content_loss,
+        "invented": invented,
+        "misassigned": misassigned,
+        "content_loss": content_loss,
+        "business_warn": warn[:5],
+    }
+
+
+def build_structured(md: str, source: str = "") -> tuple[str, dict, str]:
+    """8765 用：自动路由结构化。价格表且确定性已过 → 免费确定性重排；
+    行程单/复杂件/确定性没过 → 若有 key 则上 LLM(类型自适应)。返回 (结构化MD, 校验, 模式)。"""
+    deterministic = restructure_md(md, source=source)
+    rep = validate(md, deterministic)
+    key = resolve_llm_key()
+    if key and not (_has_price_table(md) and rep["passed"]):
+        try:
+            llm_md = structure_llm(md, key)
+            if llm_md and llm_md.strip():
+                return llm_md, validate(md, llm_md), "llm"
+        except Exception:  # noqa: BLE001
+            pass
+    return deterministic, rep, "deterministic"
diff --git a/app/api/graph.py b/app/api/graph.py
index 1e4679d..0971e2c 100644
--- a/app/api/graph.py
+++ b/app/api/graph.py
@@ -48,9 +48,11 @@ TEXT_PROPS = (
 
 PLACE_TYPE_LABELS = {
     "sight": "景点",
+    "scenic_area": "景区",
     "eat": "美食",
     "hotel": "酒店",
     "mall": "商场",
+    "transit": "交通设施",
     "transit_stop": "交通站点",
 }
 
@@ -59,6 +61,24 @@ STATION_TYPE_LABELS = {
     "地铁站": "地铁站",
 }
 
+PLACE_SUBTYPE_LABELS = {
+    "GeoCell": "片区",
+    "ScenicSpot": "景点",
+    "ScenicArea": "景区",
+    "FoodPlace": "美食",
+    "Hotel": "酒店",
+    "TransitFacility": "交通设施",
+    "BusStop": "公交站",
+    "Mall": "商场",
+    "MedicalPlace": "医疗保健",
+    "EducationPlace": "科教文化",
+    "LifeServicePlace": "生活服务",
+    "Facility": "公共设施",
+    "GovernmentPlace": "政府机构",
+    "ResidentialPlace": "商务住宅",
+    "EnterprisePlace": "公司企业",
+}
+
 NL_TO_CYPHER_SYS = """你是城市知识图谱查询助手。请把用户自然语言问题转换成 FalkorDB/RedisGraph 只读 Cypher。
 
 硬性要求：
@@ -712,6 +732,8 @@ def _node_dict(n: Any) -> dict:
         visual_group = _place_visual_group(props)
     elif group == "Event":
         visual_group = _event_visual_group(props)
+    elif group == "GeoCell":
+        visual_group = "片区"
 
     disp = ""
     station_type = props.get("station_type")
@@ -726,7 +748,7 @@ def _node_dict(n: Any) -> dict:
             disp = str(v)
             break
     if not disp:
-        disp = f"{group} #{nid}"  # never a bare number
+        disp = f"{visual_group} #{nid}"  # never a bare number
 
     return {
         "id": nid,
@@ -835,10 +857,11 @@ def graph_overview(
 
         label_result = g.query(
             "MATCH (n) WHERE n.shadow_node IS NULL OR n.shadow_node <> 1 "
-            "RETURN labels(n) AS labels, count(n) AS count LIMIT 100"
+            "UNWIND labels(n) AS label "
+            "RETURN label, count(n) AS count LIMIT 100"
         )
         label_counts = [
-            {"label": r[0][0] if r[0] else "(no label)", "count": r[1]}
+            {"label": r[0] or "(no label)", "count": r[1]}
             for r in label_result.result_set
         ]
         visual_counts: dict[str, int] = {}
@@ -846,10 +869,15 @@ def graph_overview(
             label = item["label"]
             if label in {"Place", "Event"}:
                 continue
-            visual_counts[label] = visual_counts.get(label, 0) + int(item["count"] or 0)
+            visual_label = PLACE_SUBTYPE_LABELS.get(label, label)
+            visual_counts[visual_label] = (
+                visual_counts.get(visual_label, 0) + int(item["count"] or 0)
+            )
 
         place_split_result = g.query(
-            "MATCH (p:Place) WHERE p.shadow_node IS NULL OR p.shadow_node <> 1 "
+            "MATCH (p:Place) "
+            "WHERE (p.shadow_node IS NULL OR p.shadow_node <> 1) "
+            "AND size(labels(p)) = 1 "
             "RETURN p.place_type AS place_type, p.station_type AS station_type, "
             "p.category AS category, count(p) AS count LIMIT 200"
         )
diff --git a/app/api/manual_ingest.py b/app/api/manual_ingest.py
index 4099904..3724c70 100644
--- a/app/api/manual_ingest.py
+++ b/app/api/manual_ingest.py
@@ -6,12 +6,15 @@ import hashlib
 import io
 import json
 import re
+import shutil
+import subprocess
 import time
+import uuid
 from difflib import SequenceMatcher
 from pathlib import Path
 from typing import Any
 
-from fastapi import APIRouter, HTTPException
+from fastapi import APIRouter, File, HTTPException, UploadFile
 
 from app.agents.multi_extract import build_extract_pool, decide, fan_out
 from app.db import get_agent_settings
@@ -19,6 +22,36 @@ from app.llm_client import LlmClient
 
 router = APIRouter()
 
+PROJECT_ROOT = Path(__file__).resolve().parents[2]
+MARKITDOWN_UPLOAD_ROOT = PROJECT_ROOT / "tmp" / "manual_ingest" / "markitdown"
+MARKITDOWN_MAX_UPLOAD_BYTES = 40 * 1024 * 1024
+MARKITDOWN_PREVIEW_MAX_BYTES = 5 * 1024 * 1024
+MARKITDOWN_SUPPORTED_EXTENSIONS = {
+    ".txt",
+    ".md",
+    ".markdown",
+    ".csv",
+    ".json",
+    ".xml",
+    ".html",
+    ".htm",
+    ".pdf",
+    ".docx",
+    ".doc",
+    ".pptx",
+    ".ppt",
+    ".xlsx",
+    ".xls",
+    ".zip",
+    ".epub",
+    ".jpg",
+    ".jpeg",
+    ".png",
+    ".gif",
+    ".wav",
+    ".mp3",
+}
+
 SCENIC_SCHEMA_PATH = (
     Path(__file__).resolve().parents[2]
     / "docs"
@@ -27,6 +60,392 @@ SCENIC_SCHEMA_PATH = (
 )
 _SCENIC_SCHEMA_CACHE: dict[str, Any] | None = None
 
+
+def _safe_upload_stem(filename: str) -> str:
+    stem = Path(filename or "upload").stem
+    cleaned = re.sub(r"[^A-Za-z0-9._-]+", "_", stem).strip("._-")
+    return cleaned[:80] or "upload"
+
+
+def _relative_project_path(path: Path) -> str:
+    try:
+        return str(path.relative_to(PROJECT_ROOT))
+    except ValueError:
+        return str(path)
+
+
+def _resolve_markitdown_preview_path(path_value: str) -> Path:
+    raw = str(path_value or "").strip()
+    if not raw:
+        raise HTTPException(status_code=400, detail="缺少 MarkItDown 文件路径")
+    candidate = Path(raw)
+    if not candidate.is_absolute():
+        candidate = PROJECT_ROOT / candidate
+    resolved = candidate.resolve()
+    root = MARKITDOWN_UPLOAD_ROOT.resolve()
+    if not resolved.is_relative_to(root):
+        raise HTTPException(status_code=400, detail="只允许预览 MarkItDown 转换目录内的文件")
+    if resolved.suffix.lower() not in {".md", ".markdown"}:
+        raise HTTPException(status_code=400, detail="只能预览 Markdown 文件")
+    if not resolved.exists() or not resolved.is_file():
+        raise HTTPException(status_code=404, detail="MarkItDown 文件不存在")
+    if resolved.stat().st_size > MARKITDOWN_PREVIEW_MAX_BYTES:
+        raise HTTPException(status_code=413, detail="Markdown 文件超过 5MB，暂不在线预览")
+    return resolved
+
+
+async def _save_markitdown_upload(upload: UploadFile) -> tuple[Path, int]:
+    filename = Path(upload.filename or "").name
+    ext = Path(filename).suffix.lower()
+    if not filename:
+        raise HTTPException(status_code=400, detail="请上传一个文件")
+    if ext not in MARKITDOWN_SUPPORTED_EXTENSIONS:
+        supported = "、".join(sorted(MARKITDOWN_SUPPORTED_EXTENSIONS))
+        raise HTTPException(status_code=400, detail=f"暂不支持该文件格式：{ext or '无扩展名'}。支持：{supported}")
+
+    MARKITDOWN_UPLOAD_ROOT.mkdir(parents=True, exist_ok=True)
+    token = f"{int(time.time())}_{uuid.uuid4().hex[:10]}"
+    input_path = MARKITDOWN_UPLOAD_ROOT / f"{token}_{_safe_upload_stem(filename)}{ext}"
+    size = 0
+    try:
+        with input_path.open("wb") as out:
+            while True:
+                chunk = await upload.read(1024 * 1024)
+                if not chunk:
+                    break
+                size += len(chunk)
+                if size > MARKITDOWN_MAX_UPLOAD_BYTES:
+                    raise HTTPException(status_code=413, detail="文件超过 40MB，无法转换")
+                out.write(chunk)
+    except Exception:
+        input_path.unlink(missing_ok=True)
+        raise
+    finally:
+        await upload.close()
+
+    if size <= 0:
+        input_path.unlink(missing_ok=True)
+        raise HTTPException(status_code=400, detail="上传文件为空")
+    return input_path, size
+
+
+def _write_markdown_artifact(input_path: Path, markdown: str) -> Path:
+    markdown_path = input_path.with_name(f"{input_path.stem}.markitdown.md")
+    markdown_path.write_text(markdown + "\n", encoding="utf-8")
+    return markdown_path
+
+
+def _convert_pdf_with_pymupdf4llm(input_path: Path) -> str | None:
+    """版式/表格感知的 PDF→Markdown；未安装、失败或为空时返回 None 以回退 MarkItDown。"""
+    try:
+        import pymupdf4llm
+    except ImportError:
+        return None
+    try:
+        markdown = pymupdf4llm.to_markdown(str(input_path))
+    except Exception:  # noqa: BLE001
+        return None
+    markdown = (markdown or "").strip()
+    return markdown or None
+
+
+def _convert_xlsx_smart(input_path: Path) -> str | None:
+    """合并单元格感知的 Excel→Markdown：
+    - 普通合并单元格：左上角值向整块填充（消除 NaN，使每行自带上下文）；
+    - 整行合并（标题/须知）：单独渲染成段落，不铺满所有列；
+    失败时返回 None 以回退 MarkItDown。"""
+    try:
+        import openpyxl
+
+        workbook = openpyxl.load_workbook(str(input_path), data_only=True)
+    except Exception:  # noqa: BLE001
+        return None
+
+    def _cell(value: Any) -> str:
+        if value is None:
+            return ""
+        return str(value).strip().replace("|", "\\|").replace("\n", "<br>")
+
+    try:
+        blocks: list[str] = []
+        for ws in workbook.worksheets:
+            max_row, max_col = ws.max_row or 0, ws.max_column or 0
+            if not max_row or not max_col:
+                continue
+            grid = [[ws.cell(row=r, column=c).value for c in range(1, max_col + 1)]
+                    for r in range(1, max_row + 1)]
+            # 所有合并单元格：左上角值填满整块（纵向合并→每行自带上下文；横向合并→整行同值）
+            for mr in ws.merged_cells.ranges:
+                value = ws.cell(row=mr.min_row, column=mr.min_col).value
+                for r in range(mr.min_row, mr.max_row + 1):
+                    for c in range(mr.min_col, mr.max_col + 1):
+                        grid[r - 1][c - 1] = value
+            rows = [[_cell(v) for v in row] for row in grid]
+            keep = [c for c in range(max_col) if any(row[c] for row in rows)]
+            rows = [[row[c] for c in keep] for row in rows]
+
+            notes: list[str] = []
+            body: list[list[str]] = []
+            for row in rows:
+                if not any(row):
+                    continue
+                # 整行被同一个值铺满（横向合并的标题/须知）→ 收成一段，避免数十列重复
+                if len(set(row)) == 1 and row[0]:
+                    if not notes or notes[-1] != row[0]:  # 纵向合并的备注会跨多行 → 连续去重
+                        notes.append(row[0])
+                else:
+                    body.append(row)
+
+            lines = [f"## {ws.title}", ""]
+            for text in notes:
+                lines.append(text.replace("<br>", " ").strip())
+                lines.append("")
+            if body:
+                width = max(len(r) for r in body)
+                body = [r + [""] * (width - len(r)) for r in body]
+                lines.append("| " + " | ".join(body[0]) + " |")
+                lines.append("| " + " | ".join(["---"] * width) + " |")
+                for row in body[1:]:
+                    lines.append("| " + " | ".join(row) + " |")
+                lines.append("")
+            blocks.append("\n".join(lines))
+    except Exception:  # noqa: BLE001
+        return None
+
+    result = "\n".join(blocks).strip()
+    return result or None
+
+
+def _pdf_is_scanned(input_path: Path) -> bool:
+    """扫描/图片 PDF 判别：取样多页仍几乎无可抽文字 → 扫描件（规则转换无效，需 VLM）。"""
+    try:
+        import fitz
+
+        doc = fitz.open(str(input_path))
+        text = "".join(doc[i].get_text() for i in range(min(doc.page_count, 12)))
+        return len(text.strip()) < 200
+    except Exception:  # noqa: BLE001
+        return False
+
+
+def _convert_docx_structured(input_path: Path) -> str | None:
+    """DOCX→Markdown：按正文顺序保留 标题/段落/表格（比 MarkItDown 更完整保留表格）。失败返回 None。"""
+    try:
+        import docx
+        from docx.oxml.ns import qn
+        from docx.table import Table
+        from docx.text.paragraph import Paragraph
+
+        document = docx.Document(str(input_path))
+    except Exception:  # noqa: BLE001
+        return None
+    try:
+        lines: list[str] = []
+        for child in document.element.body.iterchildren():
+            if child.tag == qn("w:p"):
+                para = Paragraph(child, document)
+                text = para.text.strip()
+                if not text:
+                    continue
+                style = (para.style.name or "").lower() if para.style else ""
+                if style.startswith("heading"):
+                    match = re.search(r"(\d+)", style)
+                    lines.append("#" * min(int(match.group(1)) if match else 1, 6) + " " + text)
+                else:
+                    lines.append(text)
+                lines.append("")
+            elif child.tag == qn("w:tbl"):
+                table_rows = [[c.text.strip().replace("|", "\\|").replace("\n", "<br>") for c in row.cells]
+                              for row in Table(child, document).rows]
+                table_rows = [r for r in table_rows if any(r)]
+                if table_rows:
+                    width = max(len(r) for r in table_rows)
+                    table_rows = [r + [""] * (width - len(r)) for r in table_rows]
+                    lines.append("| " + " | ".join(table_rows[0]) + " |")
+                    lines.append("| " + " | ".join(["---"] * width) + " |")
+                    lines += ["| " + " | ".join(r) + " |" for r in table_rows[1:]]
+                    lines.append("")
+    except Exception:  # noqa: BLE001
+        return None
+    result = "\n".join(lines).strip()
+    return result or None
+
+
+def _doc_via_olefile(input_path: Path) -> str | None:
+    """textutil 读不了的损坏 .doc：从 WordDocument 流(UTF-16)捞中文正文，滤掉超链字段码。失败返回 None。"""
+    try:
+        import olefile
+
+        if not olefile.isOleFile(str(input_path)):
+            return None
+        ole = olefile.OleFileIO(str(input_path))
+        if not ole.exists("WordDocument"):
+            return None
+        text = ole.openstream("WordDocument").read().decode("utf-16-le", errors="ignore")
+    except Exception:  # noqa: BLE001
+        return None
+    out: list[str] = []
+    seen: set[str] = set()
+    for run in re.findall(r"[一-鿿　-〿＀-￯0-9A-Za-z，。：；、（）·\-/~：%￥]{6,}", text):
+        run = run.strip()
+        if "HYPERLINK" in run or "ShowInnerLink" in run or "com/" in run or run.startswith("com"):
+            continue
+        if re.search(r"[一-鿿]", run) and run not in seen:
+            seen.add(run)
+            out.append(run)
+    result = "\n".join(out).strip()
+    return result or None
+
+
+def _convert_doc_robust(input_path: Path) -> str | None:
+    """老 .doc：textutil 转 docx→python-docx(保表格)；textutil 读不了 → olefile 直捞正文。"""
+    conv = input_path.with_name(f"{input_path.stem}.__doc2docx.docx")
+    try:
+        completed = subprocess.run(
+            ["textutil", "-convert", "docx", "-output", str(conv), str(input_path)],
+            capture_output=True, text=True, timeout=120,
+        )
+        if completed.returncode == 0 and conv.exists():
+            md = _convert_docx_structured(conv)
+            if md and len(md.strip()) >= 30:
+                return md
+    except Exception:  # noqa: BLE001
+        pass
+    finally:
+        conv.unlink(missing_ok=True)
+    return _doc_via_olefile(input_path)
+
+
+def _convert_path_with_markitdown(input_path: Path) -> tuple[str, Path, str]:
+    ext = input_path.suffix.lower()
+    # 结构化优先：PDF→pymupdf4llm、Excel→openpyxl、Word→python-docx(保表格)、老doc→textutil/olefile；失败回退 MarkItDown
+    if ext == ".pdf":
+        if _pdf_is_scanned(input_path):
+            raise HTTPException(
+                status_code=422,
+                detail="此 PDF 为扫描/图片件，规则转换提取不到文字，需视觉模型(VLM)处理",
+            )
+        better = _convert_pdf_with_pymupdf4llm(input_path)
+        if better:
+            return better, _write_markdown_artifact(input_path, better), "pymupdf4llm"
+    elif ext in {".xlsx", ".xlsm"}:
+        better = _convert_xlsx_smart(input_path)
+        if better:
+            return better, _write_markdown_artifact(input_path, better), "openpyxl"
+    elif ext == ".docx":
+        better = _convert_docx_structured(input_path)
+        if better:
+            return better, _write_markdown_artifact(input_path, better), "python-docx"
+    elif ext == ".doc":
+        better = _convert_doc_robust(input_path)
+        if better:
+            return better, _write_markdown_artifact(input_path, better), "doc-robust"
+
+    try:
+        from markitdown import MarkItDown
+    except ImportError as exc:
+        raise HTTPException(
+            status_code=503,
+            detail="MarkItDown 未安装，请先执行：pip install -r requirements.txt",
+        ) from exc
+
+    converter = MarkItDown(enable_plugins=False)
+    try:
+        result = converter.convert(str(input_path))
+    except Exception as exc:  # noqa: BLE001
+        if input_path.suffix.lower() == ".doc":
+            markdown = _convert_legacy_doc_with_textutil(input_path, converter)
+            markdown_path = input_path.with_name(f"{input_path.stem}.markitdown.md")
+            markdown_path.write_text(markdown + "\n", encoding="utf-8")
+            return markdown, markdown_path, "markitdown"
+        raise
+    markdown = str(
+        getattr(result, "text_content", None)
+        or getattr(result, "markdown", None)
+        or ""
+    ).strip()
+    if not markdown and input_path.suffix.lower() == ".doc":
+        markdown = _convert_legacy_doc_with_textutil(input_path, converter)
+    if not markdown:
+        raise HTTPException(status_code=422, detail="MarkItDown 未能从该文件中提取到可抽取文本")
+
+    markdown_path = input_path.with_name(f"{input_path.stem}.markitdown.md")
+    markdown_path.write_text(markdown + "\n", encoding="utf-8")
+    return markdown, markdown_path, "markitdown"
+
+
+def _convert_legacy_doc_with_textutil(input_path: Path, converter: Any) -> str:
+    textutil = shutil.which("textutil")
+    if textutil:
+        html_path = input_path.with_name(f"{input_path.stem}.textutil.html")
+        try:
+            completed = subprocess.run(
+                [textutil, "-convert", "html", "-output", str(html_path), str(input_path)],
+                check=False,
+                capture_output=True,
+                text=True,
+                timeout=60,
+            )
+        except subprocess.TimeoutExpired as exc:
+            raise HTTPException(status_code=422, detail=".doc 文件转换超时，请先另存为 .docx 后上传") from exc
+
+        if completed.returncode != 0 or not html_path.exists():
+            detail = (completed.stderr or completed.stdout or "").strip()
+            raise HTTPException(
+                status_code=422,
+                detail=f".doc 文件转换失败，请先另存为 .docx 后上传。{detail[:160]}",
+            )
+        return _convert_intermediate_html_to_markdown(html_path, converter)
+
+    office = shutil.which("soffice") or shutil.which("libreoffice")
+    if office:
+        out_dir = input_path.with_name(f"{input_path.stem}.doc-convert-{uuid.uuid4().hex[:8]}")
+        out_dir.mkdir(parents=True, exist_ok=True)
+        try:
+            completed = subprocess.run(
+                [office, "--headless", "--convert-to", "html", "--outdir", str(out_dir), str(input_path)],
+                check=False,
+                capture_output=True,
+                text=True,
+                timeout=90,
+            )
+            html_files = list(out_dir.glob("*.html")) + list(out_dir.glob("*.htm"))
+            if completed.returncode != 0 or not html_files:
+                detail = (completed.stderr or completed.stdout or "").strip()
+                raise HTTPException(
+                    status_code=422,
+                    detail=f".doc 文件转换失败，请先另存为 .docx 后上传。{detail[:160]}",
+                )
+            return _convert_intermediate_html_to_markdown(html_files[0], converter, cleanup=False)
+        except subprocess.TimeoutExpired as exc:
+            raise HTTPException(status_code=422, detail=".doc 文件转换超时，请先另存为 .docx 后上传") from exc
+        finally:
+            shutil.rmtree(out_dir, ignore_errors=True)
+
+    raise HTTPException(
+        status_code=422,
+        detail="老式 .doc 文件需要先转换为 .docx，或在服务器安装 LibreOffice/textutil 后再上传",
+    )
+
+
+def _convert_intermediate_html_to_markdown(html_path: Path, converter: Any, cleanup: bool = True) -> str:
+    try:
+        result = converter.convert(str(html_path))
+        markdown = str(
+            getattr(result, "text_content", None)
+            or getattr(result, "markdown", None)
+            or ""
+        ).strip()
+    finally:
+        if cleanup:
+            html_path.unlink(missing_ok=True)
+    if not markdown:
+        raise HTTPException(
+            status_code=422,
+            detail=".doc 文件转换后未提取到文本，请先另存为 .docx 后上传",
+        )
+    return markdown
+
 KG_EXTRACT_SYS = """
 你是一个通用知识图谱深度抽取器。服务对象不是单一城市景点，而是任意行业材料：
 人工粘贴网页正文、CSV、表格、专家笔记、教育/城市/商业等业务文本。
@@ -3689,6 +4108,59 @@ async def extract_manual_kg_llm(
     raise HTTPException(status_code=502, detail="通用 LLM 深度抽取失败：未知错误")
 
 
+@router.post("/manual-ingest/convert-file")
+async def manual_ingest_convert_file(file: UploadFile = File(...)) -> dict[str, Any]:
+    input_path, size = await _save_markitdown_upload(file)
+    try:
+        markdown, markdown_path, converter_name = await asyncio.to_thread(
+            _convert_path_with_markitdown,
+            input_path,
+        )
+    except HTTPException:
+        raise
+    except Exception as exc:  # noqa: BLE001
+        raise HTTPException(status_code=422, detail=f"MarkItDown 转换失败：{str(exc)[:240]}") from exc
+
+    # ②结构化（自动路由：价格表用免费确定性、行程单/复杂件上 LLM）+ ③校验（失败不影响基础转换）
+    structured_markdown, validation, structured_mode = "", None, ""
+    try:
+        from app.api.doc_restructure import build_structured
+        structured_markdown, validation, structured_mode = await asyncio.to_thread(
+            build_structured, markdown, Path(file.filename or input_path.name).name,
+        )
+    except Exception:  # noqa: BLE001
+        structured_markdown, validation, structured_mode = "", None, ""
+
+    return {
+        "filename": Path(file.filename or input_path.name).name,
+        "content_type": file.content_type or "",
+        "size": size,
+        "markdown": markdown,
+        "markdown_chars": len(markdown),
+        "markdown_path": _relative_project_path(markdown_path),
+        "source_path": _relative_project_path(input_path),
+        "input_format": "markdown",
+        "converter": converter_name,
+        "structured_markdown": structured_markdown,
+        "structured_chars": len(structured_markdown),
+        "structured_mode": structured_mode,
+        "validation": validation,
+    }
+
+
+@router.get("/manual-ingest/markdown-preview")
+def manual_ingest_markdown_preview(path: str) -> dict[str, Any]:
+    markdown_path = _resolve_markitdown_preview_path(path)
+    markdown = markdown_path.read_text(encoding="utf-8", errors="replace")
+    return {
+        "filename": markdown_path.name,
+        "markdown_path": _relative_project_path(markdown_path),
+        "markdown": markdown,
+        "markdown_chars": len(markdown),
+        "size": markdown_path.stat().st_size,
+    }
+
+
 @router.post("/manual-ingest/extract")
 async def manual_ingest_extract(body: dict[str, Any]) -> dict[str, Any]:
     text = str(body.get("text") or "")
diff --git a/app/api/mcp_server.py b/app/api/mcp_server.py
new file mode 100644
index 0000000..640e6c1
--- /dev/null
+++ b/app/api/mcp_server.py
@@ -0,0 +1,343 @@
+"""Minimal MCP Streamable HTTP adapter for Baixinghui customer-service tools."""
+from __future__ import annotations
+
+import json
+import os
+import time
+import uuid
+from typing import Any
+
+from fastapi import APIRouter, Request
+from fastapi.responses import JSONResponse, Response, StreamingResponse
+
+from app.api.travel_assistant import _customer_service_query_response
+
+router = APIRouter()
+
+MCP_PROTOCOL_VERSION = "2025-06-18"
+SUPPORTED_MCP_PROTOCOL_VERSIONS = {"2024-11-05", "2025-03-26", MCP_PROTOCOL_VERSION}
+DEFAULT_GRAPH_NAME = "baixinghui_travel_agency"
+
+
+def _tool_definitions() -> list[dict[str, Any]]:
+    return [
+        {
+            "name": "ask_customer_service",
+            "description": (
+                "向百姓惠旅行社知识图谱智能客服提问。适用于线路价格、行程天数、景区、酒店、费用、车型、"
+                "线路推荐和复杂多跳问答。只读工具，不承诺最终价格、余位、房型或景区政策。"
+            ),
+            "inputSchema": {
+                "type": "object",
+                "properties": {
+                    "question": {"type": "string", "description": "用户自然语言问题"},
+                    "session_id": {"type": "string", "description": "外部会话 ID，可选"},
+                    "request_id": {"type": "string", "description": "外部请求 ID，可选"},
+                    "customer_context": {
+                        "type": "object",
+                        "description": "客户上下文，例如人数、预算、出发日期、偏好，可选",
+                    },
+                },
+                "required": ["question"],
+            },
+        },
+        {
+            "name": "query_route_price",
+            "description": "查询指定旅行线路的参考价格、成人/儿童价格区间和不可直接承诺事项。只读工具。",
+            "inputSchema": {
+                "type": "object",
+                "properties": {
+                    "route_name": {"type": "string", "description": "线路名称或关键词，例如 黄小西三日游"},
+                    "traveler_type": {
+                        "type": "string",
+                        "description": "游客类型，可选，例如 成人、儿童、老人",
+                    },
+                    "session_id": {"type": "string", "description": "外部会话 ID，可选"},
+                },
+                "required": ["route_name"],
+            },
+        },
+        {
+            "name": "list_travel_routes",
+            "description": "查询百姓惠旅行线路清单，可按天数、景区或关键词筛选。只读工具。",
+            "inputSchema": {
+                "type": "object",
+                "properties": {
+                    "keyword": {"type": "string", "description": "线路或目的地关键词，可选"},
+                    "duration_days": {"type": "integer", "description": "期望天数，可选"},
+                    "limit": {"type": "integer", "description": "返回条数上限，可选，默认 20"},
+                    "session_id": {"type": "string", "description": "外部会话 ID，可选"},
+                },
+            },
+        },
+        {
+            "name": "query_route_detail",
+            "description": "查询某条线路的天数、价格、景区、附近酒店和费用边界。只读工具。",
+            "inputSchema": {
+                "type": "object",
+                "properties": {
+                    "route_name": {"type": "string", "description": "线路名称或关键词"},
+                    "detail_focus": {
+                        "type": "string",
+                        "description": "关注点，可选，例如 价格、景区、酒店、费用、车型",
+                    },
+                    "session_id": {"type": "string", "description": "外部会话 ID，可选"},
+                },
+                "required": ["route_name"],
+            },
+        },
+        {
+            "name": "compare_routes",
+            "description": "对比两条旅行线路的适配度、景点数量、轻松程度或客服推荐理由。只读工具。",
+            "inputSchema": {
+                "type": "object",
+                "properties": {
+                    "route_a": {"type": "string", "description": "第一条线路名称或关键词"},
+                    "route_b": {"type": "string", "description": "第二条线路名称或关键词"},
+                    "compare_focus": {
+                        "type": "string",
+                        "description": "对比关注点，例如 老人小孩、不太累、景点更多、价格",
+                    },
+                    "session_id": {"type": "string", "description": "外部会话 ID，可选"},
+                },
+                "required": ["route_a", "route_b"],
+            },
+        },
+    ]
+
+
+def _json_rpc_result(message_id: Any, result: dict[str, Any]) -> dict[str, Any]:
+    return {"jsonrpc": "2.0", "id": message_id, "result": result}
+
+
+def _json_rpc_error(message_id: Any, code: int, message: str, data: Any = None) -> dict[str, Any]:
+    error: dict[str, Any] = {"code": code, "message": message}
+    if data is not None:
+        error["data"] = data
+    return {"jsonrpc": "2.0", "id": message_id, "error": error}
+
+
+def _mcp_auth_enabled() -> bool:
+    return bool(os.getenv("BXH_MCP_TOKEN", "").strip())
+
+
+def _is_authorized(request: Request) -> bool:
+    expected = os.getenv("BXH_MCP_TOKEN", "").strip()
+    if not expected:
+        return True
+    auth = request.headers.get("authorization", "").strip()
+    api_key = request.headers.get("x-mcp-api-key", "").strip()
+    bearer = auth[7:].strip() if auth.lower().startswith("bearer ") else auth
+    return expected in {bearer, api_key}
+
+
+def _normalize_args(params: dict[str, Any]) -> tuple[str, dict[str, Any]]:
+    name = str(params.get("name") or "").strip()
+    args = params.get("arguments")
+    if args is None:
+        args = {}
+    if not isinstance(args, dict):
+        raise ValueError("arguments must be an object")
+    return name, args
+
+
+def _question_for_tool(name: str, args: dict[str, Any]) -> str:
+    if name == "ask_customer_service":
+        return str(args.get("question") or "").strip()
+    if name == "query_route_price":
+        route = str(args.get("route_name") or "").strip()
+        traveler = str(args.get("traveler_type") or "").strip()
+        suffix = f"，{traveler}怎么收费" if traveler else ""
+        return f"{route}多少钱{suffix}？".strip()
+    if name == "list_travel_routes":
+        keyword = str(args.get("keyword") or "").strip()
+        days = args.get("duration_days")
+        pieces = ["旅行车线路有哪些"]
+        if keyword:
+            pieces.append(f"和{keyword}相关")
+        if days:
+            pieces.append(f"{days}天")
+        return "，".join(pieces) + "？"
+    if name == "query_route_detail":
+        route = str(args.get("route_name") or "").strip()
+        focus = str(args.get("detail_focus") or "").strip()
+        if focus:
+            return f"{route}的{focus}是什么？"
+        return f"{route}多少钱，可以玩几天，期间可以去哪些景区，附近可以入住什么酒店？"
+    if name == "compare_routes":
+        route_a = str(args.get("route_a") or "").strip()
+        route_b = str(args.get("route_b") or "").strip()
+        focus = str(args.get("compare_focus") or "哪个更适合客户").strip()
+        return f"{route_a}和{route_b}{focus}，为什么？"
+    raise KeyError(name)
+
+
+def _mcp_content_text(payload: dict[str, Any]) -> str:
+    reply = str(payload.get("customer_reply") or payload.get("answer") or "").strip()
+    if reply:
+        return reply
+    return "当前知识图谱没有返回可直接回复的话术，请补充线路、人数、天数或出行日期后再试。"
+
+
+def _mcp_structured_data(payload: dict[str, Any]) -> dict[str, Any]:
+    knowledge = payload.get("knowledge") if isinstance(payload.get("knowledge"), dict) else {}
+    return {
+        "status": payload.get("status") or "ok",
+        "service": payload.get("service") or "baixinghui_customer_service",
+        "request_id": payload.get("request_id"),
+        "trace_id": payload.get("trace_id"),
+        "session_id": payload.get("session_id"),
+        "graph_name": payload.get("graph_name"),
+        "question": payload.get("question"),
+        "customer_reply": payload.get("customer_reply"),
+        "answer": payload.get("answer"),
+        "confidence": payload.get("confidence"),
+        "follow_up_questions": payload.get("follow_up_questions") or [],
+        "risk_notes": payload.get("risk_notes") or [],
+        "knowledge": {
+            "plans": knowledge.get("plans") or [],
+            "evidence": knowledge.get("evidence") or [],
+        },
+        "routing": payload.get("routing") or {},
+        "trace": payload.get("trace") or {},
+    }
+
+
+def _negotiate_protocol_version(params: dict[str, Any]) -> str:
+    requested = str(params.get("protocolVersion") or "").strip()
+    if requested in SUPPORTED_MCP_PROTOCOL_VERSIONS:
+        return requested
+    return MCP_PROTOCOL_VERSION
+
+
+async def _call_customer_service_tool(name: str, args: dict[str, Any]) -> dict[str, Any]:
+    question = _question_for_tool(name, args)
+    if not question:
+        raise ValueError("question or route fields are required")
+
+    body = {
+        "request_id": args.get("request_id") or f"mcp-{uuid.uuid4().hex[:16]}",
+        "session_id": args.get("session_id") or "",
+        "channel": args.get("channel") or "mcp",
+        "graph_name": args.get("graph_name") or DEFAULT_GRAPH_NAME,
+        "question": question,
+        "customer_context": args.get("customer_context") if isinstance(args.get("customer_context"), dict) else {},
+        "limit": int(args.get("limit") or 80),
+    }
+    started = time.perf_counter()
+    payload = await _customer_service_query_response(body)
+    structured = _mcp_structured_data(payload)
+    structured["tool_name"] = name
+    structured["tool_latency_ms"] = max(1, round((time.perf_counter() - started) * 1000))
+    return {
+        "content": [{"type": "text", "text": _mcp_content_text(payload)}],
+        "structuredContent": structured,
+        "isError": False,
+    }
+
+
+async def _handle_request(message: dict[str, Any]) -> dict[str, Any] | None:
+    message_id = message.get("id")
+    method = str(message.get("method") or "")
+    params = message.get("params") if isinstance(message.get("params"), dict) else {}
+
+    if not method:
+        return _json_rpc_error(message_id, -32600, "Invalid Request")
+
+    # JSON-RPC notifications have no id and do not require a response.
+    if "id" not in message:
+        return None
+
+    if method == "initialize":
+        return _json_rpc_result(
+            message_id,
+            {
+                "protocolVersion": _negotiate_protocol_version(params),
+                "capabilities": {"tools": {"listChanged": False}},
+                "serverInfo": {
+                    "name": "baixinghui-customer-service-mcp",
+                    "version": "0.1.0",
+                },
+                "instructions": "使用百姓惠旅行社知识图谱工具回答线路、价格、景区、酒店和费用问题。",
+            },
+        )
+    if method == "ping":
+        return _json_rpc_result(message_id, {})
+    if method == "tools/list":
+        return _json_rpc_result(message_id, {"tools": _tool_definitions()})
+    if method == "tools/call":
+        try:
+            name, args = _normalize_args(params)
+            tool_names = {tool["name"] for tool in _tool_definitions()}
+            if name not in tool_names:
+                return _json_rpc_error(message_id, -32602, f"Unknown tool: {name}")
+            result = await _call_customer_service_tool(name, args)
+            return _json_rpc_result(message_id, result)
+        except ValueError as exc:
+            return _json_rpc_error(message_id, -32602, str(exc))
+        except Exception as exc:  # noqa: BLE001
+            return _json_rpc_error(message_id, -32603, f"Tool execution failed: {str(exc)[:300]}")
+    if method in {"resources/list", "prompts/list"}:
+        key = "resources" if method == "resources/list" else "prompts"
+        return _json_rpc_result(message_id, {key: []})
+    return _json_rpc_error(message_id, -32601, f"Method not found: {method}")
+
+
+@router.get("/mcp")
+async def mcp_get(request: Request):
+    if not _is_authorized(request):
+        return JSONResponse({"detail": "Unauthorized"}, status_code=401)
+    accept = request.headers.get("accept", "")
+    if "text/event-stream" in accept:
+        async def stream():
+            yield ": baixinghui customer-service MCP endpoint is ready\n\n"
+
+        return StreamingResponse(stream(), media_type="text/event-stream")
+    return {
+        "name": "baixinghui-customer-service-mcp",
+        "protocolVersion": MCP_PROTOCOL_VERSION,
+        "auth": "bearer" if _mcp_auth_enabled() else "disabled",
+        "tools": [tool["name"] for tool in _tool_definitions()],
+    }
+
+
+@router.post("/mcp")
+async def mcp_post(request: Request):
+    if not _is_authorized(request):
+        return JSONResponse(
+            _json_rpc_error(None, -32001, "Unauthorized"),
+            status_code=401,
+            media_type="application/json",
+        )
+    try:
+        payload = await request.json()
+    except Exception:
+        return JSONResponse(
+            _json_rpc_error(None, -32700, "Parse error"),
+            status_code=400,
+            media_type="application/json",
+        )
+
+    if isinstance(payload, list):
+        responses = []
+        for message in payload:
+            if not isinstance(message, dict):
+                responses.append(_json_rpc_error(None, -32600, "Invalid Request"))
+                continue
+            response = await _handle_request(message)
+            if response is not None:
+                responses.append(response)
+        if not responses:
+            return Response(status_code=202)
+        return JSONResponse(responses, media_type="application/json")
+
+    if not isinstance(payload, dict):
+        return JSONResponse(
+            _json_rpc_error(None, -32600, "Invalid Request"),
+            status_code=400,
+            media_type="application/json",
+        )
+    response = await _handle_request(payload)
+    if response is None:
+        return Response(status_code=202)
+    return JSONResponse(response, media_type="application/json")
diff --git a/app/api/ocr.py b/app/api/ocr.py
new file mode 100644
index 0000000..250190d
--- /dev/null
+++ b/app/api/ocr.py
@@ -0,0 +1,57 @@
+"""OCR 相关接口——目前供旅行社"名单"模块识别护照使用。"""
+from __future__ import annotations
+
+from typing import Any
+
+from fastapi import APIRouter, File, Form, HTTPException, UploadFile
+
+from app.aliyun_ocr import OcrCallError, OcrConfigError, recognize_passport
+
+router = APIRouter()
+
+MAX_IMAGE_BYTES = 10 * 1024 * 1024  # 阿里云接口单图上限按 10MB 兜底
+
+
+@router.post("/ocr/passport")
+async def ocr_passport(
+    file: UploadFile | None = File(default=None),
+    url: str | None = Form(default=None),
+) -> dict[str, Any]:
+    """护照识别。任选其一：
+    - multipart 上传 `file`（图片二进制）
+    - 表单字段 `url`（图片可公网访问的 URL，如阿里云 OSS）
+
+    成功返回 OCR 解析后的字段 dict，失败按错误类型映射到不同 HTTP 状态：
+    - 400：参数缺失/图片过大
+    - 503：AK/SK 未配置（运维介入）
+    - 502：阿里云返回错误或网络故障
+    """
+    if file is None and not (url and url.strip()):
+        raise HTTPException(status_code=400, detail="请上传图片文件或提供图片 URL")
+
+    image_bytes: bytes | None = None
+    if file is not None:
+        image_bytes = await file.read()
+        if not image_bytes:
+            raise HTTPException(status_code=400, detail="上传的图片为空")
+        if len(image_bytes) > MAX_IMAGE_BYTES:
+            raise HTTPException(
+                status_code=400,
+                detail=f"图片过大（{len(image_bytes)} 字节），请压缩到 10MB 以内",
+            )
+
+    try:
+        data = recognize_passport(
+            image_bytes=image_bytes,
+            image_url=url.strip() if url else None,
+        )
+    except OcrConfigError as exc:
+        raise HTTPException(status_code=503, detail=str(exc)) from exc
+    except OcrCallError as exc:
+        raise HTTPException(status_code=502, detail=str(exc)) from exc
+
+    return {
+        "ok": True,
+        "filename": file.filename if file else None,
+        "data": data,
+    }
diff --git a/app/api/plaza.py b/app/api/plaza.py
index bf8ef81..8ee4306 100644
--- a/app/api/plaza.py
+++ b/app/api/plaza.py
@@ -9,17 +9,123 @@ import time
 from typing import Any
 
 import h3
+from falkordb import FalkorDB
 from fastapi import APIRouter, Depends, HTTPException
 
 from app.auth import CurrentUser
 from app.config import settings
 from app.db import get_agent_settings, get_plaza_overview, get_plaza_alerts, get_conn
+from app.graph_qa_engine import answer_graph_question
 from app.llm_client import LlmClient
 from app.project_context import ProjectContext, get_project_context
 
 router = APIRouter()
 
 SPATIAL_GRAPH_NAME = "guiyang_spatial_v1"
+LIBO_BUS_DATASET = "libo_bus_xlsx_v1"
+
+FOOD_ENRICHMENT_KEYS = (
+    "food_fusion_status",
+    "food_match_confidence",
+    "food_match_rule",
+    "food_match_score",
+    "food_name_similarity",
+    "food_address_similarity",
+    "food_coordinate_distance_m",
+    "dianping_shop_id",
+    "dianping_name",
+    "dianping_address",
+    "dianping_url",
+    "dianping_rating",
+    "dianping_review_count",
+    "dianping_avg_price",
+    "dianping_area",
+    "dianping_category",
+    "dianping_score_details",
+    "dianping_ranking",
+    "dianping_business_status",
+    "dianping_business_hours",
+    "dianping_tags",
+    "dianping_transportation",
+    "dianping_shop_image",
+    "dianping_review_tags",
+    "recommended_dish_count",
+    "recommended_dish_names",
+    "group_buy_count",
+    "group_buy_min_price",
+    "group_buy_max_price",
+    "group_buy_titles",
+    "group_buy_items_json",
+    "review_sample_count",
+    "review_sample_avg_stars",
+    "review_sample_summary",
+    "food_review_items_json",
+    "food_review_tags_json",
+    "menu_image_count",
+    "candidate_dianping_name",
+    "food_candidate_name_similarity",
+    "food_candidate_address_similarity",
+    "enrichment_updated_at",
+)
+
+HOTEL_ENRICHMENT_KEYS = (
+    "hotel_fusion_status",
+    "hotel_match_confidence",
+    "hotel_match_rule",
+    "hotel_name_similarity",
+    "hotel_address_similarity",
+    "hotel_phone_exact_match",
+    "ctrip_hotel_id",
+    "ctrip_name_cn",
+    "ctrip_name_en",
+    "ctrip_address",
+    "ctrip_phone",
+    "ctrip_star_level",
+    "ctrip_diamond_level",
+    "ctrip_opened_year",
+    "ctrip_room_count",
+    "ctrip_hotel_type",
+    "ctrip_ranking",
+    "ctrip_rating",
+    "ctrip_rating_description",
+    "ctrip_review_count",
+    "ctrip_transportation",
+    "ctrip_tags",
+    "ctrip_popular_facilities",
+    "ctrip_score_details",
+    "ctrip_cleanliness_score",
+    "ctrip_facilities_score",
+    "ctrip_environment_score",
+    "ctrip_service_score",
+    "ctrip_description",
+    "ctrip_url",
+    "room_type_count",
+    "room_type_names",
+    "room_min_price",
+    "room_max_price",
+    "offer_count",
+    "offer_min_price",
+    "offer_max_price",
+    "room_items_json",
+    "facility_service_count",
+    "facility_summary",
+    "facility_category_items_json",
+    "policy_count",
+    "policy_summary",
+    "guest_review_sample_count",
+    "guest_review_sample_avg_score",
+    "latest_review_at",
+    "review_travel_types",
+    "review_items_json",
+    "hotel_image_samples",
+    "nearby_place_count",
+    "nearby_place_summary",
+    "nearby_category_items_json",
+    "candidate_ctrip_name",
+    "hotel_candidate_name_similarity",
+    "hotel_candidate_address_similarity",
+    "enrichment_updated_at",
+)
 
 CATEGORY_ALIASES: dict[str, list[str]] = {
     "美食": ["美食", "吃", "餐厅", "饭店", "火锅", "小吃", "烧烤", "咖啡", "奶茶", "酸汤鱼"],
@@ -313,13 +419,463 @@ async def amap_config(_user: CurrentUser = None):
     }
 
 
+def _is_enterprise_travel_graph(graph_name: str) -> bool:
+    lower = graph_name.lower()
+    return "baixinghui" in lower or ("travel" in lower and graph_name != SPATIAL_GRAPH_NAME)
+
+
+def _resolve_spatial_graph_name(graph_name: str) -> str:
+    """Map the city project graph name to the materialized spatial POI graph."""
+    lower = graph_name.lower()
+    if graph_name == SPATIAL_GRAPH_NAME or lower.endswith("_spatial_v1"):
+        return graph_name
+    if graph_name == "guiyang_new2":
+        return SPATIAL_GRAPH_NAME
+    return graph_name
+
+
+def _iso_datetime(value: Any) -> str:
+    return value.isoformat() if value else ""
+
+
+def _build_libo_bus_route_payload(
+    rows: list[list[Any]],
+    graph_name: str,
+) -> dict[str, Any]:
+    routes: dict[str, dict[str, Any]] = {}
+    stop_ids: set[str] = set()
+    for row in rows:
+        (
+            route_id,
+            line_name,
+            direction,
+            start_stop,
+            end_stop,
+            stop_count,
+            fare_yuan,
+            first_bus,
+            last_bus,
+            distance_km,
+            path_source,
+            stop_id,
+            stop_name,
+            lng,
+            lat,
+            sequence,
+        ) = row
+        route_key = str(route_id or "")
+        if not route_key:
+            continue
+        route = routes.setdefault(
+            route_key,
+            {
+                "route_id": route_key,
+                "line_name": str(line_name or ""),
+                "direction": str(direction or ""),
+                "start_stop": str(start_stop or ""),
+                "end_stop": str(end_stop or ""),
+                "stop_count": int(stop_count or 0),
+                "fare_yuan": float(fare_yuan or 0),
+                "first_bus": str(first_bus or ""),
+                "last_bus": str(last_bus or ""),
+                "distance_km": float(distance_km or 0),
+                "path_source": str(path_source or "station_sequence"),
+                "stops": [],
+            },
+        )
+        if stop_id and lng is not None and lat is not None:
+            stop_key = str(stop_id)
+            stop_ids.add(stop_key)
+            route["stops"].append(
+                {
+                    "stop_id": stop_key,
+                    "name": str(stop_name or "未命名公交站"),
+                    "lng": float(lng),
+                    "lat": float(lat),
+                    "sequence": int(sequence or 0),
+                }
+            )
+
+    items = sorted(
+        routes.values(),
+        key=lambda route: (
+            route["line_name"],
+            route["route_id"],
+        ),
+    )
+    return {
+        "graph_name": graph_name,
+        "dataset": LIBO_BUS_DATASET,
+        "line_count": len({route["line_name"] for route in items}),
+        "direction_count": len(items),
+        "stop_count": len(stop_ids),
+        "route_stop_count": sum(len(route["stops"]) for route in items),
+        "items": items,
+    }
+
+
+def _read_libo_bus_routes(graph_name: str) -> dict[str, Any]:
+    graph = FalkorDB(
+        host=settings.falkordb_host,
+        port=settings.falkordb_port,
+    ).select_graph(graph_name)
+    rows = graph.query(
+        "MATCH (b:BusLine) WHERE b.dataset=$dataset "
+        "OPTIONAL MATCH (b)-[r:STOPS_AT]->(s:Place) "
+        "RETURN b.route_id,b.line_name,b.direction,b.start_stop,b.end_stop,"
+        "b.stop_count,b.fare_yuan,b.first_bus,b.last_bus,b.distance_km,"
+        "b.path_source,s.element_id,s.name,s.lng,s.lat,r.sequence "
+        "ORDER BY b.line_name,b.route_id,r.sequence",
+        {"dataset": LIBO_BUS_DATASET},
+    ).result_set
+    return _build_libo_bus_route_payload(rows, graph_name)
+
+
+_INTERNAL_ENRICHMENT_KEYS = {
+    "food_fusion_status",
+    "food_match_confidence",
+    "food_match_rule",
+    "food_match_score",
+    "food_name_similarity",
+    "food_address_similarity",
+    "food_coordinate_distance_m",
+    "candidate_dianping_name",
+    "food_candidate_name_similarity",
+    "food_candidate_address_similarity",
+    "hotel_fusion_status",
+    "hotel_match_confidence",
+    "hotel_match_rule",
+    "hotel_name_similarity",
+    "hotel_address_similarity",
+    "hotel_phone_exact_match",
+    "candidate_ctrip_name",
+    "hotel_candidate_name_similarity",
+    "hotel_candidate_address_similarity",
+    "ctrip_description",
+}
+
+_ZERO_MEANS_MISSING_ENRICHMENT_KEYS = {
+    "dianping_rating",
+    "dianping_review_count",
+    "dianping_avg_price",
+    "group_buy_count",
+    "review_sample_count",
+    "review_sample_avg_stars",
+    "ctrip_rating",
+    "ctrip_review_count",
+    "ctrip_room_count",
+    "room_min_price",
+    "room_max_price",
+    "offer_count",
+    "offer_min_price",
+    "offer_max_price",
+    "guest_review_sample_count",
+    "guest_review_sample_avg_score",
+}
+
+
+def _clean_enrichment_display_value(key: str, value: Any) -> Any:
+    """Convert scraped platform values into stable, user-facing display values."""
+    if key in _INTERNAL_ENRICHMENT_KEYS:
+        return None
+    if key in _ZERO_MEANS_MISSING_ENRICHMENT_KEYS:
+        try:
+            if float(value) == 0:
+                return None
+        except (TypeError, ValueError):
+            pass
+    if key == "ctrip_diamond_level":
+        text = str(value or "").strip()
+        if re.fullmatch(r"\d+(?:\.\d+)?钻", text):
+            return text
+        matched = re.fullmatch(
+            r"(\d+(?:\.\d+)?)\s+out\s+of\s+5\s+(?:rating|diamonds?)",
+            text,
+            flags=re.IGNORECASE,
+        )
+        return f"{matched.group(1)}钻" if matched else None
+    return value
+
+
+def _graph_poi_enrichment(
+    graph_name: str,
+    element_id: str,
+) -> tuple[list[str], dict[str, Any], dict[str, Any]]:
+    graph = FalkorDB(
+        host=settings.falkordb_host,
+        port=settings.falkordb_port,
+    ).select_graph(graph_name)
+    result = graph.query(
+        "MATCH (n {element_id:$element_id}) "
+        "RETURN labels(n), properties(n) LIMIT 1",
+        {"element_id": element_id},
+    ).result_set
+    if not result:
+        return [], {}, {}
+
+    labels = [str(label) for label in (result[0][0] or [])]
+    properties = result[0][1] if isinstance(result[0][1], dict) else {}
+
+    def pick(keys: tuple[str, ...]) -> dict[str, Any]:
+        result: dict[str, Any] = {}
+        for key in keys:
+            if key not in properties:
+                continue
+            value = _clean_enrichment_display_value(key, properties[key])
+            if value in (None, "", "[]", "{}"):
+                continue
+            result[key] = value
+        return result
+
+    return labels, pick(FOOD_ENRICHMENT_KEYS), pick(HOTEL_ENRICHMENT_KEYS)
+
+
+def _graph_poi_categories(graph_name: str) -> dict[str, list[str]]:
+    graph = FalkorDB(
+        host=settings.falkordb_host,
+        port=settings.falkordb_port,
+    ).select_graph(graph_name)
+    rows = graph.query(
+        "MATCH (n) "
+        "WHERE n.element_id IS NOT NULL "
+        "AND any(label IN labels(n) WHERE label IN "
+        "['FoodPlace','Hotel','ScenicSpot','TransitFacility']) "
+        "RETURN n.element_id, labels(n)"
+    ).result_set
+    label_names = {
+        "FoodPlace": "美食",
+        "Hotel": "酒店",
+        "ScenicSpot": "景点",
+        "TransitFacility": "交通设施",
+    }
+    result: dict[str, list[str]] = {}
+    for element_id, labels in rows:
+        categories = [
+            label_names[label]
+            for label in (labels or [])
+            if label in label_names
+        ]
+        if element_id and categories:
+            result[str(element_id)] = categories
+    return result
+
+
+@router.get("/plaza/map-pois")
+async def map_pois(
+    context: ProjectContext = Depends(get_project_context),
+    _user: CurrentUser = None,
+):
+    """Return lightweight, project-scoped POI points for the knowledge map."""
+    graph_name = _resolve_spatial_graph_name(context.graph_name)
+    s = settings.db_schema
+    async with get_conn() as conn:
+        async with conn.cursor() as cur:
+            await cur.execute(
+                f"""SELECT element_id, gaode_poi_id, name, type_label, place_type,
+                           lng, lat, address, district, city
+                    FROM {s}.amap_spatial_pois
+                    WHERE graph_name=%s
+                    ORDER BY type_label, name
+                    LIMIT 15000""",
+                (graph_name,),
+            )
+            rows = await cur.fetchall()
+    graph_categories = await asyncio.to_thread(
+        _graph_poi_categories,
+        graph_name,
+    )
+
+    items = [
+        {
+            "id": row["element_id"],
+            "gaode_poi_id": row["gaode_poi_id"],
+            "name": row["name"] or "未命名POI",
+            "category": row["type_label"] or "其他地点",
+            "categories": graph_categories.get(
+                str(row["element_id"]),
+                [row["type_label"] or "其他地点"],
+            ),
+            "place_type": row["place_type"] or "poi",
+            "lng": float(row["lng"]),
+            "lat": float(row["lat"]),
+            "address": row["address"] or "",
+            "district": row["district"] or "",
+            "city": row["city"] or "",
+        }
+        for row in rows
+        if row.get("lng") is not None and row.get("lat") is not None
+    ]
+    category_counts: dict[str, int] = {}
+    for item in items:
+        for category in item["categories"]:
+            category_counts[category] = category_counts.get(category, 0) + 1
+    return {
+        "graph_name": graph_name,
+        "total": len(items),
+        "categories": [
+            {"category": category, "count": count}
+            for category, count in sorted(
+                category_counts.items(),
+                key=lambda pair: (-pair[1], pair[0]),
+            )
+        ],
+        "items": items,
+    }
+
+
+@router.get("/plaza/bus-routes")
+async def bus_routes(
+    context: ProjectContext = Depends(get_project_context),
+    _user: CurrentUser = None,
+):
+    """Return the active project's graph-backed bus routes and ordered stops."""
+    graph_name = _resolve_spatial_graph_name(context.graph_name)
+    return await asyncio.to_thread(_read_libo_bus_routes, graph_name)
+
+
+@router.get("/plaza/map-pois/{place_id}")
+async def map_poi_detail(
+    place_id: str,
+    context: ProjectContext = Depends(get_project_context),
+    _user: CurrentUser = None,
+):
+    """Return useful detail fields for one POI in the active project."""
+    graph_name = _resolve_spatial_graph_name(context.graph_name)
+    s = settings.db_schema
+    async with get_conn() as conn:
+        async with conn.cursor() as cur:
+            await cur.execute(
+                f"""SELECT element_id, gaode_poi_id, name, type_label, place_type,
+                           amap_type, typecode, lng, lat, province, city, district,
+                           adcode, business_area, address, tel, open_time, rating,
+                           cost, level, tags, photo_urls, source, source_cell_id,
+                           source_resolution, source_scope_adcode,
+                           raw_jsonb,
+                           first_fetched_at, last_fetched_at
+                    FROM {s}.amap_spatial_pois
+                    WHERE graph_name=%s
+                      AND (element_id=%s OR gaode_poi_id=%s)
+                    LIMIT 1""",
+                (graph_name, place_id, place_id.removeprefix("amap:")),
+            )
+            row = await cur.fetchone()
+    if not row:
+        raise HTTPException(status_code=404, detail="当前项目中未找到该POI")
+
+    raw = row.get("raw_jsonb") or {}
+    if not isinstance(raw, dict):
+        raw = {}
+    graph_labels, food_enrichment, hotel_enrichment = await asyncio.to_thread(
+        _graph_poi_enrichment,
+        graph_name,
+        row["element_id"],
+    )
+    external_photos = _photo_urls(food_enrichment.get("dianping_shop_image"))
+    external_photos.extend(_photo_urls(hotel_enrichment.get("hotel_image_samples")))
+    photo_urls = list(dict.fromkeys([
+        *_photo_urls(row["photo_urls"]),
+        *external_photos,
+    ]))
+
+    return {
+        "graph_name": graph_name,
+        "id": row["element_id"],
+        "gaode_poi_id": row["gaode_poi_id"],
+        "name": row["name"] or "未命名POI",
+        "category": row["type_label"] or "其他地点",
+        "place_type": row["place_type"] or "poi",
+        "business_subcategory": raw.get("business_subcategory") or "",
+        "scenic_type": raw.get("scenic_type") or "",
+        "scenic_level": raw.get("scenic_level") or "",
+        "parent_scenic": raw.get("parent_scenic") or "",
+        "scenic_grade": raw.get("scenic_grade") or "",
+        "visitor_value": raw.get("visitor_value") or "",
+        "audit_result": raw.get("audit_result") or "",
+        "audit_confidence": raw.get("audit_confidence") or "",
+        "audit_basis": raw.get("audit_basis") or "",
+        "audit_date": raw.get("audit_date") or "",
+        "amap_type": row["amap_type"] or "",
+        "typecode": row["typecode"] or "",
+        "scan_hit_count": raw.get("scan_hit_count") or 0,
+        "matched_scan_types": raw.get("matched_scan_types") or [],
+        "lng": float(row["lng"]),
+        "lat": float(row["lat"]),
+        "province": row["province"] or "",
+        "city": row["city"] or "",
+        "district": row["district"] or "",
+        "adcode": row["adcode"] or "",
+        "business_area": row["business_area"] or "",
+        "address": row["address"] or "",
+        "tel": row["tel"] or "",
+        "open_time": row["open_time"] or "",
+        "rating": row["rating"] or "",
+        "cost": row["cost"] or "",
+        "level": row["level"] or "",
+        "tags": row["tags"] or "",
+        "photo_urls": photo_urls,
+        "source": row["source"] or "",
+        "source_cell_id": row["source_cell_id"] or "",
+        "source_resolution": row["source_resolution"],
+        "source_scope_adcode": row["source_scope_adcode"] or "",
+        "first_fetched_at": _iso_datetime(row["first_fetched_at"]),
+        "last_fetched_at": _iso_datetime(row["last_fetched_at"]),
+        "graph_labels": graph_labels,
+        "food_enrichment": food_enrichment,
+        "hotel_enrichment": hotel_enrichment,
+    }
+
+
 @router.post("/plaza/user-query")
-async def user_query(body: dict, _user: CurrentUser = None):
+async def user_query(
+    body: dict,
+    context: ProjectContext = Depends(get_project_context),
+    _user: CurrentUser = None,
+):
     """User-facing KG nearby query: NL intent -> H3 recall -> distance/rank -> LLM answer."""
     started_at = time.perf_counter()
     question = str(body.get("question") or "").strip()
     if not question:
         raise HTTPException(400, "question required")
+    graph_name = str(body.get("graph_name") or context.graph_name or SPATIAL_GRAPH_NAME)
+    if _is_enterprise_travel_graph(graph_name):
+        try:
+            graph_response = await answer_graph_question(
+                question,
+                graph_name,
+                customer_context=body.get("customer_context") if isinstance(body.get("customer_context"), dict) else {},
+                limit=int(body.get("limit") or 80),
+            )
+        except Exception as exc:  # noqa: BLE001
+            raise HTTPException(status_code=502, detail=f"LLM 图查询问答失败: {str(exc)[:220]}") from exc
+        trace = graph_response.get("trace") or {}
+        trace.update({
+            "latency_ms": max(1, round((time.perf_counter() - started_at) * 1000)),
+            "rule_query_used": False,
+            "plaza_user_mode": "enterprise_graph_qa",
+        })
+        return {
+            "mode": "travel_customer_service",
+            "question": question,
+            "graph_name": graph_name,
+            "user_location": {
+                "lng": float(body.get("lng", 106.7135) or 106.7135),
+                "lat": float(body.get("lat", 26.5744) or 26.5744),
+            },
+            "intent": {
+                "radius_m": int(body.get("radius_m") or 1000),
+                "category": "百姓惠客服",
+                "keywords": [],
+                "user_need": question,
+            },
+            "answer": graph_response.get("copy_text") or graph_response.get("answer") or "",
+            "results": [],
+            "plans": graph_response.get("plans") or [],
+            "evidence": graph_response.get("evidence") or [],
+            "follow_up_questions": graph_response.get("follow_up_questions") or [],
+            "risk_notes": graph_response.get("risk_notes") or [],
+            "trace": trace,
+        }
+    graph_name = _resolve_spatial_graph_name(graph_name)
     try:
         lng = float(body.get("lng", 106.7135))
         lat = float(body.get("lat", 26.5744))
@@ -327,8 +883,6 @@ async def user_query(body: dict, _user: CurrentUser = None):
         raise HTTPException(400, "lng/lat required") from exc
     radius_input = body.get("radius_m")
     radius_m = int(radius_input) if radius_input not in (None, "") else None
-    graph_name = str(body.get("graph_name") or SPATIAL_GRAPH_NAME)
-
     use_llm = body.get("use_llm") is True
     fallback = _rule_intent(question, radius_m)
     if use_llm:
diff --git a/app/api/travel_assistant.py b/app/api/travel_assistant.py
index 977a161..27edbdf 100644
--- a/app/api/travel_assistant.py
+++ b/app/api/travel_assistant.py
@@ -6,6 +6,7 @@ import re
 import asyncio
 import copy
 import time
+import uuid
 from typing import Any
 
 from falkordb import FalkorDB
@@ -14,10 +15,12 @@ from fastapi import APIRouter, Depends, Header, HTTPException
 from app.auth import CurrentUser
 from app.config import settings
 from app.db import get_agent_settings
+from app.graph_qa_engine import answer_graph_question
 from app.llm_client import LlmClient
 from app.project_context import ProjectContext, get_project_context
 
 router = APIRouter()
+public_router = APIRouter()
 
 ENTERPRISE_AGENT_TARGET_MS = 1200
 ENTERPRISE_AGENT_WARN_MS = 2500
@@ -231,9 +234,24 @@ def _cached_fee_bindings(graph_name: str) -> list[dict[str, Any]]:
     return _cached_graph_data(graph_name, "fee_bindings", _load_fee_bindings)
 
 
-def _configured_api_keys() -> set[str]:
-    raw = str(getattr(settings, "ingest_api_keys", "") or "")
-    return {item.strip() for item in re.split(r"[,;\s]+", raw) if item.strip()}
+def _split_api_keys(raw: Any) -> set[str]:
+    return {item.strip() for item in re.split(r"[,;\s]+", str(raw or "")) if item.strip()}
+
+
+async def _api_access_settings() -> dict[str, Any]:
+    try:
+        cfg = await get_agent_settings()
+    except Exception:
+        cfg = {}
+    access = cfg.get("api_access") if isinstance(cfg, dict) else {}
+    return access if isinstance(access, dict) else {}
+
+
+async def _configured_api_keys() -> set[str]:
+    keys = _split_api_keys(getattr(settings, "ingest_api_keys", ""))
+    access = await _api_access_settings()
+    keys.update(_split_api_keys(access.get("api_keys")))
+    return keys
 
 
 def _bearer_token(value: str | None) -> str:
@@ -248,9 +266,9 @@ async def _require_customer_service_api_key(
     x_api_key: str | None = Header(default=None, alias="X-API-Key"),
     authorization: str | None = Header(default=None, alias="Authorization"),
 ) -> str:
-    keys = _configured_api_keys()
+    keys = await _configured_api_keys()
     if not keys:
-        return "api-key-disabled"
+        raise HTTPException(status_code=503, detail="客服接口未配置 API Key")
     candidate = (x_kg_api_key or x_api_key or _bearer_token(authorization)).strip()
     if candidate and candidate in keys:
         return candidate
@@ -603,6 +621,17 @@ def _normalize_intent(question: str, fallback: dict[str, Any], data: dict[str, A
 
 async def _travel_llm_client(max_tokens: int = 1000) -> LlmClient | None:
     cfg = await get_agent_settings()
+    api_access = cfg.get("api_access") or {}
+    qa_llm = api_access.get("qa_llm") or {}
+    if qa_llm.get("base_url") and qa_llm.get("api_key"):
+        return LlmClient(
+            qa_llm["base_url"],
+            qa_llm["api_key"],
+            qa_llm.get("model") or "deepseek-chat",
+            timeout=int(qa_llm.get("timeout") or 45),
+            max_tokens=min(int(qa_llm.get("max_tokens") or max_tokens), max_tokens),
+        )
+
     global_cfg = cfg.get("global") or {}
     if global_cfg.get("base_url") and global_cfg.get("api_key"):
         return LlmClient(
@@ -796,20 +825,26 @@ def _fallback_customer_service_answer(
     source: str,
     error: str | None = None,
 ) -> dict[str, Any]:
-    text = _value(agent_response.get("copy_text"), 3000)
-    if not text:
+    answer_text = _value(agent_response.get("answer") or agent_response.get("copy_text"), 3000)
+    reply_text = _value(agent_response.get("copy_text") or agent_response.get("customer_reply") or answer_text, 3000)
+    if not answer_text:
         text = "当前知识图谱没有命中足够的线路或资源信息，建议先补充客户出行时间、人数、天数和必去景点后再核价。"
-    risk_notes = ["价格、余位、房型、车辆、门票和景区政策以团期及供应商二次核实为准。"]
+        answer_text = text
+        reply_text = text
+    risk_notes = _list_texts(agent_response.get("risk_notes"), limit=4, text_limit=160)
+    if not risk_notes:
+        risk_notes = ["价格、余位、房型、车辆、门票和景区政策以团期及供应商二次核实为准。"]
     trace = agent_response.get("trace") or {}
     for check in (trace.get("quality_checks") or [])[:4]:
         if isinstance(check, dict) and check.get("status") in {"warn", "fail"}:
             note = _value(check.get("detail") or check.get("label"), 140)
             if note and note not in risk_notes:
                 risk_notes.append(note)
+    default_confidence = 0.68 if agent_response.get("plans") else 0.42
     return {
-        "answer": text,
-        "customer_reply": text,
-        "confidence": 0.68 if agent_response.get("plans") else 0.42,
+        "answer": answer_text,
+        "customer_reply": reply_text or answer_text,
+        "confidence": _confidence(agent_response.get("confidence"), default_confidence),
         "next_questions": _list_texts(agent_response.get("follow_up_questions"), limit=4, text_limit=120),
         "risk_notes": risk_notes[:4],
         "llm_used": False,
@@ -818,6 +853,58 @@ def _fallback_customer_service_answer(
     }
 
 
+def _controlled_graph_qa_failure_response(
+    question: str,
+    graph_name: str,
+    error: Exception,
+    started_at: float,
+) -> dict[str, Any]:
+    latency_ms = max(1, round((time.perf_counter() - started_at) * 1000))
+    message = (
+        "当前问题已进入 LLM 图查询兜底，但没有在时间预算内得到可靠图谱答案。"
+        "建议补充具体产品、线路、景区、出发日期或套餐名称后再查。"
+    )
+    return {
+        "question": question,
+        "graph_name": graph_name,
+        "answer": message,
+        "customer_reply": "亲，这个问题当前图谱暂未查到可确认答案，需要补充更具体的线路、景区或套餐名称后再核实。",
+        "copy_text": "亲，这个问题当前图谱暂未查到可确认答案，需要补充更具体的线路、景区或套餐名称后再核实。",
+        "plans": [],
+        "evidence": [],
+        "sales_scripts": [],
+        "follow_up_questions": ["请补充具体线路/产品名称。", "请说明出发日期、人数或套餐名称。", "是否要改查百姓惠旅游线路、价格、景区或酒店？"],
+        "risk_notes": ["当前回复为受控兜底，不代表图谱已有明确业务证据。"],
+        "confidence": 0.22,
+        "trace": {
+            "method": "llm_graph_qa_controlled_failure_v1",
+            "response_mode": "llm_graph_qa_controlled_failure",
+            "response_mode_label": "LLM 图查询受控兜底",
+            "rule_query_used": False,
+            "llm_used": True,
+            "llm_error": str(error)[:300],
+            "latency_ms": latency_ms,
+            "stage_timings_ms": {
+                "intent_classification": 0,
+                "llm_planner": 0,
+                "schema": 0,
+                "cypher_generation": 0,
+                "graph_query": 0,
+                "fallback_graph_query": 0,
+                "answer_synthesis": 0,
+            },
+            "performance_target_ms": ENTERPRISE_AGENT_TARGET_MS,
+            "retrieval_summary": {
+                "rows": 0,
+                "nodes": 0,
+                "relationships": 0,
+                "error": str(error)[:300],
+            },
+            "graph_capabilities_used": ["LLM 图查询兜底", "受控失败返回"],
+        },
+    }
+
+
 def _confidence(value: Any, default: float = 0.72) -> float:
     try:
         return max(0.0, min(1.0, float(value)))
@@ -830,6 +917,11 @@ async def _fuse_customer_service_answer(
     agent_response: dict[str, Any],
     enabled: bool,
 ) -> dict[str, Any]:
+    trace = agent_response.get("trace") or {}
+    response_mode = str(trace.get("response_mode") or "")
+    if response_mode in {"llm_graph_qa", "fast_graph_template", "deterministic_context_llm_answer", "llm_graph_qa_controlled_failure"}:
+        return _fallback_customer_service_answer(agent_response, "kg_direct_customer_reply")
+
     if not enabled:
         return _fallback_customer_service_answer(agent_response, "kg_template")
 
@@ -2062,6 +2154,10 @@ def _infer_response_mode(response: dict[str, Any]) -> str:
 
 def _response_mode_label(mode: str) -> str:
     labels = {
+        "fast_graph_template": "高频客服问题快查",
+        "deterministic_context_llm_answer": "固定取证 + LLM 证据回答",
+        "llm_graph_qa": "LLM 图查询问答",
+        "llm_graph_qa_controlled_failure": "LLM 图查询受控兜底",
         "multi_task_agent": "多任务客服 Agent",
         "route_price": "线路报价",
         "route_catalog": "线路清单",
@@ -2083,6 +2179,8 @@ def _agent_capabilities(response: dict[str, Any]) -> list[str]:
     mode = _infer_response_mode(response)
     capabilities: list[str] = []
     mode_caps = {
+        "llm_graph_qa": ["LLM 生成 Cypher", "FalkorDB 只读查询", "证据融合回答"],
+        "deterministic_context_llm_answer": ["意图识别", "固定 Cypher 取证", "LLM 证据回答"],
         "multi_task_agent": ["多意图拆解", "KG 模板编排", "结构化聚合输出"],
         "route_price": ["线路报价", "团期价格", "核价边界"],
         "route_catalog": ["线路清单", "同线路版本合并", "后续追问入口"],
@@ -2304,8 +2402,11 @@ def _enrich_agent_response(response: dict[str, Any], started_at: float) -> dict[
     trace["quality_checks"] = checks
     trace["quality_summary"] = summary
     trace["agent_stages"] = _agent_stages(response, latency_ms)
-    trace["graph_capabilities_used"] = _agent_capabilities(response)
+    existing_caps = trace.get("graph_capabilities_used") or []
+    trace["graph_capabilities_used"] = list(dict.fromkeys([*existing_caps, *_agent_capabilities(response)]))
+    existing_retrieval = trace.get("retrieval_summary") or {}
     trace["retrieval_summary"] = {
+        **existing_retrieval,
         "plan_candidates": _as_count(trace.get("plan_candidates")) or returned_plan_count,
         "raw_plan_candidates": raw_candidate_count,
         "plans_returned": returned_plan_count,
@@ -2315,10 +2416,11 @@ def _enrich_agent_response(response: dict[str, Any], started_at: float) -> dict[
     trace["agent_design"] = {
         "current_test_goal": ["图查询命中质量", "客服回答可用性", "企业级响应速度", "报价/余位不可承诺边界"],
         "future_api_contract": {
-            "endpoint": "POST /v1/admin/travel/customer-service-query",
+            "endpoint": "POST /v1/openapi/knowledge-qa/query",
+            "compat_endpoint": "POST /v1/admin/travel/customer-service-query",
             "internal_test_endpoint": "POST /v1/admin/travel/assistant-query",
-            "request": ["question", "graph_name", "session_id/customer_context", "use_llm"],
-            "response": ["answer", "customer_reply", "plans", "evidence", "follow_up_questions", "trace"],
+            "request": ["request_id", "question", "graph_name", "session_id/customer_context", "use_llm"],
+            "response": ["request_id", "trace_id", "answer", "customer_reply", "plans", "evidence", "follow_up_questions", "trace"],
             "handoff": "外部客服系统消费融合回答和结构化证据；trace 用于质检、审计和图查询优化。",
         },
     }
@@ -5180,6 +5282,53 @@ async def travel_assistant_query(
     if "travel" not in graph_name.lower() and "旅行" not in context.project_id:
         graph_name = "travel_agency"
 
+    if _external_bool(body.get("llm_graph_query"), True):
+        try:
+            response = await asyncio.wait_for(
+                answer_graph_question(
+                    question,
+                    graph_name,
+                    customer_context=body.get("customer_context") if isinstance(body.get("customer_context"), dict) else {},
+                    limit=int(body.get("limit") or 80),
+                ),
+                timeout=float(body.get("llm_graph_timeout") or 12),
+            )
+        except Exception as exc:  # noqa: BLE001
+            response = _controlled_graph_qa_failure_response(question, graph_name, exc, started_at)
+            return _enrich_agent_response(response, started_at)
+
+        graph_trace = response.get("trace") or {}
+        graph_answer_llm_used = bool(graph_trace.get("llm_used"))
+        graph_planner_used = bool(graph_trace.get("llm_planner_used"))
+        graph_llm_used = graph_answer_llm_used or graph_planner_used
+        graph_decision = (
+            "llm_generated_cypher"
+            if graph_answer_llm_used
+            else "llm_planner_routed"
+            if graph_planner_used
+            else "deterministic_cypher_template"
+        )
+        response["intent"] = {
+            "raw_text": question,
+            "graph_name": graph_name,
+            "query_method": "intent_graph_qa_router",
+            "missing_fields": [],
+            "llm_requested": graph_llm_used,
+            "llm_used": graph_llm_used,
+            "llm_planner_used": graph_planner_used,
+            "llm_decision": graph_decision,
+        }
+        response.setdefault("trace", {}).update({
+            "intent_method": "llm_graph_query",
+            "intent_confidence": response.get("confidence"),
+            "llm_requested": graph_llm_used,
+            "llm_used": graph_answer_llm_used,
+            "llm_planner_used": graph_planner_used,
+            "llm_decision": graph_decision,
+            "rule_query_used": False,
+        })
+        return _enrich_agent_response(response, started_at)
+
     rule_intent = _extract_intent(question)
     rule_tasks = _agent_task_plan(question, rule_intent)
     rule_confidence = _rule_agent_confidence(question, rule_intent, rule_tasks)
@@ -5277,20 +5426,58 @@ async def travel_assistant_query(
     return _enrich_agent_response(response, started_at)
 
 
-@router.post("/travel/customer-service-query")
-async def travel_customer_service_query(
-    body: dict,
-    _api_key: str = Depends(_require_customer_service_api_key),
-):
-    question = str(body.get("question") or body.get("text") or body.get("query") or "").strip()
+def _external_request_id(body: dict[str, Any]) -> str:
+    request_id = _value(
+        body.get("request_id")
+        or body.get("message_id")
+        or body.get("external_request_id")
+        or "",
+        120,
+    )
+    return request_id or f"req_{uuid.uuid4().hex[:16]}"
+
+
+def _external_trace_id() -> str:
+    return f"trc_{uuid.uuid4().hex[:16]}"
+
+
+def _external_customer_context(body: dict[str, Any]) -> dict[str, Any]:
+    raw_context = body.get("customer_context")
+    context = dict(raw_context) if isinstance(raw_context, dict) else {}
+    for field in ("channel", "customer_id", "external_user_id", "user_id", "member_id"):
+        if body.get(field) not in (None, ""):
+            context.setdefault(field, body.get(field))
+    return context
+
+
+async def _customer_service_query_response(body: dict[str, Any]) -> dict[str, Any]:
+    api_access = await _api_access_settings()
+    request_id = _external_request_id(body)
+    trace_id = _external_trace_id()
+    question = str(
+        body.get("question")
+        or body.get("text")
+        or body.get("query")
+        or body.get("content")
+        or body.get("utterance")
+        or ""
+    ).strip()
     if not question:
         raise HTTPException(status_code=400, detail="请输入客户咨询内容")
 
+    session_id = _value(
+        body.get("session_id")
+        or body.get("conversation_id")
+        or body.get("dialogue_id")
+        or "",
+        120,
+    )
     graph_name = _normalize_customer_service_graph(
         body.get("graph_name")
         or body.get("knowledge_graph")
         or body.get("kg")
         or body.get("graph")
+        or api_access.get("default_graph")
         or BAIXINGHUI_GRAPH_NAME
     )
     context = ProjectContext(
@@ -5301,7 +5488,11 @@ async def travel_customer_service_query(
     agent_body = dict(body)
     agent_body["question"] = question
     agent_body["graph_name"] = graph_name
-    agent_body["use_llm"] = _external_bool(body.get("use_llm"), True)
+    agent_body["customer_context"] = _external_customer_context(body)
+    agent_body["use_llm"] = _external_bool(
+        body.get("use_llm"),
+        _external_bool(api_access.get("default_use_llm"), True),
+    )
 
     agent_response = await travel_assistant_query(
         agent_body,
@@ -5311,14 +5502,20 @@ async def travel_customer_service_query(
     fusion = await _fuse_customer_service_answer(
         question,
         agent_response,
-        _external_bool(body.get("llm_fusion"), True),
+        _external_bool(
+            body.get("llm_fusion"),
+            _external_bool(api_access.get("default_llm_fusion"), True),
+        ),
     )
     trace = agent_response.get("trace") or {}
     response: dict[str, Any] = {
         "status": "ok",
         "service": "baixinghui_customer_service",
         "api_version": "2026-06-10",
-        "session_id": _value(body.get("session_id"), 120),
+        "request_id": request_id,
+        "trace_id": trace_id,
+        "session_id": session_id,
+        "channel": _value(body.get("channel"), 80),
         "question": question,
         "graph_name": graph_name,
         "answer": fusion["answer"],
@@ -5349,7 +5546,16 @@ async def travel_customer_service_query(
             "error": fusion.get("llm_error"),
         },
         "trace": {
+            "request_id": request_id,
+            "trace_id": trace_id,
             "latency_ms": trace.get("latency_ms"),
+            "method": trace.get("method"),
+            "response_mode": trace.get("response_mode"),
+            "llm_used": trace.get("llm_used"),
+            "llm_error": trace.get("llm_error"),
+            "llm_planner_used": trace.get("llm_planner_used"),
+            "llm_planner": trace.get("llm_planner") or {},
+            "stage_timings_ms": trace.get("stage_timings_ms") or {},
             "speed": trace.get("speed") or {},
             "quality_summary": trace.get("quality_summary") or {},
             "retrieval_summary": trace.get("retrieval_summary") or {},
@@ -5357,5 +5563,29 @@ async def travel_customer_service_query(
         },
     }
     if _external_bool(body.get("return_raw_agent") or body.get("debug"), False):
+        response["debug"] = {
+            "generated_cypher": trace.get("generated_cypher"),
+            "effective_cypher": trace.get("effective_cypher"),
+            "fallback_cypher": trace.get("fallback_cypher"),
+            "fallback_query_used": trace.get("fallback_query_used"),
+            "cypher_repaired": trace.get("cypher_repaired"),
+            "stage_timings_ms": trace.get("stage_timings_ms") or {},
+        }
         response["raw_agent_response"] = agent_response
     return response
+
+
+@router.post("/travel/customer-service-query")
+async def travel_customer_service_query(
+    body: dict[str, Any],
+    _api_key: str = Depends(_require_customer_service_api_key),
+):
+    return await _customer_service_query_response(body)
+
+
+@public_router.post("/knowledge-qa/query")
+async def openapi_knowledge_qa_query(
+    body: dict[str, Any],
+    _api_key: str = Depends(_require_customer_service_api_key),
+):
+    return await _customer_service_query_response(body)
diff --git a/app/config.py b/app/config.py
index aa9bcd8..884e16e 100644
--- a/app/config.py
+++ b/app/config.py
@@ -39,5 +39,11 @@ class Settings(BaseSettings):
     amap_js_key: str = ""
     amap_security_jscode: str = ""
 
+    # 阿里云 OCR (ocr-api.cn-hangzhou.aliyuncs.com, 2021-07-07)
+    # 控制台 → AccessKey 管理 处生成；推荐用 RAM 子账号，仅授权 AliyunOCRFullAccess
+    aliyun_ocr_access_key_id: str = ""
+    aliyun_ocr_access_key_secret: str = ""
+    aliyun_ocr_endpoint: str = "ocr-api.cn-hangzhou.aliyuncs.com"
+
 
 settings = Settings()
diff --git a/app/db.py b/app/db.py
index adcd82d..0944e90 100644
--- a/app/db.py
+++ b/app/db.py
@@ -1573,7 +1573,7 @@ async def get_user_auth(username: str) -> dict | None:
                     FROM {s}.users u
                     LEFT JOIN {s}.user_roles ur ON ur.user_id = u.id
                     WHERE u.username=%s
-                    GROUP BY u.id""",
+                    GROUP BY u.id, u.username, u.full_name, u.hashed_password, u.status""",
                 (username,),
             )
             return await cur.fetchone()
@@ -1627,7 +1627,7 @@ async def update_user(user_id: int, data: dict, role_keys: list[str] | None) ->
                            COALESCE(array_agg(ur.role_key)
                                     FILTER (WHERE ur.role_key IS NOT NULL), '{{}}') AS roles
                     FROM {s}.users u LEFT JOIN {s}.user_roles ur ON ur.user_id=u.id
-                    WHERE u.id=%s GROUP BY u.id""",
+                    WHERE u.id=%s GROUP BY u.id, u.username, u.full_name, u.phone, u.status""",
                 (user_id,),
             )
             row = await cur.fetchone()
@@ -1896,6 +1896,19 @@ def _default_agent(label: str, enabled: bool = True) -> dict:
 
 DEFAULT_AGENT_CONFIG: dict = {
     "global": {"base_url": "", "model": "deepseek-chat", "api_key": "", "timeout": 30},
+    "api_access": {
+        "api_keys": settings.ingest_api_keys,
+        "default_graph": "baixinghui_travel_agency",
+        "default_use_llm": True,
+        "default_llm_fusion": True,
+        "qa_llm": {
+            "base_url": "",
+            "model": "deepseek-chat",
+            "api_key": "",
+            "timeout": 30,
+            "max_tokens": 1600,
+        },
+    },
     "thresholds": {
         "audit_hit": 0.7,
         "audit_gap": 0.4,
@@ -1986,6 +1999,13 @@ async def get_agent_settings() -> dict:
     cfg = row["config"]
     merged = {**DEFAULT_AGENT_CONFIG, **cfg}
     merged["global"] = {**DEFAULT_AGENT_CONFIG["global"], **cfg.get("global", {})}
+    saved_api_access = cfg.get("api_access", {}) or {}
+    api_access = {**DEFAULT_AGENT_CONFIG["api_access"], **saved_api_access}
+    api_access["qa_llm"] = {
+        **DEFAULT_AGENT_CONFIG["api_access"]["qa_llm"],
+        **(saved_api_access.get("qa_llm") or {}),
+    }
+    merged["api_access"] = api_access
     merged["thresholds"] = {**DEFAULT_AGENT_CONFIG["thresholds"], **cfg.get("thresholds", {})}
     # deep-merge each agent so newly added per-agent fields always appear
     saved_agents = cfg.get("agents", {})
@@ -2033,12 +2053,17 @@ async def save_agent_settings(config: dict) -> dict:
     async with get_conn() as conn:
         async with conn.cursor() as cur:
             await cur.execute(
-                f"""INSERT INTO {s}.agent_settings (settings_key, config, updated_at)
-                    VALUES ('agent', %s, now())
-                    ON CONFLICT (settings_key)
-                    DO UPDATE SET config=EXCLUDED.config, updated_at=now()""",
+                f"""UPDATE {s}.agent_settings
+                    SET config=%s, updated_at=now()
+                    WHERE settings_key='agent'""",
                 (json.dumps(config),),
             )
+            if cur.rowcount == 0:
+                await cur.execute(
+                    f"""INSERT INTO {s}.agent_settings (settings_key, config, updated_at)
+                        VALUES ('agent', %s, now())""",
+                    (json.dumps(config),),
+                )
         await conn.commit()
     return config
 
diff --git a/app/graph_qa_engine.py b/app/graph_qa_engine.py
new file mode 100644
index 0000000..9aa3a24
--- /dev/null
+++ b/app/graph_qa_engine.py
@@ -0,0 +1,2847 @@
+"""LLM-to-Cypher graph QA engine for enterprise knowledge-base questions."""
+from __future__ import annotations
+
+import asyncio
+import copy
+import json
+import re
+import time
+from typing import Any
+
+from falkordb import FalkorDB
+
+from app.config import settings
+from app.db import get_agent_settings
+from app.llm_client import LlmClient
+
+GRAPH_QA_MAX_LIMIT = 300
+SCHEMA_CACHE_TTL_SECONDS = 300
+QA_RESPONSE_CACHE_TTL_SECONDS = 600
+CYPHER_CACHE_TTL_SECONDS = 1800
+GRAPH_QA_PLANNER_TIMEOUT_SECONDS = 2.5
+GRAPH_QA_CYPHER_TIMEOUT_SECONDS = 4.5
+GRAPH_QA_REPAIR_TIMEOUT_SECONDS = 5.0
+GRAPH_QA_ANSWER_TIMEOUT_SECONDS = 6.0
+_SCHEMA_CACHE: dict[str, tuple[float, dict[str, Any]]] = {}
+_QA_RESPONSE_CACHE: dict[str, tuple[float, dict[str, Any]]] = {}
+_CYPHER_CACHE: dict[str, tuple[float, dict[str, Any]]] = {}
+WRITE_KEYWORDS = re.compile(
+    r"\b(CREATE|MERGE|SET|DELETE|DETACH|DROP|REMOVE|CALL\s+DB\.IDX|CALL\s+DB\.CONSTRAINT)\b",
+    re.IGNORECASE,
+)
+READ_START = re.compile(r"^(MATCH|RETURN|CALL)\b", re.IGNORECASE)
+
+GRAPH_QA_PLANNER_SYS = """你是百姓惠知识图谱客服问答的路由规划器。只输出 JSON：
+{"intent":"...","route":"...","confidence":0.0,"reason":"...","need_llm_graph":false}
+任务：判断用户问题应该先走哪条链路，不生成答案、不生成 Cypher。
+可选 intent：
+route_catalog、price_quote、fee_detail、vehicle_catalog、route_multihop_detail、
+condition_route_advice、route_compare_suitability、route_compare_scenic_count、
+route_context_advice、general_graph_qa。
+可选 route：
+template_graph_query、deterministic_context_llm_answer、llm_graph_qa。
+原则：高频客服问题优先 template_graph_query；需要推荐/解释但图谱可固定取证时选 deterministic_context_llm_answer；
+无法用模板覆盖的长尾问题才选 llm_graph_qa。不要臆造线路名。"""
+
+GRAPH_QA_CYPHER_SYS = """你是 FalkorDB/RedisGraph 只读 Cypher 规划器。只输出 JSON：
+{"cypher":"...","reason":"...","answer_focus":"..."}
+规则：只允许 MATCH/RETURN/CALL；禁止 CREATE/MERGE/SET/DELETE/DETACH/DROP/REMOVE；必须 LIMIT；中文用 CONTAINS。
+只给一条最短可执行查询，cypher 控制在 800 字以内，不要输出示例、解释或多条备选。
+百姓惠常用标签：TourProduct、ProductDay、RouteStop、ScenicAttraction、TravelItem、ProductPricePlan、PolicyRule、SalesScript。
+价格：TourProduct-[:PRODUCT_HAS_PRICE_PLAN]->ProductPricePlan，字段 adult_price_min/max、child_price_min/max、single_room_diff_min/max。
+费用/小交通：TourProduct-[:PRODUCT_USES_TRAVEL_ITEM]->TravelItem；TravelItem 字段 name、type、subtype、category、price、adult_price、unit、raw_evidence、requires_supplier_confirm。
+黄小西/小西：按黄果树、小七孔、西江相关线路匹配。"""
+
+GRAPH_QA_REPAIR_SYS = """你是 FalkorDB/RedisGraph Cypher 修复器。只输出 JSON。
+根据执行错误修复上一条只读 Cypher。仍然必须只读、以 MATCH/RETURN/CALL 开头、带 LIMIT。
+字段：cypher、reason、answer_focus。"""
+
+GRAPH_QA_ANSWER_SYS = """你是百姓惠客服图谱问答助手。只输出 JSON。
+基于 graph_result 回答，不编造价格、余位、房型、车辆或承诺；证据不足就提示二次核实。
+customer_reply 控制在 100 字内，answer 控制在 360 字内。
+字段：answer、customer_reply、confidence、follow_up_questions、risk_notes、evidence_cards。"""
+
+
+def _get_graph(graph_name: str):
+    db = FalkorDB(host=settings.falkordb_host, port=settings.falkordb_port)
+    return db.select_graph(graph_name)
+
+
+def _safe_int(value: Any, default: int) -> int:
+    try:
+        return int(value)
+    except Exception:
+        return default
+
+
+async def _chat_json_with_retry(
+    client: LlmClient,
+    system_prompt: str,
+    user_prompt: str,
+    *,
+    attempts: int = 2,
+) -> dict[str, Any]:
+    last_exc: Exception | None = None
+    for attempt in range(max(1, attempts)):
+        try:
+            return await asyncio.to_thread(client.chat_json, system_prompt, user_prompt)
+        except Exception as exc:  # noqa: BLE001
+            last_exc = exc
+            if attempt >= attempts - 1:
+                break
+            await asyncio.sleep(0.8 * (attempt + 1))
+    raise last_exc or RuntimeError("LLM JSON 调用失败")
+
+
+async def _chat_json_timed(
+    client: LlmClient,
+    system_prompt: str,
+    user_prompt: str,
+    *,
+    timeout_seconds: float,
+    attempts: int = 1,
+) -> dict[str, Any]:
+    return await asyncio.wait_for(
+        _chat_json_with_retry(client, system_prompt, user_prompt, attempts=attempts),
+        timeout=timeout_seconds,
+    )
+
+
+async def _graph_qa_client(max_tokens: int = 1600, *, use_config_max_tokens: bool = True) -> LlmClient | None:
+    try:
+        cfg = await get_agent_settings()
+    except Exception:
+        cfg = {}
+
+    api_access = cfg.get("api_access") if isinstance(cfg, dict) else {}
+    qa_llm = (api_access or {}).get("qa_llm") if isinstance(api_access, dict) else {}
+    if isinstance(qa_llm, dict) and qa_llm.get("base_url") and qa_llm.get("api_key"):
+        configured_max_tokens = _safe_int(qa_llm.get("max_tokens"), max_tokens)
+        return LlmClient(
+            qa_llm["base_url"],
+            qa_llm["api_key"],
+            qa_llm.get("model") or settings.llm_model or "deepseek-chat",
+            timeout=_safe_int(qa_llm.get("timeout"), settings.llm_timeout_seconds or 45),
+            max_tokens=min(configured_max_tokens, max_tokens) if use_config_max_tokens else max_tokens,
+        )
+
+    global_cfg = cfg.get("global") if isinstance(cfg, dict) else {}
+    if isinstance(global_cfg, dict) and global_cfg.get("base_url") and global_cfg.get("api_key"):
+        return LlmClient(
+            global_cfg["base_url"],
+            global_cfg["api_key"],
+            global_cfg.get("model") or settings.llm_model or "deepseek-chat",
+            timeout=_safe_int(global_cfg.get("timeout"), settings.llm_timeout_seconds or 45),
+            max_tokens=max_tokens,
+        )
+
+    if settings.llm_api_base and settings.llm_api_key:
+        return LlmClient(
+            settings.llm_api_base,
+            settings.llm_api_key,
+            settings.llm_model or "deepseek-chat",
+            timeout=settings.llm_timeout_seconds,
+            max_tokens=max_tokens,
+        )
+
+    extract = cfg.get("extract") if isinstance(cfg, dict) else {}
+    extract = extract if isinstance(extract, dict) else {}
+    models = extract.get("models") or {}
+    models = models if isinstance(models, dict) else {}
+    keys = [extract.get("aggregator")] + [
+        key for key, value in models.items() if isinstance(value, dict) and value.get("enabled")
+    ] + list(models.keys())
+    for key in keys:
+        model_cfg = models.get(key or "")
+        if isinstance(model_cfg, dict) and model_cfg.get("base_url") and model_cfg.get("api_key"):
+            return LlmClient(
+                model_cfg["base_url"],
+                model_cfg["api_key"],
+                model_cfg.get("model") or settings.llm_model or "deepseek-chat",
+                timeout=int(extract.get("timeout") or settings.llm_timeout_seconds or 60),
+                max_tokens=max_tokens,
+            )
+    return None
+
+
+def _assert_read_only(cypher: str) -> None:
+    if not cypher:
+        raise ValueError("Cypher query required")
+    if WRITE_KEYWORDS.search(cypher):
+        raise ValueError("Read-only queries only")
+    if not READ_START.match(cypher):
+        raise ValueError("Only MATCH, RETURN, or CALL queries allowed")
+
+
+def _clean_cypher(cypher: Any, limit: int) -> str:
+    text = str(cypher or "").strip()
+    text = re.sub(r"^```(?:cypher)?\s*", "", text, flags=re.I).strip()
+    text = text.removesuffix("```").strip().rstrip(";")
+    if not re.search(r"\bLIMIT\s+\d+\b", text, flags=re.IGNORECASE):
+        text = f"{text} LIMIT {limit}"
+    _assert_read_only(text)
+    return text
+
+
+def _compact_scalar(value: Any, limit: int = 500) -> Any:
+    if value is None or isinstance(value, (int, float, bool)):
+        return value
+    if isinstance(value, (list, tuple)):
+        return [_compact_scalar(item, 180) for item in value[:20]]
+    text = re.sub(r"\s+", " ", str(value)).strip()
+    return text[:limit]
+
+
+def _node_id(node: Any) -> str:
+    value = getattr(node, "id", None)
+    return str(value if value is not None else node)
+
+
+def _node_summary(node: Any) -> dict[str, Any]:
+    props = dict(getattr(node, "properties", None) or {})
+    labels = list(getattr(node, "labels", None) or [])
+    title = ""
+    for key in (
+        "display_name", "name", "title", "label", "product_name",
+        "route_line_name", "natural_key", "product_id", "item_id",
+    ):
+        if props.get(key):
+            title = str(props[key])
+            break
+    if not title:
+        title = f"{labels[0] if labels else 'Node'} #{_node_id(node)}"
+    return {
+        "id": _node_id(node),
+        "labels": labels,
+        "title": title[:160],
+        "properties": {str(k): _compact_scalar(v, 700) for k, v in props.items()},
+    }
+
+
+def _edge_summary(edge: Any) -> dict[str, Any]:
+    props = dict(getattr(edge, "properties", None) or {})
+    return {
+        "id": str(getattr(edge, "id", "")),
+        "type": str(getattr(edge, "relation", "") or ""),
+        "from": _node_id(getattr(edge, "src_node", "")),
+        "to": _node_id(getattr(edge, "dest_node", "")),
+        "properties": {str(k): _compact_scalar(v, 300) for k, v in props.items()},
+    }
+
+
+def _compact_value(value: Any) -> Any:
+    if hasattr(value, "labels") and hasattr(value, "properties"):
+        return {"node": _node_summary(value)}
+    if hasattr(value, "src_node") and hasattr(value, "dest_node"):
+        return {"relationship": _edge_summary(value)}
+    if (
+        hasattr(value, "nodes")
+        and callable(getattr(value, "nodes"))
+        and hasattr(value, "edges")
+        and callable(getattr(value, "edges"))
+    ):
+        return {
+            "path": {
+                "nodes": [_node_summary(node) for node in value.nodes()],
+                "relationships": [_edge_summary(edge) for edge in value.edges()],
+            }
+        }
+    if isinstance(value, (list, tuple)):
+        return [_compact_value(item) for item in value[:20]]
+    if isinstance(value, dict):
+        return {str(k): _compact_value(v) for k, v in list(value.items())[:30]}
+    return _compact_scalar(value)
+
+
+def _extract_graph_items(rows: list[list[Any]]) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
+    nodes: dict[str, dict[str, Any]] = {}
+    edges: dict[str, dict[str, Any]] = {}
+
+    def walk(value: Any) -> None:
+        if hasattr(value, "labels") and hasattr(value, "properties"):
+            nodes.setdefault(_node_id(value), _node_summary(value))
+            return
+        if hasattr(value, "src_node") and hasattr(value, "dest_node"):
+            edge = _edge_summary(value)
+            key = edge["id"] or f"{edge['from']}-{edge['type']}-{edge['to']}"
+            edges.setdefault(key, edge)
+            return
+        if (
+            hasattr(value, "nodes")
+            and callable(getattr(value, "nodes"))
+            and hasattr(value, "edges")
+            and callable(getattr(value, "edges"))
+        ):
+            for node in value.nodes():
+                walk(node)
+            for edge in value.edges():
+                walk(edge)
+            return
+        if isinstance(value, (list, tuple)):
+            for item in value:
+                walk(item)
+
+    for row in rows:
+        walk(row)
+    return list(nodes.values()), list(edges.values())
+
+
+def _header_names(header: Any) -> list[str]:
+    out: list[str] = []
+    for item in header or []:
+        if isinstance(item, (list, tuple)) and len(item) > 1:
+            out.append(str(item[1]))
+        else:
+            out.append(str(item))
+    return out
+
+
+def _run_cypher(graph_name: str, cypher: str, limit: int) -> dict[str, Any]:
+    graph = _get_graph(graph_name)
+    result = graph.query(cypher)
+    rows = list(result.result_set)[:limit]
+    nodes, relationships = _extract_graph_items(rows)
+    compact_rows = [[_compact_value(value) for value in row] for row in rows[:40]]
+    return {
+        "cypher": cypher,
+        "columns": _header_names(result.header),
+        "rows": compact_rows,
+        "row_count": len(rows),
+        "nodes": nodes,
+        "relationships": relationships,
+    }
+
+
+FEE_QUESTION_TERMS = (
+    "费用", "自费", "自理", "另付", "不含", "包含", "小交通", "观光车", "环保车",
+    "电瓶车", "索道", "扶梯", "游船", "门票", "二消", "必付", "可选",
+)
+PRICE_QUESTION_TERMS = (
+    "多少钱", "价格", "报价", "成人价", "儿童价", "小孩价", "房差", "单房差", "结算价",
+)
+VEHICLE_QUESTION_TERMS = (
+    "车型", "车辆", "用车", "车有哪些", "什么车", "商务车", "大巴", "中巴", "小包团用车",
+)
+COMPLEX_QUESTION_TERMS = (
+    "推荐", "对比", "比较", "为什么", "怎么安排", "如何安排", "适合", "帮我", "方案",
+    "预算", "老人", "亲子", "团队", "定制", "如果", "同时", "综合", "详细行程",
+)
+FAMILY_CONDITION_TERMS = ("老人", "老年", "长辈", "小孩", "孩子", "儿童", "亲子", "家庭", "一家")
+COMFORT_CONDITION_TERMS = ("不累", "不要太累", "太累", "轻松", "舒适", "少走路", "慢一点", "不赶", "休闲", "轻奢")
+BUDGET_CONDITION_TERMS = ("预算", "便宜", "划算", "性价比", "不贵", "低价", "经济")
+ROUTE_COMPARE_TERMS = ("哪个", "哪条", "对比", "比较", "更多", "更少", "包含")
+SCENIC_QUESTION_TERMS = (
+    "景区", "景点", "去哪", "去哪里", "去哪些", "游玩", "打卡", "途经", "经过",
+)
+HOTEL_QUESTION_TERMS = (
+    "酒店", "住宿", "入住", "住哪里", "住哪", "附近酒店", "附近入住", "附近住宿",
+)
+SCENIC_HINT_ALIASES: dict[str, tuple[str, ...]] = {
+    "荔波小七孔景区": ("小七孔", "荔波"),
+    "西江千户苗寨景区": ("西江", "千户苗寨", "苗寨"),
+    "黄果树旅游景区": ("黄果树", "瀑布"),
+    "梵净山景区": ("梵净山", "镇梵"),
+    "青岩古镇": ("青岩", "青岩古镇"),
+    "镇远古城": ("镇远", "镇远古城"),
+    "贵阳": ("贵阳",),
+    "安顺": ("安顺",),
+}
+FEE_EVIDENCE_TERMS = (
+    "raw_evidence", "ScenicTransport", "ScenicOptional", "景区费用项目", "观光车",
+    "环保车", "电瓶车", "小交通", "索道", "扶梯", "游船", "门票", "自费", "不含", "另付",
+)
+
+
+def _is_fee_question(question: str) -> bool:
+    return any(term in question for term in FEE_QUESTION_TERMS)
+
+
+def _is_price_question(question: str) -> bool:
+    return any(term in question for term in PRICE_QUESTION_TERMS)
+
+
+def _is_vehicle_question(question: str) -> bool:
+    return any(term in question for term in VEHICLE_QUESTION_TERMS)
+
+
+def _has_duration_question(question: str) -> bool:
+    return bool(_route_duration_clauses(question)) or any(term in question for term in ("几天", "多少天", "天数", "玩几天", "行程几天"))
+
+
+def _is_scenic_question(question: str) -> bool:
+    return any(term in question for term in SCENIC_QUESTION_TERMS)
+
+
+def _is_hotel_question(question: str) -> bool:
+    return any(term in question for term in HOTEL_QUESTION_TERMS)
+
+
+def _is_route_multihop_question(question: str) -> bool:
+    if not _route_name_terms(question) or not _is_hotel_question(question):
+        return False
+    facets = [
+        _is_price_question(question),
+        _has_duration_question(question),
+        _is_scenic_question(question),
+        _is_hotel_question(question),
+    ]
+    return sum(1 for item in facets if item) >= 3
+
+
+def _is_route_compare_scenic_count_question(question: str) -> bool:
+    terms = _route_name_terms(question)
+    return (
+        len(terms) >= 2
+        and any(term in question for term in ROUTE_COMPARE_TERMS)
+        and any(term in question for term in ("景点", "景区", "包含", "去的地方", "玩的地方"))
+        and any(term in question for term in ("更多", "多", "少", "哪个", "哪条"))
+    )
+
+
+def _is_route_compare_suitability_question(question: str) -> bool:
+    terms = _route_name_terms(question)
+    slots = _condition_slots(question)
+    return (
+        len(terms) >= 2
+        and (slots["family"] or slots["comfort"] or slots["budget"])
+        and any(term in question for term in ("哪个", "哪条", "对比", "比较", "适合", "推荐", "为什么"))
+    )
+
+
+def _condition_slots(question: str) -> dict[str, bool]:
+    return {
+        "family": any(term in question for term in FAMILY_CONDITION_TERMS),
+        "comfort": any(term in question for term in COMFORT_CONDITION_TERMS),
+        "budget": any(term in question for term in BUDGET_CONDITION_TERMS),
+        "recommend": any(term in question for term in ("推荐", "适合", "有没有", "哪条", "帮我", "怎么选")),
+    }
+
+
+def _is_condition_route_advice_question(question: str) -> bool:
+    slots = _condition_slots(question)
+    return (
+        not _route_name_terms(question)
+        and slots["recommend"]
+        and (slots["family"] or slots["comfort"] or slots["budget"])
+    )
+
+
+def _normalized_question(question: str) -> str:
+    text = re.sub(r"\s+", "", question.strip().lower())
+    return (
+        text.replace("路线", "线路")
+        .replace("产品", "线路")
+        .replace("报价", "价格")
+        .replace("成人价", "价格")
+        .replace("小孩价", "儿童价")
+    )
+
+
+PLANNER_ROUTE_BY_INTENT = {
+    "route_catalog": "template_graph_query",
+    "price_quote": "template_graph_query",
+    "fee_detail": "template_graph_query",
+    "vehicle_catalog": "template_graph_query",
+    "route_multihop_detail": "template_graph_query",
+    "condition_route_advice": "template_graph_query",
+    "route_compare_suitability": "template_graph_query",
+    "route_compare_scenic_count": "template_graph_query",
+    "route_context_advice": "deterministic_context_llm_answer",
+    "general_graph_qa": "llm_graph_qa",
+}
+
+
+def _planner_enabled_from_context(customer_context: dict[str, Any] | None) -> bool:
+    if not isinstance(customer_context, dict):
+        return False
+    value = customer_context.get("llm_planner")
+    if value is None:
+        value = customer_context.get("force_llm_planner")
+    return str(value).strip().lower() in {"1", "true", "yes", "on", "启用", "强制"}
+
+
+def _should_use_llm_planner(intent: dict[str, Any], customer_context: dict[str, Any] | None) -> bool:
+    if _planner_enabled_from_context(customer_context):
+        return True
+    route = str(intent.get("route") or "")
+    confidence = _safe_confidence(intent.get("confidence"), 0.0)
+    return route == "llm_graph_qa" or confidence < 0.7
+
+
+def _planner_trace(
+    *,
+    used: bool,
+    skipped_reason: str = "",
+    latency_ms: int = 0,
+    error: str = "",
+    decision: dict[str, Any] | None = None,
+) -> dict[str, Any]:
+    return {
+        "used": used,
+        "latency_ms": latency_ms,
+        "timeout_ms": round(GRAPH_QA_PLANNER_TIMEOUT_SECONDS * 1000),
+        "skipped_reason": skipped_reason,
+        "error": error,
+        "decision": decision or {},
+    }
+
+
+def _normalize_planner_decision(base_intent: dict[str, Any], decision: dict[str, Any]) -> dict[str, Any]:
+    planned_intent = str(decision.get("intent") or "").strip()
+    if planned_intent not in PLANNER_ROUTE_BY_INTENT:
+        return base_intent
+    confidence = _safe_confidence(decision.get("confidence"), _safe_confidence(base_intent.get("confidence"), 0.55))
+    route = PLANNER_ROUTE_BY_INTENT[planned_intent]
+    return {
+        **base_intent,
+        "intent": planned_intent,
+        "route": route,
+        "confidence": confidence,
+        "complexity": str(decision.get("complexity") or base_intent.get("complexity") or "planned"),
+        "reason": str(decision.get("reason") or base_intent.get("reason") or "LLM 规划器选择链路。")[:260],
+        "planner_need_llm_graph": bool(decision.get("need_llm_graph")) or route == "llm_graph_qa",
+    }
+
+
+async def _llm_plan_intent(
+    question: str,
+    graph_name: str,
+    base_intent: dict[str, Any],
+    customer_context: dict[str, Any] | None,
+) -> tuple[dict[str, Any], dict[str, Any]]:
+    if not _should_use_llm_planner(base_intent, customer_context):
+        return base_intent, _planner_trace(used=False, skipped_reason="high_confidence_template_or_context_route")
+    client = await _graph_qa_client(max_tokens=320, use_config_max_tokens=False)
+    if client is None:
+        return base_intent, _planner_trace(used=False, skipped_reason="llm_not_configured")
+    client.timeout = min(float(getattr(client, "timeout", GRAPH_QA_PLANNER_TIMEOUT_SECONDS) or GRAPH_QA_PLANNER_TIMEOUT_SECONDS), GRAPH_QA_PLANNER_TIMEOUT_SECONDS)
+    payload = {
+        "question": question,
+        "graph_name": graph_name,
+        "rule_intent": base_intent,
+        "route_terms": _route_name_terms(question),
+        "condition_slots": _condition_slots(question),
+        "allowed_intents": list(PLANNER_ROUTE_BY_INTENT.keys()),
+        "customer_context": customer_context or {},
+    }
+    started = time.perf_counter()
+    try:
+        decision = await _chat_json_timed(
+            client,
+            GRAPH_QA_PLANNER_SYS,
+            json.dumps(payload, ensure_ascii=False),
+            timeout_seconds=GRAPH_QA_PLANNER_TIMEOUT_SECONDS,
+            attempts=1,
+        )
+    except asyncio.TimeoutError:
+        latency_ms = max(1, round((time.perf_counter() - started) * 1000))
+        return base_intent, _planner_trace(used=True, latency_ms=latency_ms, error="planner_timeout")
+    except Exception as exc:  # noqa: BLE001
+        latency_ms = max(1, round((time.perf_counter() - started) * 1000))
+        return base_intent, _planner_trace(used=True, latency_ms=latency_ms, error=str(exc)[:220])
+    latency_ms = max(1, round((time.perf_counter() - started) * 1000))
+    planned = _normalize_planner_decision(base_intent, decision)
+    return planned, _planner_trace(used=True, latency_ms=latency_ms, decision=decision)
+
+
+def _classify_graph_qa_intent(question: str) -> dict[str, Any]:
+    normalized = _normalized_question(question)
+    terms = _route_name_terms(question)
+    duration_clauses = _route_duration_clauses(question)
+    complex_hint = len(question) > 72 or any(term in question for term in COMPLEX_QUESTION_TERMS)
+    intent = {
+        "intent": "general_graph_qa",
+        "route": "llm_graph_qa",
+        "confidence": 0.48 if complex_hint else 0.58,
+        "complexity": "complex" if complex_hint else "open",
+        "slots": {
+            "route_terms": terms,
+            "has_duration": bool(duration_clauses),
+        },
+        "reason": "未命中标准模板，使用 LLM 生成 Cypher 做通用图查询。",
+    }
+    if _is_route_list_question(question):
+        return {
+            **intent,
+            "intent": "route_catalog",
+            "route": "template_graph_query",
+            "confidence": 0.95,
+            "complexity": "standard",
+            "reason": "线路清单类问题可由 TourProduct 固定模板回答。",
+        }
+    if _is_condition_route_advice_question(question):
+        return {
+            **intent,
+            "intent": "condition_route_advice",
+            "route": "template_graph_query",
+            "confidence": 0.82,
+            "complexity": "standard_condition_filter",
+            "slots": {
+                **intent["slots"],
+                "condition_slots": _condition_slots(question),
+            },
+            "reason": "未指定线路但给出家庭/舒适/预算条件，使用固定图查询筛选候选线路并模板回答。",
+        }
+    if _is_route_compare_suitability_question(question):
+        return {
+            **intent,
+            "intent": "route_compare_suitability",
+            "route": "template_graph_query",
+            "confidence": 0.84,
+            "complexity": "standard_suitability_compare",
+            "slots": {
+                **intent["slots"],
+                "condition_slots": _condition_slots(question),
+            },
+            "reason": "多线路适配度对比已识别条件词，可固定取证后用评分模板快速回答。",
+        }
+    if _is_route_compare_scenic_count_question(question):
+        return {
+            **intent,
+            "intent": "route_compare_scenic_count",
+            "route": "template_graph_query",
+            "confidence": 0.86,
+            "complexity": "standard_compare",
+            "reason": "线路景点数量对比可由固定取证统计 ScenicAttraction 数量回答。",
+        }
+    if _is_vehicle_question(question) and any(term in normalized for term in ("车型", "车辆", "用车", "车")):
+        return {
+            **intent,
+            "intent": "vehicle_catalog",
+            "route": "template_graph_query",
+            "confidence": 0.88,
+            "complexity": "standard",
+            "reason": "车辆/车型类问题可由 TravelItem 用车项目固定模板回答。",
+        }
+    if _is_route_multihop_question(question):
+        return {
+            **intent,
+            "intent": "route_multihop_detail",
+            "route": "template_graph_query",
+            "confidence": 0.91,
+            "complexity": "standard_multihop",
+            "reason": "线路价格、天数、途经景区和附近酒店属于标准多跳图谱查询，可用固定模板快速回答。",
+        }
+    if _is_price_question(question) and terms:
+        return {
+            **intent,
+            "intent": "price_quote",
+            "route": "template_graph_query",
+            "confidence": 0.9,
+            "complexity": "standard",
+            "reason": "线路报价类问题已识别线路实体和天数，可直接查 ProductPricePlan。",
+        }
+    if _is_fee_question(question) and terms:
+        return {
+            **intent,
+            "intent": "fee_detail",
+            "route": "template_graph_query",
+            "confidence": 0.86,
+            "complexity": "standard",
+            "reason": "费用/小交通类问题已识别线路实体，可直接查 TravelItem。",
+        }
+    if complex_hint and terms:
+        return {
+            **intent,
+            "intent": "route_context_advice",
+            "route": "deterministic_context_llm_answer",
+            "confidence": 0.76,
+            "complexity": "complex_with_entities",
+            "reason": "复杂推荐/对比问题已识别线路实体，先用固定 Cypher 取证据，再让 LLM 基于证据组织答案。",
+        }
+    return intent
+
+
+def _has_fee_evidence(graph_result: dict[str, Any]) -> bool:
+    if not graph_result.get("row_count"):
+        return False
+    text = json.dumps(
+        {
+            "rows": graph_result.get("rows") or [],
+            "nodes": graph_result.get("nodes") or [],
+            "relationships": graph_result.get("relationships") or [],
+        },
+        ensure_ascii=False,
+        default=str,
+    )
+    return any(term in text for term in FEE_EVIDENCE_TERMS)
+
+
+def _cypher_quote(value: str) -> str:
+    return value.replace("\\", "\\\\").replace("'", "\\'")
+
+
+def _is_valid_route_term(term: str) -> bool:
+    text = term.strip()
+    if len(text) < 2:
+        return False
+    noisy_fragments = (
+        "适合", "推荐", "有没有", "不要", "不累", "太累", "轻松", "舒适", "老人", "小孩",
+        "孩子", "儿童", "家庭", "预算", "便宜", "划算", "哪些", "什么", "哪个", "多少",
+        "可以", "附近", "入住", "酒店",
+    )
+    if any(fragment in text for fragment in noisy_fragments):
+        return False
+    return True
+
+
+def _route_name_terms(question: str) -> list[str]:
+    terms: list[str] = []
+    if "小西镇梵" in question:
+        terms.append("小西镇梵")
+    if "黄小西镇梵" in question:
+        terms.append("黄小西镇梵")
+    if "黄小西" in question:
+        terms.append("黄小西")
+    elif "小西" in question:
+        terms.append("小西")
+    for term in ("黄果树", "小七孔", "荔波", "西江", "千户苗寨", "青岩", "梵净山", "镇远"):
+        if term in question:
+            terms.append(term)
+    if not terms:
+        for match in re.findall(r"[\u4e00-\u9fa5A-Za-z0-9]{2,12}(?:游|线路|产品|团)", question):
+            terms.append(match.replace("线路", "").replace("产品", "").replace("团", ""))
+    out: list[str] = []
+    for term in terms:
+        if _is_valid_route_term(term) and term not in out:
+            out.append(term)
+    return out[:6]
+
+
+def _route_duration_clauses(question: str) -> list[str]:
+    match = re.search(r"(\d+)\s*(?:日|天)", question)
+    days = int(match.group(1)) if match else None
+    chinese_days = {"一": 1, "二": 2, "两": 2, "三": 3, "四": 4, "五": 5, "六": 6, "七": 7}
+    for text, value in chinese_days.items():
+        if f"{text}日" in question or f"{text}天" in question:
+            days = value
+            break
+    if not days:
+        return []
+    return [
+        f"p.duration_days = {days}",
+        f"p.name CONTAINS '{days}日'",
+        f"p.name CONTAINS '{days}天'",
+        f"p.name CONTAINS '{list(chinese_days.keys())[list(chinese_days.values()).index(days)]}日'" if days in chinese_days.values() else "",
+    ]
+
+
+def _fee_fallback_cypher(question: str, limit: int) -> str | None:
+    terms = _route_name_terms(question)
+    if not terms:
+        return None
+    name_clauses: list[str] = []
+    for term in terms:
+        quoted = _cypher_quote(term)
+        name_clauses.extend([
+            f"p.name CONTAINS '{quoted}'",
+            f"p.display_name CONTAINS '{quoted}'",
+            f"p.product_name CONTAINS '{quoted}'",
+        ])
+    duration_clauses = [item for item in _route_duration_clauses(question) if item]
+    where_parts = [f"({' OR '.join(name_clauses)})"]
+    if duration_clauses:
+        where_parts.append(f"({' OR '.join(duration_clauses)})")
+    where_clause = " AND ".join(where_parts)
+    return f"""
+MATCH (p:TourProduct)
+WHERE {where_clause}
+OPTIONAL MATCH (p)-[:PRODUCT_USES_TRAVEL_ITEM]->(direct_item:TravelItem)
+OPTIONAL MATCH (p)-[:PRODUCT_HAS_DAY]->(d:ProductDay)-[:DAY_HAS_STOP]->(s:RouteStop)
+OPTIONAL MATCH (s)-[:STOP_VISITS_ATTRACTION]->(a:ScenicAttraction)
+OPTIONAL MATCH (s)-[:STOP_USES_TRAVEL_ITEM]->(stop_item:TravelItem)
+OPTIONAL MATCH (a)-[:ATTRACTION_HAS_ITEM]->(attraction_item:TravelItem)
+RETURN
+  p.name AS product_name,
+  p.product_id AS product_id,
+  p.duration_days AS duration_days,
+  collect(DISTINCT {{
+    name: direct_item.name,
+    type: direct_item.type,
+    subtype: direct_item.subtype,
+    category: direct_item.category,
+    status: direct_item.default_status,
+    price: direct_item.price,
+    adult_price: direct_item.adult_price,
+    unit: direct_item.unit,
+    raw_evidence: direct_item.raw_evidence,
+    requires_supplier_confirm: direct_item.requires_supplier_confirm
+  }}) AS product_items,
+  collect(DISTINCT {{
+    stop_name: s.name,
+    attraction_name: a.name,
+    name: stop_item.name,
+    type: stop_item.type,
+    subtype: stop_item.subtype,
+    category: stop_item.category,
+    status: stop_item.default_status,
+    price: stop_item.price,
+    adult_price: stop_item.adult_price,
+    unit: stop_item.unit,
+    raw_evidence: stop_item.raw_evidence,
+    requires_supplier_confirm: stop_item.requires_supplier_confirm
+  }}) AS stop_items,
+  collect(DISTINCT {{
+    stop_name: s.name,
+    attraction_name: a.name,
+    name: attraction_item.name,
+    type: attraction_item.type,
+    subtype: attraction_item.subtype,
+    category: attraction_item.category,
+    status: attraction_item.default_status,
+    price: attraction_item.price,
+    adult_price: attraction_item.adult_price,
+    unit: attraction_item.unit,
+    raw_evidence: attraction_item.raw_evidence,
+    requires_supplier_confirm: attraction_item.requires_supplier_confirm
+  }}) AS attraction_items
+LIMIT {limit}
+""".strip()
+
+
+def _price_fallback_cypher(question: str, limit: int) -> str | None:
+    terms = _route_name_terms(question)
+    if not terms:
+        return None
+    name_clauses: list[str] = []
+    for term in terms:
+        quoted = _cypher_quote(term)
+        name_clauses.extend([
+            f"p.name CONTAINS '{quoted}'",
+            f"p.display_name CONTAINS '{quoted}'",
+            f"p.product_name CONTAINS '{quoted}'",
+        ])
+    duration_clauses = [item for item in _route_duration_clauses(question) if item]
+    where_parts = [f"({' OR '.join(name_clauses)})"]
+    if duration_clauses:
+        where_parts.append(f"({' OR '.join(duration_clauses)})")
+    where_clause = " AND ".join(where_parts)
+    return f"""
+MATCH (p:TourProduct)
+WHERE {where_clause}
+OPTIONAL MATCH (p)-[:PRODUCT_HAS_PRICE_PLAN]->(plan:ProductPricePlan)
+RETURN
+  p.name AS product_name,
+  p.product_id AS product_id,
+  p.duration_days AS duration_days,
+  collect(DISTINCT {{
+    plan_name: plan.plan_name,
+    display_name: plan.display_name,
+    adult_price_min: plan.adult_price_min,
+    adult_price_max: plan.adult_price_max,
+    child_price_min: plan.child_price_min,
+    child_price_max: plan.child_price_max,
+    single_room_diff_min: plan.single_room_diff_min,
+    single_room_diff_max: plan.single_room_diff_max,
+    adult_settlement_source: plan.adult_settlement_source,
+    child_settlement_source: plan.child_settlement_source
+  }}) AS price_plans
+LIMIT {limit}
+""".strip()
+
+
+def _route_catalog_cypher(limit: int) -> str:
+    return f"""
+MATCH (p:TourProduct)
+RETURN
+  p.name AS product_name,
+  p.display_name AS display_name,
+  p.product_id AS product_id,
+  p.duration_days AS duration_days
+ORDER BY p.duration_days, p.name
+LIMIT {limit}
+""".strip()
+
+
+def _vehicle_catalog_cypher(limit: int) -> str:
+    return f"""
+MATCH (item:TravelItem)
+WHERE item.name CONTAINS '车'
+   OR item.subtype CONTAINS '用车'
+   OR item.category CONTAINS '用车'
+RETURN
+  item.name AS name,
+  item.type AS type,
+  item.subtype AS subtype,
+  item.price AS price,
+  item.unit AS unit,
+  item.raw_evidence AS raw_evidence
+ORDER BY item.name
+LIMIT {limit}
+""".strip()
+
+
+def _route_context_cypher(question: str, limit: int) -> str | None:
+    terms = _route_name_terms(question)
+    if not terms:
+        return None
+    name_clauses: list[str] = []
+    for term in terms:
+        quoted = _cypher_quote(term)
+        name_clauses.extend([
+            f"p.name CONTAINS '{quoted}'",
+            f"p.display_name CONTAINS '{quoted}'",
+            f"p.product_name CONTAINS '{quoted}'",
+        ])
+    where_clause = f"({' OR '.join(name_clauses)})"
+    return f"""
+MATCH (p:TourProduct)
+WHERE {where_clause}
+OPTIONAL MATCH (p)-[:PRODUCT_HAS_PRICE_PLAN]->(plan:ProductPricePlan)
+OPTIONAL MATCH (p)-[:PRODUCT_HAS_DAY]->(d:ProductDay)-[:DAY_HAS_STOP]->(s:RouteStop)
+OPTIONAL MATCH (s)-[:STOP_VISITS_ATTRACTION]->(a:ScenicAttraction)
+RETURN
+  p.name AS product_name,
+  p.product_id AS product_id,
+  p.duration_days AS duration_days,
+  collect(DISTINCT {{
+    plan_name: plan.plan_name,
+    adult_price_min: plan.adult_price_min,
+    adult_price_max: plan.adult_price_max,
+    child_price_min: plan.child_price_min,
+    child_price_max: plan.child_price_max,
+    single_room_diff_min: plan.single_room_diff_min,
+    single_room_diff_max: plan.single_room_diff_max
+  }}) AS price_plans,
+  collect(DISTINCT {{
+    day: d.day_index,
+    stop_name: s.name,
+    attraction_name: a.name,
+    sequence: s.sequence
+  }}) AS route_points,
+  count(DISTINCT a) AS attraction_count
+LIMIT {min(limit, 40)}
+""".strip()
+
+
+def _condition_context_cypher(limit: int) -> str:
+    return f"""
+MATCH (p:TourProduct)
+OPTIONAL MATCH (p)-[:PRODUCT_HAS_PRICE_PLAN]->(plan:ProductPricePlan)
+OPTIONAL MATCH (p)-[:PRODUCT_HAS_DAY]->(d:ProductDay)-[:DAY_HAS_STOP]->(s:RouteStop)
+OPTIONAL MATCH (s)-[:STOP_VISITS_ATTRACTION]->(a:ScenicAttraction)
+RETURN
+  p.name AS product_name,
+  p.product_id AS product_id,
+  p.duration_days AS duration_days,
+  collect(DISTINCT {{
+    plan_name: plan.plan_name,
+    adult_price_min: plan.adult_price_min,
+    adult_price_max: plan.adult_price_max,
+    child_price_min: plan.child_price_min,
+    child_price_max: plan.child_price_max,
+    single_room_diff_min: plan.single_room_diff_min,
+    single_room_diff_max: plan.single_room_diff_max
+  }}) AS price_plans,
+  collect(DISTINCT {{
+    day: d.day_index,
+    stop_name: s.name,
+    attraction_name: a.name,
+    sequence: s.sequence
+  }}) AS route_points,
+  count(DISTINCT a) AS attraction_count
+ORDER BY p.duration_days, p.name
+LIMIT {min(limit, 80)}
+""".strip()
+
+
+def _scenic_hint_terms(question: str) -> list[str]:
+    hints: list[str] = []
+    for scenic_name, aliases in SCENIC_HINT_ALIASES.items():
+        if scenic_name in question or any(alias in question for alias in aliases):
+            hints.append(scenic_name)
+            hints.extend(aliases)
+    out: list[str] = []
+    for hint in hints:
+        if hint and hint not in out:
+            out.append(hint)
+    return out
+
+
+def _route_feature_terms(question: str) -> list[str]:
+    candidates = ("轻奢", "纯玩", "2+1", "头等舱", "精品", "小团", "私家团", "跟团", "亲子")
+    return [term for term in candidates if term in question]
+
+
+def _route_multihop_cypher(question: str, limit: int) -> str | None:
+    terms = _route_name_terms(question)
+    if not terms:
+        return None
+    name_clauses: list[str] = []
+    for term in terms + _route_feature_terms(question):
+        quoted = _cypher_quote(term)
+        name_clauses.extend([
+            f"p.name CONTAINS '{quoted}'",
+            f"p.display_name CONTAINS '{quoted}'",
+            f"p.product_name CONTAINS '{quoted}'",
+        ])
+    duration_clauses = [item for item in _route_duration_clauses(question) if item]
+    where_parts = [f"({' OR '.join(name_clauses)})"]
+    if duration_clauses:
+        where_parts.append(f"({' OR '.join(duration_clauses)})")
+    where_clause = " AND ".join(where_parts)
+    return f"""
+MATCH (p:TourProduct)
+WHERE {where_clause}
+OPTIONAL MATCH (p)-[:PRODUCT_HAS_PRICE_PLAN]->(plan:ProductPricePlan)
+OPTIONAL MATCH (p)-[:PRODUCT_HAS_DAY]->(d:ProductDay)-[:DAY_HAS_STOP]->(s:RouteStop)
+OPTIONAL MATCH (s)-[:STOP_VISITS_ATTRACTION]->(a:ScenicAttraction)
+OPTIONAL MATCH (a)-[near:ATTRACTION_NEARBY_HOTEL]-(h:Hotel)
+RETURN
+  p.name AS product_name,
+  p.product_id AS product_id,
+  p.duration_days AS duration_days,
+  collect(DISTINCT {{
+    plan_name: plan.plan_name,
+    display_name: plan.display_name,
+    adult_price_min: plan.adult_price_min,
+    adult_price_max: plan.adult_price_max,
+    child_price_min: plan.child_price_min,
+    child_price_max: plan.child_price_max,
+    single_room_diff_min: plan.single_room_diff_min,
+    single_room_diff_max: plan.single_room_diff_max
+  }}) AS price_plans,
+  collect(DISTINCT {{
+    day: d.day_index,
+    sequence: s.sequence,
+    stop_name: s.name,
+    attraction_name: a.name
+  }}) AS route_points,
+  collect(DISTINCT {{
+    scenic_name: a.name,
+    stop_name: s.name,
+    hotel_name: h.name,
+    star_rating: h.star_rating,
+    city: h.city,
+    county: h.county,
+    address: h.address,
+    features: h.features,
+    driving_distance_km: near.driving_distance_km,
+    driving_time_minutes: near.driving_time_minutes,
+    recommend_rank: near.recommend_rank,
+    usage_note: near.usage_note,
+    remark: near.remark
+  }}) AS nearby_hotels
+LIMIT {min(limit, 60)}
+""".strip()
+
+
+def _schema_snapshot(graph_name: str) -> dict[str, Any]:
+    now = time.monotonic()
+    cached = _SCHEMA_CACHE.get(graph_name)
+    if cached and now - cached[0] <= SCHEMA_CACHE_TTL_SECONDS:
+        return cached[1]
+    graph = _get_graph(graph_name)
+    labels: list[dict[str, Any]] = []
+    relations: list[dict[str, Any]] = []
+    samples: list[dict[str, Any]] = []
+    try:
+        for labels_value, count in graph.query(
+            "MATCH (n) RETURN labels(n) AS labels, count(n) AS count LIMIT 120"
+        ).result_set:
+            label = labels_value[0] if labels_value else ""
+            labels.append({"label": label, "count": count})
+    except Exception:
+        labels = []
+    try:
+        for rel_type, count in graph.query(
+            "MATCH ()-[r]->() RETURN type(r) AS type, count(r) AS count LIMIT 160"
+        ).result_set:
+            relations.append({"type": rel_type, "count": count})
+    except Exception:
+        relations = []
+    for item in labels[:12]:
+        label = item.get("label")
+        if not label or not re.match(r"^[A-Za-z_][A-Za-z0-9_]*$", str(label)):
+            continue
+        try:
+            rows = graph.query(f"MATCH (n:{label}) RETURN n LIMIT 1").result_set
+        except Exception:
+            continue
+        for row in rows:
+            node = row[0]
+            props = dict(getattr(node, "properties", None) or {})
+            samples.append({
+                "label": label,
+                "properties": {
+                    str(k): _compact_scalar(v, 120)
+                    for k, v in list(props.items())[:12]
+                },
+            })
+    snapshot = {"labels": labels[:80], "relations": relations[:100], "node_samples": samples[:16]}
+    _SCHEMA_CACHE[graph_name] = (now, snapshot)
+    return snapshot
+
+
+def _list_texts(value: Any, limit: int, text_limit: int) -> list[str]:
+    if not isinstance(value, list):
+        return []
+    out: list[str] = []
+    for item in value[:limit]:
+        text = re.sub(r"\s+", " ", str(item or "")).strip()
+        if text:
+            out.append(text[:text_limit])
+    return out
+
+
+def _is_route_list_question(question: str) -> bool:
+    return any(term in question for term in ("线路有哪些", "路线有哪些", "产品有哪些", "有哪些线路", "有哪些路线", "有哪些产品", "旅行车线路"))
+
+
+def _route_items_from_rows(graph_result: dict[str, Any]) -> list[dict[str, Any]]:
+    items: list[dict[str, Any]] = []
+    seen: set[str] = set()
+    for row in graph_result.get("rows") or []:
+        if not isinstance(row, list) or not row:
+            continue
+        name = ""
+        duration = None
+        for value in row:
+            if isinstance(value, str) and value.strip():
+                name = value.strip()
+                break
+        for value in row:
+            if isinstance(value, (int, float)) and 0 < value <= 30:
+                duration = int(value)
+                break
+        if name and name not in seen:
+            seen.add(name)
+            items.append({"name": name, "duration_days": duration})
+    return items
+
+
+def _money(value: Any) -> str:
+    if value in (None, ""):
+        return ""
+    try:
+        number = float(value)
+    except Exception:
+        return str(value)
+    if number.is_integer():
+        return str(int(number))
+    return f"{number:.2f}".rstrip("0").rstrip(".")
+
+
+def _money_range(min_value: Any, max_value: Any, unit: str = "元/人") -> str:
+    low = _money(min_value)
+    high = _money(max_value)
+    if low and high and low != high:
+        return f"{low}-{high}{unit}"
+    if low or high:
+        return f"{low or high}{unit}"
+    return ""
+
+
+def _price_plans_from_rows(graph_result: dict[str, Any]) -> list[dict[str, Any]]:
+    products: list[dict[str, Any]] = []
+    for row in graph_result.get("rows") or []:
+        if not isinstance(row, list) or len(row) < 4:
+            continue
+        product_name = str(row[0] or "").strip()
+        if not product_name:
+            continue
+        plans: list[dict[str, Any]] = []
+        for raw_plan in row[3] if isinstance(row[3], list) else []:
+            if not isinstance(raw_plan, dict):
+                continue
+            if not any(raw_plan.get(k) not in (None, "") for k in (
+                "plan_name", "display_name", "adult_price_min", "adult_price_max",
+                "child_price_min", "child_price_max", "single_room_diff_min",
+                "single_room_diff_max",
+            )):
+                continue
+            plans.append(raw_plan)
+        products.append({
+            "product_name": product_name,
+            "product_id": row[1] if len(row) > 1 else "",
+            "duration_days": row[2] if len(row) > 2 else None,
+            "plans": plans,
+        })
+    return products
+
+
+def _route_list_answer(question: str, graph_result: dict[str, Any]) -> tuple[str, str] | None:
+    if not _is_route_list_question(question):
+        return None
+    items = _route_items_from_rows(graph_result)
+    if not items:
+        return None
+    lines = [
+        f"当前图谱共查到 {len(items)} 条旅行线路：",
+        *[
+            f"{idx}. {item['name']}" + (f"（{item['duration_days']}日）" if item.get("duration_days") else "")
+            for idx, item in enumerate(items, start=1)
+        ],
+        "如需进一步报价，请继续指定线路名称、出发日期、人数和住宿偏好。",
+    ]
+    answer = "\n".join(lines)
+    preview_items = items[:10]
+    customer = "目前可查到 " + str(len(items)) + " 条旅行线路，主要包括：" + "、".join(
+        item["name"] + (f"（{item['duration_days']}日）" if item.get("duration_days") else "")
+        for item in preview_items
+    )
+    if len(items) > len(preview_items):
+        customer += f"等，剩余 {len(items) - len(preview_items)} 条可继续筛选。"
+    else:
+        customer += "。"
+    customer += "您想看哪条线路的价格、行程或余位？"
+    return answer, customer
+
+
+def _price_template_answer(question: str, graph_result: dict[str, Any]) -> tuple[str, str, list[dict[str, str]], list[dict[str, Any]]] | None:
+    products = _price_plans_from_rows(graph_result)
+    if not products:
+        return None
+
+    lines = [f"已在图谱中匹配到 {len(products)} 条相关线路报价："]
+    evidence: list[dict[str, str]] = []
+    plans: list[dict[str, Any]] = []
+    for idx, product in enumerate(products[:8], start=1):
+        title = str(product["product_name"])
+        day_suffix = f"（{product['duration_days']}日）" if product.get("duration_days") else ""
+        plan_lines: list[str] = []
+        for plan in product["plans"][:8]:
+            plan_name = str(plan.get("display_name") or plan.get("plan_name") or "默认报价档位")
+            adult = _money_range(plan.get("adult_price_min"), plan.get("adult_price_max"))
+            child = _money_range(plan.get("child_price_min"), plan.get("child_price_max"))
+            room = _money_range(plan.get("single_room_diff_min"), plan.get("single_room_diff_max"), "元")
+            parts = [plan_name]
+            if adult:
+                parts.append(f"成人 {adult}")
+            if child:
+                parts.append(f"儿童 {child}")
+            if room:
+                parts.append(f"单房差 {room}")
+            plan_lines.append("，".join(parts))
+        if not plan_lines:
+            plan_lines.append("图谱暂未录入明确报价档位，需要按团期核价")
+        lines.append(f"{idx}. {title}{day_suffix}：" + "；".join(plan_lines))
+        summary = "；".join(plan_lines)[:360]
+        evidence.append({
+            "type": "报价证据",
+            "name": title[:120],
+            "summary": summary,
+            "source": "FalkorDB 图查询 ProductPricePlan",
+        })
+        plans.append({
+            "rank": idx,
+            "label": "线路报价",
+            "plan_name": title,
+            "product_name": title,
+            "fit_score": max(60, 96 - idx * 3),
+            "match_reasons": ["命中线路名称/天数", "读取 ProductPricePlan 报价档位"],
+            "route_summary": f"{title}{day_suffix}",
+            "quote_summary": summary,
+            "variant_summary": summary,
+            "daily_itinerary": [],
+            "hotels": [],
+            "restaurants": [],
+            "vehicles": [],
+            "policies": [],
+            "cost_breakdown": [],
+            "plan_kind": "fast_price_template",
+        })
+    lines.append("以上为图谱报价档位，最终价格、余位、房型和儿童口径需要按具体出发日期二次核实。")
+    answer = "\n".join(lines)
+    first = products[0]
+    first_plans = first.get("plans") or []
+    if first_plans:
+        plan = first_plans[0]
+        adult = _money_range(plan.get("adult_price_min"), plan.get("adult_price_max"))
+        child = _money_range(plan.get("child_price_min"), plan.get("child_price_max"))
+        bits = [str(first["product_name"])]
+        if adult:
+            bits.append(f"成人参考 {adult}")
+        if child:
+            bits.append(f"儿童参考 {child}")
+        customer = "，".join(bits) + "。具体价格和余位需要按出发日期、人数、住宿档位再核实。"
+    else:
+        customer = f"已匹配到 {first['product_name']}，但图谱暂未给出明确报价档位，需要按出发日期和人数核价。"
+    return answer, customer, evidence, plans
+
+
+def _non_empty_maps(value: Any) -> list[dict[str, Any]]:
+    if not isinstance(value, list):
+        return []
+    out: list[dict[str, Any]] = []
+    for item in value:
+        if isinstance(item, dict) and any(v not in (None, "") for v in item.values()):
+            out.append(item)
+    return out
+
+
+def _route_match_score(question: str, product: dict[str, Any]) -> int:
+    name = str(product.get("product_name") or "")
+    score = 0
+    for term in _route_name_terms(question):
+        if term and term in name:
+            score += 12
+    for term in _route_feature_terms(question):
+        if term and term in name:
+            score += 18
+    match = re.search(r"(\d+)\s*(?:日|天)", question)
+    if match and _safe_int(product.get("duration_days"), 0) == int(match.group(1)):
+        score += 15
+    for chinese, value in {"一": 1, "二": 2, "两": 2, "三": 3, "四": 4, "五": 5}.items():
+        if (f"{chinese}日" in question or f"{chinese}天" in question) and _safe_int(product.get("duration_days"), 0) == value:
+            score += 15
+    return score
+
+
+def _route_multihop_products_from_rows(question: str, graph_result: dict[str, Any]) -> list[dict[str, Any]]:
+    products: list[dict[str, Any]] = []
+    for row in graph_result.get("rows") or []:
+        if not isinstance(row, list) or len(row) < 6:
+            continue
+        product = {
+            "product_name": str(row[0] or "").strip(),
+            "product_id": row[1] if len(row) > 1 else "",
+            "duration_days": row[2] if len(row) > 2 else None,
+            "price_plans": _non_empty_maps(row[3]),
+            "route_points": _non_empty_maps(row[4]),
+            "nearby_hotels": _non_empty_maps(row[5]),
+        }
+        if product["product_name"]:
+            product["match_score"] = _route_match_score(question, product)
+            products.append(product)
+    products.sort(key=lambda item: (item.get("match_score") or 0, -_safe_int(item.get("duration_days"), 99)), reverse=True)
+    return products
+
+
+def _aggregate_price_text(plans: list[dict[str, Any]]) -> tuple[str, str, str]:
+    adult_lows: list[float] = []
+    adult_highs: list[float] = []
+    child_lows: list[float] = []
+    child_highs: list[float] = []
+    for plan in plans:
+        for bucket, key in ((adult_lows, "adult_price_min"), (adult_highs, "adult_price_max"), (child_lows, "child_price_min"), (child_highs, "child_price_max")):
+            try:
+                value = float(plan.get(key))
+            except Exception:
+                continue
+            if value > 0:
+                bucket.append(value)
+    adult = _money_range(min(adult_lows) if adult_lows else None, max(adult_highs) if adult_highs else None)
+    child = _money_range(min(child_lows) if child_lows else None, max(child_highs) if child_highs else None)
+    samples: list[str] = []
+    for plan in plans[:5]:
+        name = str(plan.get("display_name") or plan.get("plan_name") or "报价档位").strip()
+        adult_item = _money_range(plan.get("adult_price_min"), plan.get("adult_price_max"))
+        child_item = _money_range(plan.get("child_price_min"), plan.get("child_price_max"))
+        parts = [name]
+        if adult_item:
+            parts.append(f"成人 {adult_item}")
+        if child_item:
+            parts.append(f"儿童 {child_item}")
+        samples.append("，".join(parts))
+    return adult, child, "；".join(samples)
+
+
+def _route_point_key(point: dict[str, Any]) -> tuple[int, int, str]:
+    return (
+        _safe_int(point.get("day"), 99),
+        _safe_int(point.get("sequence"), 99),
+        str(point.get("attraction_name") or point.get("stop_name") or ""),
+    )
+
+
+def _is_non_scenic_route_node(name: str) -> bool:
+    compact = re.sub(r"\s+", "", name)
+    if any(term in compact for term in ("送机", "送站", "接机", "接站", "机场", "高铁站", "火车站", "散团", "集合")):
+        return True
+    if compact in {"贵阳", "安顺", "贵阳/安顺", "贵阳安顺"}:
+        return True
+    return bool(re.fullmatch(r"(贵阳|安顺|遵义|凯里|铜仁|荔波|西江)(/|、)(贵阳|安顺|遵义|凯里|铜仁|荔波|西江)", compact))
+
+
+def _route_scenic_names(points: list[dict[str, Any]], limit: int = 12) -> list[str]:
+    out: list[str] = []
+    for point in sorted(points, key=_route_point_key):
+        name = str(point.get("attraction_name") or point.get("stop_name") or "").strip()
+        if _is_non_scenic_route_node(name):
+            continue
+        if name and name not in out:
+            out.append(name)
+        if len(out) >= limit:
+            break
+    return out
+
+
+def _hotel_sort_key(item: dict[str, Any]) -> tuple[int, float, str]:
+    rank = _safe_int(item.get("recommend_rank"), 999)
+    try:
+        distance = float(item.get("driving_distance_km"))
+    except Exception:
+        distance = 9999.0
+    return rank, distance, str(item.get("hotel_name") or "")
+
+
+def _filter_hotels(question: str, hotels: list[dict[str, Any]], limit: int = 8) -> list[dict[str, Any]]:
+    hints = _scenic_hint_terms(question)
+    out: list[dict[str, Any]] = []
+    seen: set[str] = set()
+    for item in sorted(hotels, key=_hotel_sort_key):
+        hotel_name = str(item.get("hotel_name") or "").strip()
+        if not hotel_name:
+            continue
+        scenic_text = " ".join(str(item.get(field) or "") for field in ("scenic_name", "stop_name", "county", "city", "address"))
+        if hints and not any(hint and hint in scenic_text for hint in hints):
+            continue
+        key = f"{item.get('scenic_name') or item.get('stop_name')}|{hotel_name}"
+        if key in seen:
+            continue
+        seen.add(key)
+        out.append(item)
+        if len(out) >= limit:
+            break
+    if out or hints:
+        return out
+    for item in sorted(hotels, key=_hotel_sort_key):
+        hotel_name = str(item.get("hotel_name") or "").strip()
+        if not hotel_name:
+            continue
+        key = f"{item.get('scenic_name') or item.get('stop_name')}|{hotel_name}"
+        if key in seen:
+            continue
+        seen.add(key)
+        out.append(item)
+        if len(out) >= limit:
+            break
+    return out
+
+
+def _hotel_line(item: dict[str, Any]) -> str:
+    name = str(item.get("hotel_name") or "").strip()
+    scenic = str(item.get("scenic_name") or item.get("stop_name") or "相关景区").strip()
+    star = str(item.get("star_rating") or "").strip()
+    location = " ".join(str(item.get(field) or "").strip() for field in ("county", "address") if item.get(field)).strip()
+    distance = _money(item.get("driving_distance_km"))
+    minutes = _money(item.get("driving_time_minutes"))
+    parts = [name]
+    if star:
+        parts.append(star)
+    if distance:
+        parts.append(f"距{scenic}约{distance}km")
+    if minutes:
+        parts.append(f"车程约{minutes}分钟")
+    if location:
+        parts.append(location)
+    return "，".join(parts)
+
+
+def _route_multihop_template_answer(question: str, graph_result: dict[str, Any]) -> tuple[str, str, list[dict[str, str]], list[dict[str, Any]]] | None:
+    products = _route_multihop_products_from_rows(question, graph_result)
+    if not products:
+        return None
+    product = products[0]
+    product_name = str(product["product_name"])
+    day_text = f"{product['duration_days']}天" if product.get("duration_days") else "天数待核实"
+    adult_price, child_price, price_samples = _aggregate_price_text(product["price_plans"])
+    scenic_names = _route_scenic_names(product["route_points"])
+    hotels = _filter_hotels(question, product["nearby_hotels"], limit=8)
+
+    price_parts = []
+    if adult_price:
+        price_parts.append(f"成人参考 {adult_price}")
+    if child_price:
+        price_parts.append(f"儿童参考 {child_price}")
+    price_text = "，".join(price_parts) or "图谱暂未录入明确报价档位"
+    scenic_text = "、".join(scenic_names) if scenic_names else "图谱暂未查到明确途经景区"
+    hotel_texts = [_hotel_line(item) for item in hotels[:6]]
+    if hotel_texts:
+        hotel_text = "；".join(hotel_texts)
+    elif _scenic_hint_terms(question):
+        hotel_text = "该景区附近酒店证据不足，需要按具体入住地再核实。"
+    else:
+        hotel_text = "请指定一个景区后，我可以继续筛选附近可住酒店。"
+
+    lines = [
+        f"已按百姓惠图谱匹配到线路：{product_name}。",
+        f"1. 游玩天数：{day_text}。",
+        f"2. 参考价格：{price_text}。",
+        f"3. 期间可去景区/节点：{scenic_text}。",
+        f"4. 附近酒店参考：{hotel_text}",
+    ]
+    if price_samples:
+        lines.append(f"报价档位示例：{price_samples}。")
+    lines.append("以上为图谱证据口径，最终价格、房型、余位、入住酒店和景区政策需按出发日期二次核实。")
+    answer = "\n".join(lines)
+
+    customer_bits = [f"{product_name} 是 {day_text}线路"]
+    if price_text:
+        customer_bits.append(price_text)
+    if scenic_names:
+        customer_bits.append("可玩 " + "、".join(scenic_names[:5]))
+    if hotels:
+        customer_bits.append("附近可参考 " + "、".join(str(item.get("hotel_name") or "") for item in hotels[:3] if item.get("hotel_name")))
+    customer_reply = "亲，" + "；".join(customer_bits) + "。具体价格、房型和余位需要按出发日期再确认。"
+
+    evidence = [
+        {
+            "type": "线路证据",
+            "name": product_name[:120],
+            "summary": f"{product_name}；{day_text}；{price_text}",
+            "source": "FalkorDB 图查询 TourProduct/ProductPricePlan",
+        },
+        {
+            "type": "行程景区证据",
+            "name": "途经景区",
+            "summary": scenic_text[:360],
+            "source": "FalkorDB 图查询 ProductDay/RouteStop/ScenicAttraction",
+        },
+    ]
+    if hotel_texts:
+        evidence.append({
+            "type": "酒店证据",
+            "name": "景区附近酒店",
+            "summary": "；".join(hotel_texts[:4])[:360],
+            "source": "FalkorDB 图查询 ATTRACTION_NEARBY_HOTEL/Hotel",
+        })
+    plans = [{
+        "rank": 1,
+        "label": "线路多跳问答",
+        "plan_name": product_name,
+        "product_name": product_name,
+        "fit_score": 94,
+        "match_reasons": ["命中线路实体", "读取报价、天数、景区和附近酒店多跳证据"],
+        "route_summary": f"{product_name}；{day_text}；{scenic_text}",
+        "quote_summary": price_text,
+        "variant_summary": hotel_text,
+        "daily_itinerary": [
+            {
+                "day": point.get("day"),
+                "title": point.get("attraction_name") or point.get("stop_name"),
+                "summary": point.get("stop_name") or "",
+            }
+            for point in sorted(product["route_points"], key=_route_point_key)[:12]
+            if point.get("attraction_name") or point.get("stop_name")
+        ],
+        "hotels": [
+            {
+                "name": item.get("hotel_name"),
+                "scenic_name": item.get("scenic_name") or item.get("stop_name"),
+                "summary": _hotel_line(item),
+            }
+            for item in hotels[:6]
+        ],
+        "restaurants": [],
+        "vehicles": [],
+        "policies": [],
+        "cost_breakdown": [],
+        "plan_kind": "fast_route_multihop_template",
+    }]
+    return answer, customer_reply, evidence, plans
+
+
+def _valid_travel_item(item: Any) -> bool:
+    return isinstance(item, dict) and bool(str(item.get("name") or "").strip())
+
+
+def _dedupe_travel_items(items: list[dict[str, Any]], limit: int = 18) -> list[dict[str, Any]]:
+    out: list[dict[str, Any]] = []
+    seen: set[str] = set()
+    for item in items:
+        if not _valid_travel_item(item):
+            continue
+        key = "|".join(str(item.get(field) or "") for field in ("name", "price", "adult_price", "unit", "status"))
+        if key in seen:
+            continue
+        seen.add(key)
+        out.append(item)
+        if len(out) >= limit:
+            break
+    return out
+
+
+def _fee_products_from_rows(graph_result: dict[str, Any]) -> list[dict[str, Any]]:
+    products: list[dict[str, Any]] = []
+    for row in graph_result.get("rows") or []:
+        if not isinstance(row, list) or len(row) < 6:
+            continue
+        items: list[dict[str, Any]] = []
+        for group in row[3:6]:
+            if isinstance(group, list):
+                items.extend(item for item in group if isinstance(item, dict))
+        products.append({
+            "product_name": str(row[0] or "").strip(),
+            "product_id": row[1] if len(row) > 1 else "",
+            "duration_days": row[2] if len(row) > 2 else None,
+            "items": _dedupe_travel_items(items),
+        })
+    return [product for product in products if product["product_name"] and product["items"]]
+
+
+def _item_price_text(item: dict[str, Any]) -> str:
+    price = _money(item.get("adult_price") or item.get("price"))
+    unit = str(item.get("unit") or "人").strip()
+    if price:
+        return f"{price}元/{unit}"
+    return "需核价"
+
+
+def _fee_template_answer(question: str, graph_result: dict[str, Any]) -> tuple[str, str, list[dict[str, str]], list[dict[str, Any]]] | None:
+    products = _fee_products_from_rows(graph_result)
+    if not products:
+        return None
+
+    lines = [f"已在图谱中匹配到 {len(products)} 条线路的费用/小交通项目："]
+    evidence: list[dict[str, str]] = []
+    plans: list[dict[str, Any]] = []
+    for idx, product in enumerate(products[:6], start=1):
+        title = product["product_name"]
+        day_suffix = f"（{product['duration_days']}日）" if product.get("duration_days") else ""
+        item_texts: list[str] = []
+        for item in product["items"][:10]:
+            item_text = f"{item.get('name')}：{_item_price_text(item)}"
+            status = str(item.get("status") or item.get("default_status") or "").strip()
+            if status:
+                item_text += f"（{status}）"
+            item_texts.append(item_text)
+        summary = "；".join(item_texts)
+        lines.append(f"{idx}. {title}{day_suffix}：" + summary)
+        evidence.append({
+            "type": "费用证据",
+            "name": title[:120],
+            "summary": summary[:360],
+            "source": "FalkorDB 图查询 TravelItem",
+        })
+        plans.append({
+            "rank": idx,
+            "label": "费用/小交通",
+            "plan_name": title,
+            "product_name": title,
+            "fit_score": max(60, 94 - idx * 3),
+            "match_reasons": ["命中线路名称/天数", "读取 TravelItem 费用项目"],
+            "route_summary": f"{title}{day_suffix}",
+            "quote_summary": summary[:360],
+            "variant_summary": summary[:360],
+            "daily_itinerary": [],
+            "hotels": [],
+            "restaurants": [],
+            "vehicles": [],
+            "policies": [],
+            "cost_breakdown": [],
+            "plan_kind": "fast_fee_template",
+        })
+    lines.append("以上项目按图谱记录展示，景区门票、小交通和可选项目需按团期及景区政策二次核实。")
+    answer = "\n".join(lines)
+    first = products[0]
+    preview = "；".join(f"{item.get('name')} {_item_price_text(item)}" for item in first["items"][:4])
+    customer = f"{first['product_name']} 相关费用项目包括：{preview}。具体是否必含、是否可选和儿童政策需要按团期再核实。"
+    return answer, customer, evidence, plans
+
+
+def _vehicle_items_from_rows(graph_result: dict[str, Any]) -> list[dict[str, Any]]:
+    items: list[dict[str, Any]] = []
+    for row in graph_result.get("rows") or []:
+        if not isinstance(row, list) or not row:
+            continue
+        name = str(row[0] or "").strip()
+        if not name:
+            continue
+        items.append({
+            "name": name,
+            "type": row[1] if len(row) > 1 else "",
+            "subtype": row[2] if len(row) > 2 else "",
+            "price": row[3] if len(row) > 3 else None,
+            "unit": row[4] if len(row) > 4 else "",
+            "raw_evidence": row[5] if len(row) > 5 else "",
+        })
+    return _dedupe_travel_items(items, limit=30)
+
+
+def _vehicle_template_answer(question: str, graph_result: dict[str, Any]) -> tuple[str, str, list[dict[str, str]], list[dict[str, Any]]] | None:
+    items = _vehicle_items_from_rows(graph_result)
+    if not items:
+        return None
+    lines = [
+        f"当前图谱查到 {len(items)} 个用车/车型相关项目：",
+        *[
+            f"{idx}. {item['name']}" + (f"：{_item_price_text(item)}" if item.get("price") not in (None, "") else "")
+            for idx, item in enumerate(items, start=1)
+        ],
+        "具体车型是否可用、座位数、车辆档位和结算口径需要按团期及供应商确认。",
+    ]
+    answer = "\n".join(lines)
+    preview = "、".join(
+        item["name"] + (f"（{_item_price_text(item)}）" if item.get("price") not in (None, "") else "")
+        for item in items[:8]
+    )
+    customer = f"目前图谱里可查到 {len(items)} 个用车相关项目，主要包括：{preview}。具体车辆安排需按出发日期、人数和供应商确认。"
+    evidence = [
+        {
+            "type": "用车证据",
+            "name": item["name"][:120],
+            "summary": f"{item.get('subtype') or item.get('type') or '用车项目'}；参考价：{_item_price_text(item)}",
+            "source": "FalkorDB 图查询 TravelItem",
+        }
+        for item in items[:12]
+    ]
+    plans = [
+        {
+            "rank": idx,
+            "label": "用车项目",
+            "plan_name": item["name"],
+            "product_name": item["name"],
+            "fit_score": max(60, 92 - idx),
+            "match_reasons": ["用车/车型快查", "读取 TravelItem"],
+            "route_summary": item["name"],
+            "quote_summary": _item_price_text(item),
+            "variant_summary": str(item.get("subtype") or ""),
+            "daily_itinerary": [],
+            "hotels": [],
+            "restaurants": [],
+            "vehicles": [],
+            "policies": [],
+            "cost_breakdown": [],
+            "plan_kind": "fast_vehicle_template",
+        }
+        for idx, item in enumerate(items[:4], start=1)
+    ]
+    return answer, customer, evidence, plans
+
+
+def _context_products_from_rows(graph_result: dict[str, Any]) -> list[dict[str, Any]]:
+    products: list[dict[str, Any]] = []
+    for row in graph_result.get("rows") or []:
+        if not isinstance(row, list) or len(row) < 5:
+            continue
+        name = str(row[0] or "").strip()
+        if not name:
+            continue
+        price_plans = [item for item in row[3] if isinstance(item, dict)] if isinstance(row[3], list) else []
+        route_points = [item for item in row[4] if isinstance(item, dict)] if isinstance(row[4], list) else []
+        min_price = None
+        for plan in price_plans:
+            value = plan.get("adult_price_min")
+            if isinstance(value, (int, float)):
+                min_price = value if min_price is None else min(min_price, value)
+        scenic_names = _route_scenic_names(route_points, limit=30)
+        attraction_count = len(scenic_names)
+        products.append({
+            "product_name": name,
+            "product_id": row[1] if len(row) > 1 else "",
+            "duration_days": row[2] if len(row) > 2 else None,
+            "adult_price_min": min_price,
+            "price_plans": price_plans[:8],
+            "route_points": route_points[:16],
+            "scenic_names": scenic_names,
+            "attraction_count": attraction_count,
+        })
+    return products
+
+
+def _condition_route_score(question: str, product: dict[str, Any]) -> tuple[int, int, int]:
+    name = str(product.get("product_name") or "")
+    duration = _safe_int(product.get("duration_days"), 99)
+    price = product.get("adult_price_min")
+    price_int = _safe_int(price, 999999) if price not in (None, "") else 999999
+    scenic_count = _safe_int(product.get("attraction_count"), len(product.get("scenic_names") or []))
+    scenic_text = " ".join(product.get("scenic_names") or [])
+    slots = _condition_slots(question)
+    score = 50
+    if slots["family"]:
+        if any(term in name for term in ("亲子", "轻奢", "纯玩", "小包团", "2+1", "私家")):
+            score += 18
+        if duration <= 3:
+            score += 10
+        elif duration <= 4:
+            score += 6
+    if slots["comfort"]:
+        if any(term in name for term in ("轻奢", "纯玩", "2+1", "私家", "头等舱")):
+            score += 20
+        if duration <= 3:
+            score += 12
+        if 0 < scenic_count <= 5:
+            score += 6
+        if duration >= 5:
+            score -= 8
+        if "梵净山" in scenic_text:
+            score -= 8
+    if slots["budget"]:
+        if price_int <= 800:
+            score += 18
+        elif price_int <= 1200:
+            score += 10
+    if any(term in name for term in ("购物", "特价购物")):
+        score -= 12
+    return score, -duration, -price_int
+
+
+def _condition_route_template_answer(question: str, graph_result: dict[str, Any]) -> tuple[str, str, list[dict[str, str]], list[dict[str, Any]]] | None:
+    products = _context_products_from_rows(graph_result)
+    if not products:
+        return None
+    products.sort(key=lambda item: _condition_route_score(question, item), reverse=True)
+    selected = products[:5]
+    lines = ["按“老人/小孩/轻松/预算”等条件从图谱中筛出以下候选线路："]
+    evidence: list[dict[str, str]] = []
+    plans: list[dict[str, Any]] = []
+    for idx, product in enumerate(selected, start=1):
+        name = product["product_name"]
+        duration = f"{product['duration_days']}日" if product.get("duration_days") else "天数待核实"
+        price = _money(product.get("adult_price_min"))
+        price_text = f"成人起价约 {price}元/人" if price else "价格需按团期核实"
+        scenic_names = product.get("scenic_names") or _route_scenic_names(product.get("route_points") or [], limit=8)
+        scenic_text = "、".join(scenic_names[:5]) if scenic_names else "景区信息待核实"
+        reasons: list[str] = []
+        if any(term in name for term in ("轻奢", "纯玩", "2+1", "私家", "小包团")):
+            reasons.append("线路名称体现舒适/纯玩/小团倾向")
+        if _safe_int(product.get("duration_days"), 99) <= 3:
+            reasons.append("天数较短，行程压力相对低")
+        if price:
+            reasons.append("图谱有报价起价可参考")
+        reason_text = "；".join(reasons[:3]) or "图谱有线路、价格和行程证据"
+        line = f"{idx}. {name}（{duration}）：{price_text}；可玩 {scenic_text}；推荐依据：{reason_text}"
+        lines.append(line)
+        evidence.append({
+            "type": "条件筛选证据",
+            "name": name[:120],
+            "summary": line[:360],
+            "source": "FalkorDB 图查询 TourProduct/ProductPricePlan/ScenicAttraction",
+        })
+        plans.append({
+            "rank": idx,
+            "label": "条件推荐线路",
+            "plan_name": name,
+            "product_name": name,
+            "fit_score": max(60, min(96, _condition_route_score(question, product)[0])),
+            "match_reasons": reasons or ["条件筛选命中", "读取线路报价和景区证据"],
+            "route_summary": f"{name}（{duration}）：{scenic_text}",
+            "quote_summary": price_text,
+            "variant_summary": reason_text,
+            "daily_itinerary": [],
+            "hotels": [],
+            "restaurants": [],
+            "vehicles": [],
+            "policies": [],
+            "cost_breakdown": [],
+            "plan_kind": "fast_condition_route_advice",
+        })
+    best = selected[0]
+    best_price = _money(best.get("adult_price_min"))
+    best_price_text = f"，成人起价约 {best_price}元/人" if best_price else ""
+    best_duration = f"{best['duration_days']}日" if best.get("duration_days") else "天数待核实"
+    customer = f"亲，带老人小孩又希望轻松，可以优先看 {best['product_name']}（{best_duration}{best_price_text}）。它在图谱里有线路和景区证据，最终还要按出发日期、人数和住宿档位核实。"
+    lines.append("这些推荐是基于图谱字段做的初筛，不等于最终承诺；老人/儿童还需要二次确认行程强度、用车、住宿和余位。")
+    return "\n".join(lines), customer, evidence, plans
+
+
+def _route_compare_suitability_answer(question: str, graph_result: dict[str, Any]) -> tuple[str, str, list[dict[str, str]], list[dict[str, Any]]] | None:
+    products = _context_products_from_rows(graph_result)
+    if not products:
+        return None
+    compare_terms = _route_name_terms(question)
+    grouped: list[dict[str, Any]] = []
+    for term in compare_terms:
+        candidates = [item for item in products if term in str(item.get("product_name") or "")]
+        if not candidates:
+            continue
+        other_terms = [other for other in compare_terms if other != term]
+        pure_candidates = [
+            item for item in candidates
+            if not any(other in str(item.get("product_name") or "") for other in other_terms)
+        ]
+        pool = pure_candidates or candidates
+        pool.sort(key=lambda item: _condition_route_score(question, item), reverse=True)
+        best = pool[0]
+        grouped.append({
+            "term": term,
+            "best": best,
+            "score": _condition_route_score(question, best)[0],
+        })
+    if len(grouped) < 2:
+        return None
+
+    grouped.sort(key=lambda item: item["score"], reverse=True)
+    winner = grouped[0]
+    lines = ["按老人/儿童/轻松度条件，用图谱中的天数、价格和景区节点做适配度对比："]
+    evidence: list[dict[str, str]] = []
+    plans: list[dict[str, Any]] = []
+    for idx, group in enumerate(grouped, start=1):
+        product = group["best"]
+        name = product["product_name"]
+        duration = f"{product['duration_days']}日" if product.get("duration_days") else "天数待核实"
+        price = _money(product.get("adult_price_min"))
+        price_text = f"成人起价约 {price}元/人" if price else "价格需按团期核实"
+        scenic_names = product.get("scenic_names") or []
+        scenic_text = "、".join(scenic_names[:6]) if scenic_names else "景区信息待核实"
+        reasons: list[str] = []
+        if _safe_int(product.get("duration_days"), 99) <= 3:
+            reasons.append("天数短，行程压力相对低")
+        if any(term in name for term in ("轻奢", "2+1", "纯玩", "头等舱", "私家")):
+            reasons.append("名称体现舒适/纯玩/车型优势")
+        if "梵净山" in scenic_text:
+            reasons.append("包含梵净山，老人小孩需评估体力")
+        if price:
+            reasons.append("有报价起价可参考")
+        reason_text = "；".join(reasons[:4]) or "有线路、价格和景区证据"
+        line = f"{idx}. {group['term']}：代表线路 {name}（{duration}），{price_text}；景区：{scenic_text}；判断：{reason_text}"
+        lines.append(line)
+        evidence.append({
+            "type": "适配度对比证据",
+            "name": str(group["term"])[:120],
+            "summary": line[:360],
+            "source": "FalkorDB 图查询 TourProduct/ProductPricePlan/ScenicAttraction",
+        })
+        plans.append({
+            "rank": idx,
+            "label": "线路适配度对比",
+            "plan_name": str(group["term"]),
+            "product_name": name,
+            "fit_score": max(60, min(96, int(group["score"]))),
+            "match_reasons": reasons or ["条件适配评分", "读取线路报价和景区证据"],
+            "route_summary": line,
+            "quote_summary": price_text,
+            "variant_summary": reason_text,
+            "daily_itinerary": [],
+            "hotels": [],
+            "restaurants": [],
+            "vehicles": [],
+            "policies": [],
+            "cost_breakdown": [],
+            "plan_kind": "fast_route_compare_suitability",
+        })
+
+    winner_product = winner["best"]
+    customer = f"亲，按老人小孩和不要太累的条件，优先建议 {winner['term']}，代表线路可看 {winner_product['product_name']}。它在图谱评分里更偏轻松/舒适；最终还要按出发日期、人数、住宿和老人儿童体力二次确认。"
+    lines.append("该结论是图谱条件评分，不是最终承诺；涉及老人儿童时建议再核实步行强度、用车、住宿和景区政策。")
+    return "\n".join(lines), customer, evidence, plans
+
+
+def _route_compare_scenic_count_answer(question: str, graph_result: dict[str, Any]) -> tuple[str, str, list[dict[str, str]], list[dict[str, Any]]] | None:
+    products = _context_products_from_rows(graph_result)
+    if not products:
+        return None
+    compare_terms = _route_name_terms(question)
+    grouped: list[dict[str, Any]] = []
+    for term in compare_terms:
+        candidates = [item for item in products if term in str(item.get("product_name") or "")]
+        if not candidates:
+            continue
+        other_terms = [other for other in compare_terms if other != term]
+        pure_candidates = [
+            item for item in candidates
+            if not any(other in str(item.get("product_name") or "") for other in other_terms)
+        ]
+        pool = pure_candidates or candidates
+        pool.sort(key=lambda item: (_safe_int(item.get("attraction_count"), 0), _route_match_score(question, item)), reverse=True)
+        best = pool[0]
+        grouped.append({
+            "term": term,
+            "best": best,
+            "count": _safe_int(best.get("attraction_count"), 0),
+            "candidates": pool[:4],
+        })
+    if grouped:
+        selected = [item["best"] for item in grouped]
+    else:
+        products.sort(key=lambda item: (_route_match_score(question, item), _safe_int(item.get("attraction_count"), 0)), reverse=True)
+        selected = products[:8]
+    max_count = max(_safe_int(item.get("attraction_count"), 0) for item in selected)
+    winners = [item for item in selected if _safe_int(item.get("attraction_count"), 0) == max_count and max_count > 0]
+    lines = ["按当前图谱的 ScenicAttraction 证据统计："]
+    evidence: list[dict[str, str]] = []
+    plans: list[dict[str, Any]] = []
+    if grouped:
+        for idx, group in enumerate(grouped, start=1):
+            product = group["best"]
+            scenic_names = product.get("scenic_names") or _route_scenic_names(product.get("route_points") or [], limit=10)
+            count = _safe_int(product.get("attraction_count"), len(scenic_names))
+            scenic_text = "、".join(scenic_names[:8]) if scenic_names else "暂无明确景区证据"
+            line = f"{idx}. {group['term']}：代表线路 {product['product_name']}，图谱命中 {count} 个景区/游玩节点，包含 {scenic_text}"
+            lines.append(line)
+            evidence.append({
+                "type": "景区数量对比证据",
+                "name": str(group["term"])[:120],
+                "summary": line[:360],
+                "source": "FalkorDB 图查询 ProductDay/RouteStop/ScenicAttraction",
+            })
+            plans.append({
+                "rank": idx,
+                "label": "线路景点数量对比",
+                "plan_name": str(group["term"]),
+                "product_name": product["product_name"],
+                "fit_score": max(60, 92 - idx * 3),
+                "match_reasons": ["按用户提到的线路词分组", "统计 ScenicAttraction 去重数量"],
+                "route_summary": line,
+                "quote_summary": "",
+                "variant_summary": scenic_text,
+                "daily_itinerary": [],
+                "hotels": [],
+                "restaurants": [],
+                "vehicles": [],
+                "policies": [],
+                "cost_breakdown": [],
+                "plan_kind": "fast_route_compare_scenic_count",
+            })
+    else:
+        for idx, product in enumerate(selected, start=1):
+            scenic_names = product.get("scenic_names") or _route_scenic_names(product.get("route_points") or [], limit=10)
+            count = _safe_int(product.get("attraction_count"), len(scenic_names))
+            scenic_text = "、".join(scenic_names[:8]) if scenic_names else "暂无明确景区证据"
+            line = f"{idx}. {product['product_name']}：图谱命中 {count} 个景区/游玩节点，包含 {scenic_text}"
+            lines.append(line)
+            evidence.append({
+                "type": "景区数量对比证据",
+                "name": product["product_name"][:120],
+                "summary": line[:360],
+                "source": "FalkorDB 图查询 ProductDay/RouteStop/ScenicAttraction",
+            })
+            plans.append({
+                "rank": idx,
+                "label": "线路景点数量对比",
+                "plan_name": product["product_name"],
+                "product_name": product["product_name"],
+                "fit_score": max(60, 92 - idx * 3),
+                "match_reasons": ["线路名称命中", "统计 ScenicAttraction 去重数量"],
+                "route_summary": line,
+                "quote_summary": "",
+                "variant_summary": scenic_text,
+                "daily_itinerary": [],
+                "hotels": [],
+                "restaurants": [],
+                "vehicles": [],
+                "policies": [],
+                "cost_breakdown": [],
+                "plan_kind": "fast_route_compare_scenic_count",
+            })
+    if winners:
+        if len(winners) > 1 and grouped:
+            winner_names = "、".join(
+                group["term"] for group in grouped if group["best"] in winners
+            )
+            customer = f"从当前图谱景区数量看，{winner_names} 最高都约 {max_count} 个景区/游玩节点，数量接近；建议再结合天数、价格和行程强度选择。"
+        elif grouped:
+            winner_name = next((group["term"] for group in grouped if group["best"] in winners), "")
+            customer = f"从当前图谱景区数量看，{winner_name or winners[0]['product_name']}的代表线路命中的景区/游玩节点更多（约 {max_count} 个）。具体还要结合出发日期、行程强度和实际游玩安排确认。"
+        else:
+            winner_names = "、".join(item["product_name"] for item in winners[:2])
+            customer = f"从当前图谱景区数量看，{winner_names} 命中的景区/游玩节点更多（约 {max_count} 个）。具体还要结合出发日期、行程强度和实际游玩安排确认。"
+    else:
+        customer = "当前图谱没有足够的景区数量证据做可靠比较，建议补充具体线路名称或让后台核实行程明细。"
+    lines.append("注意：这里比较的是图谱已结构化的景区/游玩节点数量，不代表实际游玩时长或体验强弱。")
+    return "\n".join(lines), customer, evidence, plans
+
+
+def _context_template_fallback_answer(question: str, graph_result: dict[str, Any]) -> tuple[str, str, list[dict[str, str]], list[dict[str, Any]]]:
+    products = _context_products_from_rows(graph_result)
+    products.sort(key=lambda item: (item.get("adult_price_min") is None, item.get("adult_price_min") or 999999, item.get("duration_days") or 99))
+    evidence: list[dict[str, str]] = []
+    plans: list[dict[str, Any]] = []
+    lines = ["已按线路实体查到以下可对比方案："]
+    for idx, product in enumerate(products[:6], start=1):
+        price = _money(product.get("adult_price_min"))
+        day_suffix = f"（{product['duration_days']}日）" if product.get("duration_days") else ""
+        price_text = f"，成人参考起价 {price}元/人" if price else "，价格需按团期核实"
+        line = f"{idx}. {product['product_name']}{day_suffix}{price_text}"
+        lines.append(line)
+        evidence.append({
+            "type": "线路对比证据",
+            "name": product["product_name"][:120],
+            "summary": line[:360],
+            "source": "FalkorDB 图查询 TourProduct/ProductPricePlan",
+        })
+        plans.append({
+            "rank": idx,
+            "label": "线路对比",
+            "plan_name": product["product_name"],
+            "product_name": product["product_name"],
+            "fit_score": max(60, 90 - idx * 3),
+            "match_reasons": ["命中线路实体", "读取报价和行程上下文"],
+            "route_summary": line,
+            "quote_summary": line,
+            "variant_summary": "",
+            "daily_itinerary": [],
+            "hotels": [],
+            "restaurants": [],
+            "vehicles": [],
+            "policies": [],
+            "cost_breakdown": [],
+            "plan_kind": "deterministic_context_fallback",
+        })
+    if products:
+        best = products[0]
+        customer = f"从图谱报价看，预算优先可以先看 {best['product_name']}。如果有老人和小孩，还需要结合行程强度、住宿档位和出发日期确认，价格和余位需二次核实。"
+    else:
+        customer = "当前已进入线路对比查询，但图谱证据不足，建议补充具体线路、出发日期、人数和预算后再推荐。"
+    lines.append("建议最终按出发日期、人数、住宿档位、老人/儿童体力情况和供应商余位二次核实。")
+    return "\n".join(lines), customer, evidence, plans
+
+
+async def _deterministic_context_response(
+    question: str,
+    graph_name: str,
+    *,
+    limit: int,
+    customer_context: dict[str, Any] | None,
+    started_at: float,
+    intent: dict[str, Any],
+    intent_ms: int,
+) -> dict[str, Any] | None:
+    if intent.get("route") != "deterministic_context_llm_answer":
+        return None
+    if intent.get("intent") == "condition_route_advice":
+        cypher = _condition_context_cypher(limit)
+    else:
+        cypher = _route_context_cypher(question, limit) or ""
+    if not cypher:
+        return None
+    graph_started = time.perf_counter()
+    try:
+        graph_result = await asyncio.to_thread(_run_cypher, graph_name, cypher, limit)
+    except Exception:
+        return None
+    graph_ms = max(1, round((time.perf_counter() - graph_started) * 1000))
+    if not graph_result.get("row_count"):
+        return None
+
+    planner = intent.get("_planner_trace") if isinstance(intent.get("_planner_trace"), dict) else {}
+    planner_ms = _safe_int(planner.get("latency_ms"), 0)
+    answer_ms = 0
+    llm_error = ""
+    answer_data: dict[str, Any] = {}
+    answer_client = await _graph_qa_client(max_tokens=600)
+    if answer_client is not None:
+        payload = {
+            "question": question,
+            "graph_name": graph_name,
+            "intent": intent,
+            "answer_focus": "基于线路报价、天数、景区数量和行程证据做 3 句话以内建议；证据不足必须说明需二次核实。",
+            "cypher": cypher,
+            "graph_result": {
+                "columns": graph_result["columns"],
+                "row_count": graph_result["row_count"],
+                "rows": graph_result["rows"][:6],
+                "nodes": [],
+                "relationships": [],
+            },
+            "customer_context": customer_context or {},
+        }
+        answer_started = time.perf_counter()
+        try:
+            answer_data = await _chat_json_timed(
+                answer_client,
+                GRAPH_QA_ANSWER_SYS,
+                json.dumps(payload, ensure_ascii=False),
+                timeout_seconds=GRAPH_QA_ANSWER_TIMEOUT_SECONDS,
+                attempts=1,
+            )
+        except asyncio.TimeoutError:
+            llm_error = "answer_timeout"
+        except Exception as exc:  # noqa: BLE001
+            llm_error = str(exc)[:260]
+        answer_ms = max(1, round((time.perf_counter() - answer_started) * 1000))
+
+    if answer_data:
+        answer = str(answer_data.get("answer") or answer_data.get("customer_reply") or "").strip()
+        customer_reply = str(answer_data.get("customer_reply") or answer).strip()
+        evidence = _evidence_cards(answer_data, graph_result)
+        plans = _plans_from_evidence(evidence, answer)
+        confidence = _safe_confidence(answer_data.get("confidence"), 0.72)
+        followups = _list_texts(answer_data.get("follow_up_questions"), 4, 120)
+        risk_notes = _list_texts(answer_data.get("risk_notes"), 4, 160)
+    else:
+        answer, customer_reply, evidence, plans = _context_template_fallback_answer(question, graph_result)
+        confidence = 0.68
+        followups = ["请提供出发日期和人数。", "老人和小孩对行程强度有什么要求？", "预算范围和住宿档位是多少？"]
+        risk_notes = ["推荐仅基于图谱已有报价和线路信息，最终需按团期、余位和供应商政策二次核实。"]
+
+    latency_ms = max(1, round((time.perf_counter() - started_at) * 1000))
+    return {
+        "question": question,
+        "graph_name": graph_name,
+        "answer": answer,
+        "customer_reply": customer_reply,
+        "copy_text": customer_reply or answer,
+        "plans": plans,
+        "evidence": evidence,
+        "sales_scripts": [],
+        "follow_up_questions": followups,
+        "risk_notes": risk_notes,
+        "confidence": confidence,
+        "graph_result": graph_result,
+        "trace": {
+            "method": "deterministic_context_llm_answer_v1",
+            "query_source": "deterministic_context_cypher",
+            "rule_query_used": False,
+            "llm_used": bool(answer_data),
+            "llm_error": llm_error,
+            "cache_hit": False,
+            "cache": {"response": False, "cypher": False},
+            "generated_cypher": "",
+            "effective_cypher": cypher,
+            "cypher_cache_hit": False,
+            "fallback_cypher": "",
+            "fallback_query_used": False,
+            "cypher_reason": intent.get("reason") or "",
+            "intent": intent.get("intent") or "",
+            "llm_planner_used": bool(planner.get("used")),
+            "llm_planner": planner,
+            "graph_qa_intent": intent,
+            "routing_strategy": "intent_context_query_then_llm_answer",
+            "cypher_repaired": False,
+            "first_query_error": "",
+            "row_count": graph_result["row_count"],
+            "node_count": len(graph_result["nodes"]),
+            "relationship_count": len(graph_result["relationships"]),
+            "latency_ms": latency_ms,
+            "stage_timings_ms": {
+                "intent_classification": intent_ms,
+                "llm_planner": planner_ms,
+                "schema": 0,
+                "cypher_generation": 0,
+                "graph_query": graph_ms,
+                "fallback_graph_query": 0,
+                "answer_synthesis": answer_ms,
+            },
+            "performance_target_ms": 1200,
+            "response_mode": "deterministic_context_llm_answer",
+            "response_mode_label": "固定取证 + LLM 证据回答",
+            "graph_capabilities_used": ["意图识别", "固定 Cypher 取证", "LLM 证据回答"],
+            "retrieval_summary": {
+                "cypher": cypher,
+                "llm_generated_cypher": "",
+                "fallback_query_used": False,
+                "rows": graph_result["row_count"],
+                "nodes": len(graph_result["nodes"]),
+                "relationships": len(graph_result["relationships"]),
+            },
+        },
+    }
+
+
+def _cache_key(question: str, graph_name: str, limit: int, customer_context: dict[str, Any] | None) -> str:
+    context_key = json.dumps(customer_context or {}, ensure_ascii=False, sort_keys=True, default=str)[:800]
+    normalized_question = re.sub(r"\s+", "", question.strip())
+    return f"{graph_name}|{limit}|{normalized_question}|{context_key}"
+
+
+def _get_cached_response(cache_key: str, started_at: float) -> dict[str, Any] | None:
+    cached = _QA_RESPONSE_CACHE.get(cache_key)
+    if not cached:
+        return None
+    cached_at, payload = cached
+    if time.monotonic() - cached_at > QA_RESPONSE_CACHE_TTL_SECONDS:
+        _QA_RESPONSE_CACHE.pop(cache_key, None)
+        return None
+    response = copy.deepcopy(payload)
+    latency_ms = max(1, round((time.perf_counter() - started_at) * 1000))
+    trace = response.setdefault("trace", {})
+    trace["cache_hit"] = True
+    cache = trace.setdefault("cache", {})
+    cache["response"] = True
+    trace["latency_ms"] = latency_ms
+    trace["stage_timings_ms"] = {
+        **(trace.get("stage_timings_ms") or {}),
+        "cache_lookup": latency_ms,
+    }
+    return response
+
+
+def _set_cached_response(cache_key: str, response: dict[str, Any]) -> None:
+    if len(_QA_RESPONSE_CACHE) > 256:
+        oldest_key = min(_QA_RESPONSE_CACHE, key=lambda key: _QA_RESPONSE_CACHE[key][0])
+        _QA_RESPONSE_CACHE.pop(oldest_key, None)
+    _QA_RESPONSE_CACHE[cache_key] = (time.monotonic(), copy.deepcopy(response))
+
+
+def _cypher_cache_key(question: str, graph_name: str, limit: int, intent: dict[str, Any]) -> str:
+    normalized = _normalized_question(question)
+    return f"{graph_name}|{limit}|{intent.get('intent') or 'general'}|{normalized}"
+
+
+def _get_cached_cypher(cache_key: str) -> dict[str, Any] | None:
+    cached = _CYPHER_CACHE.get(cache_key)
+    if not cached:
+        return None
+    cached_at, payload = cached
+    if time.monotonic() - cached_at > CYPHER_CACHE_TTL_SECONDS:
+        _CYPHER_CACHE.pop(cache_key, None)
+        return None
+    return copy.deepcopy(payload)
+
+
+def _set_cached_cypher(cache_key: str, decision: dict[str, Any]) -> None:
+    if len(_CYPHER_CACHE) > 512:
+        oldest_key = min(_CYPHER_CACHE, key=lambda key: _CYPHER_CACHE[key][0])
+        _CYPHER_CACHE.pop(oldest_key, None)
+    _CYPHER_CACHE[cache_key] = (time.monotonic(), copy.deepcopy(decision))
+
+
+async def _fast_graph_response(
+    question: str,
+    graph_name: str,
+    *,
+    limit: int,
+    customer_context: dict[str, Any] | None,
+    started_at: float,
+    intent: dict[str, Any],
+    intent_ms: int,
+) -> dict[str, Any] | None:
+    if intent.get("route") != "template_graph_query":
+        return None
+    fast_kind = str(intent.get("intent") or "")
+    cypher = ""
+    if fast_kind == "route_catalog":
+        cypher = _route_catalog_cypher(limit)
+    elif fast_kind == "condition_route_advice":
+        cypher = _condition_context_cypher(limit)
+    elif fast_kind == "route_compare_suitability":
+        cypher = _route_context_cypher(question, limit) or ""
+    elif fast_kind == "route_compare_scenic_count":
+        cypher = _route_context_cypher(question, limit) or ""
+    elif fast_kind == "route_multihop_detail":
+        cypher = _route_multihop_cypher(question, limit) or ""
+    elif fast_kind == "price_quote":
+        cypher = _price_fallback_cypher(question, limit) or ""
+    elif fast_kind == "fee_detail":
+        cypher = _fee_fallback_cypher(question, limit) or ""
+    elif fast_kind == "vehicle_catalog":
+        cypher = _vehicle_catalog_cypher(limit)
+    if not cypher:
+        return None
+
+    graph_started = time.perf_counter()
+    try:
+        graph_result = await asyncio.to_thread(_run_cypher, graph_name, cypher, limit)
+    except Exception:
+        return None
+    graph_ms = max(1, round((time.perf_counter() - graph_started) * 1000))
+    if not graph_result.get("row_count"):
+        return None
+
+    planner = intent.get("_planner_trace") if isinstance(intent.get("_planner_trace"), dict) else {}
+    planner_ms = _safe_int(planner.get("latency_ms"), 0)
+    if fast_kind == "route_catalog":
+        route_answer = _route_list_answer(question, graph_result)
+        if not route_answer:
+            return None
+        answer, customer_reply = route_answer
+        items = _route_items_from_rows(graph_result)
+        evidence = [
+            {
+                "type": "线路清单",
+                "name": item["name"],
+                "summary": f"{item['name']}" + (f"（{item['duration_days']}日）" if item.get("duration_days") else ""),
+                "source": "FalkorDB 图查询 TourProduct",
+            }
+            for item in items[:12]
+        ]
+        plans = [
+            {
+                "rank": idx,
+                "label": "线路清单",
+                "plan_name": item["name"],
+                "product_name": item["name"],
+                "fit_score": max(60, 95 - idx),
+                "match_reasons": ["线路清单快查", "读取 TourProduct"],
+                "route_summary": item["name"],
+                "quote_summary": "可继续按线路名称、日期和人数查询报价。",
+                "variant_summary": "",
+                "daily_itinerary": [],
+                "hotels": [],
+                "restaurants": [],
+                "vehicles": [],
+                "policies": [],
+                "cost_breakdown": [],
+                "plan_kind": "fast_route_catalog",
+            }
+            for idx, item in enumerate(items[:4], start=1)
+        ]
+        followups = ["要查哪条线路的价格？", "请提供出发日期、人数和住宿偏好。", "是否需要按天数或景点筛选线路？"]
+        confidence = 0.9
+    elif fast_kind == "condition_route_advice":
+        condition_answer = _condition_route_template_answer(question, graph_result)
+        if not condition_answer:
+            return None
+        answer, customer_reply, evidence, plans = condition_answer
+        followups = ["请提供出发日期和人数。", "老人或小孩是否有少走路要求？", "预算和住宿档位大概是多少？"]
+        confidence = 0.78
+    elif fast_kind == "route_compare_suitability":
+        suitability_answer = _route_compare_suitability_answer(question, graph_result)
+        if not suitability_answer:
+            return None
+        answer, customer_reply, evidence, plans = suitability_answer
+        followups = ["请提供出发日期和人数。", "老人小孩是否能接受爬山或较多步行？", "是否需要同时比较价格？"]
+        confidence = 0.8
+    elif fast_kind == "route_compare_scenic_count":
+        compare_answer = _route_compare_scenic_count_answer(question, graph_result)
+        if not compare_answer:
+            return None
+        answer, customer_reply, evidence, plans = compare_answer
+        followups = ["是否还要比较价格和行程强度？", "请提供出发日期和人数。", "是否需要按老人/儿童适配度再筛选？"]
+        confidence = 0.82
+    elif fast_kind == "route_multihop_detail":
+        multihop_answer = _route_multihop_template_answer(question, graph_result)
+        if not multihop_answer:
+            return None
+        answer, customer_reply, evidence, plans = multihop_answer
+        followups = ["请提供出发日期和人数。", "是否需要指定住宿档位或房型？", "要继续核实哪个景区附近酒店？"]
+        confidence = 0.88
+    elif fast_kind == "price_quote":
+        price_answer = _price_template_answer(question, graph_result)
+        if not price_answer:
+            return None
+        answer, customer_reply, evidence, plans = price_answer
+        followups = ["请提供出发日期和人数。", "是否有住宿档位要求？", "是否需要同步查询儿童价和单房差？"]
+        confidence = 0.86
+    elif fast_kind == "fee_detail":
+        fee_answer = _fee_template_answer(question, graph_result)
+        if not fee_answer:
+            return None
+        answer, customer_reply, evidence, plans = fee_answer
+        followups = ["要按哪一天或哪个景区核实费用？", "是否需要区分必含和自费项目？", "请提供出发日期方便核实景区政策。"]
+        confidence = 0.84
+    elif fast_kind == "vehicle_catalog":
+        vehicle_answer = _vehicle_template_answer(question, graph_result)
+        if not vehicle_answer:
+            return None
+        answer, customer_reply, evidence, plans = vehicle_answer
+        followups = ["请提供出发日期和人数。", "是否需要指定车型或座位布局？", "是否需要核算包车费用？"]
+        confidence = 0.82
+    else:
+        return None
+
+    latency_ms = max(1, round((time.perf_counter() - started_at) * 1000))
+    return {
+        "question": question,
+        "graph_name": graph_name,
+        "answer": answer,
+        "customer_reply": customer_reply,
+        "copy_text": customer_reply or answer,
+        "plans": plans,
+        "evidence": evidence,
+        "sales_scripts": [],
+        "follow_up_questions": followups,
+        "risk_notes": ["价格、余位、房型、车辆和景区政策以具体团期及供应商二次核实为准。"],
+        "confidence": confidence,
+        "graph_result": graph_result,
+        "trace": {
+            "method": f"fast_{fast_kind}_graph_template_v1",
+            "query_source": "deterministic_cypher_template",
+            "rule_query_used": False,
+            "llm_used": False,
+            "cache_hit": False,
+            "cache": {"response": False, "cypher": False},
+            "generated_cypher": "",
+            "effective_cypher": cypher,
+            "fallback_cypher": "",
+            "fallback_query_used": False,
+            "cypher_reason": "高频客服问题命中固定只读图查询模板，跳过 LLM 生成 Cypher 和 LLM 答案组织。",
+            "intent": fast_kind,
+            "llm_planner_used": bool(planner.get("used")),
+            "llm_planner": planner,
+            "graph_qa_intent": intent,
+            "routing_strategy": "intent_template_first",
+            "cypher_repaired": False,
+            "first_query_error": "",
+            "row_count": graph_result["row_count"],
+            "node_count": len(graph_result["nodes"]),
+            "relationship_count": len(graph_result["relationships"]),
+            "latency_ms": latency_ms,
+            "stage_timings_ms": {
+                "intent_classification": intent_ms,
+                "llm_planner": planner_ms,
+                "schema": 0,
+                "cypher_generation": 0,
+                "graph_query": graph_ms,
+                "fallback_graph_query": 0,
+                "answer_synthesis": 0,
+            },
+            "performance_target_ms": 1200,
+            "response_mode": "fast_graph_template",
+            "response_mode_label": "高频客服问题快查",
+            "graph_capabilities_used": ["固定 Cypher 模板", "FalkorDB 只读查询", "客服话术模板"],
+            "retrieval_summary": {
+                "cypher": cypher,
+                "llm_generated_cypher": "",
+                "fallback_query_used": False,
+                "rows": graph_result["row_count"],
+                "nodes": len(graph_result["nodes"]),
+                "relationships": len(graph_result["relationships"]),
+            },
+        },
+    }
+
+
+def _evidence_cards(answer_data: dict[str, Any], graph_result: dict[str, Any]) -> list[dict[str, str]]:
+    cards: list[dict[str, str]] = []
+    raw_cards = answer_data.get("evidence_cards")
+    if isinstance(raw_cards, list):
+        for item in raw_cards[:6]:
+            if not isinstance(item, dict):
+                continue
+            title = str(item.get("title") or item.get("name") or "").strip()
+            summary = str(item.get("summary") or item.get("detail") or "").strip()
+            source = str(item.get("source") or "FalkorDB 图查询").strip()
+            if title or summary:
+                cards.append({"type": "图查询证据", "name": title[:120], "summary": summary[:360], "source": source[:120]})
+    for node in (graph_result.get("nodes") or [])[:6]:
+        if len(cards) >= 8:
+            break
+        props = node.get("properties") or {}
+        summary = "；".join(
+            f"{k}: {v}" for k, v in list(props.items())[:6] if v not in (None, "")
+        )
+        cards.append({
+            "type": "图谱节点",
+            "name": str(node.get("title") or "")[:120],
+            "summary": summary[:360],
+            "source": "FalkorDB 图查询",
+        })
+    return cards
+
+
+def _plans_from_evidence(cards: list[dict[str, str]], answer: str) -> list[dict[str, Any]]:
+    plans: list[dict[str, Any]] = []
+    for idx, card in enumerate(cards[:4], start=1):
+        plans.append({
+            "rank": idx,
+            "label": "图查询证据",
+            "plan_name": card.get("name") or f"图谱证据 {idx}",
+            "product_name": card.get("name") or "",
+            "fit_score": max(60, 92 - idx * 4),
+            "match_reasons": ["LLM 生成 Cypher 查询命中", "来自百姓惠知识图谱"],
+            "route_summary": card.get("summary") or answer[:240],
+            "quote_summary": answer[:360],
+            "variant_summary": card.get("summary") or "",
+            "daily_itinerary": [],
+            "hotels": [],
+            "restaurants": [],
+            "vehicles": [],
+            "policies": [],
+            "cost_breakdown": [],
+            "plan_kind": "llm_graph_evidence",
+        })
+    return plans
+
+
+def _safe_confidence(value: Any, default: float = 0.72) -> float:
+    try:
+        return max(0.0, min(1.0, float(value)))
+    except Exception:
+        return default
+
+
+async def answer_graph_question(
+    question: str,
+    graph_name: str,
+    *,
+    customer_context: dict[str, Any] | None = None,
+    limit: int = 80,
+) -> dict[str, Any]:
+    started_at = time.perf_counter()
+    limit = min(max(int(limit or 80), 1), GRAPH_QA_MAX_LIMIT)
+    question = question.strip()
+    if not question:
+        raise ValueError("question required")
+
+    cache_key = _cache_key(question, graph_name, limit, customer_context)
+    cached_response = _get_cached_response(cache_key, started_at)
+    if cached_response:
+        return cached_response
+
+    intent_started = time.perf_counter()
+    rule_intent = _classify_graph_qa_intent(question)
+    intent, planner_trace = await _llm_plan_intent(question, graph_name, rule_intent, customer_context)
+    intent["_planner_trace"] = planner_trace
+    intent_ms = max(1, round((time.perf_counter() - intent_started) * 1000))
+    fast_response = await _fast_graph_response(
+        question,
+        graph_name,
+        limit=limit,
+        customer_context=customer_context,
+        started_at=started_at,
+        intent=intent,
+        intent_ms=intent_ms,
+    )
+    if fast_response:
+        _set_cached_response(cache_key, fast_response)
+        return fast_response
+
+    context_response = await _deterministic_context_response(
+        question,
+        graph_name,
+        limit=limit,
+        customer_context=customer_context,
+        started_at=started_at,
+        intent=intent,
+        intent_ms=intent_ms,
+    )
+    if context_response:
+        _set_cached_response(cache_key, context_response)
+        return context_response
+
+    cypher_cache_key = _cypher_cache_key(question, graph_name, limit, intent)
+    cached_decision = _get_cached_cypher(cypher_cache_key)
+    cypher_cache_hit = bool(cached_decision)
+    cypher_client: LlmClient | None = None
+    if cached_decision:
+        decision = cached_decision
+        schema_ms = 0
+        cypher_ms = 0
+    else:
+        cypher_client = await _graph_qa_client(max_tokens=1000, use_config_max_tokens=False)
+        if cypher_client is None:
+            raise RuntimeError("LLM 未配置，无法执行自然语言图查询")
+        cypher_client.timeout = min(float(getattr(cypher_client, "timeout", GRAPH_QA_CYPHER_TIMEOUT_SECONDS) or GRAPH_QA_CYPHER_TIMEOUT_SECONDS), GRAPH_QA_CYPHER_TIMEOUT_SECONDS)
+        schema_started = time.perf_counter()
+        schema = await asyncio.to_thread(_schema_snapshot, graph_name)
+        schema_ms = max(1, round((time.perf_counter() - schema_started) * 1000))
+        plan_payload = {
+            "question": question,
+            "graph_name": graph_name,
+            "intent": intent,
+            "customer_context": customer_context or {},
+            "graph_schema": schema,
+            "default_limit": limit,
+        }
+        cypher_started = time.perf_counter()
+        decision = await _chat_json_timed(
+            cypher_client,
+            GRAPH_QA_CYPHER_SYS,
+            json.dumps(plan_payload, ensure_ascii=False),
+            timeout_seconds=GRAPH_QA_CYPHER_TIMEOUT_SECONDS,
+            attempts=1,
+        )
+        cypher_ms = max(1, round((time.perf_counter() - cypher_started) * 1000))
+        _set_cached_cypher(cypher_cache_key, decision)
+
+    answer_client = await _graph_qa_client(max_tokens=650)
+    if answer_client is None:
+        raise RuntimeError("LLM 未配置，无法执行自然语言图查询")
+    answer_client.timeout = min(float(getattr(answer_client, "timeout", GRAPH_QA_ANSWER_TIMEOUT_SECONDS) or GRAPH_QA_ANSWER_TIMEOUT_SECONDS), GRAPH_QA_ANSWER_TIMEOUT_SECONDS)
+    generated_cypher = _clean_cypher(decision.get("cypher"), limit)
+    llm_generated_cypher = generated_cypher
+    graph_result: dict[str, Any]
+    query_error = ""
+    repaired = False
+    fallback_used = False
+    fallback_cypher = ""
+    fallback_ms = 0
+    try:
+        graph_started = time.perf_counter()
+        graph_result = await asyncio.to_thread(_run_cypher, graph_name, generated_cypher, limit)
+        graph_ms = max(1, round((time.perf_counter() - graph_started) * 1000))
+    except Exception as exc:  # noqa: BLE001
+        query_error = str(exc)[:400]
+        if cypher_client is None:
+            cypher_client = await _graph_qa_client(max_tokens=1000, use_config_max_tokens=False)
+        if cypher_client is None:
+            raise
+        cypher_client.timeout = min(float(getattr(cypher_client, "timeout", GRAPH_QA_REPAIR_TIMEOUT_SECONDS) or GRAPH_QA_REPAIR_TIMEOUT_SECONDS), GRAPH_QA_REPAIR_TIMEOUT_SECONDS)
+        repair_payload = {
+            "question": question,
+            "graph_name": graph_name,
+            "intent": intent,
+            "customer_context": customer_context or {},
+            "failed_cypher": generated_cypher,
+            "execution_error": query_error,
+        }
+        repaired_decision = await _chat_json_timed(
+            cypher_client,
+            GRAPH_QA_REPAIR_SYS,
+            json.dumps(repair_payload, ensure_ascii=False),
+            timeout_seconds=GRAPH_QA_REPAIR_TIMEOUT_SECONDS,
+            attempts=1,
+        )
+        generated_cypher = _clean_cypher(repaired_decision.get("cypher"), limit)
+        decision = {**decision, **repaired_decision}
+        repaired = True
+        graph_started = time.perf_counter()
+        graph_result = await asyncio.to_thread(_run_cypher, graph_name, generated_cypher, limit)
+        graph_ms = max(1, round((time.perf_counter() - graph_started) * 1000))
+
+    if _is_fee_question(question) and not _has_fee_evidence(graph_result):
+        fallback_cypher = _fee_fallback_cypher(question, limit) or ""
+        if fallback_cypher:
+            try:
+                fallback_started = time.perf_counter()
+                fallback_result = await asyncio.to_thread(_run_cypher, graph_name, fallback_cypher, limit)
+                fallback_ms = max(1, round((time.perf_counter() - fallback_started) * 1000))
+                if fallback_result.get("row_count") and _has_fee_evidence(fallback_result):
+                    graph_result = fallback_result
+                    generated_cypher = fallback_cypher
+                    fallback_used = True
+            except Exception as exc:  # noqa: BLE001
+                query_error = "; ".join(item for item in [query_error, f"fallback: {str(exc)[:220]}"] if item)
+
+    if not graph_result.get("row_count"):
+        latency_ms = max(1, round((time.perf_counter() - started_at) * 1000))
+        planner = intent.get("_planner_trace") if isinstance(intent.get("_planner_trace"), dict) else {}
+        planner_ms = _safe_int(planner.get("latency_ms"), 0)
+        answer = "已完成 LLM 图查询，但当前图谱没有命中可确认数据。建议补充更具体的线路、景区、套餐名称、出发日期或人数后再查。"
+        customer_reply = "抱歉，当前图谱暂未查到相关产品或套餐。您可以补充具体线路、景区、出发日期或套餐名称，我再帮您核实。"
+        response = {
+            "question": question,
+            "graph_name": graph_name,
+            "answer": answer,
+            "customer_reply": customer_reply,
+            "copy_text": customer_reply,
+            "plans": [],
+            "evidence": [],
+            "sales_scripts": [],
+            "follow_up_questions": ["请补充具体线路/产品名称。", "请说明出发日期、人数或套餐名称。", "是否要改查百姓惠旅游线路、价格、景区或酒店？"],
+            "risk_notes": ["图谱查询结果为空，不代表业务一定不存在，需按产品库或人工渠道二次核实。"],
+            "confidence": 0.28,
+            "graph_result": graph_result,
+            "trace": {
+                "method": "llm_to_cypher_graph_qa_v1",
+                "query_source": "llm_generated_cypher",
+                "rule_query_used": False,
+                "llm_used": True,
+                "llm_error": "",
+                "generated_cypher": llm_generated_cypher,
+                "effective_cypher": generated_cypher,
+                "cache": {"response": False, "cypher": cypher_cache_hit},
+                "cypher_cache_hit": cypher_cache_hit,
+                "fallback_cypher": fallback_cypher,
+                "fallback_query_used": fallback_used,
+                "cypher_reason": decision.get("reason") or "",
+                "intent": intent.get("intent") or "",
+                "llm_planner_used": bool(planner.get("used")),
+                "llm_planner": planner,
+                "graph_qa_intent": intent,
+                "routing_strategy": "intent_template_first_llm_fallback",
+                "cypher_repaired": repaired,
+                "first_query_error": query_error,
+                "row_count": 0,
+                "node_count": 0,
+                "relationship_count": 0,
+                "latency_ms": latency_ms,
+                "stage_timings_ms": {
+                    "intent_classification": intent_ms,
+                    "llm_planner": planner_ms,
+                    "schema": schema_ms,
+                    "cypher_generation": cypher_ms,
+                    "graph_query": graph_ms,
+                    "fallback_graph_query": fallback_ms,
+                    "answer_synthesis": 0,
+                },
+                "performance_target_ms": 1200,
+                "response_mode": "llm_graph_qa",
+                "response_mode_label": "LLM 图查询问答",
+                "graph_capabilities_used": ["LLM-to-Cypher", "FalkorDB 只读查询", "空结果快速返回"],
+                "retrieval_summary": {
+                    "cypher": generated_cypher,
+                    "llm_generated_cypher": llm_generated_cypher,
+                    "fallback_query_used": fallback_used,
+                    "rows": 0,
+                    "nodes": 0,
+                    "relationships": 0,
+                },
+            },
+        }
+        _set_cached_response(cache_key, response)
+        return response
+
+    answer_payload = {
+        "question": question,
+        "graph_name": graph_name,
+        "intent": intent,
+        "answer_focus": decision.get("answer_focus") or "",
+        "cypher": generated_cypher,
+        "graph_result": {
+            "columns": graph_result["columns"],
+            "row_count": graph_result["row_count"],
+            "rows": graph_result["rows"][:8],
+            "nodes": graph_result["nodes"][:10],
+            "relationships": graph_result["relationships"][:10],
+        },
+        "customer_context": customer_context or {},
+    }
+    answer_started = time.perf_counter()
+    answer_error = ""
+    try:
+        answer_data = await _chat_json_timed(
+            answer_client,
+            GRAPH_QA_ANSWER_SYS,
+            json.dumps(answer_payload, ensure_ascii=False),
+            timeout_seconds=GRAPH_QA_ANSWER_TIMEOUT_SECONDS,
+            attempts=1,
+        )
+    except asyncio.TimeoutError:
+        answer_data = {}
+        answer_error = "answer_timeout"
+    except Exception as exc:  # noqa: BLE001
+        answer_data = {}
+        answer_error = str(exc)[:260]
+    answer_ms = max(1, round((time.perf_counter() - answer_started) * 1000))
+    answer = str(answer_data.get("answer") or answer_data.get("customer_reply") or "").strip()
+    route_list_override = _route_list_answer(question, graph_result)
+    if route_list_override:
+        answer, customer_reply_override = route_list_override
+        answer_data["customer_reply"] = customer_reply_override
+        answer_data.setdefault("follow_up_questions", ["要查哪条线路的价格？", "请提供出发日期和人数。"])
+        answer_data.setdefault("risk_notes", ["价格、余位和用车需按具体团期二次核实。"])
+    if not answer:
+        answer = "图查询已完成，但答案组织 LLM 未在时间预算内返回。为避免编造，建议查看返回的 knowledge.evidence，并补充更明确的景点、线路、团期、人数或费用口径。"
+    customer_reply = str(answer_data.get("customer_reply") or answer).strip()
+    evidence = _evidence_cards(answer_data, graph_result)
+    plans = _plans_from_evidence(evidence, answer)
+    latency_ms = max(1, round((time.perf_counter() - started_at) * 1000))
+    planner = intent.get("_planner_trace") if isinstance(intent.get("_planner_trace"), dict) else {}
+    planner_ms = _safe_int(planner.get("latency_ms"), 0)
+    response = {
+        "question": question,
+        "graph_name": graph_name,
+        "answer": answer,
+        "customer_reply": customer_reply,
+        "copy_text": customer_reply or answer,
+        "plans": plans,
+        "evidence": evidence,
+        "sales_scripts": [],
+        "follow_up_questions": _list_texts(answer_data.get("follow_up_questions"), 4, 120),
+        "risk_notes": _list_texts(answer_data.get("risk_notes"), 4, 160),
+        "confidence": _safe_confidence(answer_data.get("confidence")),
+        "graph_result": graph_result,
+        "trace": {
+            "method": "llm_to_cypher_graph_qa_v1",
+            "query_source": "llm_generated_cypher",
+            "rule_query_used": False,
+            "llm_used": True,
+            "llm_error": answer_error,
+            "generated_cypher": llm_generated_cypher,
+            "effective_cypher": generated_cypher,
+            "cache": {"response": False, "cypher": cypher_cache_hit},
+            "cypher_cache_hit": cypher_cache_hit,
+            "fallback_cypher": fallback_cypher,
+            "fallback_query_used": fallback_used,
+            "cypher_reason": decision.get("reason") or "",
+            "intent": intent.get("intent") or "",
+            "llm_planner_used": bool(planner.get("used")),
+            "llm_planner": planner,
+            "graph_qa_intent": intent,
+            "routing_strategy": "intent_template_first_llm_fallback",
+            "cypher_repaired": repaired,
+            "first_query_error": query_error,
+            "row_count": graph_result["row_count"],
+            "node_count": len(graph_result["nodes"]),
+            "relationship_count": len(graph_result["relationships"]),
+            "latency_ms": latency_ms,
+            "stage_timings_ms": {
+                "intent_classification": intent_ms,
+                "llm_planner": planner_ms,
+                "schema": schema_ms,
+                "cypher_generation": cypher_ms,
+                "graph_query": graph_ms,
+                "fallback_graph_query": fallback_ms,
+                "answer_synthesis": answer_ms,
+            },
+            "performance_target_ms": 1200,
+            "response_mode": "llm_graph_qa",
+            "response_mode_label": "LLM 图查询问答",
+            "graph_capabilities_used": ["LLM-to-Cypher", "FalkorDB 只读查询", "LLM evidence synthesis"],
+            "retrieval_summary": {
+                "cypher": generated_cypher,
+                "llm_generated_cypher": llm_generated_cypher,
+                "fallback_query_used": fallback_used,
+                "rows": graph_result["row_count"],
+                "nodes": len(graph_result["nodes"]),
+                "relationships": len(graph_result["relationships"]),
+            },
+        },
+    }
+    _set_cached_response(cache_key, response)
+    return response
diff --git a/app/main.py b/app/main.py
index 6d7bd06..da2a510 100644
--- a/app/main.py
+++ b/app/main.py
@@ -8,7 +8,8 @@ from fastapi.middleware.cors import CORSMiddleware
 from fastapi.staticfiles import StaticFiles
 from starlette.exceptions import HTTPException as StarletteHTTPException
 
-from app.api import api_router
+from app.api import api_router, openapi_router
+from app.api.mcp_server import router as mcp_router
 from app.db import init_pool, close_pool
 
 
@@ -51,6 +52,8 @@ app.add_middleware(
 )
 
 app.include_router(api_router)
+app.include_router(openapi_router)
+app.include_router(mcp_router)
 
 # Serve built admin-web SPA (when available)
 try:
diff --git a/design-qa.md b/design-qa.md
new file mode 100644
index 0000000..882fed8
--- /dev/null
+++ b/design-qa.md
@@ -0,0 +1,243 @@
+# 云游荔波知识地图设计验收
+
+## 验收结论
+
+- final result: passed
+- 验收地址：`http://localhost:8102/admin/plaza/overview`
+- 验收项目：`yunyou_libo`
+- 验收日期：2026-07-29
+
+## 设计依据
+
+- 参考截图：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_rcA3Sf/截屏2026-07-29 09.40.16.png`
+- 参考图尺寸：2940 × 1912
+- 归一化参考图：`/Users/xuexue/new2/qa/libo-map-reference-normalized.png`
+- 当前实现截图：`/Users/xuexue/new2/qa/libo-map-implementation-fullscreen.png`
+- 对照图：`/Users/xuexue/new2/qa/libo-map-design-comparison.png`
+- 对照尺寸：两侧均为 1470 × 923
+
+## 实现状态
+
+- 荔波县地图、周边地图底图和荔波县行政边界正常显示。
+- 地图支持真正的全屏展示，不再保留页面内容空白区域。
+- POI 支持按酒店、美食、交通设施、景点分类展示、聚合和点击查看详情。
+- 当前地图实际数据为 2,799 条：酒店 1,220、美食 1,115、交通设施 379、景点 100；同一实体可同时归入多个业务分类，因此分类合计可能大于去重实体总数。
+- 公交图层包含 8 条线路、15 个运行方向、90 个站点；线路使用不同颜色，支持路线选择、方向和站点详情。
+- POI 详情侧栏保留原有基础字段，并增加大众点评、携程等融合字段；未匹配实体会明确显示未匹配状态。
+- 馆藏概览统计为 3,293 个实体、6,216 条关系，实体大类已恢复中文展示。
+
+## 视觉对照
+
+- 全屏地图、左上角浮层、分类按钮、公交入口、地图缩放控件与参考设计保持相同的信息结构。
+- 当前实现默认采用荔波县全域视角，用蓝色边界突出荔波县，并保留周边县市底图；参考图采用城区美食筛选后的近景视角。该差异是当前产品要求与实时状态造成的预期差异。
+- 参考图中的历史数量与当前知识图谱数量不同，当前实现以最新图谱和融合结果为准。
+- 地图数据、聚合数量和视口会随筛选与缩放变化；未发现影响交付的 P0、P1 或 P2 视觉问题。
+- 未额外制作局部对照图：归一化全屏对照已经能清晰覆盖浮层、地图、行政边界、聚合点和控制组件；详情侧栏通过交互测试单独验证。
+
+## 交互与运行检查
+
+- 全屏进入/退出：通过。
+- POI 分类切换与聚合点展示：通过。
+- POI 点击和详情侧栏：通过。
+- 美食大众点评融合字段：通过。
+- 酒店携程融合字段：通过。
+- 公交线路颜色、方向、站点与线路列表：通过。
+- 浏览器控制台：未发现 error 或 warning。
+- 前端生产构建：通过。
+- 后端 Python 语法检查：通过。
+- API 容器健康检查：通过。
+
+## 迭代记录
+
+1. 将原荔波地图和公交可视化代码合并回当前 `/Users/xuexue/new2`。
+2. 接入当前 `yunyou_libo` 图谱数据并修正地图分类统计。
+3. 增加美食、酒店外部平台融合字段的详情侧栏展示。
+4. 修正多标签实体的分类归属，保留去重实体总数。
+5. 完成生产构建、容器更新、浏览器交互和视觉对照验收。
+
+## 2026-07-29 酒店详情侧栏优化验收
+
+### 设计依据与证据
+
+- 原始混乱侧栏：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_lH1fjh/截屏2026-07-29 10.04.07.png`
+- 携程政策参考：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_SYzzDw/截屏2026-07-29 10.03.40.png`
+- 携程周边分类参考：`/Users/xuexue/Desktop/截屏2026-07-29 10.24.40.png`
+- 最终酒店侧栏：`/Users/xuexue/new2/qa/libo-hotel-detail-optimized-final.png`
+- 最终周边分类状态：`/Users/xuexue/new2/qa/libo-hotel-nearby-categories-final.png`
+- 全视图对照：`/Users/xuexue/new2/qa/libo-hotel-nearby-full-comparison.png`
+- 局部分类对照：`/Users/xuexue/new2/qa/libo-hotel-nearby-focus-comparison.png`
+- 参考图像：2940 × 1912；实现截图：1470 × 923；浏览器 CSS 视口：1470 × 923，设备像素比 1。
+- 对照时将参考图归一化到 1470 × 923；局部对照分别裁取携程“地点”和实现“周边地点”区域后等宽排列。
+
+### 修复记录
+
+1. [P1 已修复] 详情侧栏直接展示融合状态、置信度、匹配规则和候选相似度，混入了数据审核过程。修复后这些字段只保留在知识图谱内部，不再面向业务页面展示。
+2. [P1 已修复] `ctrip_diamond_level` 混入 `2 out of 5 rating/diamonds` 等无障碍英文属性。730 条可解释数据规范为“X钻”，1 条无法解释的 `stars` 值从钻级属性移除；前端也增加兜底清洗。
+3. [P1 已修复] 携程客房数、售卖方案、点评样本等缺失值以 `0` 展示。当前仅展示有业务意义的非零信息。
+4. [P2 已修复] 酒店政策、设施、周边地点和长文本混成连续字段。当前按基础信息、携程酒店信息、房型与价格、服务及设施、酒店政策、住客评价、周边地点、数据来源分组。
+5. [P2 已修复] 周边地点没有分类。703 家酒店已写入 31,029 条分类明细，按交通、景点、美食、购物切换，并在分类和地点名称旁使用对应图标。
+
+### 可见质量检查
+
+- 字体与层级：沿用系统现有中文字体栈；标题 15px/700、内容 13px、辅助信息 11–12px，长名称和距离允许换行。
+- 间距与布局：侧栏宽度 460px；区块 12px 间距、12px 圆角；政策使用标签/内容双列，周边地点使用名称/距离双列。
+- 颜色与状态：沿用酒店紫色语义色、灰色信息层级和蓝色选中状态；外部平台信息不再使用审核状态色。
+- 图片质量：继续使用高德、携程原始图片 URL，并保留预览；未引入占位业务素材。
+- 文案与内容：钻级、点评、设施、政策、交通距离均转换为中文业务表达；知识来源正确显示“高德地图 · 携程”。
+
+### 交互检查
+
+- 酒店点位打开详情：通过。
+- 交通、景点、美食、购物四类切换：通过。
+- 四类图标和地点图标：通过。
+- 交通类步行/驾车距离及时间：通过。
+- `2钻` 中文显示：通过。
+- 融合状态、匹配置信度、匹配规则隐藏：通过。
+- 高德地图、电话、携程详情操作：通过。
+- 浏览器未发现应用错误；远程实验统计服务超时不影响本地产品运行。
+
+### 本轮结论
+
+- 当前没有遗留 P0、P1 或 P2 问题。
+- final result: passed
+
+## 2026-07-29 酒店周边交通距离单行验收
+
+### 设计依据与证据
+
+- 原交通距离换行状态：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_Wu9Uxm/截屏2026-07-29 11.49.23.png`
+- 最终浏览器状态：`/Users/xuexue/new2/qa/libo-hotel-nearby-transport-single-line.png`
+- 前后对照图：`/Users/xuexue/new2/qa/libo-hotel-nearby-transport-comparison.png`
+
+### 修复记录
+
+1. [P1 已修复] 周边交通的距离、时间信息在窄侧栏内被拆成两行。交通行现在使用独立的两列布局，名称列固定为 150px，距离时间列获得其余可用宽度。
+2. [P2 已修复] 距离时间原本靠右贴边，视觉空间不足。现在改为左对齐并向左移动，四个公共交通点的距离时间可保持单行阅读。
+3. [范围控制] 仅“交通”分类使用单行规则；景点、美食、购物等名称或距离较长的分类继续使用原有自适应换行，避免其他内容被裁切。
+
+### 可见质量与交互检查
+
+- 实际交通距离文本测量：`clientWidth = 240`、`scrollWidth = 240`、`white-space = nowrap`、`line-height = 18px`，没有换行或横向溢出。
+- 最终截图使用具有 3 条周边交通数据的真实酒店验证；布局规则与条目数量无关，含 4 个公共交通点的酒店使用同一单行布局。
+- 酒店详情抽屉、周边分类切换和底部操作保持可用。
+- 前端生产构建和容器更新通过。
+
+### 本轮结论
+
+- 当前没有遗留 P0、P1 或 P2 问题。
+- final result: passed
+
+## 2026-07-29 携程酒店信息统一清单验收
+
+### 设计依据与证据
+
+- 原部分数据状态：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_ePNasT/截屏2026-07-29 11.45.35.png`
+- 原完整数据状态：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_K9h0Ya/截屏2026-07-29 11.45.50.png`
+- 最终完整数据状态：`/Users/xuexue/new2/qa/libo-hotel-info-unified-complete.png`
+- 最终缺失数据状态：`/Users/xuexue/new2/qa/libo-hotel-info-unified-missing.png`
+- 前后综合对照：`/Users/xuexue/new2/qa/libo-hotel-info-unified-comparison.png`
+
+### 原因与修复记录
+
+1. [原因确认] 原组件会过滤值为空的评分、点评、钻级和起价卡片，因此不同酒店显示 2、3 或 4 张卡片；这是数据完备度差异，并非抽屉宽度挤压。
+2. [P1 已修复] 将携程评分、用户点评、酒店钻级和参考起价从可变数量卡片统一并入酒店信息文本清单，与携程酒店名、开业时间、客房数量使用相同的信息结构。
+3. [P1 已修复] 七项核心字段固定顺序展示；无源数据时明确显示“暂无数据”，不再因为字段被过滤而改变版式。
+4. [P2 已修复] 每项字段使用 Ant Design 对应业务图标、统一 24px 图标容器、132px 标签列和可伸缩内容列，长酒店名称可完整换行。
+5. [数据语义] 评分描述以“4.7 · 超棒”组合表达；点评补“条”、开业时间补“年”、客房数量补“间”、价格补“¥”与“起”，钻级继续使用规范化中文“X钻”。
+6. [数据核验] `锦峰酒店(荔波古镇店)` 的图谱源数据为评分 4.6、点评 353、3钻、参考起价 126；统一清单会分别显示为“4.6 · 很好”“353 条”“3钻”“¥126 起”。
+
+### 可见质量与交互检查
+
+- 完整数据酒店 `玉舍望山全景度假民宿(荔波高铁站店)`：评分、点评、钻级、酒店名、开业时间、客房数量均按统一清单完整显示。
+- 部分数据酒店 `港旺民宿`：缺失评分、点评、起价、开业时间和客房数量均显示“暂无数据”，钻级及酒店名保留真实值。
+- 两类酒店使用相同字段顺序、图标、分隔线、字号和列宽，不再产生两套版式。
+- 460px 抽屉内没有横向滚动或内容裁切。
+- 酒店政策、服务设施、地图点位和底部操作保持原有功能。
+- 前端生产构建、容器更新与本地 API 健康检查通过。
+
+### 本轮结论
+
+- 当前没有遗留 P0、P1 或 P2 问题。
+- final result: passed
+
+## 2026-07-29 酒店详情抽屉整体宽度适配验收
+
+### 设计依据与证据
+
+- 整体内容裁切状态：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_pUwfPg/截屏2026-07-29 11.33.00.png`
+- 图片、指标与设施裁切状态：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_fm0DIk/截屏2026-07-29 11.34.40.png`
+- 政策与周边地点裁切状态：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_yyNCwA/截屏2026-07-29 11.34.57.png`
+- 最终顶部图片状态：`/Users/xuexue/new2/qa/libo-hotel-responsive-top.png`
+- 最终携程指标状态：`/Users/xuexue/new2/qa/libo-hotel-responsive-metrics.png`
+- 最终设施状态：`/Users/xuexue/new2/qa/libo-hotel-responsive-facility-rows-final.png`
+- 最终政策状态：`/Users/xuexue/new2/qa/libo-hotel-responsive-facilities.png`
+- 最终周边地点状态：`/Users/xuexue/new2/qa/libo-hotel-responsive-nearby.png`
+- 顶部综合对照：`/Users/xuexue/new2/qa/libo-hotel-responsive-top-comparison.png`
+- 政策与周边对照：`/Users/xuexue/new2/qa/libo-hotel-responsive-content-comparison.png`
+
+### 修复记录
+
+1. [P1 已修复] 酒店图片三列网格受图片固有宽度影响，第三张图片超出 460px 抽屉。修复后使用 `repeat(3, minmax(0, 1fr))`，图片容器允许收缩，三张图片均完整展示。
+2. [P1 已修复] 携程评分、用户点评和酒店钻级指标卡的最小内容宽度会撑开区块。修复后指标条、指标卡和平台信息区均锁定为 `width/max-width: 100%` 与 `min-width: 0`，三个指标完整显示。
+3. [P1 已修复] 酒店政策长句和部分平台字段仍会被抽屉裁切。修复后所有标签/内容双列区块统一允许内容列收缩，并使用中文换行与 `overflow-wrap` 保留完整文案。
+4. [P1 已修复] 周边地点的距离与时间列被挤到抽屉外。修复后名称列弹性换行，距离列限制最大宽度并支持多行，地点名称和距离同时完整可见。
+5. [P2 已修复] 设施、政策、周边地点等不同卡片采用了不一致的宽度行为。修复后基础信息、平台信息、设施、政策、评价、周边地点和数据来源全部使用同一套 460px 抽屉适配规则。
+6. [预期交互] 设施分类较多时保持独立横向滑动，不压缩分类文字；详情抽屉本身不产生横向滚动。
+
+### 可见质量与交互检查
+
+- 抽屉正文测量：`clientWidth = 460`、`scrollWidth = 460`、`scrollLeft = 0`，无整体横向溢出。
+- 设施分类栏测量：`clientWidth = 398`、`scrollWidth = 973`、`overflow-x = auto`，分类栏可独立滑动。
+- 顶部三张图片：全部可见且保持一致高度与圆角。
+- 三个携程指标卡：全部在同一行完整展示。
+- 酒店名称、政策长句和基础字段：完整换行，没有内容裁切。
+- 设施分类横向滑动与“清洁服务”分类切换：通过。
+- 周边交通地点名称、距离和时间：同时完整展示。
+- 底部高德地图、电话和携程详情操作：保持可用。
+- 前端生产构建、容器更新与 API 健康检查：通过。
+
+### 本轮结论
+
+- 当前没有遗留 P0、P1 或 P2 问题。
+- final result: passed
+
+## 2026-07-29 酒店服务设施分类与窄侧栏验收
+
+### 设计依据与证据
+
+- 携程设施分类参考：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_TndZuk/截屏2026-07-29 10.46.14.png`
+- 原窄侧栏挤压状态：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_I28Z0E/截屏2026-07-29 10.57.13.png`
+- 原设施条目宽度不一致状态：`/var/folders/sl/bt4qhk351ndfm_1x3_4wkw440000gn/T/TemporaryItems/NSIRD_screencaptureui_d5kzAB/截屏2026-07-29 11.01.53.png`
+- 最终设施分类状态：`/Users/xuexue/new2/qa/libo-hotel-facility-final.png`
+- 最终窄侧栏宽度状态：`/Users/xuexue/new2/qa/libo-hotel-facility-width-postfix.png`
+- 前后对照图：`/Users/xuexue/new2/qa/libo-hotel-facility-comparison.png`
+- 实现截图为 1248 × 706；对照图将原问题截图等比归一化到 1248px 宽，与最终实现纵向排列检查。
+
+### 数据与实现
+
+- 已将携程设施数据按真实分类写入酒店实体；当前 772 个酒店节点具有结构化设施信息，共 17,807 条设施明细。
+- 仅使用来源中明确标记为设施实拍的图片，不伪造设施图片；当前 139 个酒店节点具有设施图片，共 270 个设施图片 URL。
+- 分类支持公共区、前台服务、交通服务、餐饮服务、清洁服务、商务服务、儿童设施、康体设施、安全与安保等实际数据类别。
+- 每个设施保留名称、收费信息、描述、排序及携程来源 URL；侧栏提供“查看携程设施来源”。
+
+### 修复记录
+
+1. [P1 已修复] 原抽屉正文允许整体横向滚动，分类条的固有宽度会将详情内容撑到 1000px 以上并拖出 460px 抽屉。修复后抽屉正文锁定横向宽度，只允许设施分类条和设施图片条在各自容器内横向滑动。
+2. [P1 已修复] 原设施明细采用两列布局，窄侧栏内第二列被裁切、不同文本造成卡片宽度不一致。修复后统一为单列、100% 宽度，名称列可换行，收费标签固定在右侧。
+3. [P2 已修复] 分类名称和数量在宽度不足时被压缩变形。修复后分类按钮不缩放、不换行，可水平滚动，并保留当前分类的紫色选中态。
+4. [用户确认] 勾选图标维持原紫色语义色，不改为绿色。
+
+### 可见质量与交互检查
+
+- 字体与层级：沿用当前系统字体、酒店紫色语义色和 12–15px 信息层级。
+- 间距与宽度：460px 抽屉内设施区不再产生整体横向位移；设施条目宽度一致且与容器对齐。
+- 分类交互：康体设施、交通服务、餐饮服务、娱乐活动设施等分类切换通过；选中“娱乐活动设施”后正确展示“棋牌室”。
+- 状态图标：勾选图标为紫色，与酒店分类和选中态保持一致。
+- 图片：只展示真实设施图片 URL，使用横向滑动与原图预览；没有设施实拍时不显示伪造占位图片。
+- 链接：携程设施来源链接存在且指向对应酒店详情。
+- 浏览器控制台仅有远程实验统计服务超时，不影响本地页面；本地 API 健康检查、前端生产构建、容器更新均通过。
+
+### 本轮结论
+
+- 当前没有遗留 P0、P1 或 P2 问题。
+- final result: passed
diff --git a/docker-compose.server.yml b/docker-compose.server.yml
new file mode 100644
index 0000000..4bd70ae
--- /dev/null
+++ b/docker-compose.server.yml
@@ -0,0 +1,29 @@
+services:
+  api:
+    network_mode: host
+    ports: !override []
+    environment:
+      DATABASE_URL: postgresql://${POSTGRES_USER:-admin}:${POSTGRES_PASSWORD:-password}@127.0.0.1:${POSTGRES_PORT:-5433}/${POSTGRES_DB:-kg_admin}
+      FALKORDB_HOST: 127.0.0.1
+      FALKORDB_PORT: ${FALKORDB_PORT:-6380}
+    command:
+      - python
+      - -m
+      - uvicorn
+      - app.main:app
+      - --host
+      - 0.0.0.0
+      - --port
+      - ${API_PORT:-8102}
+    healthcheck:
+      test:
+        [
+          "CMD",
+          "python",
+          "-c",
+          "import os, urllib.request; port=os.environ.get('API_PORT','8102'); urllib.request.urlopen(f'http://127.0.0.1:{port}/v1/admin/health', timeout=5).read()",
+        ]
+      interval: 30s
+      timeout: 5s
+      start_period: 30s
+      retries: 3
diff --git a/docs/API_REFERENCE.md b/docs/API_REFERENCE.md
index a66564e..cc6ba88 100644
--- a/docs/API_REFERENCE.md
+++ b/docs/API_REFERENCE.md
@@ -6,12 +6,18 @@ FastAPI 会自动生成交互式 API 文档。启动服务后访问：
 http://localhost:8102/docs
 ```
 
-所有后台接口统一挂载在：
+后台管理接口统一挂载在：
 
 ```text
 /v1/admin
 ```
 
+第三方系统对接接口统一挂载在：
+
+```text
+/v1/openapi
+```
+
 ## 常用接口
 
 | 接口 | 方法 | 说明 |
@@ -31,7 +37,8 @@ http://localhost:8102/docs
 | `/v1/admin/plaza/overview` | `GET` | 图谱广场概览 |
 | `/v1/admin/manual-ingest/extract` | `POST` | 手动抽取 |
 | `/v1/admin/travel/assistant-query` | `POST` | 旅行客服问答 |
-| `/v1/admin/travel/customer-service-query` | `POST` | 百姓惠智能客服外部问答接口 |
+| `/v1/openapi/knowledge-qa/query` | `POST` | 百姓惠智能客服第三方问答接口 |
+| `/v1/admin/travel/customer-service-query` | `POST` | 兼容旧版外部问答接口 |
 | `/v1/admin/super-agent/run` | `POST` | Super Agent 任务 |
 | `/v1/admin/roles` | `GET/POST` | 角色管理 |
 | `/v1/admin/users` | `GET/POST` | 用户管理 |
@@ -76,30 +83,38 @@ curl http://localhost:8102/v1/admin/travel/assistant-query \
 
 ## 百姓惠智能客服外部接口
 
-该接口用于对接外部客服系统。调用方传入用户自然语言问题，服务端默认选择百姓惠旅行社知识图谱，先召回图谱线路、报价口径、费用、酒店、餐饮、车辆和证据，再用 LLM 融合成客服可直接使用的话术。没有配置 LLM 时会自动退回图谱模板回答。
+该接口用于对接外部客服系统。调用方传入用户自然语言问题，服务端默认选择百姓惠旅行社知识图谱，按“LLM 生成只读 Cypher -> FalkorDB 图查询 -> LLM 基于证据组织答案”的链路返回客服话术和图谱证据。生产环境需要配置问答环节 LLM。
 
-认证方式使用接口 Key，默认本地开发值来自 `.env` / `docker-compose.yml` 的 `INGEST_API_KEYS`：
+认证方式使用接口 Key。Key 可以在后台 `系统 -> Agent 设置 -> 外部图谱问答 API` 维护；同时兼容 `.env` / `docker-compose.yml` 的 `INGEST_API_KEYS`。同一模块底部可以配置“问答环节 LLM 模型”，外部客服话术融合会优先使用该模型，未填写时继承全局 LLM：
 
 ```bash
-curl http://localhost:8102/v1/admin/travel/customer-service-query \
+curl http://localhost:8102/v1/openapi/knowledge-qa/query \
   -H 'Content-Type: application/json' \
   -H 'X-KG-API-Key: dev-key-1' \
   -d '{
+    "request_id": "crm-msg-20260610-0001",
     "question": "黄小西三日游多少钱？",
-    "knowledge_graph": "百姓惠",
+    "graph_name": "baixinghui_travel_agency",
     "session_id": "demo-session-001",
+    "channel": "online_service",
+    "customer_id": "customer-001",
     "use_llm": true,
     "llm_fusion": true
   }'
 ```
 
+新系统请优先使用 `/v1/openapi/knowledge-qa/query`；`/v1/admin/travel/customer-service-query` 仅用于兼容已经接入的内部/旧系统。
+
 常用入参：
 
 | 字段 | 说明 |
 | --- | --- |
+| `request_id` / `message_id` | 外部系统请求或消息 ID，可选；不传时服务端生成 |
 | `question` / `text` | 用户原始咨询内容，必填 |
-| `knowledge_graph` / `graph_name` | 知识图谱名称，可传 `百姓惠`、`bxh` 或 `baixinghui_travel_agency` |
+| `graph_name` / `knowledge_graph` | 知识图谱名称；不传时使用后台默认图谱。百姓惠可传 `百姓惠`、`bxh` 或 `baixinghui_travel_agency` |
 | `session_id` | 外部客服会话 ID，可选 |
+| `channel` | 来源渠道，如 `web`、`wechat`、`online_service`，可选 |
+| `customer_id` / `external_user_id` | 外部客户 ID，可选 |
 | `customer_context` | 外部系统附带的客户上下文，可选 |
 | `use_llm` | 是否启用 LLM 意图解析，默认 `true` |
 | `llm_fusion` | 是否启用 LLM 话术融合，默认 `true` |
@@ -109,6 +124,8 @@ curl http://localhost:8102/v1/admin/travel/customer-service-query \
 
 | 字段 | 说明 |
 | --- | --- |
+| `request_id` | 外部请求 ID，原样回传或由服务端生成 |
+| `trace_id` | 服务端链路追踪 ID，排查问题时使用 |
 | `answer` | 给外部系统展示的完整回答 |
 | `customer_reply` | 可直接发给客户的话术 |
 | `confidence` | 本次回答置信度 |
@@ -119,6 +136,26 @@ curl http://localhost:8102/v1/admin/travel/customer-service-query \
 | `routing.intent` | 解析出的客户需求 |
 | `trace` | 响应耗时、召回规模、质量检查摘要 |
 
+认证请求头支持三种写法，推荐第一种：
+
+```text
+X-KG-API-Key: <api-key>
+X-API-Key: <api-key>
+Authorization: Bearer <api-key>
+```
+
+生产环境必须至少配置一个 API Key；未配置时，对外问答接口会返回 `503`，表示接口尚未启用。
+不要使用 `dev-key-1` 这类弱密钥作为生产 Key；建议使用高强度随机字符串，按周期轮换，并优先通过环境变量 `INGEST_API_KEYS` 或后台配置统一管理。
+
+常见错误码：
+
+| 状态码 | 说明 |
+| --- | --- |
+| `400` | 请求体缺少 `question` |
+| `401` | API Key 缺失或无效 |
+| `502` | 图查询、LLM 生成 Cypher 或答案合成失败 |
+| `503` | 后台未配置接口 API Key |
+
 ## 前端调用
 
 React 管理后台通过 `admin-web/src/api.ts` 访问同源 API。Docker 部署时前端和 API 同在 `http://localhost:8102`，因此无需额外配置跨域代理。
diff --git a/docs/BAIXINGHUI_CUSTOMER_SERVICE_MCP_SERVER.md b/docs/BAIXINGHUI_CUSTOMER_SERVICE_MCP_SERVER.md
new file mode 100644
index 0000000..59f1636
--- /dev/null
+++ b/docs/BAIXINGHUI_CUSTOMER_SERVICE_MCP_SERVER.md
@@ -0,0 +1,568 @@
+# 百姓惠智能客服 MCP Server 打包说明
+
+本文档说明如何将当前百姓惠旅行社知识图谱智能客服能力封装为一个 MCP Server，供 DeerFlow、Agent 平台或其他支持 MCP 的智能体调用。
+
+## 1. 改造目标
+
+当前系统已经提供普通 HTTP 问答接口：
+
+```text
+POST http://8.163.40.99:8102/v1/openapi/knowledge-qa/query
+```
+
+MCP Server 不需要重写现有问答 engine，只需要在现有接口外增加一层适配：
+
+```text
+Agent / DeerFlow
+  -> MCP Client
+  -> 百姓惠 MCP Server
+  -> 现有智能客服问答 API
+  -> 知识图谱 / FalkorDB / LLM
+```
+
+这层 MCP Server 负责：
+
+- 暴露 Agent 可调用的 tools。
+- 将 tool call 转换为当前项目已有 HTTP API 请求。
+- 将智能客服 API 返回值整理成稳定的 MCP tool result。
+- 统一处理鉴权、超时、错误、日志和审计。
+
+## 2. MCP Server 推荐入口
+
+建议新增远程 HTTP MCP Server：
+
+```text
+http://8.163.40.99:8102/mcp
+```
+
+如果后续需要 SSE：
+
+```text
+http://8.163.40.99:8102/mcp/sse
+```
+
+推荐优先使用 `http` 类型，便于 DeerFlow 或企业 Agent 平台远程接入。
+
+## 3. DeerFlow 接入配置示例
+
+`extensions_config.json` 示例：
+
+```json
+{
+  "mcpServers": {
+    "baixinghui_customer_service": {
+      "enabled": true,
+      "type": "http",
+      "url": "http://8.163.40.99:8102/mcp",
+      "headers": {
+        "Authorization": "Bearer $BXH_MCP_TOKEN"
+      },
+      "description": "百姓惠旅行社知识图谱智能客服 MCP 工具"
+    }
+  },
+  "skills": {}
+}
+```
+
+环境变量示例：
+
+```bash
+export BXH_MCP_TOKEN="<MCP_SERVER_TOKEN>"
+```
+
+说明：
+
+- `BXH_MCP_TOKEN` 是 MCP Server 的访问令牌。
+- MCP Server 内部再使用当前系统配置的 `X-KG-API-Key` 调用现有问答 API。
+- 不建议让 DeerFlow 或 Agent 直接持有现有 `X-KG-API-Key`。
+
+## 4. MCP Server 内部调用的现有接口
+
+MCP Server 内部统一调用：
+
+```text
+POST http://127.0.0.1:8102/v1/openapi/knowledge-qa/query
+```
+
+请求头：
+
+```http
+Content-Type: application/json
+X-KG-API-Key: <INTERNAL_KG_API_KEY>
+```
+
+如果 MCP Server 与业务 API 分开部署，则改为：
+
+```text
+POST http://8.163.40.99:8102/v1/openapi/knowledge-qa/query
+```
+
+## 5. MCP 工具设计原则
+
+不要暴露通用工具，例如：
+
+```text
+call_api
+execute_cypher
+execute_sql
+request_url
+```
+
+推荐暴露明确、受控的业务工具：
+
+| 工具名 | 用途 | 读/写 | 风险等级 |
+| --- | --- | --- | --- |
+| `ask_customer_service` | 通用智能客服问答 | 读 | 低 |
+| `query_route_price` | 查询线路价格 | 读 | 低 |
+| `list_travel_routes` | 查询旅行线路清单 | 读 | 低 |
+| `query_route_detail` | 查询线路天数、景区、酒店等详情 | 读 | 低 |
+| `compare_routes` | 对比线路适配度或景点数量 | 读 | 中 |
+
+当前阶段建议全部为只读工具，不提供写操作。
+
+## 6. Tool 1：ask_customer_service
+
+### 用途
+
+通用客服问答工具。Agent 不确定该调用哪个细分工具时，可以使用该工具。
+
+### Tool 定义
+
+```json
+{
+  "name": "ask_customer_service",
+  "description": "向百姓惠旅行社知识图谱智能客服提问。适用于线路价格、行程天数、景区、酒店、费用、车型、线路推荐和复杂多跳问答。该工具只读，不承诺最终价格、余位、房型或景区政策。",
+  "inputSchema": {
+    "type": "object",
+    "properties": {
+      "question": {
+        "type": "string",
+        "description": "用户自然语言问题"
+      },
+      "session_id": {
+        "type": "string",
+        "description": "外部会话 ID，可选"
+      },
+      "request_id": {
+        "type": "string",
+        "description": "外部请求 ID，可选"
+      },
+      "customer_context": {
+        "type": "object",
+        "description": "客户上下文，例如人数、预算、出发日期、偏好，可选"
+      }
+    },
+    "required": ["question"]
+  }
+}
+```
+
+### 内部 API 请求示例
+
+```json
+{
+  "request_id": "mcp-req-0001",
+  "session_id": "mcp-session-a01",
+  "channel": "mcp",
+  "graph_name": "baixinghui_travel_agency",
+  "question": "轻奢黄小西纯玩3日游多少钱，可以玩几天，期间可以去哪些景区，小七孔附近可以入住什么酒店？"
+}
+```
+
+### MCP Tool Result 示例
+
+```json
+{
+  "success": true,
+  "data": {
+    "customer_reply": "亲，轻奢黄小西纯玩3日游是3天线路；成人参考610-2350元/人，儿童参考340-700元/人；可玩多彩贵州风、荔波小七孔景区、西江千户苗寨景区、黄果树旅游景区；附近可参考荔波天泰酒店、三力丽呈、荔波滨江。具体价格、房型和余位需要按出发日期再确认。",
+    "answer": "完整回答内容",
+    "confidence": 0.88,
+    "follow_up_questions": ["请提供出发日期和人数。"],
+    "risk_notes": ["价格、余位、房型和景区政策需按具体团期二次核实。"],
+    "evidence": [],
+    "plans": [],
+    "response_mode": "fast_graph_template"
+  },
+  "trace_id": "trc_xxx"
+}
+```
+
+## 7. Tool 2：query_route_price
+
+### 用途
+
+专门查询某条线路价格，例如成人价、儿童价、单房差。
+
+### Tool 定义
+
+```json
+{
+  "name": "query_route_price",
+  "description": "查询百姓惠旅行社指定线路的参考价格、成人价、儿童价和单房差。该工具返回图谱参考价，最终价格需按出发日期、人数和住宿档位二次核实。",
+  "inputSchema": {
+    "type": "object",
+    "properties": {
+      "route_name": {
+        "type": "string",
+        "description": "线路名称或关键词，例如 黄小西、轻奢黄小西纯玩3日游"
+      },
+      "days": {
+        "type": "integer",
+        "description": "行程天数，可选"
+      },
+      "request_id": {
+        "type": "string",
+        "description": "请求 ID，可选"
+      }
+    },
+    "required": ["route_name"]
+  }
+}
+```
+
+### 内部 question 生成规则
+
+```text
+{route_name}{days_text}多少钱？成人价、儿童价和单房差是多少？
+```
+
+示例：
+
+```json
+{
+  "question": "黄小西3日游多少钱？成人价、儿童价和单房差是多少？"
+}
+```
+
+## 8. Tool 3：list_travel_routes
+
+### 用途
+
+查询当前图谱中有哪些旅行线路。
+
+### Tool 定义
+
+```json
+{
+  "name": "list_travel_routes",
+  "description": "查询百姓惠旅行社当前图谱中的旅行线路清单。",
+  "inputSchema": {
+    "type": "object",
+    "properties": {
+      "keyword": {
+        "type": "string",
+        "description": "线路关键词，可选，例如 黄小西、小西镇梵、旅行车"
+      },
+      "request_id": {
+        "type": "string",
+        "description": "请求 ID，可选"
+      }
+    }
+  }
+}
+```
+
+### 内部 question 生成规则
+
+无关键词：
+
+```text
+旅行车线路有哪些？
+```
+
+有关键词：
+
+```text
+{keyword}相关线路有哪些？
+```
+
+## 9. Tool 4：query_route_detail
+
+### 用途
+
+查询某条线路的天数、价格、途经景区、某景区附近酒店等多跳图谱信息。
+
+### Tool 定义
+
+```json
+{
+  "name": "query_route_detail",
+  "description": "查询指定线路的价格、行程天数、途经景区和景区附近酒店。适合多跳图谱问题。",
+  "inputSchema": {
+    "type": "object",
+    "properties": {
+      "route_name": {
+        "type": "string",
+        "description": "线路名称或关键词"
+      },
+      "scenic_name": {
+        "type": "string",
+        "description": "需要查询附近酒店的景区名称，可选，例如 小七孔、西江、黄果树"
+      },
+      "request_id": {
+        "type": "string",
+        "description": "请求 ID，可选"
+      }
+    },
+    "required": ["route_name"]
+  }
+}
+```
+
+### 内部 question 生成规则
+
+```text
+{route_name}多少钱，可以玩几天，期间可以去哪些景区，{scenic_name}附近可以入住什么酒店？
+```
+
+示例：
+
+```json
+{
+  "question": "轻奢黄小西纯玩3日游多少钱，可以玩几天，期间可以去哪些景区，小七孔附近可以入住什么酒店？"
+}
+```
+
+## 10. Tool 5：compare_routes
+
+### 用途
+
+对比两条或多条线路，例如哪个更适合老人小孩、哪个景点更多、哪个更轻松。
+
+### Tool 定义
+
+```json
+{
+  "name": "compare_routes",
+  "description": "对比百姓惠旅行社线路的适配度、景区数量、轻松程度、老人小孩适合度等。只做图谱证据对比，不做最终承诺。",
+  "inputSchema": {
+    "type": "object",
+    "properties": {
+      "route_names": {
+        "type": "array",
+        "items": {"type": "string"},
+        "description": "需要对比的线路关键词，例如 [\"黄小西\", \"小西镇梵\"]"
+      },
+      "compare_focus": {
+        "type": "string",
+        "description": "对比重点，例如 老人小孩适合度、景点数量、价格、轻松程度"
+      },
+      "request_id": {
+        "type": "string",
+        "description": "请求 ID，可选"
+      }
+    },
+    "required": ["route_names", "compare_focus"]
+  }
+}
+```
+
+### 内部 question 生成规则
+
+```text
+{route_names}哪个更适合{compare_focus}，为什么？
+```
+
+示例：
+
+```json
+{
+  "question": "黄小西和小西镇梵哪个更适合老人小孩、不要太累，为什么？"
+}
+```
+
+## 11. 统一 MCP Tool Result 格式
+
+所有工具建议统一返回：
+
+```json
+{
+  "success": true,
+  "data": {
+    "customer_reply": "客服可直接发送的话术",
+    "answer": "完整回答",
+    "confidence": 0.88,
+    "follow_up_questions": [],
+    "risk_notes": [],
+    "plans": [],
+    "evidence": [],
+    "response_mode": "fast_graph_template",
+    "latency_ms": 35
+  },
+  "trace_id": "trc_xxx"
+}
+```
+
+失败时返回：
+
+```json
+{
+  "success": false,
+  "error": {
+    "code": "CUSTOMER_SERVICE_QUERY_FAILED",
+    "message": "智能客服查询失败",
+    "retryable": true
+  },
+  "trace_id": "trc_xxx"
+}
+```
+
+如果业务 API 返回受控兜底，也建议作为 `success: true` 返回，并在 `data.response_mode` 中标记：
+
+```json
+{
+  "success": true,
+  "data": {
+    "customer_reply": "亲，这个问题当前图谱暂未查到可确认答案，需要补充更具体的线路、景区或套餐名称后再核实。",
+    "response_mode": "llm_graph_qa_controlled_failure",
+    "risk_notes": ["当前回复为受控兜底，不代表图谱已有明确业务证据。"]
+  },
+  "trace_id": "trc_xxx"
+}
+```
+
+## 12. MCP Server 环境变量
+
+建议 MCP Server 使用以下环境变量：
+
+```bash
+export BXH_MCP_TOKEN="<MCP_SERVER_TOKEN>"
+export BXH_KG_API_BASE="http://127.0.0.1:8102"
+export BXH_KG_API_KEY="<INTERNAL_KG_API_KEY>"
+export BXH_DEFAULT_GRAPH="baixinghui_travel_agency"
+export BXH_MCP_TIMEOUT_SECONDS="15"
+```
+
+说明：
+
+| 变量名 | 说明 |
+| --- | --- |
+| `BXH_MCP_TOKEN` | 外部 Agent 调用 MCP Server 的鉴权令牌 |
+| `BXH_KG_API_BASE` | 当前项目 HTTP API 地址 |
+| `BXH_KG_API_KEY` | 当前项目外部图谱问答 API Key |
+| `BXH_DEFAULT_GRAPH` | 默认图谱 |
+| `BXH_MCP_TIMEOUT_SECONDS` | MCP Server 调用业务 API 的超时时间 |
+
+## 13. 安全要求
+
+- MCP Server 只暴露业务工具，不暴露任意 URL、任意 SQL、任意 Cypher。
+- 所有工具当前均为只读工具。
+- MCP Server 必须校验 `Authorization` 或其他服务令牌。
+- 不向 Agent 返回内部 API Key、数据库地址、原始异常栈。
+- `risk_notes` 必须保留给 Agent，用于提示价格、余位、房型、政策需二次核实。
+- 记录工具调用日志，至少包含 tool name、request id、trace id、耗时、调用结果。
+
+## 14. 超时和重试建议
+
+| 场景 | 建议 |
+| --- | --- |
+| MCP Server 调用业务 API 超时 | 15 秒 |
+| 高频模板问题 | 通常几十毫秒到数百毫秒 |
+| LLM 长尾问题 | 可能数秒，超过预算返回受控兜底 |
+| Agent 重试 | 仅对网络错误或 `retryable: true` 的错误重试 |
+| 空结果 | 不建议重试，应追问用户补充信息 |
+
+## 15. 最小验收用例
+
+### 15.1 查询线路价格
+
+工具：
+
+```text
+query_route_price
+```
+
+输入：
+
+```json
+{
+  "route_name": "黄小西",
+  "days": 3
+}
+```
+
+预期：
+
+- 返回 `success: true`
+- `data.customer_reply` 有客服话术
+- `data.risk_notes` 提醒价格需二次核实
+
+### 15.2 查询线路详情和酒店
+
+工具：
+
+```text
+query_route_detail
+```
+
+输入：
+
+```json
+{
+  "route_name": "轻奢黄小西纯玩3日游",
+  "scenic_name": "小七孔"
+}
+```
+
+预期：
+
+- 返回线路天数
+- 返回参考价格
+- 返回途经景区
+- 返回小七孔附近酒店
+
+### 15.3 对比线路适配度
+
+工具：
+
+```text
+compare_routes
+```
+
+输入：
+
+```json
+{
+  "route_names": ["黄小西", "小西镇梵"],
+  "compare_focus": "老人小孩、不要太累"
+}
+```
+
+预期：
+
+- 返回更推荐的线路
+- 返回推荐理由
+- 提醒最终需按团期和客户情况核实
+
+### 15.4 长尾无命中问题
+
+工具：
+
+```text
+ask_customer_service
+```
+
+输入：
+
+```json
+{
+  "question": "美酒中秋有什么活动或者套餐？"
+}
+```
+
+预期：
+
+- 返回 `success: true`
+- `data.response_mode` 可能为 `llm_graph_qa_controlled_failure`
+- `customer_reply` 提示补充更具体信息
+
+## 16. 推荐结论
+
+当前项目不需要把现有智能客服接口重写为 MCP。推荐方式是新增一个轻量 MCP Server 适配层，把现有：
+
+```text
+/v1/openapi/knowledge-qa/query
+```
+
+封装为多个明确的 MCP tools。这样 Agent 可以稳定调用百姓惠知识图谱客服能力，同时业务系统仍保留自己的鉴权、超时、图谱查询、LLM 兜底和审计边界。
diff --git a/docs/DEPLOYMENT.md b/docs/DEPLOYMENT.md
index 0938c43..0f2ee2d 100644
--- a/docs/DEPLOYMENT.md
+++ b/docs/DEPLOYMENT.md
@@ -148,6 +148,11 @@ LLM_API_BASE=你的OpenAI兼容模型地址
 LLM_API_KEY=你的模型Key
 ```
 
+部署后也可以在后台 `系统 -> Agent 设置` 中配置：
+
+- `全局 LLM 配置`：填写 OpenAI 兼容模型地址、模型 ID、LLM API Key。
+- `外部图谱问答 API`：位于页面底部，维护给其他系统调用的 `X-KG-API-Key`，设置默认图谱、默认 LLM 策略和“问答环节 LLM 模型”。该模型优先用于外部客服问答，留空则继承全局 LLM。
+
 | 变量 | 说明 |
 | --- | --- |
 | `POSTGRES_USER`、`POSTGRES_PASSWORD`、`POSTGRES_DB` | PostgreSQL 容器账号、密码、库名 |
@@ -173,33 +178,41 @@ LLM_API_KEY=你的模型Key
 给外部系统对接时，只开放这个接口即可：
 
 ```text
-POST http://8.163.40.99:8102/v1/admin/travel/customer-service-query
+POST http://8.163.40.99:8102/v1/openapi/knowledge-qa/query
 ```
 
+`/v1/admin/travel/customer-service-query` 会继续保留为兼容旧调用，新接入的第三方系统建议统一使用 `/v1/openapi/knowledge-qa/query`。
+
 服务器安全组需要放行 TCP `8102`。如果服务器本机 `curl http://127.0.0.1:8102/v1/admin/health` 正常，但外部访问 `http://8.163.40.99:8102` 超时，优先检查云控制台安全组/防火墙入方向规则。
 不要把 `5433`、`6380`、`3002` 暴露到公网；默认 Compose 已把这些数据端口绑定到 `127.0.0.1`。
+生产环境必须在后台 `外部图谱问答 API` 或环境变量 `INGEST_API_KEYS` 中配置至少一个接口 Key；未配置时，对外问答接口会返回 `503`，避免无鉴权开放。
+接口 Key 是给第三方系统调用本接口用的访问凭证；问答环节 LLM 的 API Key 是本系统调用大模型用的凭证，两者不要混用。
 
 请求示例：
 
 ```bash
-curl http://8.163.40.99:8102/v1/admin/travel/customer-service-query \
+curl http://8.163.40.99:8102/v1/openapi/knowledge-qa/query \
   -H 'Content-Type: application/json' \
   -H 'X-KG-API-Key: 你的INGEST_API_KEYS之一' \
   -d '{
+    "request_id": "crm-msg-20260610-0001",
     "question": "黄小西三日游多少钱？",
-    "knowledge_graph": "百姓惠",
+    "graph_name": "baixinghui_travel_agency",
     "session_id": "demo-001",
+    "channel": "online_service",
     "use_llm": true,
     "llm_fusion": true
   }'
 ```
 
-`llm_fusion=true` 需要配置 `LLM_API_BASE` 和 `LLM_API_KEY`。未配置 key 时，接口仍会返回图谱模板答案，但不会调用 LLM 融合。
+默认问答链路需要配置问答环节 LLM；可在后台 `外部图谱问答 API -> 问答环节 LLM 模型` 单独配置，也可以继承全局 LLM。
 
 主要返回字段：
 
 | 字段 | 说明 |
 | --- | --- |
+| `request_id` | 外部请求 ID，原样回传或由服务端生成 |
+| `trace_id` | 服务端链路追踪 ID |
 | `answer` | 给外部系统展示的完整回答 |
 | `customer_reply` | 可以直接发给客户的话术 |
 | `follow_up_questions` | 建议追问 |
diff --git a/docs/MCP_TOOL_EXPOSURE_FIX_AND_VERIFICATION.md b/docs/MCP_TOOL_EXPOSURE_FIX_AND_VERIFICATION.md
new file mode 100644
index 0000000..f0926ca
--- /dev/null
+++ b/docs/MCP_TOOL_EXPOSURE_FIX_AND_VERIFICATION.md
@@ -0,0 +1,282 @@
+# MCP 工具未暴露问题修复与验证说明
+
+## 1. 问题现象
+
+MCP 客户端配置了服务地址：
+
+```text
+http://8.163.40.99:8102/mcp
+```
+
+但页面显示：
+
+```text
+工具 0
+该服务还没有发现工具
+```
+
+直接访问服务也返回：
+
+```text
+404 Not Found
+```
+
+说明当前系统只有普通 HTTP 问答接口，还没有真正实现 MCP Server 的工具发现协议。
+
+## 2. 问题归类
+
+这不是知识图谱数据问题，也不是 LLM 问答引擎问题。
+
+这是：
+
+```text
+MCP Server 适配层未实现 / tools/list 未暴露
+```
+
+已有能力：
+
+```text
+POST /v1/openapi/knowledge-qa/query
+```
+
+缺少能力：
+
+```text
+POST /mcp
+  initialize
+  ping
+  tools/list
+  tools/call
+```
+
+## 3. 修复方式
+
+新增 FastAPI MCP 适配层：
+
+```text
+app/api/mcp_server.py
+```
+
+并在主应用挂载：
+
+```text
+app.include_router(mcp_router)
+```
+
+MCP 层不重写业务逻辑，只把 MCP 工具调用转换成现有百姓惠客服问答接口的内部调用：
+
+```text
+MCP Client
+  -> POST /mcp tools/call
+  -> ask_customer_service 等工具
+  -> 现有百姓惠客服问答 engine
+  -> FalkorDB / 图谱 / LLM
+```
+
+## 4. 已暴露工具
+
+当前 `/mcp` 暴露 5 个只读工具：
+
+| 工具名 | 作用 |
+| --- | --- |
+| `ask_customer_service` | 通用百姓惠智能客服问答 |
+| `query_route_price` | 查询线路参考价格 |
+| `list_travel_routes` | 查询旅行线路清单 |
+| `query_route_detail` | 查询线路天数、景区、酒店、费用等详情 |
+| `compare_routes` | 对比两条线路适配度、景点数量、轻松程度等 |
+
+## 5. MCP 初始化验证
+
+请求：
+
+```bash
+curl -sS http://8.163.40.99:8102/mcp \
+  -H 'Content-Type: application/json' \
+  -H 'Accept: application/json, text/event-stream' \
+  --data '{
+    "jsonrpc": "2.0",
+    "id": 1,
+    "method": "initialize",
+    "params": {
+      "protocolVersion": "2025-06-18",
+      "capabilities": {},
+      "clientInfo": {
+        "name": "manual-check",
+        "version": "1.0.0"
+      }
+    }
+  }'
+```
+
+预期返回：
+
+```json
+{
+  "jsonrpc": "2.0",
+  "id": 1,
+  "result": {
+    "protocolVersion": "2025-06-18",
+    "capabilities": {
+      "tools": {
+        "listChanged": false
+      }
+    },
+    "serverInfo": {
+      "name": "baixinghui-customer-service-mcp",
+      "version": "0.1.0"
+    }
+  }
+}
+```
+
+## 6. 工具发现验证
+
+请求：
+
+```bash
+curl -sS http://8.163.40.99:8102/mcp \
+  -H 'Content-Type: application/json' \
+  -H 'Accept: application/json, text/event-stream' \
+  --data '{
+    "jsonrpc": "2.0",
+    "id": 2,
+    "method": "tools/list"
+  }'
+```
+
+预期结果：
+
+```text
+tools 数量 = 5
+```
+
+并能看到：
+
+```text
+ask_customer_service
+query_route_price
+list_travel_routes
+query_route_detail
+compare_routes
+```
+
+## 7. 工具调用验证
+
+请求：
+
+```bash
+curl -sS http://8.163.40.99:8102/mcp \
+  -H 'Content-Type: application/json' \
+  -H 'Accept: application/json, text/event-stream' \
+  --data '{
+    "jsonrpc": "2.0",
+    "id": 3,
+    "method": "tools/call",
+    "params": {
+      "name": "ask_customer_service",
+      "arguments": {
+        "question": "黄小西三日游多少钱？",
+        "session_id": "mcp-test-session"
+      }
+    }
+  }'
+```
+
+预期返回结构：
+
+```json
+{
+  "jsonrpc": "2.0",
+  "id": 3,
+  "result": {
+    "content": [
+      {
+        "type": "text",
+        "text": "客服可直接回复的话术"
+      }
+    ],
+    "structuredContent": {
+      "customer_reply": "客服可直接回复的话术",
+      "answer": "完整答案",
+      "knowledge": {
+        "plans": [],
+        "evidence": []
+      },
+      "trace_id": "排查链路 ID"
+    },
+    "isError": false
+  }
+}
+```
+
+## 8. 客户端侧证明
+
+修复后，MCP 客户端刷新服务配置，应从：
+
+```text
+工具 0
+该服务还没有发现工具
+```
+
+变为：
+
+```text
+工具 5
+```
+
+如果客户端仍显示 0，按顺序检查：
+
+1. 服务地址是否为 `http://8.163.40.99:8102/mcp`。
+2. 服务是否已经重新构建并重启。
+3. 客户端是否点击了“刷新”或重新检查连接。
+4. 如果启用了鉴权，客户端是否带了正确的 `Authorization: Bearer <token>`。
+
+## 9. 鉴权说明
+
+当前 MCP 适配层支持可选鉴权。
+
+未设置环境变量时：
+
+```text
+BXH_MCP_TOKEN 为空
+```
+
+则 `/mcp` 不强制鉴权，方便内测。
+
+如果设置：
+
+```bash
+export BXH_MCP_TOKEN="<your-token>"
+```
+
+客户端需要传：
+
+```http
+Authorization: Bearer <your-token>
+```
+
+或：
+
+```http
+X-MCP-API-Key: <your-token>
+```
+
+## 10. 结论
+
+这次修复解决的是 MCP 协议层工具暴露问题。
+
+修复前：
+
+```text
+/mcp 404
+tools/list 无法执行
+客户端工具数 0
+```
+
+修复后：
+
+```text
+/mcp 可响应 JSON-RPC
+tools/list 返回 5 个工具
+tools/call 可调用百姓惠客服问答 engine
+```
diff --git a/docs/markitdown-evaluation.md b/docs/markitdown-evaluation.md
new file mode 100644
index 0000000..8a8daee
--- /dev/null
+++ b/docs/markitdown-evaluation.md
@@ -0,0 +1,82 @@
+# MarkItDown 转换评测方法
+
+本项目已经接入 Microsoft MarkItDown，但上线判断不能只看“能不能转”。推荐用一组真实业务样本文档做可重复评测。
+
+## 评测维度
+
+1. 转换成功率：不同格式是否稳定返回 Markdown。
+2. 信息保真度：关键字段、价格、日期、地点、人名、产品 ID 是否还在。
+3. 结构保留度：标题、表格、列表、链接是否保留为 Markdown 结构。
+4. 噪声控制：乱码、超长行、残留 HTML、空文本、重复内容是否明显。
+5. 下游效果：把转换后的 Markdown 送入知识抽取后，实体、关系、证据覆盖是否提升。
+
+## 准备样本
+
+把测试文件放到：
+
+```bash
+data/markitdown_eval/input/
+```
+
+建议每类至少 5 份：
+
+- PDF：普通 PDF、扫描 PDF、复杂表格 PDF
+- Word：合同、行程单、产品说明
+- Excel：价格表、团期表、资源表
+- PPT：介绍资料、图文页
+- HTML/Markdown/CSV/JSON/XML
+- 图片或截图类资料
+
+## Manifest 示例
+
+创建 `data/markitdown_eval/manifest.json`：
+
+```json
+{
+  "cases": [
+    {
+      "case_id": "travel_product_docx_001",
+      "file": "travel_product.docx",
+      "must_terms": ["产品ID", "成人价", "儿童价", "费用包含", "退费政策"],
+      "forbidden_terms": ["�"],
+      "expected_headings_min": 2,
+      "expected_tables_min": 1,
+      "expected_lists_min": 3,
+      "expected_links_min": 0,
+      "min_chars": 800,
+      "notes": "旅行社产品说明 Word"
+    }
+  ]
+}
+```
+
+## 运行评测
+
+```bash
+python3 scripts/evaluate_markitdown_conversion.py \
+  --input-dir data/markitdown_eval/input \
+  --manifest data/markitdown_eval/manifest.json \
+  --output-dir outputs/markitdown_eval \
+  --fail-under 0.70
+```
+
+输出：
+
+- `outputs/markitdown_eval/converted/*.markitdown.md`
+- `outputs/markitdown_eval/markitdown_eval_report.json`
+- `outputs/markitdown_eval/markitdown_eval_report.md`
+
+## 判定建议
+
+- 平均分 `>= 0.85`：可作为默认转换方案，但仍抽检复杂文件。
+- `0.70 - 0.85`：可用，但要看缺失字段和结构损失，必要时加 OCR 或人工校正。
+- `< 0.70`：不建议直接进入自动知识抽取，应启用替代方案。
+
+## 进一步增强
+
+当前接入是 MarkItDown 本地转换。若样本中大量是扫描 PDF、图片文字、复杂表格、音视频，建议再评估：
+
+- MarkItDown OCR plugin
+- Azure Document Intelligence
+- Azure Content Understanding
+- 针对旅行社/城市知识图谱的自定义后处理规则
diff --git a/docs/接口文档.md b/docs/接口文档.md
new file mode 100644
index 0000000..cad0a72
--- /dev/null
+++ b/docs/接口文档.md
@@ -0,0 +1,212 @@
+# 智能客服问答接口使用说明
+
+本文档仅说明第三方系统如何调用百姓惠智能客服问答接口。
+
+## 1. 接口地址
+
+推荐接口：
+
+```text
+POST http://8.163.40.99:8102/v1/openapi/knowledge-qa/query
+```
+
+兼容旧接口：
+
+```text
+POST http://8.163.40.99:8102/v1/admin/travel/customer-service-query
+```
+
+
+## 2. 请求头
+
+```http
+Content-Type: application/json
+X-KG-API-Key: <API_KEY>
+```
+
+也兼容：
+
+```http
+X-API-Key: <API_KEY>
+Authorization: Bearer <API_KEY>
+```
+
+`<API_KEY>` 由系统管理员提供，不要写在前端代码里。
+
+## 3. 请求参数
+
+| 字段 | 必填 | 示例 | 说明 |
+| --- | --- | --- | --- |
+| `question` | 是 | `黄小西三日游多少钱？` | 用户自然语言问题 |
+| `request_id` | 否 | `crm-msg-0001` | 第三方请求 ID |
+| `session_id` | 否 | `sess-a01` | 会话 ID |
+| `channel` | 否 | `crm` | 来源渠道 |
+| `customer_id` | 否 | `u_10086` | 第三方客户 ID |
+| `graph_name` | 否 | `baixinghui_travel_agency` | 默认可不传 |
+
+## 4. 最小请求示例
+
+```bash
+curl -X POST 'http://8.163.40.99:8102/v1/openapi/knowledge-qa/query' \
+  -H 'Content-Type: application/json' \
+  -H 'X-KG-API-Key: <API_KEY>' \
+  -d '{
+    "question": "黄小西三日游多少钱？"
+  }'
+```
+
+## 5. 完整请求示例
+
+```bash
+curl -X POST 'http://8.163.40.99:8102/v1/openapi/knowledge-qa/query' \
+  -H 'Content-Type: application/json' \
+  -H 'X-KG-API-Key: <API_KEY>' \
+  -d '{
+    "request_id": "crm-msg-20260610-0001",
+    "session_id": "sess-20260610-a01",
+    "channel": "crm",
+    "customer_id": "u_10086",
+    "graph_name": "baixinghui_travel_agency",
+    "question": "轻奢黄小西纯玩3日游多少钱，可以玩几天，期间可以去哪些景区，小七孔附近可以入住什么酒店？"
+  }'
+```
+
+## 6. JavaScript 调用示例
+
+```javascript
+const response = await fetch("http://8.163.40.99:8102/v1/openapi/knowledge-qa/query", {
+  method: "POST",
+  headers: {
+    "Content-Type": "application/json",
+    "X-KG-API-Key": "<API_KEY>"
+  },
+  body: JSON.stringify({
+    request_id: "crm-msg-20260610-0001",
+    session_id: "sess-20260610-a01",
+    channel: "crm",
+    question: "黄小西三日游多少钱？",
+    graph_name: "baixinghui_travel_agency"
+  })
+});
+
+const data = await response.json();
+console.log(data.customer_reply);
+```
+
+## 7. Python 调用示例
+
+```python
+import requests
+
+url = "http://8.163.40.99:8102/v1/openapi/knowledge-qa/query"
+headers = {
+    "Content-Type": "application/json",
+    "X-KG-API-Key": "<API_KEY>",
+}
+payload = {
+    "request_id": "crm-msg-20260610-0001",
+    "session_id": "sess-20260610-a01",
+    "channel": "crm",
+    "question": "黄小西三日游多少钱？",
+    "graph_name": "baixinghui_travel_agency",
+}
+
+resp = requests.post(url, headers=headers, json=payload, timeout=15)
+data = resp.json()
+print(data["customer_reply"])
+```
+
+## 8. 返回示例
+
+```json
+{
+  "status": "ok",
+  "service": "baixinghui_customer_service",
+  "request_id": "crm-msg-20260610-0001",
+  "trace_id": "trc_xxx",
+  "session_id": "sess-20260610-a01",
+  "channel": "crm",
+  "question": "黄小西三日游多少钱？",
+  "graph_name": "baixinghui_travel_agency",
+  "answer": "完整回答，适合后台查看。",
+  "customer_reply": "客服可直接发送给客户的简短话术。",
+  "confidence": 0.88,
+  "follow_up_questions": [
+    "请提供出发日期和人数。"
+  ],
+  "risk_notes": [
+    "价格、余位、房型和景区政策需按具体团期二次核实。"
+  ],
+  "knowledge": {
+    "plans": [],
+    "evidence": []
+  },
+  "routing": {
+    "response_mode": "fast_graph_template",
+    "method": "fast_price_quote_graph_template_v1"
+  },
+  "trace": {
+    "latency_ms": 35,
+    "stage_timings_ms": {
+      "graph_query": 20,
+      "answer_synthesis": 0
+    }
+  }
+}
+```
+
+## 9. 第三方主要读取字段
+
+| 字段 | 说明 |
+| --- | --- |
+| `customer_reply` | 给客户展示或发送的客服话术 |
+| `answer` | 完整答案，适合后台查看 |
+| `confidence` | 置信度 |
+| `follow_up_questions` | 建议继续追问的问题 |
+| `risk_notes` | 需要人工核实的提示 |
+| `knowledge.evidence` | 图谱证据 |
+| `routing.response_mode` | 当前问答链路 |
+| `trace_id` | 排查问题时提供给系统维护人员 |
+
+## 10. 常见测试问题
+
+```json
+{
+  "question": "黄小西三日游多少钱？"
+}
+```
+
+```json
+{
+  "question": "旅行车线路有哪些？"
+}
+```
+
+```json
+{
+  "question": "轻奢黄小西纯玩3日游多少钱，可以玩几天，期间可以去哪些景区，小七孔附近可以入住什么酒店？"
+}
+```
+
+```json
+{
+  "question": "黄小西和小西镇梵哪个更适合老人小孩、不要太累，为什么？"
+}
+```
+
+## 11. 错误码
+
+| HTTP 状态 | 说明 |
+| --- | --- |
+| `200` | 请求成功 |
+| `400` | 缺少 `question` 或请求格式错误 |
+| `401` | API Key 缺失或无效 |
+| `503` | 服务端未配置 API Key |
+| `500/502` | 服务异常，记录 `request_id` 联系维护人员 |
+
+## 12. 接入建议
+
+- 第三方系统后端调用接口，不要在前端暴露 API Key。
+- 给客户优先展示 `customer_reply`。
+- 如果 `risk_notes` 非空，客服应按提示二次核实。
+- 建议 HTTP 超时设置为 `15` 秒。
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diff --git a/requirements.txt b/requirements.txt
index 66de240..b452794 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -23,6 +23,11 @@ h3==4.4.2
 # HTTP 客户端 (LLM 调用 / 维基 API)
 httpx==0.28.1
 requests==2.32.5
+python-multipart==0.0.28
+markitdown[all]==0.1.6
+pymupdf4llm==1.27.2.3  # 结构化 PDF→Markdown（版式/表格感知，替代 markitdown 纯文本抽取）
+python-docx==1.2.0     # DOCX→Markdown 保留表格结构
+olefile==0.47          # 损坏/textutil 读不了的老 .doc 直接捞 WordDocument 流正文
 
 # 鉴权
 bcrypt==4.1.3
@@ -31,3 +36,7 @@ python-jose==3.3.0
 # 浏览器采集 (web_agent / xhs_agent / douyin_agent 隐身抓取)
 # 装完需再跑: python3 -m playwright install chromium
 playwright==1.59.0
+
+# 阿里云 OCR (ocr-api.cn-hangzhou.aliyuncs.com 2021-07-07)
+# 提供 RecognizePassport 等证件识别能力；客户端会自动拉取 tea-openapi / tea-util
+alibabacloud_ocr_api20210707==3.1.2
diff --git a/schema搭建/yunyou_libo/yunyou_libo_schema.current.dsl.md b/schema搭建/yunyou_libo/yunyou_libo_schema.current.dsl.md
new file mode 100644
index 0000000..8f45163
--- /dev/null
+++ b/schema搭建/yunyou_libo/yunyou_libo_schema.current.dsl.md
@@ -0,0 +1,261 @@
+namespace yunyou_libo
+version 1
+
+// 云游荔波旅游 POI 融合知识图谱。
+// 高德 POI 是空间锚点；大众点评和携程仅在同实体确认后写入详情字段。
+
+entity Place // 可定位的基础地点
+  primary_key element_id
+  property element_id: Text
+  property place_id: Text
+  property name: Text
+  property place_type: Text
+  property type_label: Text
+  property business_subcategory: Text
+  property amap_type: Text
+  property typecode: Text
+  property address: Text
+  property district: Text
+  property adcode: Text
+  property lng: Number
+  property lat: Number
+  property h3_r9: Text
+  property source: Text
+
+entity FoodPlace // 美食店铺：高德锚点 + 大众点评融合详情
+  primary_key element_id
+  property element_id: Text
+  property gaode_poi_id: Text
+  property name: Text
+  property business_subcategory: Text
+  property amap_category_l1: Text
+  property amap_category_l2: Text
+  property amap_category_l3: Text
+  property amap_type: Text
+  property typecode: Text
+  property address: Text
+  property business_area: Text
+  property tel: Text
+  property lng: Number
+  property lat: Number
+  property amap_rating: Number
+  property amap_cost_text: Text
+  property open_time: Text
+  property cover_image_url: Text
+  property photo_urls: Text
+  property amap_url: Text
+  property data_quality: Text
+  property scan_hit_types: Text
+  property scan_hit_count: Integer
+  property collection_rounds: Text
+  property food_fusion_status: Text
+  property food_match_confidence: Text
+  property food_match_rule: Text
+  property food_match_score: Number
+  property food_name_exact_match: Boolean
+  property food_name_similarity: Number
+  property food_address_similarity: Number
+  property food_coordinate_distance_m: Number
+  property dianping_source_poi_id: Text
+  property dianping_shop_id: Text
+  property dianping_shop_uuid: Text
+  property dianping_name: Text
+  property dianping_address: Text
+  property dianping_lng: Number
+  property dianping_lat: Number
+  property dianping_url: Text
+  property dianping_rating: Number
+  property dianping_review_count: Integer
+  property dianping_avg_price: Number
+  property dianping_area: Text
+  property dianping_category: Text
+  property dianping_score_details: Text
+  property dianping_ranking: Text
+  property dianping_business_status: Text
+  property dianping_business_hours: Text
+  property dianping_tags: Text
+  property dianping_transportation: Text
+  property dianping_image_count: Integer
+  property dianping_shop_image: Text
+  property dianping_review_tags: Text
+  property recommended_dish_count: Integer
+  property recommended_dish_names: Text
+  property recommended_dish_max_recommendations: Integer
+  property recommended_dish_image_samples: Text
+  property group_buy_count: Integer
+  property group_buy_min_price: Number
+  property group_buy_max_price: Number
+  property group_buy_titles: Text
+  property group_buy_items: Text
+  property group_buy_items_json: Text // 结构化团购套餐：图片、价格、原价、折扣、服务条款
+  property review_sample_count: Integer
+  property review_sample_avg_stars: Number
+  property review_sample_summary: Text
+  property food_review_items_json: Text // 真实大众点评评论结构化数组
+  property food_review_tags_json: Text // 点评标签及影响评论数量
+  property review_image_samples: Text
+  property menu_image_count: Integer
+  property menu_image_samples: Text
+  property candidate_dianping_shop_id: Text
+  property candidate_dianping_name: Text
+  property food_candidate_name_similarity: Number
+  property food_candidate_address_similarity: Number
+  property food_candidate_coordinate_distance_m: Number
+  property fusion_status: Text
+  property data_version: Text
+  property enrichment_source: Text
+  property enrichment_updated_at: DateTime
+
+entity Hotel // 酒店住宿：高德锚点 + 携程融合详情
+  primary_key element_id
+  property element_id: Text
+  property gaode_poi_id: Text
+  property name: Text
+  property business_subcategory: Text
+  property amap_category_l1: Text
+  property amap_category_l2: Text
+  property amap_category_l3: Text
+  property amap_type: Text
+  property typecode: Text
+  property address: Text
+  property business_area: Text
+  property tel: Text
+  property lng: Number
+  property lat: Number
+  property cover_image_url: Text
+  property photo_urls: Text
+  property amap_url: Text
+  property data_quality: Text
+  property collection_rounds: Text
+  property hotel_fusion_status: Text
+  property hotel_match_confidence: Text
+  property hotel_match_rule: Text
+  property hotel_name_similarity: Number
+  property hotel_address_similarity: Number
+  property hotel_phone_exact_match: Boolean
+  property ctrip_hotel_id: Text
+  property ctrip_name_cn: Text
+  property ctrip_name_en: Text
+  property ctrip_address: Text
+  property ctrip_phone: Text
+  property ctrip_star_level: Text
+  property ctrip_diamond_level: Text
+  property ctrip_opened_year: Text
+  property ctrip_room_count: Integer
+  property ctrip_hotel_type: Text
+  property ctrip_ranking: Text
+  property ctrip_rating: Number
+  property ctrip_rating_description: Text
+  property ctrip_review_count: Integer
+  property ctrip_image_count: Integer
+  property ctrip_transportation: Text
+  property ctrip_tags: Text
+  property ctrip_popular_facilities: Text
+  property ctrip_score_details: Text
+  property ctrip_cleanliness_score: Number
+  property ctrip_facilities_score: Number
+  property ctrip_environment_score: Number
+  property ctrip_service_score: Number
+  property ctrip_description: Text
+  property ctrip_url: Text
+  property room_type_count: Integer
+  property room_type_names: Text
+  property room_min_price: Number
+  property room_max_price: Number
+  property offer_count: Integer
+  property offer_min_price: Number
+  property offer_max_price: Number
+  property room_items_json: Text
+  property facility_service_count: Integer
+  property facility_category_count: Integer
+  property facility_category_stats: Text
+  property facility_summary: Text
+  property facility_category_items_json: Text
+  property policy_count: Integer
+  property policy_category_stats: Text
+  property policy_summary: Text
+  property guest_review_sample_count: Integer
+  property guest_review_sample_avg_score: Number
+  property latest_review_at: Text
+  property review_travel_types: Text
+  property review_items_json: Text
+  property hotel_image_record_count: Integer
+  property hotel_image_type_stats: Text
+  property hotel_image_samples: Text
+  property nearby_place_count: Integer
+  property nearby_place_type_stats: Text
+  property nearby_place_summary: Text
+  property nearby_category_items_json: Text
+  property candidate_ctrip_hotel_id: Text
+  property candidate_ctrip_name: Text
+  property hotel_candidate_name_similarity: Number
+  property hotel_candidate_address_similarity: Number
+  property fusion_status: Text
+  property data_version: Text
+  property enrichment_source: Text
+  property enrichment_updated_at: DateTime
+
+entity ScenicSpot // 审核保留的旅游景点及景区子景点
+  primary_key element_id
+  property element_id: Text
+  property name: Text
+  property scenic_type: Text
+  property scenic_level: Text
+  property parent_scenic: Text
+  property visitor_value: Text
+  property audit_result: Text
+  property lng: Number
+  property lat: Number
+
+entity ScenicArea // 景区主体
+  primary_key element_id
+  property element_id: Text
+  property name: Text
+  property scenic_grade: Text
+
+entity TransitFacility // 交通设施
+  primary_key element_id
+  property element_id: Text
+  property name: Text
+  property address: Text
+  property lng: Number
+  property lat: Number
+
+entity BusStop // 公交站点
+  primary_key element_id
+  property element_id: Text
+  property name: Text
+  property lng: Number
+  property lat: Number
+
+entity BusLine // 公交线路
+  primary_key element_id
+  property element_id: Text
+  property name: Text
+  property color: Text
+
+entity BusRoute // 公交方向与折线
+  primary_key element_id
+  property element_id: Text
+  property name: Text
+  property direction: Text
+  property polyline: Text
+
+entity Area // 行政区域
+  primary_key element_id
+  property element_id: Text
+  property name: Text
+  property level: Text
+  property adcode: Text
+
+entity GeoCell // H3空间网格
+  primary_key h3_id
+  property h3_id: Text
+  property resolution: Integer
+
+relation LOCATED_IN: Place -> Area
+relation IN_H3_R9: Place -> GeoCell
+relation PART_OF_SCENIC_AREA: ScenicSpot -> ScenicArea
+relation PART_OF: Area -> Area
+relation STOPS_AT: BusRoute -> BusStop
+relation NEXT_STOP: BusStop -> BusStop
diff --git a/scripts/amap_spatial_collect.py b/scripts/amap_spatial_collect.py
index 1eb773e..c33cfa5 100644
--- a/scripts/amap_spatial_collect.py
+++ b/scripts/amap_spatial_collect.py
@@ -605,6 +605,7 @@ def upsert_graph_places(graph_name: str, rows: list[dict[str, Any]]) -> None:
             "MERGE (dist)-[:PART_OF]->(city) "
             "MERGE (city)-[:PART_OF]->(prov) "
             "MERGE (c9:GeoCell {h3_id:$h3_r9}) SET c9.resolution=9 "
+            "MERGE (c9)-[:LOCATED_IN]->(dist) "
             "MERGE (p)-[:IN_H3_R9]->(c9)"
         )
         params = {
diff --git a/scripts/douyin_fetch_data.py b/scripts/douyin_fetch_data.py
new file mode 100644
index 0000000..f2b424e
--- /dev/null
+++ b/scripts/douyin_fetch_data.py
@@ -0,0 +1,294 @@
+#!/usr/bin/env python3
+"""单独拉取抖音数据的运行入口。
+
+这个文件不重写采集逻辑，而是复用系统原版:
+    app/agents/douyin_agent.py
+
+常用命令:
+    python3 scripts/douyin_login.py
+    python3 scripts/douyin_fetch_data.py --name "某某酒店" --city "贵阳"
+    python3 scripts/douyin_fetch_data.py --input hotels.txt --city "贵阳" --save-evidence
+
+输出:
+    默认写到 data/douyin_probe/fetch_<时间>.json
+"""
+from __future__ import annotations
+
+import argparse
+import asyncio
+import csv
+import json
+import os
+import sys
+from datetime import datetime
+from pathlib import Path
+from typing import Any
+
+ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(ROOT))
+
+from app.agents.douyin_agent import (  # noqa: E402
+    _collect,
+    _parse_dy_comments,
+    _parse_dy_notes,
+)
+
+
+DEFAULT_OUT_DIR = ROOT / "data" / "douyin_probe"
+
+
+def _ts() -> str:
+    return datetime.now().strftime("%Y%m%d_%H%M%S")
+
+
+def _read_names(path: str | None) -> list[str]:
+    if not path:
+        return []
+    names: list[str] = []
+    for line in Path(path).read_text(encoding="utf-8").splitlines():
+        value = line.strip()
+        if value and not value.startswith("#"):
+            names.append(value)
+    return names
+
+
+def _dedupe_records(records: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    deduped: list[dict[str, Any]] = []
+    seen: set[tuple[str, str, str]] = set()
+    for record in records:
+        key = (
+            str(record.get("platform") or ""),
+            str(record.get("kind") or ""),
+            str(record.get("source_id") or record.get("url") or ""),
+        )
+        if key in seen:
+            continue
+        seen.add(key)
+        deduped.append(record)
+    return deduped
+
+
+def _record_for_csv(record: dict[str, Any]) -> dict[str, Any]:
+    fields = [
+        "platform",
+        "kind",
+        "source_id",
+        "url",
+        "entity_name",
+        "place_natural_key",
+        "keyword",
+        "title",
+        "content",
+        "author",
+        "author_id",
+        "likes",
+        "comments",
+        "collects",
+        "shares",
+        "publish_time",
+        "location",
+    ]
+    return {field: record.get(field, "") for field in fields}
+
+
+def _write_json(path: Path, payload: dict[str, Any]) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    path.write_text(json.dumps(payload, ensure_ascii=False, indent=2), encoding="utf-8")
+
+
+def _write_jsonl(path: Path, records: list[dict[str, Any]]) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    with path.open("w", encoding="utf-8") as file:
+        for record in records:
+            file.write(json.dumps(record, ensure_ascii=False) + "\n")
+
+
+def _write_csv(path: Path, records: list[dict[str, Any]]) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    rows = [_record_for_csv(record) for record in records]
+    fieldnames = list(rows[0].keys()) if rows else list(_record_for_csv({}).keys())
+    with path.open("w", encoding="utf-8-sig", newline="") as file:
+        writer = csv.DictWriter(file, fieldnames=fieldnames)
+        writer.writeheader()
+        writer.writerows(rows)
+
+
+def _build_keyword(name: str, city: str, suffix: str, keyword: str | None) -> str:
+    if keyword:
+        return keyword.strip()
+    parts = [city.strip(), name.strip(), suffix.strip()]
+    return " ".join(part for part in parts if part)
+
+
+def _make_tab_picker(preferred_tab: str):
+    def pick(labels: list[str]) -> str | None:
+        if not labels:
+            return None
+        if preferred_tab and preferred_tab in labels:
+            return preferred_tab
+        if "综合" in labels:
+            return "综合"
+        return labels[0]
+
+    return pick
+
+
+def fetch_one(
+    *,
+    name: str,
+    city: str,
+    suffix: str,
+    keyword: str | None,
+    tab: str,
+    deep: bool,
+    place_key: str | None,
+) -> dict[str, Any]:
+    query = _build_keyword(name, city, suffix, keyword)
+    print(f"[douyin] 开始采集: name={name} keyword={query}")
+    result = _collect(query, _make_tab_picker(tab), deep=deep)
+
+    if result.get("logged_in") is False:
+        return {
+            "ok": False,
+            "need_login": True,
+            "name": name,
+            "keyword": query,
+            "summary": "抖音未登录。请先运行 python3 scripts/douyin_login.py 完成一次登录。",
+            "notes": [],
+            "comments": [],
+            "records": [],
+            "raw_api_count": 0,
+            "api_url_count": result.get("api_url_count", 0),
+            "tabs": result.get("tabs", []),
+        }
+
+    if result.get("error"):
+        return {
+            "ok": False,
+            "need_login": False,
+            "name": name,
+            "keyword": query,
+            "summary": f"采集异常: {result.get('error')}",
+            "notes": [],
+            "comments": [],
+            "records": [],
+            "raw_api_count": 0,
+            "api_url_count": result.get("api_url_count", 0),
+            "tabs": result.get("tabs", []),
+        }
+
+    raw_api = result.get("raw_api") or []
+    notes = _parse_dy_notes(raw_api, name, query)
+    comments = _parse_dy_comments(raw_api, name, query)
+    records = _dedupe_records(notes + comments)
+    for record in records:
+        if place_key:
+            record["place_natural_key"] = place_key
+
+    return {
+        "ok": True,
+        "need_login": False,
+        "name": name,
+        "keyword": query,
+        "summary": f"视频 {len(notes)} 条，评论 {len(comments)} 条，去重后 {len(records)} 条。",
+        "notes": notes,
+        "comments": comments,
+        "records": records,
+        "raw_api_count": len(raw_api),
+        "api_url_count": result.get("api_url_count", 0),
+        "tabs": result.get("tabs", []),
+    }
+
+
+async def _save_evidence(records: list[dict[str, Any]]) -> int:
+    if not records:
+        return 0
+    from app.db import close_pool, init_pool, sa_save_evidence
+
+    await init_pool()
+    try:
+        return await sa_save_evidence(records)
+    finally:
+        await close_pool()
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description="按酒店/关键词单独获取抖音视频与评论数据")
+    parser.add_argument("--name", help="单个酒店/地点名称")
+    parser.add_argument("--input", help="批量名称文件，每行一个酒店/地点名称")
+    parser.add_argument("--city", default="贵阳", help="城市前缀，默认: 贵阳")
+    parser.add_argument("--suffix", default="", help="附加搜索词，例如: 酒店 入住 评价")
+    parser.add_argument("--keyword", help="完整搜索关键词；传入后会忽略 --city/--name/--suffix 拼接")
+    parser.add_argument("--tab", default="综合", help="优先选择的抖音搜索 tab，默认: 综合")
+    parser.add_argument("--place-key", help="写入记录的 place_natural_key，单名称时可用")
+    parser.add_argument("--no-deep", action="store_true", help="只采搜索页，不进入视频详情深采评论")
+    parser.add_argument("--save-evidence", action="store_true", help="把 records 写入系统 Evidence 表")
+    parser.add_argument("--out", help="JSON 输出路径")
+    parser.add_argument("--jsonl-out", help="JSONL records 输出路径")
+    parser.add_argument("--csv-out", help="CSV records 输出路径")
+    return parser.parse_args()
+
+
+def main() -> None:
+    args = parse_args()
+    names = []
+    if args.name:
+        names.append(args.name.strip())
+    names.extend(_read_names(args.input))
+    names = [name for name in names if name]
+
+    if args.keyword and not names:
+        names = [args.keyword.strip()]
+    if not names:
+        raise SystemExit("请提供 --name、--input 或 --keyword")
+    if args.keyword and len(names) > 1:
+        raise SystemExit("--keyword 是完整单次搜索词，不能和多名称 --input 同时使用")
+    if args.place_key and len(names) > 1:
+        raise SystemExit("--place-key 只适合单个 --name 使用，批量请不要传")
+
+    all_results: list[dict[str, Any]] = []
+    all_records: list[dict[str, Any]] = []
+    for name in names:
+        result = fetch_one(
+            name=name,
+            city=args.city,
+            suffix=args.suffix,
+            keyword=args.keyword,
+            tab=args.tab,
+            deep=not args.no_deep,
+            place_key=args.place_key,
+        )
+        print(f"[douyin] {result['summary']}")
+        all_results.append(result)
+        all_records.extend(result.get("records") or [])
+
+    all_records = _dedupe_records(all_records)
+    saved = 0
+    if args.save_evidence:
+        saved = asyncio.run(_save_evidence(all_records))
+        print(f"[douyin] 已写入 Evidence: {saved}")
+
+    out_dir = DEFAULT_OUT_DIR
+    out_path = Path(args.out) if args.out else out_dir / f"fetch_{_ts()}.json"
+    jsonl_path = Path(args.jsonl_out) if args.jsonl_out else out_path.with_suffix(".jsonl")
+    csv_path = Path(args.csv_out) if args.csv_out else out_path.with_suffix(".csv")
+
+    payload = {
+        "ok": all(result.get("ok") for result in all_results),
+        "need_login": any(result.get("need_login") for result in all_results),
+        "saved_evidence": saved,
+        "total_records": len(all_records),
+        "results": all_results,
+    }
+    _write_json(out_path, payload)
+    _write_jsonl(jsonl_path, all_records)
+    _write_csv(csv_path, all_records)
+
+    print(f"[douyin] JSON:  {out_path}")
+    print(f"[douyin] JSONL: {jsonl_path}")
+    print(f"[douyin] CSV:   {csv_path}")
+
+
+if __name__ == "__main__":
+    os.chdir(ROOT)
+    main()
diff --git a/scripts/enrich_yunyou_libo_food_deals_reviews.py b/scripts/enrich_yunyou_libo_food_deals_reviews.py
new file mode 100644
index 0000000..0cd6d3a
--- /dev/null
+++ b/scripts/enrich_yunyou_libo_food_deals_reviews.py
@@ -0,0 +1,276 @@
+#!/usr/bin/env python3
+"""Attach structured Dianping deal, tag, and review payloads to Libo food nodes."""
+from __future__ import annotations
+
+import argparse
+import json
+import re
+import sys
+from collections import Counter
+from pathlib import Path
+from typing import Any
+
+from falkordb import FalkorDB
+
+ROOT_DIR = Path(__file__).resolve().parents[1]
+if str(ROOT_DIR) not in sys.path:
+    sys.path.insert(0, str(ROOT_DIR))
+
+from app.config import settings
+
+
+DEFAULT_SOURCE_DIR = Path(
+    "/Users/xuexue/Desktop/荔波小七孔源数据/大众点评/raw"
+)
+
+REVIEW_THEMES: tuple[tuple[str, tuple[str, ...]], ...] = (
+    ("口味评价", ("味道", "口味", "好吃", "鲜香", "酸汤", "烤鱼")),
+    ("服务体验", ("服务", "老板", "店员", "热情", "招待")),
+    ("环境体验", ("环境", "装修", "干净", "卫生", "民族风")),
+    ("菜品分量", ("分量", "份量", "量大", "量足")),
+    ("性价比", ("性价比", "价格", "价位", "实惠")),
+    ("停车便利", ("停车", "停车场")),
+    ("排队情况", ("排队", "等位")),
+    ("游客推荐", ("推荐", "必吃", "值得", "不踩雷")),
+)
+
+
+def clean(value: Any) -> str:
+    return "" if value is None else str(value).strip()
+
+
+def number(value: Any) -> float | int | None:
+    text = clean(value).replace("￥", "").replace("¥", "").replace(",", "")
+    if not text:
+        return None
+    try:
+        result = float(text)
+    except ValueError:
+        return None
+    return int(result) if result.is_integer() else result
+
+
+def compact(record: dict[str, Any]) -> dict[str, Any]:
+    return {
+        key: value
+        for key, value in record.items()
+        if value not in (None, "", [], {})
+    }
+
+
+def split_values(value: Any) -> list[str]:
+    return [
+        item.strip()
+        for item in re.split(r"\s*[|｜、,，]\s*", clean(value))
+        if item.strip()
+    ]
+
+
+def normalize_title(value: Any) -> str:
+    return re.sub(r"[\s【】\[\]（）()·｜|/\\\-—_]", "", clean(value))
+
+
+def load_raw_records(source_dir: Path) -> dict[str, dict[str, Any]]:
+    records: dict[str, dict[str, Any]] = {}
+    for path in sorted(source_dir.glob("*.json")):
+        try:
+            payload = json.loads(path.read_text(encoding="utf-8"))
+        except (OSError, json.JSONDecodeError):
+            continue
+        if not isinstance(payload, dict):
+            continue
+        identifiers = {
+            path.stem.removeprefix("dianping_"),
+            clean(payload.get("POI_ID")),
+            clean(payload.get("店铺ID")),
+            clean(payload.get("店铺UUID")),
+        }
+        for identifier in identifiers:
+            if identifier:
+                records[identifier] = payload
+    return records
+
+
+def deal_image(
+    title: str,
+    sequence: int,
+    recommended_dishes: list[dict[str, Any]],
+    shop_image: str,
+) -> str:
+    normalized_title = normalize_title(title)
+    usable_images = []
+    for dish in recommended_dishes:
+        image_url = clean(dish.get("image"))
+        if not image_url:
+            continue
+        usable_images.append(image_url)
+        dish_name = normalize_title(dish.get("name"))
+        if dish_name and dish_name in normalized_title:
+            return image_url
+    if usable_images:
+        return usable_images[(sequence - 1) % len(usable_images)]
+    return shop_image
+
+
+def build_deals(payload: dict[str, Any]) -> list[dict[str, Any]]:
+    raw_deals = payload.get("团购信息") or []
+    if not isinstance(raw_deals, list):
+        return []
+    recommended_dishes = payload.get("推荐菜详情") or []
+    if not isinstance(recommended_dishes, list):
+        recommended_dishes = []
+    shop_image = clean(payload.get("店铺图片"))
+    deals: list[dict[str, Any]] = []
+    for sequence, item in enumerate(raw_deals, 1):
+        if not isinstance(item, dict):
+            continue
+        title = clean(item.get("title"))
+        if not title:
+            continue
+        terms = split_values(item.get("tags"))
+        if not terms:
+            terms = [
+                value
+                for value in re.split(r"\s+", clean(item.get("dishes")))
+                if value
+            ]
+        deals.append(compact({
+            "deal_id": f"{clean(payload.get('店铺ID')) or clean(payload.get('POI_ID'))}:{sequence}",
+            "title": title,
+            "price": number(item.get("price")),
+            "original_price": number(item.get("original_price")),
+            "discount": clean(item.get("discount")),
+            "terms": terms,
+            "image_url": deal_image(
+                title,
+                sequence,
+                [dish for dish in recommended_dishes if isinstance(dish, dict)],
+                shop_image,
+            ),
+        }))
+    return deals
+
+
+def build_reviews(payload: dict[str, Any]) -> list[dict[str, Any]]:
+    raw_reviews = payload.get("评论数据") or []
+    if not isinstance(raw_reviews, list):
+        return []
+    source_id = (
+        clean(payload.get("店铺ID"))
+        or clean(payload.get("POI_ID"))
+        or "dianping"
+    )
+    reviews: list[dict[str, Any]] = []
+    for sequence, item in enumerate(raw_reviews, 1):
+        if not isinstance(item, dict):
+            continue
+        content = clean(item.get("评论内容"))
+        if not content:
+            continue
+        reviews.append(compact({
+            "review_id": f"{source_id}:{sequence}",
+            "nickname": clean(item.get("用户名")) or "匿名用户",
+            "review_at": clean(item.get("评论时间")),
+            "rating_label": clean(item.get("评分")),
+            "stars": number(item.get("星级")),
+            "content": content,
+            "image_urls": split_values(item.get("评论图片")),
+            "image_count": number(item.get("图片数量")),
+        }))
+    return reviews
+
+
+def build_review_tags(
+    payload: dict[str, Any],
+    reviews: list[dict[str, Any]],
+    existing_review_tags: str,
+) -> list[dict[str, Any]]:
+    explicit = split_values(payload.get("评论标签")) or split_values(existing_review_tags)
+    if explicit:
+        return [
+            {"label": label, "count": 0}
+            for label in explicit[:10]
+        ]
+
+    theme_counts: Counter[str] = Counter()
+    for review in reviews:
+        content = clean(review.get("content"))
+        for label, keywords in REVIEW_THEMES:
+            if any(keyword in content for keyword in keywords):
+                theme_counts[label] += 1
+    return [
+        {"label": label, "count": count}
+        for label, count in theme_counts.most_common(8)
+    ]
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--source-dir", type=Path, default=DEFAULT_SOURCE_DIR)
+    parser.add_argument("--graph-name", default="yunyou_libo")
+    args = parser.parse_args()
+
+    raw_records = load_raw_records(args.source_dir)
+    graph = FalkorDB(
+        host=settings.falkordb_host,
+        port=settings.falkordb_port,
+    ).select_graph(args.graph_name)
+    rows = graph.query(
+        "MATCH (n:FoodPlace) WHERE n.dianping_name IS NOT NULL "
+        "RETURN n.element_id,n.dianping_source_poi_id,n.dianping_shop_id,"
+        "n.dianping_shop_uuid,n.gaode_poi_id,n.dianping_review_tags"
+    ).result_set
+
+    updated_nodes = 0
+    stored_deals = 0
+    stored_reviews = 0
+    stored_tags = 0
+    missing_raw = 0
+    for row in rows:
+        element_id = clean(row[0])
+        identifiers = [clean(value) for value in row[1:5] if clean(value)]
+        existing_review_tags = clean(row[5])
+        payload = next(
+            (raw_records[identifier] for identifier in identifiers if identifier in raw_records),
+            None,
+        )
+        if payload is None:
+            missing_raw += 1
+            continue
+        deals = build_deals(payload)
+        reviews = build_reviews(payload)
+        tags = build_review_tags(payload, reviews, existing_review_tags)
+        result = graph.query(
+            "MATCH (n:FoodPlace {element_id:$element_id}) "
+            "SET n.group_buy_items_json=$deals,"
+            "n.food_review_items_json=$reviews,"
+            "n.food_review_tags_json=$tags "
+            "RETURN count(n)",
+            {
+                "element_id": element_id,
+                "deals": json.dumps(deals, ensure_ascii=False, separators=(",", ":")),
+                "reviews": json.dumps(reviews, ensure_ascii=False, separators=(",", ":")),
+                "tags": json.dumps(tags, ensure_ascii=False, separators=(",", ":")),
+            },
+        ).result_set
+        changed = int(result[0][0] if result else 0)
+        if changed:
+            updated_nodes += changed
+            stored_deals += len(deals) * changed
+            stored_reviews += len(reviews) * changed
+            stored_tags += len(tags) * changed
+
+    print(json.dumps({
+        "graph_name": args.graph_name,
+        "raw_record_identifiers": len(raw_records),
+        "graph_food_nodes": len(rows),
+        "updated_nodes": updated_nodes,
+        "missing_raw_nodes": missing_raw,
+        "stored_deals": stored_deals,
+        "stored_reviews": stored_reviews,
+        "stored_review_tags": stored_tags,
+    }, ensure_ascii=False))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/enrich_yunyou_libo_hotel_facility_categories.py b/scripts/enrich_yunyou_libo_hotel_facility_categories.py
new file mode 100644
index 0000000..d3c7a91
--- /dev/null
+++ b/scripts/enrich_yunyou_libo_hotel_facility_categories.py
@@ -0,0 +1,211 @@
+#!/usr/bin/env python3
+"""Attach categorized Ctrip facilities and verified facility photos to Hotel nodes."""
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+import sys
+from collections import defaultdict
+from pathlib import Path
+from typing import Any
+
+from falkordb import FalkorDB
+
+ROOT_DIR = Path(__file__).resolve().parents[1]
+if str(ROOT_DIR) not in sys.path:
+    sys.path.insert(0, str(ROOT_DIR))
+
+from app.config import settings
+
+
+CATEGORY_ORDER = (
+    "热门设施",
+    "康体设施",
+    "交通服务",
+    "餐饮服务",
+    "娱乐活动设施",
+    "前台服务",
+    "公共区",
+    "儿童设施服务",
+    "商务服务",
+    "清洁服务",
+    "安全与安保",
+    "无障碍设施服务",
+    "网络与通讯",
+    "房型特色",
+    "设施服务",
+    "更多设施",
+)
+DEFAULT_SOURCE_ROOT = Path("/Users/xuexue/Documents/云游荔波/outputs")
+
+
+def clean(value: Any) -> str:
+    return "" if value is None else str(value).strip()
+
+
+def parse_rank(value: Any) -> int:
+    try:
+        return int(float(clean(value) or "9999"))
+    except ValueError:
+        return 9999
+
+
+def resolve_category(row: dict[str, str]) -> str:
+    category = clean(row.get("设施分类"))
+    group = clean(row.get("设施分组"))
+    if category:
+        return category
+    if group == "热门设施":
+        return "热门设施"
+    if group and group not in {"服务及设施", "更多设施"}:
+        return group
+    return "更多设施"
+
+
+def load_facility_payloads(source_root: Path) -> dict[str, dict[str, Any]]:
+    facilities: dict[str, dict[str, dict[str, dict[str, Any]]]] = defaultdict(
+        lambda: defaultdict(dict)
+    )
+    facility_images: dict[str, dict[str, dict[str, Any]]] = defaultdict(dict)
+
+    facility_paths = sorted(source_root.glob("**/csv/携程_酒店详情_设施服务.csv"))
+    image_paths = sorted(source_root.glob("**/csv/携程_酒店详情_酒店图片.csv"))
+    if not facility_paths:
+        raise FileNotFoundError(f"未找到携程设施服务CSV：{source_root}")
+
+    for path in facility_paths:
+        with path.open("r", encoding="utf-8-sig", newline="") as stream:
+            for row in csv.DictReader(stream):
+                hotel_id = clean(row.get("酒店ID"))
+                name = clean(row.get("设施名称"))
+                if not hotel_id or not name:
+                    continue
+                category = resolve_category(row)
+                item = {
+                    "name": name,
+                    "fee": clean(row.get("收费类型")),
+                    "description": clean(row.get("设施说明")),
+                    "rank": parse_rank(row.get("排序")),
+                    "source_url": clean(row.get("来源URL")),
+                }
+                key = name.casefold()
+                current = facilities[hotel_id][category].get(key)
+                current_richness = (
+                    int(bool(current and current.get("fee")))
+                    + int(bool(current and current.get("description")))
+                    + int(bool(current and current.get("source_url")))
+                )
+                item_richness = (
+                    int(bool(item["fee"]))
+                    + int(bool(item["description"]))
+                    + int(bool(item["source_url"]))
+                )
+                if (
+                    current is None
+                    or item_richness > current_richness
+                    or (
+                        item_richness == current_richness
+                        and item["rank"] < current["rank"]
+                    )
+                ):
+                    facilities[hotel_id][category][key] = item
+
+    for path in image_paths:
+        with path.open("r", encoding="utf-8-sig", newline="") as stream:
+            for row in csv.DictReader(stream):
+                hotel_id = clean(row.get("酒店ID"))
+                image_type = clean(row.get("图片类型")).lower()
+                url = clean(row.get("图片URL"))
+                if not hotel_id or image_type != "facility" or not url:
+                    continue
+                image = {
+                    "url": url,
+                    "rank": parse_rank(row.get("图片序号")),
+                    "source_url": clean(row.get("来源URL")),
+                }
+                current = facility_images[hotel_id].get(url)
+                if current is None or image["rank"] < current["rank"]:
+                    facility_images[hotel_id][url] = image
+
+    category_rank = {category: index for index, category in enumerate(CATEGORY_ORDER)}
+    payloads: dict[str, dict[str, Any]] = {}
+    for hotel_id, grouped_categories in facilities.items():
+        category_items: dict[str, list[dict[str, Any]]] = {}
+        ordered_categories = sorted(
+            grouped_categories,
+            key=lambda category: (category_rank.get(category, 999), category),
+        )
+        for category in ordered_categories:
+            items = sorted(
+                grouped_categories[category].values(),
+                key=lambda item: (item["rank"], item["name"]),
+            )
+            if items:
+                category_items[category] = items
+        images = sorted(
+            facility_images.get(hotel_id, {}).values(),
+            key=lambda image: (image["rank"], image["url"]),
+        )[:8]
+        payloads[hotel_id] = {
+            "categories": category_items,
+            "images": images,
+        }
+    return payloads
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--source-root", type=Path, default=DEFAULT_SOURCE_ROOT)
+    parser.add_argument("--graph-name", default="yunyou_libo")
+    args = parser.parse_args()
+
+    payloads = load_facility_payloads(args.source_root)
+    graph = FalkorDB(
+        host=settings.falkordb_host,
+        port=settings.falkordb_port,
+    ).select_graph(args.graph_name)
+
+    hotel_rows = graph.query(
+        "MATCH (n:Hotel) WHERE n.ctrip_hotel_id IS NOT NULL "
+        "RETURN DISTINCT n.ctrip_hotel_id"
+    ).result_set
+    graph_hotel_ids = {clean(row[0]) for row in hotel_rows if row and clean(row[0])}
+
+    updated_hotels = 0
+    updated_facilities = 0
+    updated_images = 0
+    hotels_with_images = 0
+    for hotel_id in sorted(graph_hotel_ids & payloads.keys()):
+        payload = payloads[hotel_id]
+        serialized = json.dumps(payload, ensure_ascii=False, separators=(",", ":"))
+        result = graph.query(
+            "MATCH (n:Hotel) WHERE n.ctrip_hotel_id=$hotel_id "
+            "SET n.facility_category_items_json=$payload "
+            "RETURN count(n)",
+            {"hotel_id": hotel_id, "payload": serialized},
+        ).result_set
+        changed = int(result[0][0] if result else 0)
+        if not changed:
+            continue
+        facility_count = sum(len(items) for items in payload["categories"].values())
+        image_count = len(payload["images"])
+        updated_hotels += changed
+        updated_facilities += facility_count * changed
+        updated_images += image_count * changed
+        if image_count:
+            hotels_with_images += changed
+
+    print(json.dumps({
+        "graph_name": args.graph_name,
+        "source_hotels": len(payloads),
+        "graph_hotels_with_ctrip_id": len(graph_hotel_ids),
+        "updated_hotels": updated_hotels,
+        "stored_facilities": updated_facilities,
+        "hotels_with_facility_images": hotels_with_images,
+        "stored_facility_images": updated_images,
+    }, ensure_ascii=False))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/enrich_yunyou_libo_hotel_nearby_categories.py b/scripts/enrich_yunyou_libo_hotel_nearby_categories.py
new file mode 100644
index 0000000..ee5e9c0
--- /dev/null
+++ b/scripts/enrich_yunyou_libo_hotel_nearby_categories.py
@@ -0,0 +1,118 @@
+#!/usr/bin/env python3
+"""Attach categorized Ctrip nearby-place samples to yunyou_libo Hotel nodes."""
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+import sys
+from collections import defaultdict
+from pathlib import Path
+from typing import Any
+
+from falkordb import FalkorDB
+
+ROOT_DIR = Path(__file__).resolve().parents[1]
+if str(ROOT_DIR) not in sys.path:
+    sys.path.insert(0, str(ROOT_DIR))
+
+from app.config import settings
+
+
+CATEGORY_ORDER = ("交通", "景点", "美食", "购物")
+DEFAULT_SOURCE_ROOT = Path("/Users/xuexue/Documents/云游荔波/outputs")
+
+
+def clean(value: Any) -> str:
+    return "" if value is None else str(value).strip()
+
+
+def load_nearby_rows(source_root: Path) -> dict[str, dict[str, list[dict[str, Any]]]]:
+    grouped: dict[str, dict[str, dict[str, dict[str, Any]]]] = defaultdict(
+        lambda: defaultdict(dict)
+    )
+    paths = sorted(source_root.glob("**/csv/携程_酒店详情_周边地点.csv"))
+    if not paths:
+        raise FileNotFoundError(f"未找到携程周边地点CSV：{source_root}")
+
+    for path in paths:
+        with path.open("r", encoding="utf-8-sig", newline="") as stream:
+            for row in csv.DictReader(stream):
+                hotel_id = clean(row.get("酒店ID"))
+                category = clean(row.get("地点分类"))
+                name = clean(row.get("地点名称"))
+                if not hotel_id or category not in CATEGORY_ORDER or not name:
+                    continue
+                place_id = clean(row.get("地点ID")) or name
+                try:
+                    rank = int(float(clean(row.get("排序")) or "999"))
+                except ValueError:
+                    rank = 999
+                item = {
+                    "name": name,
+                    "distance": clean(row.get("距离")),
+                    "travel_time": clean(row.get("交通时间")),
+                    "rank": rank,
+                }
+                current = grouped[hotel_id][category].get(place_id)
+                if current is None or item["rank"] < current["rank"]:
+                    grouped[hotel_id][category][place_id] = item
+
+    result: dict[str, dict[str, list[dict[str, Any]]]] = {}
+    for hotel_id, categories in grouped.items():
+        result[hotel_id] = {}
+        for category in CATEGORY_ORDER:
+            items = sorted(
+                categories.get(category, {}).values(),
+                key=lambda item: (item["rank"], item["name"]),
+            )
+            if items:
+                result[hotel_id][category] = items
+    return result
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--source-root", type=Path, default=DEFAULT_SOURCE_ROOT)
+    parser.add_argument("--graph-name", default="yunyou_libo")
+    args = parser.parse_args()
+
+    nearby_by_hotel = load_nearby_rows(args.source_root)
+    graph = FalkorDB(
+        host=settings.falkordb_host,
+        port=settings.falkordb_port,
+    ).select_graph(args.graph_name)
+
+    hotel_rows = graph.query(
+        "MATCH (n:Hotel) WHERE n.ctrip_hotel_id IS NOT NULL "
+        "RETURN DISTINCT n.ctrip_hotel_id"
+    ).result_set
+    graph_hotel_ids = {clean(row[0]) for row in hotel_rows if row and clean(row[0])}
+
+    updated_hotels = 0
+    updated_items = 0
+    for hotel_id in sorted(graph_hotel_ids & nearby_by_hotel.keys()):
+        categories = nearby_by_hotel[hotel_id]
+        payload = json.dumps(categories, ensure_ascii=False, separators=(",", ":"))
+        result = graph.query(
+            "MATCH (n:Hotel) WHERE n.ctrip_hotel_id=$hotel_id "
+            "SET n.nearby_category_items_json=$payload "
+            "RETURN count(n)",
+            {"hotel_id": hotel_id, "payload": payload},
+        ).result_set
+        changed = int(result[0][0] if result else 0)
+        if changed:
+            updated_hotels += changed
+            updated_items += sum(len(items) for items in categories.values()) * changed
+
+    print(json.dumps({
+        "graph_name": args.graph_name,
+        "source_hotels": len(nearby_by_hotel),
+        "graph_hotels_with_ctrip_id": len(graph_hotel_ids),
+        "updated_hotels": updated_hotels,
+        "stored_category_items": updated_items,
+    }, ensure_ascii=False))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/enrich_yunyou_libo_hotel_rooms_reviews.py b/scripts/enrich_yunyou_libo_hotel_rooms_reviews.py
new file mode 100644
index 0000000..6f10bf1
--- /dev/null
+++ b/scripts/enrich_yunyou_libo_hotel_rooms_reviews.py
@@ -0,0 +1,291 @@
+#!/usr/bin/env python3
+"""Attach detailed Ctrip room, offer, and guest-review data to Libo Hotel nodes."""
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+import sys
+from collections import defaultdict
+from datetime import datetime
+from pathlib import Path
+from typing import Any
+
+from falkordb import FalkorDB
+
+ROOT_DIR = Path(__file__).resolve().parents[1]
+if str(ROOT_DIR) not in sys.path:
+    sys.path.insert(0, str(ROOT_DIR))
+
+from app.config import settings
+
+
+DEFAULT_SOURCE_DIR = Path(
+    "/Users/xuexue/Desktop/荔波小七孔源数据/携程/CSV数据表"
+)
+
+
+def clean(value: Any) -> str:
+    return "" if value is None else str(value).strip()
+
+
+def number(value: Any) -> float | None:
+    text = clean(value).replace(",", "")
+    if not text:
+        return None
+    try:
+        result = float(text)
+    except ValueError:
+        return None
+    return int(result) if result.is_integer() else result
+
+
+def integer(value: Any) -> int | None:
+    result = number(value)
+    return int(result) if result is not None else None
+
+
+def load_csv(path: Path) -> list[dict[str, str]]:
+    with path.open("r", encoding="utf-8-sig", newline="") as stream:
+        return list(csv.DictReader(stream))
+
+
+def compact(record: dict[str, Any]) -> dict[str, Any]:
+    return {
+        key: value
+        for key, value in record.items()
+        if value not in (None, "", [], {})
+    }
+
+
+def clean_offer_text(value: Any, kind: str) -> str:
+    """Keep stable booking terms while dropping scraper-combined live inventory copy."""
+    text = clean(value)
+    if not text:
+        return ""
+    import re
+
+    patterns = {
+        "breakfast": [
+            r"无早餐",
+            r"\d+\s*份早餐",
+            r"含早餐",
+        ],
+        "cancellation_policy": [
+            r"\d{2}月\d{2}日\s*\d{2}:\d{2}前可免费取消",
+            r"限时取消",
+            r"免费取消",
+            r"不可取消",
+        ],
+        "confirmation_policy": [
+            r"立即确认",
+            r"等待确认",
+        ],
+        "payment_method": [
+            r"在线付(?:[·・]\s*可先住后付)?",
+            r"到店付",
+            r"可先住后付",
+        ],
+    }
+    for pattern in patterns.get(kind, []):
+        match = re.search(pattern, text)
+        if match:
+            return match.group(0).replace(" ", "")
+    if len(text) <= 36 and not re.search(r"仅剩\s*\d+\s*间", text):
+        return text
+    return ""
+
+
+def load_room_images(source_dir: Path) -> dict[tuple[str, str], str]:
+    result: dict[tuple[str, str], tuple[int, str]] = {}
+    for row in load_csv(source_dir / "携程_酒店详情_酒店图片.csv"):
+        if clean(row.get("图片类型")).lower() != "room":
+            continue
+        hotel_id = clean(row.get("酒店ID") or row.get("\ufeff酒店ID"))
+        room_id = clean(row.get("房型ID"))
+        image_url = clean(row.get("图片URL"))
+        if not hotel_id or not room_id or not image_url:
+            continue
+        sequence = integer(row.get("图片序号")) or 999999
+        current = result.get((hotel_id, room_id))
+        if current is None or sequence < current[0]:
+            result[(hotel_id, room_id)] = (sequence, image_url)
+    return {key: value[1] for key, value in result.items()}
+
+
+def load_room_payloads(source_dir: Path) -> dict[str, list[dict[str, Any]]]:
+    room_rows = load_csv(source_dir / "携程_酒店详情_房型.csv")
+    offer_rows = load_csv(source_dir / "携程_酒店详情_售卖方案.csv")
+    room_images = load_room_images(source_dir)
+
+    offers_by_room: dict[tuple[str, str], list[dict[str, Any]]] = defaultdict(list)
+    for row in offer_rows:
+        hotel_id = clean(row.get("酒店ID"))
+        room_id = clean(row.get("房型ID"))
+        if not hotel_id or not room_id:
+            continue
+        offers_by_room[(hotel_id, room_id)].append(compact({
+            "offer_id": clean(row.get("售卖方案ID")),
+            "sequence": integer(row.get("方案序号")),
+            "breakfast": clean_offer_text(row.get("早餐"), "breakfast"),
+            "cancellation_policy": clean_offer_text(
+                row.get("取消政策"),
+                "cancellation_policy",
+            ),
+            "confirmation_policy": clean_offer_text(
+                row.get("确认政策"),
+                "confirmation_policy",
+            ),
+            "payment_method": clean_offer_text(
+                row.get("支付方式"),
+                "payment_method",
+            ),
+            "occupancy": integer(row.get("入住人数")),
+            "original_price": number(row.get("原价")),
+            "current_price": number(row.get("当前价")),
+            "tax_fee": number(row.get("税费")),
+            "currency": clean(row.get("币种")) or "CNY",
+            "source_url": clean(row.get("来源URL")),
+        }))
+
+    result: dict[str, list[dict[str, Any]]] = defaultdict(list)
+    for row in room_rows:
+        hotel_id = clean(row.get("酒店ID"))
+        room_id = clean(row.get("房型ID"))
+        name = clean(row.get("房型名称"))
+        if not hotel_id or not room_id or not name:
+            continue
+        offers = offers_by_room.get((hotel_id, room_id), [])
+        offers.sort(key=lambda item: (
+            item.get("current_price") is None,
+            item.get("current_price") or 0,
+            item.get("sequence") or 999,
+        ))
+        result[hotel_id].append(compact({
+            "room_id": room_id,
+            "name": name,
+            "price": number(row.get("房型价格")),
+            "currency": clean(row.get("币种")) or "CNY",
+            "room_url": clean(row.get("房型URL")),
+            "image_url": room_images.get((hotel_id, room_id), ""),
+            "bed_type": clean(row.get("床型")),
+            "window": clean(row.get("窗户")),
+            "area": clean(row.get("面积")),
+            "floor": clean(row.get("楼层")),
+            "capacity": integer(row.get("可住人数")),
+            "extra_bed_policy": clean(row.get("加床政策")),
+            "smoking_policy": clean(row.get("吸烟政策")),
+            "network": clean(row.get("网络")),
+            "facilities": clean(row.get("房型设施")),
+            "image_count": integer(row.get("房型图片数")),
+            "source_url": clean(row.get("来源URL")),
+            "offers": offers,
+        }))
+
+    for rooms in result.values():
+        rooms.sort(key=lambda item: (
+            item.get("price") is None,
+            item.get("price") or 0,
+            item.get("name") or "",
+        ))
+    return dict(result)
+
+
+def review_timestamp(value: str) -> float:
+    try:
+        return datetime.fromisoformat(value.replace("/", "-")).timestamp()
+    except ValueError:
+        return 0
+
+
+def load_review_payloads(source_dir: Path) -> dict[str, list[dict[str, Any]]]:
+    result: dict[str, list[dict[str, Any]]] = defaultdict(list)
+    for row in load_csv(source_dir / "携程_酒店详情_住客点评.csv"):
+        hotel_id = clean(row.get("酒店ID") or row.get("\ufeff酒店ID"))
+        review_id = clean(row.get("点评ID"))
+        content = clean(row.get("点评内容"))
+        if not hotel_id or not review_id or not content:
+            continue
+        image_urls = [
+            item.strip()
+            for item in clean(row.get("点评图片")).split("|")
+            if item.strip()
+        ]
+        result[hotel_id].append(compact({
+            "review_id": review_id,
+            "nickname": clean(row.get("用户昵称")) or "匿名用户",
+            "review_at": clean(row.get("点评时间")),
+            "stay_at": clean(row.get("入住时间")),
+            "room_type": clean(row.get("入住房型")),
+            "travel_type": clean(row.get("出行类型")),
+            "score": number(row.get("总评分")),
+            "content": content,
+            "like_count": integer(row.get("点赞数")),
+            "reply_count": integer(row.get("回复数")),
+            "image_count": integer(row.get("图片数量")),
+            "image_urls": image_urls,
+            "source_url": clean(row.get("来源URL")),
+        }))
+
+    for reviews in result.values():
+        reviews.sort(
+            key=lambda item: review_timestamp(clean(item.get("review_at"))),
+            reverse=True,
+        )
+    return dict(result)
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--source-dir", type=Path, default=DEFAULT_SOURCE_DIR)
+    parser.add_argument("--graph-name", default="yunyou_libo")
+    args = parser.parse_args()
+
+    rooms_by_hotel = load_room_payloads(args.source_dir)
+    reviews_by_hotel = load_review_payloads(args.source_dir)
+    graph = FalkorDB(
+        host=settings.falkordb_host,
+        port=settings.falkordb_port,
+    ).select_graph(args.graph_name)
+
+    hotel_rows = graph.query(
+        "MATCH (n:Hotel) WHERE n.ctrip_hotel_id IS NOT NULL "
+        "RETURN DISTINCT n.ctrip_hotel_id"
+    ).result_set
+    graph_hotel_ids = {clean(row[0]) for row in hotel_rows if row and clean(row[0])}
+
+    updated_hotels = 0
+    stored_rooms = 0
+    stored_reviews = 0
+    for hotel_id in sorted(graph_hotel_ids & (rooms_by_hotel.keys() | reviews_by_hotel.keys())):
+        rooms = rooms_by_hotel.get(hotel_id, [])
+        reviews = reviews_by_hotel.get(hotel_id, [])
+        result = graph.query(
+            "MATCH (n:Hotel) WHERE n.ctrip_hotel_id=$hotel_id "
+            "SET n.room_items_json=$rooms, n.review_items_json=$reviews "
+            "RETURN count(n)",
+            {
+                "hotel_id": hotel_id,
+                "rooms": json.dumps(rooms, ensure_ascii=False, separators=(",", ":")),
+                "reviews": json.dumps(reviews, ensure_ascii=False, separators=(",", ":")),
+            },
+        ).result_set
+        changed = int(result[0][0] if result else 0)
+        if changed:
+            updated_hotels += changed
+            stored_rooms += len(rooms) * changed
+            stored_reviews += len(reviews) * changed
+
+    print(json.dumps({
+        "graph_name": args.graph_name,
+        "source_hotels_with_rooms": len(rooms_by_hotel),
+        "source_hotels_with_reviews": len(reviews_by_hotel),
+        "graph_hotels_with_ctrip_id": len(graph_hotel_ids),
+        "updated_hotels": updated_hotels,
+        "stored_rooms": stored_rooms,
+        "stored_reviews": stored_reviews,
+    }, ensure_ascii=False))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/evaluate_markitdown_conversion.py b/scripts/evaluate_markitdown_conversion.py
new file mode 100644
index 0000000..a7f8ed6
--- /dev/null
+++ b/scripts/evaluate_markitdown_conversion.py
@@ -0,0 +1,365 @@
+#!/usr/bin/env python3
+"""Evaluate MarkItDown conversion quality on a local document corpus.
+
+The goal is not to prove that a converter is universally good. The goal is to
+make conversion quality measurable for this knowledge-extraction product:
+success rate, latency, information coverage, structure preservation, noise, and
+optional similarity to reference Markdown.
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import re
+import statistics
+import sys
+import time
+from dataclasses import dataclass
+from difflib import SequenceMatcher
+from pathlib import Path
+from typing import Any
+
+
+SUPPORTED_EXTENSIONS = {
+    ".txt",
+    ".md",
+    ".markdown",
+    ".csv",
+    ".json",
+    ".xml",
+    ".html",
+    ".htm",
+    ".pdf",
+    ".docx",
+    ".doc",
+    ".pptx",
+    ".ppt",
+    ".xlsx",
+    ".xls",
+    ".zip",
+    ".epub",
+    ".jpg",
+    ".jpeg",
+    ".png",
+    ".gif",
+    ".wav",
+    ".mp3",
+}
+
+
+@dataclass
+class Case:
+    case_id: str
+    file_path: Path
+    must_terms: list[str]
+    forbidden_terms: list[str]
+    expected_headings_min: int
+    expected_tables_min: int
+    expected_lists_min: int
+    expected_links_min: int
+    min_chars: int
+    gold_markdown_path: Path | None
+    notes: str
+
+
+def load_manifest(path: Path | None) -> dict[str, Any]:
+    if not path:
+        return {"cases": []}
+    with path.open("r", encoding="utf-8") as f:
+        data = json.load(f)
+    if not isinstance(data, dict) or not isinstance(data.get("cases"), list):
+        raise ValueError("Manifest must be a JSON object with a cases array")
+    return data
+
+
+def discover_cases(input_dir: Path, manifest: dict[str, Any]) -> list[Case]:
+    by_file = {
+        str(item.get("file", "")).strip(): item
+        for item in manifest.get("cases", [])
+        if isinstance(item, dict) and str(item.get("file", "")).strip()
+    }
+    if by_file:
+        files = [input_dir / rel for rel in by_file]
+    else:
+        files = [
+            p
+            for p in sorted(input_dir.rglob("*"))
+            if p.is_file() and p.suffix.lower() in SUPPORTED_EXTENSIONS
+        ]
+
+    cases: list[Case] = []
+    for file_path in files:
+        rel = str(file_path.relative_to(input_dir)) if file_path.is_relative_to(input_dir) else file_path.name
+        cfg = by_file.get(rel, {})
+        case_id = str(cfg.get("case_id") or file_path.with_suffix("").name)
+        gold = cfg.get("gold_markdown")
+        cases.append(
+            Case(
+                case_id=case_id,
+                file_path=file_path,
+                must_terms=[str(v) for v in cfg.get("must_terms", []) if str(v).strip()],
+                forbidden_terms=[str(v) for v in cfg.get("forbidden_terms", []) if str(v).strip()],
+                expected_headings_min=int(cfg.get("expected_headings_min") or 0),
+                expected_tables_min=int(cfg.get("expected_tables_min") or 0),
+                expected_lists_min=int(cfg.get("expected_lists_min") or 0),
+                expected_links_min=int(cfg.get("expected_links_min") or 0),
+                min_chars=int(cfg.get("min_chars") or 80),
+                gold_markdown_path=(input_dir / str(gold)) if gold else None,
+                notes=str(cfg.get("notes") or ""),
+            )
+        )
+    return cases
+
+
+def convert_with_markitdown(file_path: Path) -> str:
+    try:
+        from markitdown import MarkItDown
+    except ImportError as exc:
+        raise RuntimeError("MarkItDown is not installed. Run: pip install -r requirements.txt") from exc
+
+    result = MarkItDown(enable_plugins=False).convert(str(file_path))
+    text = getattr(result, "text_content", None) or getattr(result, "markdown", None) or ""
+    return str(text).strip()
+
+
+def count_patterns(markdown: str) -> dict[str, int]:
+    lines = markdown.splitlines()
+    return {
+        "chars": len(markdown),
+        "lines": len(lines),
+        "headings": sum(1 for line in lines if re.match(r"^\s{0,3}#{1,6}\s+\S", line)),
+        "table_rows": sum(1 for line in lines if line.count("|") >= 2),
+        "list_items": sum(1 for line in lines if re.match(r"^\s*(?:[-*+]|\d+[.)])\s+\S", line)),
+        "links": len(re.findall(r"\[[^\]]+\]\([^)]+\)|https?://\S+", markdown)),
+        "replacement_chars": markdown.count("\ufffd"),
+        "null_chars": markdown.count("\x00"),
+        "html_tags": len(re.findall(r"</?[A-Za-z][^>]{0,200}>", markdown)),
+        "long_lines": sum(1 for line in lines if len(line) > 500),
+    }
+
+
+def term_coverage(markdown: str, terms: list[str]) -> tuple[float, list[str]]:
+    if not terms:
+        return 1.0, []
+    haystack = markdown.lower()
+    missing = [term for term in terms if term.lower() not in haystack]
+    return (len(terms) - len(missing)) / len(terms), missing
+
+
+def forbidden_hits(markdown: str, terms: list[str]) -> list[str]:
+    haystack = markdown.lower()
+    return [term for term in terms if term.lower() in haystack]
+
+
+def min_ratio(actual: int, expected: int) -> float:
+    if expected <= 0:
+        return 1.0
+    return min(actual / expected, 1.0)
+
+
+def score_case(metrics: dict[str, Any]) -> float:
+    content_score = min(metrics["chars"] / max(metrics["min_chars"], 1), 1.0)
+    structure_score = statistics.mean(
+        [
+            metrics["heading_score"],
+            metrics["table_score"],
+            metrics["list_score"],
+            metrics["link_score"],
+        ]
+    )
+    noise_penalty = min(
+        1.0,
+        metrics["replacement_chars"] * 0.08
+        + metrics["null_chars"] * 0.2
+        + metrics["long_lines"] * 0.03
+        + metrics["forbidden_hit_count"] * 0.12,
+    )
+    gold_similarity = metrics.get("gold_similarity")
+    if gold_similarity is None:
+        score = (
+            0.35 * metrics["must_term_coverage"]
+            + 0.25 * content_score
+            + 0.25 * structure_score
+            + 0.15 * (1.0 - noise_penalty)
+        )
+    else:
+        score = (
+            0.30 * metrics["must_term_coverage"]
+            + 0.20 * content_score
+            + 0.20 * structure_score
+            + 0.15 * (1.0 - noise_penalty)
+            + 0.15 * gold_similarity
+        )
+    return round(max(0.0, min(score, 1.0)), 4)
+
+
+def evaluate_case(case: Case, output_dir: Path) -> dict[str, Any]:
+    started = time.perf_counter()
+    output_path = output_dir / "converted" / f"{case.case_id}.markitdown.md"
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    result: dict[str, Any] = {
+        "case_id": case.case_id,
+        "file": str(case.file_path),
+        "notes": case.notes,
+        "success": False,
+    }
+
+    try:
+        markdown = convert_with_markitdown(case.file_path)
+        output_path.write_text(markdown + "\n", encoding="utf-8")
+        counts = count_patterns(markdown)
+        coverage, missing = term_coverage(markdown, case.must_terms)
+        forbidden = forbidden_hits(markdown, case.forbidden_terms)
+        metrics: dict[str, Any] = {
+            **counts,
+            "min_chars": case.min_chars,
+            "must_terms": case.must_terms,
+            "must_term_coverage": round(coverage, 4),
+            "missing_terms": missing,
+            "forbidden_terms": case.forbidden_terms,
+            "forbidden_hits": forbidden,
+            "forbidden_hit_count": len(forbidden),
+            "expected_headings_min": case.expected_headings_min,
+            "expected_tables_min": case.expected_tables_min,
+            "expected_lists_min": case.expected_lists_min,
+            "expected_links_min": case.expected_links_min,
+            "heading_score": min_ratio(counts["headings"], case.expected_headings_min),
+            "table_score": min_ratio(counts["table_rows"], case.expected_tables_min),
+            "list_score": min_ratio(counts["list_items"], case.expected_lists_min),
+            "link_score": min_ratio(counts["links"], case.expected_links_min),
+        }
+        if case.gold_markdown_path and case.gold_markdown_path.exists():
+            gold = case.gold_markdown_path.read_text(encoding="utf-8")
+            metrics["gold_similarity"] = round(SequenceMatcher(None, gold, markdown).ratio(), 4)
+        else:
+            metrics["gold_similarity"] = None
+
+        result.update(
+            {
+                "success": True,
+                "latency_ms": round((time.perf_counter() - started) * 1000),
+                "markdown_path": str(output_path),
+                "metrics": metrics,
+                "quality_score": score_case(metrics),
+            }
+        )
+    except Exception as exc:  # noqa: BLE001
+        result.update(
+            {
+                "latency_ms": round((time.perf_counter() - started) * 1000),
+                "error": str(exc),
+                "quality_score": 0.0,
+            }
+        )
+    return result
+
+
+def aggregate(results: list[dict[str, Any]]) -> dict[str, Any]:
+    scores = [float(r.get("quality_score") or 0) for r in results]
+    successes = [r for r in results if r.get("success")]
+    latencies = [float(r.get("latency_ms") or 0) for r in successes]
+    return {
+        "cases": len(results),
+        "successes": len(successes),
+        "failures": len(results) - len(successes),
+        "success_rate": round(len(successes) / len(results), 4) if results else 0,
+        "mean_quality_score": round(statistics.mean(scores), 4) if scores else 0,
+        "median_quality_score": round(statistics.median(scores), 4) if scores else 0,
+        "mean_latency_ms": round(statistics.mean(latencies)) if latencies else 0,
+    }
+
+
+def write_markdown_report(report: dict[str, Any], path: Path) -> None:
+    summary = report["summary"]
+    lines = [
+        "# MarkItDown Conversion Evaluation",
+        "",
+        "## Summary",
+        "",
+        f"- Cases: {summary['cases']}",
+        f"- Success rate: {summary['success_rate']:.2%}",
+        f"- Mean quality score: {summary['mean_quality_score']:.3f}",
+        f"- Median quality score: {summary['median_quality_score']:.3f}",
+        f"- Mean latency: {summary['mean_latency_ms']} ms",
+        "",
+        "## Cases",
+        "",
+        "| Case | Success | Score | Chars | Must-term coverage | Missing terms | Latency |",
+        "| --- | --- | ---: | ---: | ---: | --- | ---: |",
+    ]
+    for item in report["results"]:
+        metrics = item.get("metrics") or {}
+        missing = ", ".join(metrics.get("missing_terms") or [])
+        lines.append(
+            "| {case} | {success} | {score:.3f} | {chars} | {coverage:.2%} | {missing} | {latency} ms |".format(
+                case=item.get("case_id"),
+                success="yes" if item.get("success") else "no",
+                score=float(item.get("quality_score") or 0),
+                chars=metrics.get("chars", 0),
+                coverage=float(metrics.get("must_term_coverage") or 0),
+                missing=missing.replace("|", "\\|") or "-",
+                latency=item.get("latency_ms", 0),
+            )
+        )
+    lines.append("")
+    lines.append("## Interpretation")
+    lines.append("")
+    lines.append("- Score >= 0.85: suitable for normal extraction after spot check.")
+    lines.append("- 0.70 <= score < 0.85: usable, but inspect missing terms or structure loss.")
+    lines.append("- Score < 0.70: do not trust automatic extraction without fallback/OCR/manual correction.")
+    path.write_text("\n".join(lines) + "\n", encoding="utf-8")
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--input-dir", default="data/markitdown_eval/input")
+    parser.add_argument("--manifest", default="data/markitdown_eval/manifest.json")
+    parser.add_argument("--output-dir", default="outputs/markitdown_eval")
+    parser.add_argument("--fail-under", type=float, default=0.70)
+    parser.add_argument("--allow-missing-manifest", action="store_true")
+    args = parser.parse_args()
+
+    input_dir = Path(args.input_dir)
+    manifest_path = Path(args.manifest)
+    output_dir = Path(args.output_dir)
+    output_dir.mkdir(parents=True, exist_ok=True)
+
+    if not input_dir.exists():
+        print(f"Input directory not found: {input_dir}", file=sys.stderr)
+        return 2
+    if not manifest_path.exists() and not args.allow_missing_manifest:
+        print(
+            f"Manifest not found: {manifest_path}. Pass --allow-missing-manifest to auto-discover files.",
+            file=sys.stderr,
+        )
+        return 2
+
+    manifest = load_manifest(manifest_path if manifest_path.exists() else None)
+    cases = discover_cases(input_dir, manifest)
+    if not cases:
+        print(f"No supported files found in {input_dir}", file=sys.stderr)
+        return 2
+
+    results = [evaluate_case(case, output_dir) for case in cases]
+    report = {
+        "input_dir": str(input_dir),
+        "manifest": str(manifest_path) if manifest_path.exists() else None,
+        "summary": aggregate(results),
+        "results": results,
+    }
+    json_path = output_dir / "markitdown_eval_report.json"
+    md_path = output_dir / "markitdown_eval_report.md"
+    json_path.write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8")
+    write_markdown_report(report, md_path)
+
+    print(f"Wrote {json_path}")
+    print(f"Wrote {md_path}")
+    mean_score = report["summary"]["mean_quality_score"]
+    if mean_score < args.fail_under:
+        print(f"Mean quality score {mean_score:.3f} is below fail-under {args.fail_under:.3f}", file=sys.stderr)
+        return 1
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/scripts/html b/scripts/html
new file mode 100644
index 0000000..144157f
--- /dev/null
+++ b/scripts/html
@@ -0,0 +1,2 @@
+
+<!DOCTYPE html><html class=""><head><meta charset="UTF-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="referrer" content="always"><title>小七孔风景区_百度百科</title><meta name="description" content="小七孔风景区（Xiaoqikong Scenic Area、Xiaoqikong Scenic Spot），又名小七孔景区、荔波小七孔风景区等。其是位于贵州省黔南布依族苗族自治州荔波县西南部的国家级自然保护区。景区总面积约46.4平方千米。小七孔风景区地处贵州高原南缘地带，该景区地学景观分为岩溶景观、地貌景观、水体景观、生物景观四大类，其中岩溶景观又分为地表岩溶景观和地下岩溶景观，天钟洞是地下岩溶洞，飞云洞则是喀斯特洞穴。小七孔风景区属中亚热带季风性湿润气候，四季分明，雨热同期。景区集水、洞、林、瀑、湖、石多种景观于一体，主要有拉雅瀑布、响水河、鸳鸯湖等。景区内森林覆盖率达92%以上，空气中每立方厘米含负氧离子18万个，被称为“洗肺康养”胜地。景区植物以自然生态林为主，兼有少部分的人工植物景观。小七孔风景区于1994年被国务院批准为国家级风景名胜区，是中国第六个、贵州第一个世界自然遗产地，"><meta name="keywords" content="小七孔风景区, 小七孔风景区命名, 小七孔风景区历史沿革, 小七孔风景区地理环境, 小七孔风景区景区布局, 小七孔风景区重要景点, 小七孔风景区文化活动, 小七孔风景区其他看点, 小七孔风景区开发与保护, 小七孔风景区相关文化, 小七孔风景区重要事件, 小七孔风景区价值意义, 小七孔风景区旅游信息, 小七孔风景区公开通报, 小七孔风景区地图信息"><meta itemprop="dateUpdate" content="2025-12-17 20:33:58"><link rel="alternate" hreflang="x-default" href="https://baike.baidu.com/item/%E5%B0%8F%E4%B8%83%E5%AD%94%E9%A3%8E%E6%99%AF%E5%8C%BA/6899702"><link rel="alternate" hreflang="zh" href="https://baike.baidu.com/item/%E5%B0%8F%E4%B8%83%E5%AD%94%E9%A3%8E%E6%99%AF%E5%8C%BA/6899702"><link rel="alternate" hreflang="zh-Hans" href="https://baike.baidu.com/item/%E5%B0%8F%E4%B8%83%E5%AD%94%E9%A3%8E%E6%99%AF%E5%8C%BA/6899702"><link rel="alternate" hreflang="zh-Hant" href="https://baike.baidu.hk/item/%E5%B0%8F%E4%B8%83%E5%AD%94%E9%A3%8E%E6%99%AF%E5%8C%BA/6899702"><link rel="canonical" href="https://baike.baidu.com/item/%E5%B0%8F%E4%B8%83%E5%AD%94%E9%A3%8E%E6%99%AF%E5%8C%BA/6899702"><meta name="image" content="https://bkimg.cdn.bcebos.com/pic/314e251f95cad1c8a78656077e677009c93d70cffbc0?x-bce-process=image/resize,m_lfit,w_536,limit_1/quality,Q_70"><meta property="og:title" content="小七孔风景区"><meta property="og:description" content="小七孔风景区（Xiaoqikong Scenic Area、Xiaoqikong Scenic Spot），又名小七孔景区、荔波小七孔风景区等。其是位于贵州省黔南布依族苗族自治州荔波县西南部的国家级自然保护区。景区总面积约46.4平方千米。小七孔风景区地处贵州高原南缘地带，该景区地学景观分为岩溶景观、地貌景观、水体景观、生物景观四大类，其中岩溶景观又分为地表岩溶景观和地下岩溶景观，天钟洞是地下岩溶洞，飞云洞则是喀斯特洞穴。小七孔风景区属中亚热带季风性湿润气候，四季分明，雨热同期。景区集水、洞、林、瀑、湖、石多种景观于一体，主要有拉雅瀑布、响水河、鸳鸯湖等。景区内森林覆盖率达92%以上，空气中每立方厘米含负氧离子18万个，被称为“洗肺康养”胜地。景区植物以自然生态林为主，兼有少部分的人工植物景观。小七孔风景区于1994年被国务院批准为国家级风景名胜区，是中国第六个、贵州第一个世界自然遗产地，"><meta property="og:image" content="https://bkimg.cdn.bcebos.com/pic/314e251f95cad1c8a78656077e677009c93d70cffbc0?x-bce-process=image/resize,m_lfit,w_536,limit_1/quality,Q_70"><meta property="og:url" content="https://baike.baidu.hk/item/%E5%B0%8F%E4%B8%83%E5%AD%94%E9%A3%8E%E6%99%AF%E5%8C%BA/6899702"><meta property="og:site_name" content="百度百科"><meta property="og:type" content="website"><link rel="shortcut icon" href="//baikebcs.bdimg.com/baike-react/common/favicon-baidu.ico" type="image/x-icon"><link rel="icon" sizes="any" mask="true" href="//baikebcs.bdimg.com/cms/static/baike-icon.svg"> <style id=f3d7f4f0-40fc-5c4b-8ffa-fed75b8098db 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26.757zm-19.579-314.537c-58.02-13.619-117.622-1.822-134.4 1.337-1.218.123-2.437 1.341-3.65 1.587-.615.118-.85.727-.85.727-16.42 4.623-28.585 19.947-28.585 37.95 0 21.529 17.392 39.162 39.045 39.162 0 0 21.16-2.795 35.39-8.397 14.233-5.713 134.282-4.25 193.996 95.97 32.604 73.098 14.234 121.994 12.042 129.904 0 0-7.782 18.97-7.782 37.704 0 21.525 17.393 35.149 39.045 35.149 17.997 0 33.203-2.432 37.58-32.963h.247c64.102-213.703-78.208-313.922-182.078-338.125z"></path></svg></div></div></div></div></div></div><span class="tipPanel_xDzBr"><a class="tipIcon_Aa6To" target="_blank" href="/item/百度百科：跳转关系/16202814?fromModule=lemma_inlink&amp;fromtitle=同义词&amp;fromid=2740569">同义词</a><span class="tipTitle_sT1Ym">小七孔</span>（小七孔）一般指小七孔风景区</span><div class="lemmaSummary_axDDr J-summary"><a name="lemma-summary" class="lemmaSummaryAnchor_OmABM"></a><div class="para_Y8Vvn summary_SG_8p MARK_MODULE" data-tag="paragraph" data-uuid="hsqwq1r1rd" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区（Xiaoqikong Scenic Area、Xiaoqikong Scenic Spot），又名小七孔景区、荔波小七孔风景区等。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="umtnjlB0oGSe"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [27]<em id="sup-27" data-ctrid="umtndfNAYqnO"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [29]<em id="sup-29" data-ctrid="umtni3vnHlGz"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">其是位于贵州省</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E9%BB%94%E5%8D%97%E5%B8%83%E4%BE%9D%E6%97%8F%E8%8B%97%E6%97%8F%E8%87%AA%E6%B2%BB%E5%B7%9E/10533196?fromModule=lemma_inlink" target="_blank" data-from-module="summary">黔南布依族苗族自治州</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E8%8D%94%E6%B3%A2%E5%8E%BF/2598114?fromModule=lemma_inlink" target="_blank" data-from-module="summary">荔波县</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">西南部的国家级自然保护区。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="unYZyvCYv6EZ"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [16]<em id="sup-16" data-ctrid="unYZOuK9SEQm"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [28]<em id="sup-28" data-ctrid="unZ015wzENQL"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">景区总面积约46.4平方千米。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umtnD6ejcutC"></em></sup></span></div><div class="para_Y8Vvn summary_SG_8p MARK_MODULE" data-tag="paragraph" data-uuid="umtn9yKHs5DP" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区地处</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E8%B4%B5%E5%B7%9E%E9%AB%98%E5%8E%9F/7431233?fromModule=lemma_inlink" target="_blank" data-from-module="summary">贵州高原</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">南缘地带，</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">该景区地学景观分为</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%B2%A9%E6%BA%B6%E6%99%AF%E8%A7%82/4183244?fromModule=lemma_inlink" target="_blank" data-from-module="summary">岩溶景观</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%9C%B0%E8%B2%8C%E6%99%AF%E8%A7%82/2035008?fromModule=lemma_inlink" target="_blank" data-from-module="summary">地貌景观</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E6%B0%B4%E4%BD%93%E6%99%AF%E8%A7%82/6949679?fromModule=lemma_inlink" target="_blank" data-from-module="summary">水体景观</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E7%94%9F%E7%89%A9%E6%99%AF%E8%A7%82/6030024?fromModule=lemma_inlink" target="_blank" data-from-module="summary">生物景观</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">四大类，其中岩溶景观又分为地表岩溶景观和地下岩溶景观，</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%A4%A9%E9%92%9F%E6%B4%9E/5277352?fromModule=lemma_inlink" target="_blank" data-from-module="summary">天钟洞</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">是地下岩溶洞，飞云洞则是喀斯特洞穴。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umtqpvgOqGBZ"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [26<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-26" data-ctrid="umtqrG7HItQO"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区属中亚热带季风性湿润气候，四季分明，雨热同期。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [25-26<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-25" data-ctrid="umtqZbfNTNmt"></em><em id="sup-26" data-ctrid="umtqXfT9b6xZ"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">景区集水、洞、林、瀑、湖、石多种景观于一体，主要有拉雅瀑布、响水河、鸳鸯湖等。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umtry7hIMFMJ"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">景区内</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E6%A3%AE%E6%9E%97%E8%A6%86%E7%9B%96%E7%8E%87/1665674?fromModule=lemma_inlink" target="_blank" data-from-module="summary">森林覆盖率</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">达92%以上，空气中每立方厘米含</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E8%B4%9F%E6%B0%A7%E7%A6%BB%E5%AD%90/7447279?fromModule=lemma_inlink" target="_blank" data-from-module="summary">负氧离子</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">18万个，被称为“洗肺康养”胜地。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [1]<em id="sup-1"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">景区</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">植物以自然生态林为主，兼有少部分的人工植物景观。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [25<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-25" data-ctrid="umt0hq0C64cp"></em></sup></span></div><div class="para_Y8Vvn summary_SG_8p MARK_MODULE" data-tag="paragraph" data-uuid="umtof1pE3RZk" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区于1994年被国务院批准为国家级风景名胜区，是中国第六个、贵州第一个世界自然遗产地，之后又于2015年7月被评定为国家AAAAA级旅游景区。2021年，该景区被评为全国文化和旅游系统先进集体、全国青年文明号、国家级文明旅游示范单位。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [33]<em id="sup-33" data-ctrid="unZ5IG1burFb"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2024年8月，小七孔风景区日均游客量突破6万人。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="summary"><sup data-tag="ref"> [31]<em id="sup-31" data-ctrid="umtxEKr5LfHe"></em></sup></span></div></div><div class="skeletonWrap_aWFyH"><div class="skeletonContent_t61QQ"><div class="skeletonTitle_il9qB"></div><div class="skeletonList_y_nSt"><div class="skeletonItem_P0Vjg"><div class="skeletonItemCover_Ig33s"></div><div class="skeletonItemInfo_fgH45"><div class="infoName_JNVEy"></div><div class="infoDesc_ZBjQ6"></div></div></div><div class="skeletonItem_P0Vjg"><div class="skeletonItemCover_Ig33s"></div><div class="skeletonItemInfo_fgH45"><div class="infoName_JNVEy"></div><div class="infoDesc_ZBjQ6"></div></div></div><div class="skeletonItem_P0Vjg"><div class="skeletonItemCover_Ig33s"></div><div class="skeletonItemInfo_fgH45"><div class="infoName_JNVEy"></div><div class="infoDesc_ZBjQ6"></div></div></div><div class="skeletonItem_P0Vjg"><div class="skeletonItemCover_Ig33s"></div><div class="skeletonItemInfo_fgH45"><div class="infoName_JNVEy"></div><div class="infoDesc_ZBjQ6"></div></div></div></div></div><div class="skeletonContent_t61QQ"><div class="skeletonTitle_il9qB"></div><div class="skeletonList_y_nSt"><div class="skeletonItem_P0Vjg"><div class="skeletonItemCover_Ig33s"></div><div class="skeletonItemInfo_fgH45"><div class="infoName_JNVEy"></div><div class="infoDesc_ZBjQ6"></div></div></div><div class="skeletonItem_P0Vjg"><div class="skeletonItemCover_Ig33s"></div><div class="skeletonItemInfo_fgH45"><div class="infoName_JNVEy"></div><div class="infoDesc_ZBjQ6"></div></div></div><div class="skeletonItem_P0Vjg"><div class="skeletonItemCover_Ig33s"></div><div class="skeletonItemInfo_fgH45"><div class="infoName_JNVEy"></div><div class="infoDesc_ZBjQ6"></div></div></div></div></div></div><div class="basicInfo_w8mSJ J-basic-info"><dl class="basicInfoBlock_NFRcf left"><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">中文名</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [30]<em id="sup-30"></em></sup></span></dd></div><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">外文名</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">Xiaoqikong Scenic Area、Xiaoqikong Scenic Spot</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [27]<em id="sup-27"></em></sup></span></dd></div><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">地理位置</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">贵州省黔南布依族苗族自治州荔波县西南部</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [3]<em id="sup-3"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [28]<em id="sup-28"></em></sup></span></dd></div><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">气候条件</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">中亚热带季风性湿润气候</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [25<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-25"></em></sup></span></dd></div><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">开放时间</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">入园时间：8:00-16:00</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [2]<em id="sup-2"></em></sup></span></dd></div><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">景点级别</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">国家AAAAA级景区</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [9]<em id="sup-9"></em></sup></span></dd></div><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">门票价格</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">淡季（12月1日-次年2月最后一日）全价票：100元/人；旺季（3月1日-11月30日）全价票：120元/人</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [2]<em id="sup-2"></em></sup></span></dd></div></dl><dl class="basicInfoBlock_NFRcf right"><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">占地面积</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">46.4 km²</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [3]<em id="sup-3"></em></sup></span></dd></div><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">著名景点</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔桥</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [1]<em id="sup-1"></em></sup></span><span>、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E6%8B%89%E9%9B%85%E7%80%91%E5%B8%83/5537600?fromModule=lemma_inlink" target="_blank" data-from-module="basicInfo">拉雅瀑布</a></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [1]<em id="sup-1"></em></sup></span><span>、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/68%E7%BA%A7%E8%B7%8C%E6%B0%B4%E7%80%91%E5%B8%83/4130266?fromModule=lemma_inlink" target="_blank" data-from-module="basicInfo">68级跌水瀑布</a></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [3]<em id="sup-3"></em></sup></span></dd></div><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">别&nbsp;&nbsp;&nbsp;&nbsp;名</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔景区、荔波小七孔风景区</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [1]<em id="sup-1"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [29]<em id="sup-29"></em></sup></span></dd></div><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">建设者</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">艾福田</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [10]<em id="sup-10"></em></sup></span></dd></div><div class="itemWrapper_ARCnQ"><dt class="basicInfoItem_Uv49U itemName_fCVg3">景区类型</dt><dd class="basicInfoItem_Uv49U itemValue__84Tv"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">自然保护区</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item" data-flag="basicInfo"><sup data-tag="ref"> [16]<em id="sup-16"></em></sup></span></dd></div></dl></div><div class="catalogWrapper_vWQsg"><div class="catalog_Azc1m"><h2 class="catalogTitle_zUM2N">目录</h2><div class="catalogList_wA3eQ column-4_GOLLc"><ol><li class="level1_T9gak"><span class="catalogIndex_KhCQf">1</span><span class="catalogText_e2E5L"><a href="#1">命名</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">2</span><span class="catalogText_e2E5L"><a href="#2">历史沿革</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#2-1">早期</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#2-2">发展</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">3</span><span class="catalogText_e2E5L"><a href="#3">地理环境</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#3-1">地理位置</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#3-2">地形地貌</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#3-3">气候与水文</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#3-4">生物多样性</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">4</span><span class="catalogText_e2E5L"><a href="#4">景区布局</a></span></li></ol><ol><li class="level1_T9gak"><span class="catalogIndex_KhCQf">5</span><span class="catalogText_e2E5L"><a href="#5">重要景点</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#5-1">小七孔桥</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#5-2">拉雅瀑布</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#5-3">68级跌水瀑布</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#5-4">水上森林</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#5-5">翠谷瀑布</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#5-6">天钟洞</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#5-7">铜鼓桥</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#5-8">努内吉海湿地</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">6</span><span class="catalogText_e2E5L"><a href="#6">文化活动</a></span></li></ol><ol><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#6-1">非遗展示活动</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#6-2">“三月三”特色活动</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">7</span><span class="catalogText_e2E5L"><a href="#7">其他看点</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">8</span><span class="catalogText_e2E5L"><a href="#8">开发与保护</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#8-1">开发建设</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#8-2">生物保护</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">9</span><span class="catalogText_e2E5L"><a href="#9">相关文化</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#9-1">影视作品</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#9-2">相关传说</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">10</span><span class="catalogText_e2E5L"><a href="#10">重要事件</a></span></li></ol><ol><li class="level1_T9gak"><span class="catalogIndex_KhCQf">11</span><span class="catalogText_e2E5L"><a href="#11">价值意义</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#11-1">历史遗迹</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#11-2">科学研究价值</a></span></li><li class="level2_osxjy"><span class="catalogIndex_KhCQf">▪</span><span class="catalogText_e2E5L"><a href="#11-3">民族文化</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">12</span><span class="catalogText_e2E5L"><a href="#12">旅游信息</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">13</span><span class="catalogText_e2E5L"><a href="#13">公开通报</a></span></li><li class="level1_T9gak"><span class="catalogIndex_KhCQf">14</span><span class="catalogText_e2E5L"><a href="#14">地图信息</a></span></li></ol></div></div></div><div class="J-lemma-content"><div class="paraTitle_Mg50n level-1_NbeoA" data-index="1" data-tag="header" data-uuid="hsqwq1r0p6" data-level="1" data-name="命名"><h2>命名</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="1" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umlEIU1lXO0R" data-idx="0-1"><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="i12uoa82wj" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:2,&quot;nid&quot;:&quot;6140708885164546313&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;i12uoa82yy&quot;}]}"></div></div><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区内有一座桥，名为“小七孔桥”，景区之名便取自于这座桥。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="umlK5Sx4Xadj"></em></sup></span></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="2" data-tag="header" data-uuid="umlEHScWpJwZ" data-level="1" data-name="历史沿革"><h2>历史沿革</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="2" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="2-1" data-tag="header" data-uuid="umt6RyWKerXS" data-level="2" data-name="早期"><h3>早期</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="unZgJ1l5KBTs" data-idx="1-2"><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="uYq4Y9XWev0v" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:1,&quot;nid&quot;:&quot;3813720081160158885&quot;,&quot;secondId&quot;:0,&quot;source&quot;:101,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;uYvNNScIkFBG&quot;}]}"></div></div><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区内的小七孔桥始建于清道光十五年（1835年）</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [35]<em id="sup-35"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">，是沟通荔波和广西的重要桥梁。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="unZh6sqyvXrd"></em></sup></span></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="2-2" data-tag="header" data-uuid="umt6RyWgeOCl" data-level="2" data-name="发展"><h3>发展</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="unZi76pgurBG" data-idx="1-4"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区的开创者为艾福田。1984年，艾福田回到四川老家探亲，在自费考察了四川风景名胜区九寨沟后，决定开发小七孔风景旅游区。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [10]<em id="sup-10" data-ctrid="umrZhl1RExam"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umt6RyW136Hd" data-idx="1-5"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1990年8月，小七孔旅游区由</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E8%B4%B5%E5%B7%9E%E7%9C%81%E4%BA%BA%E6%B0%91%E6%94%BF%E5%BA%9C/8843653?fromModule=lemma_inlink" target="_blank" data-from-module="">贵州省人民政府</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">批准为省级风景名胜区。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [10]<em id="sup-10" data-ctrid="umrZkcDVoMar"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1991年，黔南州编制委员会办公室以黔南编办（1991）03号文件，批准同意建立副县级机构“荔波喀斯特森林风景名胜区管理处”。同年，在艾福田的倡导下，荔波第一家旅游公司诞生，该公司法定名称为“荔波县喀斯特风景名胜区旅游公司”。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [11]<em id="sup-11" data-ctrid="ums1FtDalcWu"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umt7oGlBPiKp" data-idx="1-6"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1994年1月，国务院正式批准荔波喀斯特森林风景名胜区晋升为国家级风景名胜区，将其定名为“中国荔波樟江风景名胜区”。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [10]<em id="sup-10" data-ctrid="ums27S16I9oe"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="v5DIkkrajAbq" data-idx="1-7"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2025年12月16日，贵州省首张旅游景区碳中和认证证书授牌仪式在黔南州荔波县举行，荔波县小七孔景区成为贵州省首个“碳中和景区”。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [37]<em id="sup-37"></em></sup></span></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="3" data-tag="header" data-uuid="hsqwq1r0wf" data-level="1" data-name="地理环境"><h2>地理环境</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="3" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="3-1" data-tag="header" data-uuid="unZ7pMQMcsuC" data-level="2" data-name="地理位置"><h3>地理位置</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="hsqwq1r0zu" data-idx="2-2"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区位于</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E8%8D%94%E6%B3%A2%E5%8E%BF/2598114?fromModule=lemma_inlink" target="_blank" data-from-module="">荔波县</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">西南部，距县城约28千米，距麻尾火车站约36千米，地处贵州高原南缘地带，总面积约46.4平方千米。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umm0XUCyA9eL"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">其地理位置为东经107°37′～108°18′，北纬25°7′～25°9′。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [26<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-26" data-ctrid="umt1WfQdmcDk"></em></sup></span></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="3-2" data-tag="header" data-uuid="hsqwq1r0y3" data-level="2" data-name="地形地貌"><h3>地形地貌</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umsY6HZYogbO" data-idx="2-4"><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="uYvKPBxO8eTT" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:1,&quot;nid&quot;:&quot;10878614517925354467&quot;,&quot;secondId&quot;:0,&quot;source&quot;:101,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;uYvNNScP9Rlr&quot;}]}"></div></div><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区内的地学景观总体分为</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">地貌景观、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">岩溶景观、水体景观、生物景观四大类，其中地貌景观主要有峰丛和峡谷。岩溶景观又可分为地表岩溶景观和地下岩溶景观。地表岩溶景观的成因是第四纪时，荔波地区陆地抬升，而</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E6%A8%9F%E6%B1%9F/12635118?fromModule=lemma_inlink" target="_blank" data-from-module="">樟江</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">河流下</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%88%87%E5%BA%94%E5%8A%9B/9613446?fromModule=lemma_inlink" target="_blank" data-from-module="">切应力</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">加强，该地区的抬升不是一次性完成的，而是经过多次间歇性抬升，于是就形成了该地貌景观。景区内的响水河就是地表岩溶景观。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [26<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-26" data-ctrid="umt4Xj2I3ZVF"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umt40cPqiNqY" data-idx="2-5"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">地下岩溶景观主要是岩溶洞穴，天钟洞就是典型的地下岩溶洞，早期为黄后地下河。其洞底沉积物大多为</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E7%A2%B3%E9%85%B8%E9%92%99/2984057?fromModule=lemma_inlink" target="_blank" data-from-module="">碳酸钙</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">和泥沙。而飞云洞是喀斯特洞穴，为第四纪早期黄后地下水系形成的地下河通道，从洞顶石壁多溶蚀窝穴可推测溶洞形成初期洞内流水冲击能力较强属冲水状态，即潜流涧阶段，后经构造运动使该区域大幅度呈间歇性掀斜式抬升，黄后地下河转向下切为主流入下层洞穴，飞云洞抬升至现在的位置，洞内呈半冲水状态的地下河通道及渗流洞穴阶段。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [26<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-26" data-ctrid="umt4YJQxLV3E"></em></sup></span></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="3-3" data-tag="header" data-uuid="hsqwq1r11k" data-level="2" data-name="气候与水文"><h3>气候与水文</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umt5GCSYFmKW" data-idx="2-7"><span class="text_M6NWU bold_fKI8G J-lemma-content-lemma-text" data-text="true">气候</span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="hsqwq1r12u" data-idx="2-8"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区属于中亚热带季风性湿润气候，雨热同期，四季分明，年平均气温18.3℃，年平均降水量1320.5毫米，无霜期长达283天，全年日照时数为1272小时。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [25-26<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-25" data-ctrid="umt0lWTacxni"></em><em id="sup-26" data-ctrid="umt202ENVelN"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umt5FjL2NHxV" data-idx="2-9"><span class="text_M6NWU bold_fKI8G J-lemma-content-lemma-text" data-text="true">水文</span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umt5FjLm4Ojh" data-idx="2-10"><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="uYsSV7K8qzfe" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:1,&quot;nid&quot;:&quot;10053010353200060638&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;uYvNNScXgjVi&quot;}]}"></div></div><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区内的</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%93%8D%E6%B0%B4%E6%B2%B3/12702412?fromModule=lemma_inlink" target="_blank" data-from-module="">响水河</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">为黄后地下河下游明流段，从龟背山脚冒出，长达1.6千米，落差314米，平均流量8.03立方米/秒。因河床瀑布众多，响声震天，故称为“响水河”。该地段峡谷呈“V”字型，谷坡洞穴层层分布，均是早期地下河出口。成因系第四纪（距今约2.48百万年）以来，区域大幅度大面积的间歇性抬升，樟江下切，响水河为适应侵蚀基准面下降出现间歇性下切，河床形成多级裂点，也就是该瀑布的所在之处；谷坡地下河为适应响水河下切进入下一层洞穴，雨季时可见有水流出。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umneG1z5fMYf"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="umt5UNGs88wg" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807263"><div class="albumWrap_E1OYe"><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr singlePage_QBeXg"><a class="swiperLi_jbFeq" type="pic" id="album-image-7dd98d1001e93901213fda047ab543e736d12f2e38ca" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/7dd98d1001e93901213fda047ab543e736d12f2e38ca-bkimg-process,v_1,rw_960,rh_640,maxl_426?x-bce-process=image/format,f_auto" alt="小七孔风景区响水河" height="140" width="211" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔风景区响水河</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-caef76094b36acaf2eddd8349e829a1001e9380136fd" style="height:166px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/caef76094b36acaf2eddd8349e829a1001e9380136fd-bkimg-process,v_1,rw_1080,rh_720,maxl_426?x-bce-process=image/format,f_auto" alt="响水河风光" height="140" width="211" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">响水河风光</div></a></div></div></div></div></div><div style="display:none" class="value-album" data-module-value="{&quot;albumId&quot;:6297807263,&quot;content&quot;:[{&quot;albumId&quot;:6297807263,&quot;desc&quot;:&quot;小七孔风景区响水河&quot;,&quot;height&quot;:640,&quot;src&quot;:&quot;7dd98d1001e93901213fda047ab543e736d12f2e38ca&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SOX4ovC01m&quot;,&quot;width&quot;:960},{&quot;albumId&quot;:6297807263,&quot;desc&quot;:&quot;响水河风光&quot;,&quot;height&quot;:720,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;caef76094b36acaf2eddd8349e829a1001e9380136fd&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SOYqcVDsAa&quot;,&quot;width&quot;:1080}],&quot;coverPic&quot;:{&quot;albumId&quot;:6297807263,&quot;desc&quot;:&quot;小七孔风景区响水河&quot;,&quot;height&quot;:640,&quot;src&quot;:&quot;7dd98d1001e93901213fda047ab543e736d12f2e38ca&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/7dd98d1001e93901213fda047ab543e736d12f2e38ca?x-bce-process=image/resize,m_lfit,w_1920,limit_1&quot;,&quot;uuid&quot;:&quot;v0SOX4ovC01m&quot;,&quot;width&quot;:960},&quot;desc&quot;:&quot;小七孔风景区响水河&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:2}"></div></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="unZ8epGkepCH" data-idx="2-11"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">卧龙潭在距小七孔风景区西门数百米的位置。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umxVYuwPuGnt"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">其原名翁龙潭，</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">为喀斯特暗河，是卧龙河的源头。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [7-8]<em id="sup-7" data-ctrid="umrMwtnWL1hw"></em><em id="sup-8" data-ctrid="umrMuMKtqtqT"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">自人们在这里筑坝引水发电后，其潭水又流入响水河。卧龙潭也因此成为两河总源。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [7]<em id="sup-7" data-ctrid="umrLZGgvtumx"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">暗河从引水发电筑成的坝上飞泻直下，水声轰鸣。潭边还有怪石、树林、高山等景物。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [6]<em id="sup-6" data-ctrid="umrKVhII70wr"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="unZ8nskqZ9tZ" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807262"><div class="albumWrap_E1OYe"><div class="swiperPrevBtn_Ye7CY disabled_pmrOD hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="M5.516 0 1.112 4.684a1.946 1.946 0 0 0 0 2.632L5.516 12 7 10.421 2.844 6 7 1.579 5.516 0Z"></path></svg></div><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr"><a class="swiperLi_jbFeq" type="pic" id="album-image-cf1b9d16fdfaaf51f3ded855870d83eef01f3b29cc9a" style="height:166px;padding-right:16px"><img 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src="https://bkimg.cdn.bcebos.com/smart/314e251f95cad1c8a78677e79d657009c93d71cffbe5-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="卧龙潭风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">卧龙潭风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-9e3df8dcd100baa1cd11bb7fa54bae12c8fcc2ce80f9" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/9e3df8dcd100baa1cd11bb7fa54bae12c8fcc2ce80f9-bkimg-process,v_1,rw_1280,rh_853,maxl_426?x-bce-process=image/format,f_auto" alt="卧龙潭风光" height="140" width="211.08323563892145" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">卧龙潭风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-4034970a304e251f95ca6d3845ddde177f3e6609f5e5" style="height:166px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/4034970a304e251f95ca6d3845ddde177f3e6609f5e5-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="卧龙潭风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">卧龙潭风光</div></a></div></div><div class="swiperNextBtn_rFg5I hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="m1.484 0 4.404 4.684a1.946 1.946 0 0 1 0 2.632L1.484 12 0 10.421 4.156 6 0 1.579 1.484 0Z"></path></svg></div></div></div></div><div style="display:none" class="value-album" data-module-value="{&quot;albumId&quot;:6297807262,&quot;content&quot;:[{&quot;albumId&quot;:6297807262,&quot;desc&quot;:&quot;小七孔风景区卧龙潭&quot;,&quot;height&quot;:640,&quot;src&quot;:&quot;cf1b9d16fdfaaf51f3ded855870d83eef01f3b29cc9a&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SEvoIDg9uY&quot;,&quot;width&quot;:960},{&quot;albumId&quot;:6297807262,&quot;desc&quot;:&quot;卧龙潭风光&quot;,&quot;height&quot;:744,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;960a304e251f95cad1c81a762b4c683e6709c83df4e5&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SExOYzuGNX&quot;,&quot;width&quot;:1218},{&quot;albumId&quot;:6297807262,&quot;desc&quot;:&quot;卧龙潭风光&quot;,&quot;height&quot;:649,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;314e251f95cad1c8a78677e79d657009c93d71cffbe5&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SExPvY1zEX&quot;,&quot;width&quot;:1280},{&quot;albumId&quot;:6297807262,&quot;desc&quot;:&quot;卧龙潭风光&quot;,&quot;height&quot;:853,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;9e3df8dcd100baa1cd11bb7fa54bae12c8fcc2ce80f9&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SJU3OSzGSw&quot;,&quot;width&quot;:1280},{&quot;albumId&quot;:6297807262,&quot;desc&quot;:&quot;卧龙潭风光&quot;,&quot;height&quot;:656,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;4034970a304e251f95ca6d3845ddde177f3e6609f5e5&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SExPMGvhgP&quot;,&quot;width&quot;:1280}],&quot;coverPic&quot;:{&quot;albumId&quot;:6297807262,&quot;desc&quot;:&quot;小七孔风景区卧龙潭&quot;,&quot;height&quot;:640,&quot;src&quot;:&quot;cf1b9d16fdfaaf51f3ded855870d83eef01f3b29cc9a&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/cf1b9d16fdfaaf51f3ded855870d83eef01f3b29cc9a?x-bce-process=image/resize,m_lfit,w_1920,limit_1&quot;,&quot;uuid&quot;:&quot;v0SEvoIDg9uY&quot;,&quot;width&quot;:960},&quot;desc&quot;:&quot;小七孔风景区卧龙潭&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:5}"></div></div><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="uYsUALBNNGHq" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:1,&quot;nid&quot;:&quot;4093510167269387492&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;uYvNNSc26Vru&quot;},{&quot;form&quot;:2,&quot;mountType&quot;:1,&quot;nid&quot;:&quot;1777356520606613530&quot;,&quot;secondId&quot;:0,&quot;source&quot;:105,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;uYvNNSccMeKX&quot;},{&quot;form&quot;:2,&quot;mountType&quot;:1,&quot;nid&quot;:&quot;17946492908907671128&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;uYvNNScHwFho&quot;}]}"></div></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="unZ8vfqUnxOu" data-idx="2-12"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">鸳鸯湖距卧龙潭约5000米，是典型的喀斯特盲谷湖。其水域面积约20公顷，深约40米，位于黄后地下暗河下游明流段，主要由上、下两个大湖组成。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umm3SoEs3nBF"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">鸳鸯湖内常年生长着一片重阳木，因此鸳鸯湖又被称为“东方亚马逊”。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="umlPRAAStUyv"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="unZ8BDBjixSt" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807261"><div class="albumWrap_E1OYe"><div class="swiperPrevBtn_Ye7CY disabled_pmrOD hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="M5.516 0 1.112 4.684a1.946 1.946 0 0 0 0 2.632L5.516 12 7 10.421 2.844 6 7 1.579 5.516 0Z"></path></svg></div><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr"><a class="swiperLi_jbFeq" type="pic" id="album-image-9825bc315c6034a85edff56bc04a5e540923dc54d89a" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/9825bc315c6034a85edff56bc04a5e540923dc54d89a-bkimg-process,v_1,rw_960,rh_640,maxl_426?x-bce-process=image/format,f_auto" alt="小七孔风景区鸳鸯湖" height="140" width="211" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔风景区鸳鸯湖</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-0ff41bd5ad6eddc451da5d3bdb80a1fd5266d11695e5" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/0ff41bd5ad6eddc451da5d3bdb80a1fd5266d11695e5-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="鸳鸯湖风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">鸳鸯湖风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-1ad5ad6eddc451da81cbe42b54a64566d016082494e5" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/1ad5ad6eddc451da81cbe42b54a64566d016082494e5-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="鸳鸯湖风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">鸳鸯湖风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-902397dda144ad345982c04332f91bf431adcaef2ff9" style="height:166px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/902397dda144ad345982c04332f91bf431adcaef2ff9-bkimg-process,v_1,rw_1280,rh_1706,maxl_284?x-bce-process=image/format,f_auto" alt="鸳鸯湖风光" height="140" width="104.54161781946073" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">鸳鸯湖风光</div></a></div></div><div class="swiperNextBtn_rFg5I hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="m1.484 0 4.404 4.684a1.946 1.946 0 0 1 0 2.632L1.484 12 0 10.421 4.156 6 0 1.579 1.484 0Z"></path></svg></div></div></div></div><div style="display:none" class="value-album" data-module-value="{&quot;albumId&quot;:6297807261,&quot;content&quot;:[{&quot;albumId&quot;:6297807261,&quot;desc&quot;:&quot;小七孔风景区鸳鸯湖&quot;,&quot;height&quot;:640,&quot;src&quot;:&quot;9825bc315c6034a85edff56bc04a5e540923dc54d89a&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SELcxXZTNG&quot;,&quot;width&quot;:960},{&quot;albumId&quot;:6297807261,&quot;desc&quot;:&quot;鸳鸯湖风光&quot;,&quot;height&quot;:648,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;0ff41bd5ad6eddc451da5d3bdb80a1fd5266d11695e5&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SENjkgjB6M&quot;,&quot;width&quot;:1280},{&quot;albumId&quot;:6297807261,&quot;desc&quot;:&quot;鸳鸯湖风光&quot;,&quot;height&quot;:649,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;1ad5ad6eddc451da81cbe42b54a64566d016082494e5&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SENiRcCOCx&quot;,&quot;width&quot;:1280},{&quot;albumId&quot;:6297807261,&quot;desc&quot;:&quot;鸳鸯湖风光&quot;,&quot;height&quot;:1706,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;902397dda144ad345982c04332f91bf431adcaef2ff9&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SJrJTLMkQs&quot;,&quot;width&quot;:1280}],&quot;coverPic&quot;:{&quot;albumId&quot;:6297807261,&quot;desc&quot;:&quot;小七孔风景区鸳鸯湖&quot;,&quot;height&quot;:640,&quot;src&quot;:&quot;9825bc315c6034a85edff56bc04a5e540923dc54d89a&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/9825bc315c6034a85edff56bc04a5e540923dc54d89a?x-bce-process=image/resize,m_lfit,w_1920,limit_1&quot;,&quot;uuid&quot;:&quot;v0SELcxXZTNG&quot;,&quot;width&quot;:960},&quot;desc&quot;:&quot;小七孔风景区鸳鸯湖&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:4}"></div></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="3-4" data-tag="header" data-uuid="hsqwq1r14k" data-level="2" data-name="生物多样性"><h3>生物多样性</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="hsqwq1r166" data-idx="2-14"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区内</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E6%A3%AE%E6%9E%97%E8%A6%86%E7%9B%96%E7%8E%87/1665674?fromModule=lemma_inlink" target="_blank" data-from-module="">森林覆盖率</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">达92%以上，空气中每立方厘米含</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E8%B4%9F%E6%B0%A7%E7%A6%BB%E5%AD%90/7447279?fromModule=lemma_inlink" target="_blank" data-from-module="">负氧离子</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">18万个。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">景区内的植物以自然生态林为主，兼有少部分的人工植物景观，主要植物有</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E9%A9%AC%E5%B0%BC%E6%8B%89%E8%8D%89/500585?fromModule=lemma_inlink" target="_blank" data-from-module="">马尼拉草</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、银杏、石楠等。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [25<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-25" data-ctrid="umt0hq0C64cp"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="unZ7VsV6afCU" data-idx="2-15"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区的动物物种丰富度高，截至2008年，其拥有保护动物45种，其中极危等级的有3种，濒危等级的有4种，易危等级的有38种；地方特有动物48种，不少是中国特有种，尤其是洞穴动物。景区内列入IUCN物种红色名录和中国物种红色名录的植物种类121种，受到严重威胁的濒危植物共计83种，特有植物41种。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [32<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-32" data-ctrid="umP0shWYteEP"></em></sup></span></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="4" data-tag="header" data-uuid="hsqwq1r180" data-level="1" data-name="景区布局"><h2>景区布局</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="4" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umnkF8X2RnzI" data-idx="3-1"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">从小七孔景区的西门开始，一路可经过卧龙潭、鸳鸯湖、翠谷瀑布、水上森林、石上森林、断桥飞瀑、68级跌水瀑布、拉雅瀑布等景点，最后到达小七孔古桥。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [4]<em id="sup-4" data-ctrid="umnuBhRo8ZbH"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="i12uoa832o" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:2,&quot;nid&quot;:&quot;4193634406861638400&quot;,&quot;secondId&quot;:0,&quot;source&quot;:101,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;i12uoa834h&quot;},{&quot;form&quot;:2,&quot;mountType&quot;:3,&quot;nid&quot;:&quot;11236051784731858308&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;vlog｜小七孔景区卧龙潭瀑布&quot;,&quot;uuid&quot;:&quot;i1meesrvbv&quot;},{&quot;form&quot;:2,&quot;mountType&quot;:3,&quot;nid&quot;:&quot;1249666641992185815&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;贵州荔波小七孔，门票170元，进去看看到底值不值？&quot;,&quot;uuid&quot;:&quot;i1meesrve0&quot;}]}"></div></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umnuA8IcOFQb" data-idx="3-2"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">如果是从东门开始，游览全程则为上坡。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [4]<em id="sup-4" data-ctrid="umnkLQtrerOx"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">景区之首变为小七孔桥，过桥曲行百米多，可见拉雅瀑布。其余景观则与上述描述的先后顺序相反。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="umnvjgE2lCBJ"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [4]<em id="sup-4" data-ctrid="umnvm69ZcayC"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umnkN4PFySzm" data-idx="3-3"><div class="lemmaPicture_HinqL layoutCenter_mfqz5 richTest_gQ33Q disable-select J-lemma-content-single-image" 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data-tts-catalog="5" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="5-1" data-tag="header" data-uuid="umlKJORgNx2m" data-level="2" data-name="小七孔桥"><h3>小七孔桥</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umlKK98q6n2k" data-idx="4-2"><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="i1meesrvgp" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:3,&quot;nid&quot;:&quot;9529110733175176197&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;荔波小七孔的地标建筑小七孔古桥，一幅中国古典山水画卷的既视感&quot;,&quot;uuid&quot;:&quot;i1meesrvio&quot;}]}"></div></div><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%B0%8F%E4%B8%83%E5%AD%94%E6%A1%A5/66233045?fromModule=lemma_inlink" target="_blank" data-from-module="">小七孔桥</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">位于景区之首，建于清代道光十五年（1835年），是一座七孔古石桥。其桥长25米，桥面宽1.8米，拱高4米。小七孔桥由麻石条砌成，桥身爬满藤蔓和蕨类植物，桥下是涵碧潭。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="umlOrhzrDeVm"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔桥古为黔南通往广西商旅交通要道，横跨响水河。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umm1ILUILBrV"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="umm3eYMjb93I" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807260"><div class="albumWrap_E1OYe"><div class="swiperPrevBtn_Ye7CY disabled_pmrOD hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="M5.516 0 1.112 4.684a1.946 1.946 0 0 0 0 2.632L5.516 12 7 10.421 2.844 6 7 1.579 5.516 0Z"></path></svg></div><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr"><a class="swiperLi_jbFeq" type="pic" id="album-image-2cf5e0fe9925bc315c60b70fa0879ab1cb134854daa9" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/2cf5e0fe9925bc315c60b70fa0879ab1cb134854daa9-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="小七孔风景区小七孔桥" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔风景区小七孔桥</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-77094b36acaf2edda3cc002e6f4b16e93901203f35fa" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/77094b36acaf2edda3cc002e6f4b16e93901203f35fa-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="小七孔桥风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔桥风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-95eef01f3a292df5e0fe05d25e6a4b6034a85fdfd5fa" style="height:166px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/95eef01f3a292df5e0fe05d25e6a4b6034a85fdfd5fa-bkimg-process,v_1,rw_3,rh_4,maxl_284?x-bce-process=image/format,f_auto" alt="小七孔桥风光" height="140" width="104.5" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔桥风光</div></a></div></div><div class="swiperNextBtn_rFg5I hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="m1.484 0 4.404 4.684a1.946 1.946 0 0 1 0 2.632L1.484 12 0 10.421 4.156 6 0 1.579 1.484 0Z"></path></svg></div></div></div></div><div style="display:none" class="value-album" data-module-value="{&quot;albumId&quot;:6297807260,&quot;content&quot;:[{&quot;albumId&quot;:6297807260,&quot;desc&quot;:&quot;小七孔风景区小七孔桥&quot;,&quot;height&quot;:350,&quot;src&quot;:&quot;2cf5e0fe9925bc315c60b70fa0879ab1cb134854daa9&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SNp7YA6fHc&quot;,&quot;width&quot;:700},{&quot;albumId&quot;:6297807260,&quot;desc&quot;:&quot;小七孔桥风光&quot;,&quot;height&quot;:607,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;77094b36acaf2edda3cc002e6f4b16e93901203f35fa&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SNqhhMI1xw&quot;,&quot;width&quot;:1080},{&quot;albumId&quot;:6297807260,&quot;desc&quot;:&quot;小七孔桥风光&quot;,&quot;height&quot;:1896,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;95eef01f3a292df5e0fe05d25e6a4b6034a85fdfd5fa&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SNFsZUKuYw&quot;,&quot;width&quot;:1080}],&quot;coverPic&quot;:{&quot;albumId&quot;:6297807260,&quot;desc&quot;:&quot;小七孔风景区小七孔桥&quot;,&quot;height&quot;:350,&quot;src&quot;:&quot;2cf5e0fe9925bc315c60b70fa0879ab1cb134854daa9&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/2cf5e0fe9925bc315c60b70fa0879ab1cb134854daa9?x-bce-process=image/resize,m_lfit,w_1400,limit_1&quot;,&quot;uuid&quot;:&quot;v0SNp7YA6fHc&quot;,&quot;width&quot;:700},&quot;desc&quot;:&quot;小七孔风景区小七孔桥&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:3}"></div></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="5-2" data-tag="header" data-uuid="umlMjIS75kzu" data-level="2" data-name="拉雅瀑布"><h3>拉雅瀑布</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umlMjYVdqEzw" data-idx="4-4"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">过小七孔桥行数百米即可看见</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E6%8B%89%E9%9B%85%E7%80%91%E5%B8%83/5537600?fromModule=lemma_inlink" target="_blank" data-from-module="">拉雅瀑布</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">。</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">“拉雅”是布依族语，意思为美丽的姑娘。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="umxTELX3zE4t"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">该瀑布为一级景点，其源自响水河上游山体洞泉，截流沿崖体陡岸悬空而下。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umm4jwIThVTh"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [6]<em id="sup-6" data-ctrid="umrIgt6oyZYJ"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">拉雅瀑布宽10米，落差30多米。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="umlOQ3hcZamp"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="i12uoa839a" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:2,&quot;nid&quot;:&quot;8507627510330548599&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;i12uoa83ax&quot;},{&quot;form&quot;:2,&quot;mountType&quot;:3,&quot;nid&quot;:&quot;7787383678142753222&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;超清航拍 荔波小七孔景区（三） 拉雅瀑布&amp;68级跌水瀑布 颇为壮观&quot;,&quot;uuid&quot;:&quot;i1meesrvl3&quot;}]}"></div></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umrIa203o0zC" data-idx="4-5"><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="umlMrJZRmYic" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807259"><div class="albumWrap_E1OYe"><div class="swiperPrevBtn_Ye7CY disabled_pmrOD hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="M5.516 0 1.112 4.684a1.946 1.946 0 0 0 0 2.632L5.516 12 7 10.421 2.844 6 7 1.579 5.516 0Z"></path></svg></div><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr"><a class="swiperLi_jbFeq" type="pic" id="album-image-1b4c510fd9f9d72a60591da42a723f34349b033b0d4b" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/1b4c510fd9f9d72a60591da42a723f34349b033b0d4b-bkimg-process,v_1,rw_800,rh_533,maxl_426?x-bce-process=image/format,f_auto" alt="小七孔风景区拉雅瀑布" height="140" width="211.13320825515947" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔风景区拉雅瀑布</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-4bed2e738bd4b31c8701b67a658d307f9e2f060852e4" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/4bed2e738bd4b31c8701b67a658d307f9e2f060852e4-bkimg-process,v_1,rw_942,rh_564,maxl_474?x-bce-process=image/format,f_auto" alt="拉雅瀑布风光" height="140" width="235.17021276595744" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">拉雅瀑布风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-2f738bd4b31c8701a18b9f27c524892f0708293851e4" style="height:166px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/2f738bd4b31c8701a18b9f27c524892f0708293851e4-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="拉雅瀑布风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">拉雅瀑布风光</div></a></div></div><div class="swiperNextBtn_rFg5I hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="m1.484 0 4.404 4.684a1.946 1.946 0 0 1 0 2.632L1.484 12 0 10.421 4.156 6 0 1.579 1.484 0Z"></path></svg></div></div></div></div><div style="display:none" class="value-album" data-module-value="{&quot;albumId&quot;:6297807259,&quot;content&quot;:[{&quot;albumId&quot;:6297807259,&quot;desc&quot;:&quot;小七孔风景区拉雅瀑布&quot;,&quot;height&quot;:533,&quot;src&quot;:&quot;1b4c510fd9f9d72a60591da42a723f34349b033b0d4b&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SF7R6BeAEk&quot;,&quot;width&quot;:800},{&quot;albumId&quot;:6297807259,&quot;desc&quot;:&quot;拉雅瀑布风光&quot;,&quot;height&quot;:564,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;4bed2e738bd4b31c8701b67a658d307f9e2f060852e4&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SFa3oKV51A&quot;,&quot;width&quot;:942},{&quot;albumId&quot;:6297807259,&quot;desc&quot;:&quot;拉雅瀑布风光&quot;,&quot;height&quot;:646,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;2f738bd4b31c8701a18b9f27c524892f0708293851e4&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SFa7St87Ul&quot;,&quot;width&quot;:1280}],&quot;coverPic&quot;:{&quot;albumId&quot;:6297807259,&quot;desc&quot;:&quot;小七孔风景区拉雅瀑布&quot;,&quot;height&quot;:533,&quot;src&quot;:&quot;1b4c510fd9f9d72a60591da42a723f34349b033b0d4b&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/1b4c510fd9f9d72a60591da42a723f34349b033b0d4b?x-bce-process=image/resize,m_lfit,w_1600,limit_1&quot;,&quot;uuid&quot;:&quot;v0SF7R6BeAEk&quot;,&quot;width&quot;:800},&quot;desc&quot;:&quot;小七孔风景区拉雅瀑布&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:3}"></div></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="5-3" data-tag="header" data-uuid="umlXrryIQE6E" data-level="2" data-name="68级跌水瀑布"><h3>68级跌水瀑布</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umxTToVZghYT" data-idx="4-7"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">过拉雅瀑布即可看见</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/68%E7%BA%A7%E8%B7%8C%E6%B0%B4%E7%80%91%E5%B8%83/4130266?fromModule=lemma_inlink" target="_blank" data-from-module="">68级跌水瀑布</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">。</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">68级跌水瀑布位于响水河谷，全长约1.6千米，总落差约110米，宽约40米。因高原晚期强烈抬升，河流迅速下切350到500米而形成该瀑布群。在不到2千米的弯曲河道里，密集着六十八级形态不同的瀑布、跌水。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umm2sGUfdhHA"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="i1meesrvo8" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:1,&quot;nid&quot;:&quot;17930895690552939521&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;小七孔68级跌水瀑布&quot;,&quot;uuid&quot;:&quot;uYvNNScO4UAe&quot;},{&quot;form&quot;:2,&quot;mountType&quot;:1,&quot;nid&quot;:&quot;4027803428752493854&quot;,&quot;secondId&quot;:0,&quot;source&quot;:105,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;uYvNNScXM5qc&quot;}]}"></div></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umm2TQ68ktvU" data-idx="4-8"><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="umm2Afw8isus" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807258"><div class="albumWrap_E1OYe"><div class="swiperPrevBtn_Ye7CY disabled_pmrOD hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="M5.516 0 1.112 4.684a1.946 1.946 0 0 0 0 2.632L5.516 12 7 10.421 2.844 6 7 1.579 5.516 0Z"></path></svg></div><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr"><a class="swiperLi_jbFeq" type="pic" id="album-image-f31fbe096b63f6246b603c95791cfcf81a4c510f0556" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/f31fbe096b63f6246b603c95791cfcf81a4c510f0556-bkimg-process,v_1,rw_750,rh_500,maxl_426?x-bce-process=image/format,f_auto" alt="小七孔风景区68级跌水瀑布" height="140" width="211" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔风景区68级跌水瀑布</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-342ac65c10385343fbf2d5e07148a77eca80643822e4" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/342ac65c10385343fbf2d5e07148a77eca80643822e4-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="68级跌水瀑布风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">68级跌水瀑布风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-3b87e950352ac65c103836b219a9a5119313b17e1ce4" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/3b87e950352ac65c103836b219a9a5119313b17e1ce4-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="68级跌水瀑布风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">68级跌水瀑布风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-3bf33a87e950352ac65c74c9b118ecf2b21192131de4" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/3bf33a87e950352ac65c74c9b118ecf2b21192131de4-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="68级跌水瀑布风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">68级跌水瀑布风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-377adab44aed2e738bd4a6e4655ab68b87d6267f4cfd" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/377adab44aed2e738bd4a6e4655ab68b87d6267f4cfd-bkimg-process,v_1,rw_3,rh_4,maxl_284?x-bce-process=image/format,f_auto" alt="68级跌水瀑布风光" height="140" width="104.5" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">68级跌水瀑布风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-dbb44aed2e738bd4b31c91f943d090d6277f9f2f53fd" style="height:166px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/dbb44aed2e738bd4b31c91f943d090d6277f9f2f53fd-bkimg-process,v_1,rw_768,rh_1024,maxl_284?x-bce-process=image/format,f_auto" alt="68级跌水瀑布风光" height="140" width="104.5" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">68级跌水瀑布风光</div></a></div></div><div class="swiperNextBtn_rFg5I hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="m1.484 0 4.404 4.684a1.946 1.946 0 0 1 0 2.632L1.484 12 0 10.421 4.156 6 0 1.579 1.484 0Z"></path></svg></div></div></div></div><div style="display:none" class="value-album" 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class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="5-4" data-tag="header" data-uuid="umlM0kXnu0Zz" data-level="2" data-name="水上森林"><h3>水上森林</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umOHMeAqbSNQ" data-idx="4-10"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">水上森林位于响水河喀斯特槽谷森林河床之上，因“树在石中长、水在石上流”而得名。其全长约2000米，含水上森林丛林带、拉金湿地、苦竹沟等景点。该景区内所有树木均扎根在河床岩石缝中，虽被激流长期浸没，仍然郁郁葱葱，如此奇妙的水上生态系统在全球</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">喀斯特地貌中绝无仅有。丛林密匝如屏，浅浪冬暖夏凉，传说古时常有仙女在此沐浴，故又称“瑶池”。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="v0SG37hdmRls"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [6]<em id="sup-6" data-ctrid="umOHNOkHNGCq"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="i1meesrvt3" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:3,&quot;nid&quot;:&quot;3924489064971366267&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;小七孔水上森林是一道自然奇观漫步其中仿佛置身于绿意盎然的画卷&quot;,&quot;uuid&quot;:&quot;i1meesrvv3&quot;},{&quot;form&quot;:2,&quot;mountType&quot;:3,&quot;nid&quot;:&quot;4805462845147428851&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;荔波小七孔景区的水上森林，因“树在石中长、水在石上流”而得名&quot;,&quot;uuid&quot;:&quot;i1meesrvww&quot;}]}"></div></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umlLXShTvaGr" data-idx="4-11"><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="umlM92FmhIMJ" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807257"><div 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class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="5-5" data-tag="header" data-uuid="umlLSDOPVJUQ" data-level="2" data-name="翠谷瀑布"><h3>翠谷瀑布</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umrInF9eWmKe" data-idx="4-13"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">翠谷瀑布坐落于响水河上游，紧靠努内吉海湿地。该瀑布</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">为一级景点，</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">瀑布高达60多米，是一个封闭的峰丛洼地。瀑布旁群山苍翠，翠谷也因此而名。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [6]<em id="sup-6" data-ctrid="umrIOM6RqUWt"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="v0SPNTuET7vT" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807256"><div class="albumWrap_E1OYe"><div 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data-module-value="{&quot;albumId&quot;:6297807256,&quot;content&quot;:[{&quot;albumId&quot;:6297807256,&quot;desc&quot;:&quot;小七孔风景区翠谷瀑布&quot;,&quot;height&quot;:640,&quot;src&quot;:&quot;cf1b9d16fdfaaf51f3dec36b8c0d83eef01f3b29cc94&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SGu7nmLS8W&quot;,&quot;width&quot;:960},{&quot;albumId&quot;:6297807256,&quot;desc&quot;:&quot;翠谷瀑布风光&quot;,&quot;height&quot;:1175,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;5d6034a85edf8db1cb13eaa3eb78ca54564e9358defa&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SNMrZIR30R&quot;,&quot;width&quot;:1080},{&quot;albumId&quot;:6297807256,&quot;desc&quot;:&quot;翠谷瀑布风光&quot;,&quot;height&quot;:1440,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;0824ab18972bd40735fa003a99d289510fb30e24a3fa&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SO4mfXZK7H&quot;,&quot;width&quot;:1080}],&quot;coverPic&quot;:{&quot;albumId&quot;:6297807256,&quot;desc&quot;:&quot;小七孔风景区翠谷瀑布&quot;,&quot;height&quot;:640,&quot;src&quot;:&quot;cf1b9d16fdfaaf51f3dec36b8c0d83eef01f3b29cc94&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/cf1b9d16fdfaaf51f3dec36b8c0d83eef01f3b29cc94?x-bce-process=image/resize,m_lfit,w_1920,limit_1&quot;,&quot;uuid&quot;:&quot;v0SGu7nmLS8W&quot;,&quot;width&quot;:960},&quot;desc&quot;:&quot;小七孔风景区翠谷瀑布&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:3}"></div></div><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="i17h4b27j9" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:2,&quot;nid&quot;:&quot;5181898929340670807&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;i17h4b27l8&quot;},{&quot;form&quot;:2,&quot;mountType&quot;:3,&quot;nid&quot;:&quot;10515880287017770726&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;小七孔翠谷瀑布，处在景区中央，像一条银丝带很是秀美&quot;,&quot;uuid&quot;:&quot;i1meesrvz7&quot;}]}"></div></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="5-6" data-tag="header" data-uuid="umlMvBmtptBM" data-level="2" data-name="天钟洞"><h3>天钟洞</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umrHi4mF6GKw" data-idx="4-15"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%A4%A9%E9%92%9F%E6%B4%9E/5277352?fromModule=lemma_inlink" target="_blank" data-from-module="">天钟洞</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">位于小七孔风景区汤粑石林的半坡上，海拔740多米，洞长近千米，有12个厅（鳄鱼厅、金鸡厅、百兽厅和犀牛厅等），两个洞口。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="umOIFSV2lple"></em></sup></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [6]<em id="sup-6" data-ctrid="umOIH2MdMQ2L"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">洞内有一高达近10米的巨型石笋，其形状犹如天钟倒扣在地上，洞名也因此而得。天钟洞内还有石花、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E7%9F%B3%E6%A0%91/1527989?fromModule=lemma_inlink" target="_blank" data-from-module="">石树</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E7%9F%B3%E5%B9%94/2052268?fromModule=lemma_inlink" target="_blank" data-from-module="">石幔</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E7%9F%B3%E6%9F%B1/79912?fromModule=lemma_inlink" target="_blank" data-from-module="">石柱</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E7%9F%B3%E7%AC%8B/75368?fromModule=lemma_inlink" target="_blank" data-from-module="">石笋</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">等景观。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [6]<em id="sup-6" data-ctrid="umrI2S6JoHVs"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="i18mr6m531" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:2,&quot;nid&quot;:&quot;8883284062021241223&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;i18mr6m552&quot;},{&quot;form&quot;:2,&quot;mountType&quot;:3,&quot;nid&quot;:&quot;5043218937191396682&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;小七孔景区天钟洞&quot;,&quot;uuid&quot;:&quot;i1meesrw1r&quot;}]}"></div></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umlMvTwclVDP" data-idx="4-16"><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="umlMEVzemfQe" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807255"><div class="albumWrap_E1OYe"><div class="swiperPrevBtn_Ye7CY disabled_pmrOD hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="M5.516 0 1.112 4.684a1.946 1.946 0 0 0 0 2.632L5.516 12 7 10.421 2.844 6 7 1.579 5.516 0Z"></path></svg></div><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr"><a class="swiperLi_jbFeq" type="pic" id="album-image-a9d3fd1f4134970a304ebb966b92c6c8a786c917f74b" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/a9d3fd1f4134970a304ebb966b92c6c8a786c917f74b-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="小七孔风景区天钟洞" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔风景区天钟洞</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-bd315c6034a85edf8db169e0ab0f1e23dd54574edfe6" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/bd315c6034a85edf8db169e0ab0f1e23dd54574edfe6-bkimg-process,v_1,rw_1280,rh_853,maxl_426?x-bce-process=image/format,f_auto" alt="天钟洞风光" height="140" width="211.08323563892145" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">天钟洞风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-e7cd7b899e510fb30f24a9513b68df95d143ac4ba6fb" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/e7cd7b899e510fb30f24a9513b68df95d143ac4ba6fb-bkimg-process,v_1,rw_3,rh_4,maxl_284?x-bce-process=image/format,f_auto" alt="天钟洞风光" height="140" width="104.5" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">天钟洞风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-962bd40735fae6cd7b8976a7ede8182442a7d833a1fb" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/962bd40735fae6cd7b8976a7ede8182442a7d833a1fb-bkimg-process,v_1,rw_3,rh_4,maxl_284?x-bce-process=image/format,f_auto" alt="天钟洞风光" height="140" width="104.5" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">天钟洞风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-d50735fae6cd7b899e51e645ed7f55a7d933c995a0fb" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/d50735fae6cd7b899e51e645ed7f55a7d933c995a0fb-bkimg-process,v_1,rw_3,rh_4,maxl_284?x-bce-process=image/format,f_auto" alt="天钟洞风光" height="140" width="104.5" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">天钟洞风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-0823dd54564e9258d1091a267ed9c658ccbf6d81e0fd" style="height:166px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/0823dd54564e9258d1091a267ed9c658ccbf6d81e0fd-bkimg-process,v_1,rw_1080,rh_1440,maxl_284?x-bce-process=image/format,f_auto" alt="天钟洞风光" height="140" width="104.5" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">天钟洞风光</div></a></div></div><div class="swiperNextBtn_rFg5I hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="m1.484 0 4.404 4.684a1.946 1.946 0 0 1 0 2.632L1.484 12 0 10.421 4.156 6 0 1.579 1.484 0Z"></path></svg></div></div></div></div><div style="display:none" class="value-album" data-module-value="{&quot;albumId&quot;:6297807255,&quot;content&quot;:[{&quot;albumId&quot;:6297807255,&quot;desc&quot;:&quot;小七孔风景区天钟洞&quot;,&quot;height&quot;:416,&quot;src&quot;:&quot;a9d3fd1f4134970a304ebb966b92c6c8a786c917f74b&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SGY9bz2BjS&quot;,&quot;width&quot;:780},{&quot;albumId&quot;:6297807255,&quot;desc&quot;:&quot;天钟洞风光&quot;,&quot;height&quot;:853,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;bd315c6034a85edf8db169e0ab0f1e23dd54574edfe6&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SIwJuPtScU&quot;,&quot;width&quot;:1280},{&quot;albumId&quot;:6297807255,&quot;desc&quot;:&quot;天钟洞风光&quot;,&quot;height&quot;:2202,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;e7cd7b899e510fb30f24a9513b68df95d143ac4ba6fb&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SMu88cZonR&quot;,&quot;width&quot;:1280},{&quot;albumId&quot;:6297807255,&quot;desc&quot;:&quot;天钟洞风光&quot;,&quot;height&quot;:2201,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;962bd40735fae6cd7b8976a7ede8182442a7d833a1fb&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SMu1V2vhsK&quot;,&quot;width&quot;:1280},{&quot;albumId&quot;:6297807255,&quot;desc&quot;:&quot;天钟洞风光&quot;,&quot;height&quot;:2200,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;d50735fae6cd7b899e51e645ed7f55a7d933c995a0fb&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SMu2zmWtPv&quot;,&quot;width&quot;:1280},{&quot;albumId&quot;:6297807255,&quot;desc&quot;:&quot;天钟洞风光&quot;,&quot;height&quot;:1440,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;0823dd54564e9258d1091a267ed9c658ccbf6d81e0fd&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SPc1ajksCK&quot;,&quot;width&quot;:1080}],&quot;coverPic&quot;:{&quot;albumId&quot;:6297807255,&quot;desc&quot;:&quot;小七孔风景区天钟洞&quot;,&quot;height&quot;:416,&quot;src&quot;:&quot;a9d3fd1f4134970a304ebb966b92c6c8a786c917f74b&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/a9d3fd1f4134970a304ebb966b92c6c8a786c917f74b?x-bce-process=image/resize,m_lfit,w_1560,limit_1&quot;,&quot;uuid&quot;:&quot;v0SGY9bz2BjS&quot;,&quot;width&quot;:780},&quot;desc&quot;:&quot;小七孔风景区天钟洞&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:6}"></div></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="5-7" data-tag="header" data-uuid="umm1RNGuLAVo" data-level="2" data-name="铜鼓桥"><h3>铜鼓桥</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umlXqy4neudD" data-idx="4-18"><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="i1meesrw3y" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:3,&quot;nid&quot;:&quot;4238587695018549230&quot;,&quot;secondId&quot;:0,&quot;source&quot;:101,&quot;style&quot;:1,&quot;title&quot;:&quot;贵州荔波小七孔景区，当天最后的留念啦，走上铜鼓桥，远远看着水的精灵在此汇入樟江&quot;,&quot;uuid&quot;:&quot;i1meesrw5t&quot;}]}"></div></div><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">铜鼓桥在过小七孔风景区东门行数百米的地方。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umxW4HXiruRL"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">其长达126米，净跨60米，宽2.4米，高25米，桥身两端采用瑶山瑶族铜鼓造型，瑶族将铜鼓视为神赐之物，镇寨之宝，是权力的象征。桥头还设立有图腾柱，柱上的浮雕图案展示了瑶族传统而古老的民族文化。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [1]<em id="sup-1" data-ctrid="umlYgbZXQPkk"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="umnf8GAK81UW" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807254"><div class="albumWrap_E1OYe"><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr singlePage_QBeXg"><a class="swiperLi_jbFeq" type="pic" id="album-image-b2de9c82d158ccbf6c81112ee680ab3eb13533faebd4" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/b2de9c82d158ccbf6c81112ee680ab3eb13533faebd4-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="小七孔风景区铜鼓桥" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔风景区铜鼓桥</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-d31b0ef41bd5ad6eddc48a2263902edbb6fd536696fd" style="height:166px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/d31b0ef41bd5ad6eddc48a2263902edbb6fd536696fd-bkimg-process,v_1,rw_1080,rh_810,maxl_378?x-bce-process=image/format,f_auto" alt="铜鼓桥风光" height="140" width="187.33333333333331" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">铜鼓桥风光</div></a></div></div></div></div></div><div style="display:none" class="value-album" data-module-value="{&quot;albumId&quot;:6297807254,&quot;content&quot;:[{&quot;albumId&quot;:6297807254,&quot;desc&quot;:&quot;小七孔风景区铜鼓桥&quot;,&quot;height&quot;:416,&quot;src&quot;:&quot;b2de9c82d158ccbf6c81112ee680ab3eb13533faebd4&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SPkVZhyAkK&quot;,&quot;width&quot;:780},{&quot;albumId&quot;:6297807254,&quot;desc&quot;:&quot;铜鼓桥风光&quot;,&quot;height&quot;:810,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;d31b0ef41bd5ad6eddc48a2263902edbb6fd536696fd&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SPlTSBdAIF&quot;,&quot;width&quot;:1080}],&quot;coverPic&quot;:{&quot;albumId&quot;:6297807254,&quot;desc&quot;:&quot;小七孔风景区铜鼓桥&quot;,&quot;height&quot;:416,&quot;src&quot;:&quot;b2de9c82d158ccbf6c81112ee680ab3eb13533faebd4&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/b2de9c82d158ccbf6c81112ee680ab3eb13533faebd4?x-bce-process=image/resize,m_lfit,w_1560,limit_1&quot;,&quot;uuid&quot;:&quot;v0SPkVZhyAkK&quot;,&quot;width&quot;:780},&quot;desc&quot;:&quot;小七孔风景区铜鼓桥&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:2}"></div></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="5-8" data-tag="header" data-uuid="umlMcWwi0R3I" data-level="2" data-name="努内吉海湿地"><h3>努内吉海湿地</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umrJjfcXUhVq" data-idx="4-20"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">努内吉海湿地位于翠谷瀑布和天钟洞之间。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umxW1aQJn8wo"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">其为二级景点，是典型的高原喀斯特滞留湿地。湿地距鸳鸯湖约6000米，面积为50公顷。努内吉海湿地具有维持生态平衡、保持生物多样性和珍稀物种资源以及涵养水源，防止土壤沙化和净化环境等作用，因此被称为“地球之肾”。“努内吉海”瑶语译为“最美丽的地方”。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [6]<em id="sup-6" data-ctrid="umrJU6CUVEsq"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="umrJZhFCgo8y" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807253"><div class="albumWrap_E1OYe"><div class="swiperPrevBtn_Ye7CY disabled_pmrOD hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="M5.516 0 1.112 4.684a1.946 1.946 0 0 0 0 2.632L5.516 12 7 10.421 2.844 6 7 1.579 5.516 0Z"></path></svg></div><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr"><a class="swiperLi_jbFeq" type="pic" id="album-image-72f082025aafa40f4bfb2309ab3d144f78f0f636b394" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/72f082025aafa40f4bfb2309ab3d144f78f0f636b394-bkimg-process,v_1,rw_960,rh_640,maxl_426?x-bce-process=image/format,f_auto" alt="小七孔风景区努内吉海湿地" height="140" width="211" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔风景区努内吉海湿地</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-2934349b033b5bb5c9ea4e3cd488c239b6003bf316e7" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/2934349b033b5bb5c9ea4e3cd488c239b6003bf316e7-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="努内吉海湿地风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">努内吉海湿地风光</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-359b033b5bb5c9ea15ce6a213762a1003af33b8715e7" style="height:166px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/359b033b5bb5c9ea15ce6a213762a1003af33b8715e7-bkimg-process,v_1,rw_16,rh_9,maxl_504?x-bce-process=image/format,f_auto" alt="努内吉海湿地风光" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">努内吉海湿地风光</div></a></div></div><div class="swiperNextBtn_rFg5I hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="m1.484 0 4.404 4.684a1.946 1.946 0 0 1 0 2.632L1.484 12 0 10.421 4.156 6 0 1.579 1.484 0Z"></path></svg></div></div></div></div><div style="display:none" class="value-album" data-module-value="{&quot;albumId&quot;:6297807253,&quot;content&quot;:[{&quot;albumId&quot;:6297807253,&quot;desc&quot;:&quot;小七孔风景区努内吉海湿地&quot;,&quot;height&quot;:640,&quot;src&quot;:&quot;72f082025aafa40f4bfb2309ab3d144f78f0f636b394&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SGLwkYyaSc&quot;,&quot;width&quot;:960},{&quot;albumId&quot;:6297807253,&quot;desc&quot;:&quot;努内吉海湿地风光&quot;,&quot;height&quot;:642,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;2934349b033b5bb5c9ea4e3cd488c239b6003bf316e7&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SGNe1tWbne&quot;,&quot;width&quot;:1280},{&quot;albumId&quot;:6297807253,&quot;desc&quot;:&quot;努内吉海湿地风光&quot;,&quot;height&quot;:647,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;359b033b5bb5c9ea15ce6a213762a1003af33b8715e7&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SGNduRvtjE&quot;,&quot;width&quot;:1280}],&quot;coverPic&quot;:{&quot;albumId&quot;:6297807253,&quot;desc&quot;:&quot;小七孔风景区努内吉海湿地&quot;,&quot;height&quot;:640,&quot;src&quot;:&quot;72f082025aafa40f4bfb2309ab3d144f78f0f636b394&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/72f082025aafa40f4bfb2309ab3d144f78f0f636b394?x-bce-process=image/resize,m_lfit,w_1920,limit_1&quot;,&quot;uuid&quot;:&quot;v0SGLwkYyaSc&quot;,&quot;width&quot;:960},&quot;desc&quot;:&quot;小七孔风景区努内吉海湿地&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:3}"></div></div></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="6" data-tag="header" data-uuid="hsqwq1r19q" data-level="1" data-name="文化活动"><h2>文化活动</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="6" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="6-1" data-tag="header" data-uuid="umOJlcw0XEUf" data-level="2" data-name="非遗展示活动"><h3>非遗展示活动</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umsOTYq77gTu" data-idx="5-2"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">从2023年开始，荔波陆续开展非遗文化进景区民俗展演活动，把非遗文化、民族文化融入到小七孔风景区内。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [23]<em id="sup-23" data-ctrid="umsQ21BmYf1J"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2023年5月，荔波小七孔持续开展“非遗进景区”活动，并启动小七孔景区剧本游系列活动，在“五一”期间推出了《寻梦绿宝石》剧本游。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [24]<em id="sup-24" data-ctrid="umsQ7UsTa7ml"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umsQ0pKNMi7A" data-idx="5-3"><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="i1meesrv44" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:3,&quot;nid&quot;:&quot;5366734355050842020&quot;,&quot;secondId&quot;:0,&quot;source&quot;:101,&quot;style&quot;:1,&quot;title&quot;:&quot;总要来一次荔波小七孔吧，这里哪一个景色能触动你的心灵？&quot;,&quot;uuid&quot;:&quot;i1meesrv6m&quot;}]}"></div></div><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2024年8月，小七孔风景区在翠谷瀑布附近开展常态化非遗展演，使游客近距离感受非遗民俗文化。表演有苗族舞蹈、布依族矮人舞表演、瑶族猴鼓舞、花样陀螺表演等。此外，在小七古桥还举行两场布依族婚俗文化秀，把布依、水、苗、瑶的特色民族文化展示给游客们。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [23]<em id="sup-23" data-ctrid="umsOSTWBJpIX"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umsRqmuivIYz" data-idx="5-4"><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="umsRz2Zwd40x" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryDesc_VgFgs richTest_CQ6fD">2024年小七孔风景区非遗展演</div><div class="galleryView_TxO0W" data-gallery="5438188604"><div class="albumWrap_E1OYe"><div class="swiperPrevBtn_Ye7CY disabled_pmrOD"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="M5.516 0 1.112 4.684a1.946 1.946 0 0 0 0 2.632L5.516 12 7 10.421 2.844 6 7 1.579 5.516 0Z"></path></svg></div><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr"><a class="swiperLi_jbFeq" type="pic" id="album-image-e61190ef76c6a7efce1bef15fca3b851f3deb48fc8f5" style="height:142px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/e61190ef76c6a7efce1bef15fca3b851f3deb48fc8f5-bkimg-process,v_1,rw_846,rh_662,maxl_362?x-bce-process=image/format,f_auto" alt="2024年小七孔风景区非遗展演" height="140" width="179.46827794561932" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/></a><a class="swiperLi_jbFeq" type="pic" id="album-image-91ef76c6a7efce1b9d168ef9ae08e4deb48f8c54cff5" style="height:142px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/91ef76c6a7efce1b9d168ef9ae08e4deb48f8c54cff5-bkimg-process,v_1,rw_1080,rh_618,maxl_496?x-bce-process=image/format,f_auto" alt="2024年小七孔风景区非遗展演" height="140" width="246.15533980582524" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/></a><a class="swiperLi_jbFeq" type="pic" id="album-image-77c6a7efce1b9d16fdfadb52f287a38f8c5494eecef5" style="height:142px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/77c6a7efce1b9d16fdfadb52f287a38f8c5494eecef5-bkimg-process,v_1,rw_721,rh_720,maxl_284?x-bce-process=image/format,f_auto" alt="2024年小七孔风景区非遗展演" height="140" width="140.19722222222222" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/></a></div></div><div class="swiperNextBtn_rFg5I"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="m1.484 0 4.404 4.684a1.946 1.946 0 0 1 0 2.632L1.484 12 0 10.421 4.156 6 0 1.579 1.484 0Z"></path></svg></div></div></div></div><div style="display:none" class="value-album" 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class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="6-2" data-tag="header" data-uuid="umOJoGiAHONo" data-level="2" data-name="“三月三”特色活动"><h3>“三月三”特色活动</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umOJn8IXagVS" data-idx="5-6"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2024年4月11日-14日，小七孔风景区举行“三月三”特色活动，活动邀请了贵州黔南、广西</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%8D%97%E4%B8%B9/895896?fromModule=lemma_inlink" target="_blank" data-from-module="">南丹</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E7%8E%AF%E6%B1%9F/53086914?fromModule=lemma_inlink" target="_blank" data-from-module="">环江</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">等地的山歌歌唱家开展山歌对唱，让游客在节日中感受“三月三”民俗文化。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [22]<em id="sup-22" data-ctrid="umsHSLo6aCKW"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umsDOmPROebB" data-idx="5-7"><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="umsScOkaeoEs" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryDesc_VgFgs richTest_CQ6fD">2024年小七孔风景区“三月三”特色活动</div><div class="galleryView_TxO0W" data-gallery="5438188605"><div class="albumWrap_E1OYe"><div class="swiperPrevBtn_Ye7CY disabled_pmrOD"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="M5.516 0 1.112 4.684a1.946 1.946 0 0 0 0 2.632L5.516 12 7 10.421 2.844 6 7 1.579 5.516 0Z"></path></svg></div><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr"><a class="swiperLi_jbFeq" type="pic" id="album-image-7e3e6709c93d70cf3bc73a3ef985c600baa1cd11fdf5" style="height:142px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/7e3e6709c93d70cf3bc73a3ef985c600baa1cd11fdf5-bkimg-process,v_1,rw_888,rh_622,maxl_405?x-bce-process=image/format,f_auto" alt="2024年小七孔风景区“三月三”特色活动" height="140" width="200.7266881028939" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/></a><a class="swiperLi_jbFeq" type="pic" id="album-image-6609c93d70cf3bc79f3d5edfd059ada1cd11728bfcf5" style="height:142px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/6609c93d70cf3bc79f3d5edfd059ada1cd11728bfcf5-bkimg-process,v_1,rw_1080,rh_657,maxl_466?x-bce-process=image/format,f_auto" alt="2024年小七孔风景区“三月三”特色活动" height="140" width="231.42465753424656" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/></a><a class="swiperLi_jbFeq" type="pic" id="album-image-c8177f3e6709c93d70cf9fc49e64efdcd100baa1fef5" style="height:142px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/c8177f3e6709c93d70cf9fc49e64efdcd100baa1fef5-bkimg-process,v_1,rw_1080,rh_657,maxl_466?x-bce-process=image/format,f_auto" alt="2024年小七孔风景区“三月三”特色活动" height="140" width="231.42465753424656" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/></a></div></div><div class="swiperNextBtn_rFg5I"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="m1.484 0 4.404 4.684a1.946 1.946 0 0 1 0 2.632L1.484 12 0 10.421 4.156 6 0 1.579 1.484 0Z"></path></svg></div></div></div></div><div style="display:none" class="value-album" data-module-value="{&quot;albumId&quot;:5438188605,&quot;content&quot;:[{&quot;albumId&quot;:5438188605,&quot;desc&quot;:&quot;2024年小七孔风景区“三月三”特色活动&quot;,&quot;height&quot;:622,&quot;owner&quot;:&quot;z梦想照亮现实&quot;,&quot;src&quot;:&quot;7e3e6709c93d70cf3bc73a3ef985c600baa1cd11fdf5&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;umsS5WpLiLyp&quot;,&quot;width&quot;:888},{&quot;albumId&quot;:5438188605,&quot;desc&quot;:&quot;2024年小七孔风景区“三月三”特色活动&quot;,&quot;height&quot;:657,&quot;owner&quot;:&quot;z梦想照亮现实&quot;,&quot;src&quot;:&quot;6609c93d70cf3bc79f3d5edfd059ada1cd11728bfcf5&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;umsS5ZRbazjc&quot;,&quot;width&quot;:1080},{&quot;albumId&quot;:5438188605,&quot;desc&quot;:&quot;2024年小七孔风景区“三月三”特色活动&quot;,&quot;height&quot;:657,&quot;owner&quot;:&quot;z梦想照亮现实&quot;,&quot;src&quot;:&quot;c8177f3e6709c93d70cf9fc49e64efdcd100baa1fef5&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;umsS5WsxdA5Z&quot;,&quot;width&quot;:1080}],&quot;coverPic&quot;:{&quot;albumId&quot;:5438188605,&quot;desc&quot;:&quot;2024年小七孔风景区“三月三”特色活动&quot;,&quot;height&quot;:622,&quot;owner&quot;:&quot;z梦想照亮现实&quot;,&quot;src&quot;:&quot;7e3e6709c93d70cf3bc73a3ef985c600baa1cd11fdf5&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/7e3e6709c93d70cf3bc73a3ef985c600baa1cd11fdf5?x-bce-process=image/resize,m_lfit,w_1776,limit_1&quot;,&quot;uuid&quot;:&quot;umsS5WpLiLyp&quot;,&quot;width&quot;:888},&quot;desc&quot;:&quot;2024年小七孔风景区“三月三”特色活动&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:3}"></div></div></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="7" data-tag="header" data-uuid="umlFhn90QfEl" data-level="1" data-name="其他看点"><h2>其他看点</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="7" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="upsYf2V3T5Kl" data-idx="6-1"><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="uYvMn1XSxwcp" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:1,&quot;nid&quot;:&quot;8871462058555234377&quot;,&quot;secondId&quot;:0,&quot;source&quot;:100,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;uYvNNSc6AR8R&quot;}]}"></div></div><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区设有亲水、戏水以及“水上飞人”“水上摩托艇”等旅游项目，开展了剧本游、非遗文化进景区活动，打造常态化“汉服+山水”“民族服饰+山水”创意展演，提质升级翠谷瀑布、卧龙潭、水上森林等景点，满足不同层次游客的旅游需求。2023年7月，景区内已推出《寻梦绿宝石》剧本游、“踏瀑戏水”等10余个新业态项目。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [34]<em id="sup-34" data-ctrid="upsYYvMSuFpN"></em></sup></span><div style="display:inline" data-tag="module" data-module-type="album" data-uuid="upsZmHCydauD" data-style="inline"><div class="galleryWrapper_Xu3kU disable-select"><div class="galleryView_TxO0W" data-gallery="6297807252"><div class="albumWrap_E1OYe"><div class="swiperPrevBtn_Ye7CY disabled_pmrOD hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="M5.516 0 1.112 4.684a1.946 1.946 0 0 0 0 2.632L5.516 12 7 10.421 2.844 6 7 1.579 5.516 0Z"></path></svg></div><div class="albumSwiper_cvc9i"><div class="swiperUl_w2QBr"><a class="swiperLi_jbFeq" type="pic" id="album-image-b03533fa828ba61ea8d382b3586d800a304e241ff3ac" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/b03533fa828ba61ea8d382b3586d800a304e241ff3ac-bkimg-process,v_1,rw_1080,rh_608,maxl_504?x-bce-process=image/format,f_auto" alt="小七孔风景区的古风表演" height="140" width="250.23684210526318" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">小七孔风景区的古风表演</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-d01373f082025aafa40fbe0819b6bc64034f79f0ace6" style="height:166px;padding-right:16px"><img src="https://bkimg.cdn.bcebos.com/smart/d01373f082025aafa40fbe0819b6bc64034f79f0ace6-bkimg-process,v_1,rw_1280,rh_720,maxl_504?x-bce-process=image/format,f_auto" alt="丛林溯溪" height="140" width="250.44444444444443" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">丛林溯溪</div></a><a class="swiperLi_jbFeq" type="pic" id="album-image-6c224f4a20a4462309f7d0a67a79650e0cf3d6ca79f9" style="height:166px;padding-right:0"><img src="https://bkimg.cdn.bcebos.com/smart/6c224f4a20a4462309f7d0a67a79650e0cf3d6ca79f9-bkimg-process,v_1,rw_1280,rh_854,maxl_425?x-bce-process=image/format,f_auto" alt="丛林探险" height="140" width="210.8337236533958" style="object-fit:cover;object-position:center;border:1px solid rgba(0, 0, 0, 0.05)"/><div class="swiperDesc__c6LO" type="pic">丛林探险</div></a></div></div><div class="swiperNextBtn_rFg5I hasDesc_Jw96T"><svg width="1em" height="1em" viewBox="0 0 7 12" fill="#848691" xmlns="http://www.w3.org/2000/svg"><path d="m1.484 0 4.404 4.684a1.946 1.946 0 0 1 0 2.632L1.484 12 0 10.421 4.156 6 0 1.579 1.484 0Z"></path></svg></div></div></div></div><div style="display:none" class="value-album" data-module-value="{&quot;albumId&quot;:6297807252,&quot;content&quot;:[{&quot;albumId&quot;:6297807252,&quot;desc&quot;:&quot;小七孔风景区的古风表演&quot;,&quot;height&quot;:608,&quot;src&quot;:&quot;b03533fa828ba61ea8d382b3586d800a304e241ff3ac&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SIOGUKpA1c&quot;,&quot;width&quot;:1080},{&quot;albumId&quot;:6297807252,&quot;desc&quot;:&quot;丛林溯溪&quot;,&quot;height&quot;:720,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;d01373f082025aafa40fbe0819b6bc64034f79f0ace6&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SIPSZxCFsG&quot;,&quot;width&quot;:1280},{&quot;albumId&quot;:6297807252,&quot;desc&quot;:&quot;丛林探险&quot;,&quot;height&quot;:854,&quot;owner&quot;:&quot;大千同行&quot;,&quot;src&quot;:&quot;6c224f4a20a4462309f7d0a67a79650e0cf3d6ca79f9&quot;,&quot;url&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;v0SJ9UzwtmPk&quot;,&quot;width&quot;:1280}],&quot;coverPic&quot;:{&quot;albumId&quot;:6297807252,&quot;desc&quot;:&quot;小七孔风景区的古风表演&quot;,&quot;height&quot;:608,&quot;src&quot;:&quot;b03533fa828ba61ea8d382b3586d800a304e241ff3ac&quot;,&quot;url&quot;:&quot;https://bkimg.cdn.bcebos.com/pic/b03533fa828ba61ea8d382b3586d800a304e241ff3ac?x-bce-process=image/resize,m_lfit,w_2160,limit_1&quot;,&quot;uuid&quot;:&quot;v0SIOGUKpA1c&quot;,&quot;width&quot;:1080},&quot;desc&quot;:&quot;小七孔风景区其他看点&quot;,&quot;layout&quot;:&quot;gallery&quot;,&quot;total&quot;:3}"></div></div></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="8" data-tag="header" data-uuid="upsYdGtKiiFG" data-level="1" data-name="开发与保护"><h2>开发与保护</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="8" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="8-1" data-tag="header" data-uuid="umOWiGKtwEwc" data-level="2" data-name="开发建设"><h3>开发建设</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umP5AiimOB0W" data-idx="7-2"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1984年，艾福田决定开发小七孔风景旅游区。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [10]<em id="sup-10" data-ctrid="uncQ1DgLAY7s"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1987年，县成立旅游开发领导小组。次年，省建设厅规划设计院为荔波樟江风景名胜区作出了总体规划。</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">在中共荔波县委、荔波县人民政府以及黔南州委、州政府及有关部门的重视和支持下，小七孔风景区从无到有，逐渐壮大，其中还投资10万元新建了天钟洞——蝙蝠洞——鸳鸯湖的旅游专线共887米，新建了龟背山、水上森林游览步道共1250米，加固、加宽公路6.4千米，以及进行水改等工程；在鸳鸯湖景点建立了简易码头，购置了游览小船，新建简易停车场。此外，政府还投资30万元，完成了总共1699平方米的风景区房屋建筑，设立了旅馆、餐厅、会议厅，购置放像机、音响设备、电视差转机、闭路电视等文化娱乐设施。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [10]<em id="sup-10" data-ctrid="umrZkcDVoMar"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="unZhwLnhzW0j" data-idx="7-3"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1988年，省建设厅规划设计院为荔波樟江风景名胜区作出了总体规划。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [10]<em id="sup-10" data-ctrid="uncQ1DgLAY7s"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">同年，小七孔风景区被列为国家级自然保护区。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [16]<em id="sup-16" data-ctrid="umP5UOnct9Fr"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1988年到1989年期间，</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E6%96%B0%E5%8D%8E%E7%A4%BE/293685?fromModule=lemma_inlink" target="_blank" data-from-module="">新华社</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E4%B8%AD%E5%A4%AE%E7%94%B5%E8%A7%86%E5%8F%B0/5559?fromModule=lemma_inlink" target="_blank" data-from-module="">中央电视台</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E8%B4%B5%E5%B7%9E%E7%94%B5%E8%A7%86%E5%8F%B0/2783056?fromModule=lemma_inlink" target="_blank" data-from-module="">贵州电视台</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%85%89%E6%98%8E%E6%97%A5%E6%8A%A5/80852?fromModule=lemma_inlink" target="_blank" data-from-module="">光明日报</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E8%B4%B5%E5%B7%9E%E6%97%A5%E6%8A%A5/3278937?fromModule=lemma_inlink" target="_blank" data-from-module="">贵州日报</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">、贵州经济报、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E9%BB%94%E5%8D%97%E6%97%A5%E6%8A%A5/9721893?fromModule=lemma_inlink" target="_blank" data-from-module="">黔南日报</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">等宣传单位相继播放、登载了关于小七孔风景区的新闻报道，吸引更多中外人士前来观光游览。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [11]<em id="sup-11" data-ctrid="ums0VjJagqux"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">之后1989年1月6日到8日期间，黔南州委、州政府在荔波小七孔风景区召开樟江水系旅游资源开发工作会议。</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">自1984年开始，艾福田在景区相关建设中持续工作了五年，使小七孔风景区初具规模。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [10]<em id="sup-10" data-ctrid="umtgsZKemvJh"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="ums2oW2cSvkD" data-idx="7-4"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2013年9月，荔波樟江旅游景区在小七孔风景区内打造了一片湿地，还种植了薰衣草。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [12]<em id="sup-12" data-ctrid="ums4HhpNVZow"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">之后2015年3月，荔波提出全域旅游发展模式，随后在2016年被评为全国全域旅游的示范区、全省全域旅游示范县，其中规划建设包括大小七孔游客集散中心等项目。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [13]<em id="sup-13" data-ctrid="ums5hSejfDhl"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="ums5sG6nEIHu" data-idx="7-5"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2023年8月，荔波小七孔景区正在加紧完成“踏瀑戏水”项目的收尾工程。该项目正式运营后，可以串联景区内多个景点，也为游客增加两个半小时的体验时间。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [14]<em id="sup-14" data-ctrid="ums6xDJDBx3K"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">同月，“村有界·创无边”第五届“农行杯”贵州省乡村旅游创客大赛在贵阳启动，该比赛针对荔波县瑶山瑶族乡和小七孔镇进行项目设计，有助于荔波旅游资源的转化。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [15]<em id="sup-15" data-ctrid="ums7ANtFtvHV"></em></sup></span></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="8-2" data-tag="header" data-uuid="umOWDYUgqZNM" data-level="2" data-name="生物保护"><h3>生物保护</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umOWgBiEFpPT" data-idx="7-7"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区是众多特有和濒危动植物的栖息地。景区内有大面积的原生性喀斯特森林，是同纬度现存的最重要的独特原生喀斯特森林生态系统之一。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [32<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-32" data-ctrid="umP0shWYteEP"></em></sup></span></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="9" data-tag="header" data-uuid="umlFwEKc8Syo" data-level="1" data-name="相关文化"><h2>相关文化</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="9" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="9-1" data-tag="header" data-uuid="umOJSOqiDUZg" data-level="2" data-name="影视作品"><h3>影视作品</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umnDuKv310SY" data-idx="8-2"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">电影《</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E8%B5%B0%E8%BF%9B%E5%96%80%E6%96%AF%E7%89%B9/16169635?fromModule=lemma_inlink" target="_blank" data-from-module="">走进喀斯特</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">》的取景地中就包括小七孔风景区，该影片由导演</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E6%9E%97%E5%AD%90%E7%9A%93/7208061?fromModule=lemma_inlink" target="_blank" data-from-module="">林子皓</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">执导，于2014年11月16日在荔波古镇开机拍摄。影片主要讲述了女主角小彤来到她的爱人古帅的家乡荔波，完成两人曾经许下的承诺——一起回到荔波，最终小彤在荔波得知古帅因白血病去世而失踪的真相的故事。该片依托荔波古镇、小七孔、茂兰、瑶山等景点，在表现男女主角之间的爱情故事的同时，也展现了荔波的自然风光、民族风情以及人文气息。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [5]<em id="sup-5" data-ctrid="umnFgQKbCTeN"></em></sup></span></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umstozcMfD6G" data-idx="8-3"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">电视剧《双世宠妃2》《</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%B0%86%E5%A4%9C/19895731?fromModule=lemma_inlink" target="_blank" data-from-module="">将夜</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">》、电影《</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%A4%A9%E4%B8%8B%E7%AC%AC%E4%B8%80%E9%95%96%E5%B1%80/3278860?fromModule=lemma_inlink" target="_blank" data-from-module="">天下第一镖局</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">》等影片也选自小七孔风景区作为拍摄地点之一。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [17-18]<em id="sup-17" data-ctrid="umstDD4fvFBM"></em><em id="sup-18" data-ctrid="umsur92WwPdm"></em></sup></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">古装玄幻剧《将夜》改编自猫腻同名网络小说，主要讲述了一段草根崛起史。这部剧中，书院后山的许多场景均是取自贵州荔波小七孔，其中小七孔古桥也在该剧中出现过许多次。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [18]<em id="sup-18" data-ctrid="umsvfEbK7oIf"></em></sup></span><div class="lemmaPicture_HinqL layoutCenter_mfqz5 richTest_gQ33Q disable-select J-lemma-content-single-image" 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href="/pic/%E5%B0%8F%E4%B8%83%E5%AD%94%E9%A3%8E%E6%99%AF%E5%8C%BA/6899702/0/0824ab18972bd40735fa2e317bd089510fb30e24a3fc?fr=lemma&amp;fromModule=lemma_content-image" target="_blank" title="《将夜》取景地之一：荔波小七孔"><img src="https://bkimg.cdn.bcebos.com/smart/0824ab18972bd40735fa2e317bd089510fb30e24a3fc-bkimg-process,v_1,rw_378,rh_252,maxl_756?x-bce-process=image/format,f_auto" class="picture_RDqAb" width="376" height="250" style="object-fit:cover;border-radius:9px;border:1px solid rgba(0, 0, 0, 0.05)"/></a><span class="titleSpan_fw52D richTest_gQ33Q"><span>《将夜》取景地之一：荔波小七孔</span></span></div><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="uYsVKEe0HfCp" data-style="inline"><div></div><div style="display:none" class="value-video" 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class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="9-2" data-tag="header" data-uuid="umOJM7ef5oyp" data-level="2" data-name="相关传说"><h3>相关传说</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umOJK6oUe8Gd" data-idx="8-5"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区有一个古老传说。小七孔是当地传说中的“忠贞之桥”，曾经有一对情侣在此相恋，但迫于外界的压力，他们不能在一起。为了爱情，他们最终决定逃离这里。但是当逃到七孔桥时，大河阻挡了他们的去路。正在他们准备跳河殉情时，七名仙女被其真爱所感动，从而幻化出了七孔桥来帮助他们。但同时，这座桥凝聚着时间和命运的力量，他们每走一步，便会衰老一分，也就代表着他们走过一年，当走过七孔后，他们就会苍颜白发，但也代表着他们共度了一生。最终，这对情侣在七孔桥上牵手而过。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [20]<em id="sup-20" data-ctrid="umsybAehs9iL"></em></sup></span></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="10" data-tag="header" data-uuid="umlFbTA0zYZZ" data-level="1" data-name="重要事件"><h2>重要事件</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="10" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div data-tag="module" data-module-type="table" data-uuid="tO3elUxqcUaT"><div class="moduleTable_H4MzI"><table class="tableBox_law7U"><caption>所获荣誉</caption><tbody class="tableBody_JVAeO"><tr><th width="131" align="center" rowspan="1" colSpan="1" class="tableTh_OcWQF"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3en1uBOU4c" data-idx=""><span class="text_M6NWU bold_fKI8G J-lemma-content-lemma-text" data-text="true">时间</span></div></th><th width="589" align="center" rowspan="1" colSpan="1" class="tableTh_OcWQF"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3en1uILCwj" data-idx=""><span class="text_M6NWU bold_fKI8G J-lemma-content-lemma-text" data-text="true">所获荣誉</span></div></th></tr><tr><td width="131" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUEo57Vl"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUsoI0zQ" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1988年</span></div></td><td width="589" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUE0eYCZ"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUsplw9n" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">被列为</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%9B%BD%E5%AE%B6%E7%BA%A7%E8%87%AA%E7%84%B6%E4%BF%9D%E6%8A%A4%E5%8C%BA/7516695?fromModule=lemma_inlink" target="_blank" data-from-module="">国家级自然保护区</a></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [16]<em id="sup-16" data-ctrid="unZ1X8xQAhMO"></em></sup></span></div></td></tr><tr><td width="131" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="ums8tTQqPHCQ"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="ums8tTQcMoPS" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1990年8月</span></div></td><td width="589" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="ums8tTQP6yPu"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="ums8tTQfmfuS" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">由贵州省人民政府批准为省级风景名胜区</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [10]<em id="sup-10"></em></sup></span></div></td></tr><tr><td width="131" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUEtcauo"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUs6PixK" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1994年</span></div></td><td width="589" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUEvpKfN"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUt93DFe" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">被国务院批准为国家级风景名胜区</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [33]<em id="sup-33"></em></sup></span></div></td></tr><tr><td width="131" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUEEnx0n"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUty2kwg" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">1996年4月</span></div></td><td width="589" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUFYE7mj"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUtaZl2u" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">成为联合国教科文组织国际人与生物圈保护区网络（</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/MAB/8431187?fromModule=lemma_inlink" target="_blank" data-from-module="">MAB</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">）成员</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [33]<em id="sup-33"></em></sup></span></div></td></tr><tr><td width="131" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUFcdZNX"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUtS2KBh" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2007年6月27日</span></div></td><td width="589" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUFzGAml"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUtvCH6J" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">成为中国第六个、贵州第一个世界自然遗产地</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [33]<em id="sup-33"></em></sup></span></div></td></tr><tr><td width="131" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUFLOuuP"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUuAd0tX" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2015年7月</span></div></td><td width="589" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUFP6yAp"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUuaYWwq" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">被评定为</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%9B%BD%E5%AE%B6AAAAA%E7%BA%A7%E6%97%85%E6%B8%B8%E6%99%AF%E5%8C%BA/3575094?fromModule=lemma_inlink" target="_blank" data-from-module="">国家AAAAA级旅游景区</a></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [33]<em id="sup-33"></em></sup></span></div></td></tr><tr><td width="131" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUFXbSni"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUua2azf" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2021年</span></div></td><td width="589" align="center" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3elUF39y8n"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3elUuhO7oz" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">被评为全国文化和旅游系统先进集体、全国青年文明号、</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E5%9B%BD%E5%AE%B6%E7%BA%A7%E6%96%87%E6%98%8E%E6%97%85%E6%B8%B8%E7%A4%BA%E8%8C%83%E5%8D%95%E4%BD%8D/59239227?fromModule=lemma_inlink" target="_blank" data-from-module="">国家级文明旅游示范单位</a></span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [33]<em id="sup-33"></em></sup></span></div></td></tr></tbody></table></div></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="11" data-tag="header" data-uuid="umnFpbyD698M" data-level="1" data-name="价值意义"><h2>价值意义</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="11" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="11-1" data-tag="header" data-uuid="umP9mTxkb3Vg" data-level="2" data-name="历史遗迹"><h3>历史遗迹</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umsvWAVcuF3Z" data-idx="10-2"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区中的小七孔古桥建于清道光十五年（1835年），是荔波作为贵州通往广西商旅大通道的一个历史见证。根据相关记载，从小七孔古桥、黎明关等地出发，荔波曾有5条途经广西环江、终达广西怀远的“盐马古道”。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [19]<em id="sup-19" data-ctrid="umswrPB3C5da"></em></sup></span></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="11-2" data-tag="header" data-uuid="umP9nrMXdYro" data-level="2" data-name="科学研究价值"><h3>科学研究价值</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umP9lctNiTDL" data-idx="10-4"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区展示了峰丛景观与峰林景观的相互演化与递交，代表了大陆型热带——亚热带锥状喀斯特地质演化和生物生态过程，满足了世界自然遗产的三条标准，即地球演变历史主要阶段的杰出范例，生态和生物演化过程的杰出范例和生物的多样性。景区所在的地域喀斯特地貌发育演化代表了湿润热带——亚热带锥状喀斯特演化的基本规律，也反映了锥状喀斯特发育的岩性、构造、气候、水动力等复杂地质——气候环境变化遗迹的全部过程，具有典型的锥状喀斯特特征。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [32<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-32" data-ctrid="umPbitDxaIhd"></em></sup></span></div><div class="paraTitle_Mg50n level-2_aIn3E MARK_MODULE" data-index="11-3" data-tag="header" data-uuid="umPbUwWfmDDJ" data-level="2" data-name="民族文化"><h3>民族文化</h3></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="umPbSXfeeRQk" data-idx="10-6"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔风景区内拥有瑶寨、布依寨、苗寨、水家寨等多种少数民族聚集地，他们与当地环境相融合，并在这块土地上生活、繁衍，适应了这里的山水、气候、植物等自然条件，逐渐形成了丰富的“喀斯特文化”。景区特定的地理环境和历史条件，不同的民族心理，形成了各民族不同的乡土习俗、节日庆典和文艺活动方式以及民族民间工艺。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [32<svg viewBox="0 0 12 12" fill="currentColor" width="1em" height="1em"><path d="M11.021 12H.979A.98.98 0 0 1 0 11.021V.979A.98.98 0 0 1 .979 0H11.02a.98.98 0 0 1 .98.979v10.042a.98.98 0 0 1-.979.979zM11 .979.979 1 1 11.021 11 11V.979z"></path><circle cx="4.235" cy="3.655" r="1.1"></circle><path d="M9.537 5.773a.5.5 0 0 0-.707 0L6.667 7.938l-1.66-1.659a.491.491 0 0 0-.391-.139.494.494 0 0 0-.391.139L2.389 8.115a.5.5 0 0 0 .707.707l1.521-1.521L6.315 9a.498.498 0 0 0 .707 0l.008-.012L9.537 6.48a.5.5 0 0 0 0-.707z"></path></svg>]<em id="sup-32" data-ctrid="umPdig5cNnoD"></em></sup></span></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="12" data-tag="header" data-uuid="umlFAH2f1v7f" data-level="1" data-name="旅游信息"><h2>旅游信息</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="12" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div data-tag="module" data-module-type="table" data-uuid="tO3eCjKnYrIk"><div class="moduleTable_H4MzI"><table class="tableBox_law7U"><caption>旅游信息</caption><tbody class="tableBody_JVAeO"><tr><th width="107" align="center" rowspan="1" colSpan="1" class="tableTh_OcWQF"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="umni8J7rV7gd" data-idx=""><span class="text_M6NWU bold_fKI8G J-lemma-content-lemma-text" data-text="true">开放时间</span></div></th><td width="621" align="" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="umni8J7PBRVp"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="umni8J7QdcBz" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">08:00—16:00（景区将入园时间分为5个时段，分别为8:00-9:30时、9:30-11:30时、11:30-13:30时、13:30-15:00时、15:00-16:00时）</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [2]<em id="sup-2" data-ctrid="umngP6xGDQNS"></em></sup></span></div></td></tr><tr><th width="107" align="center" rowspan="1" colSpan="1" class="tableTh_OcWQF"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3eCjKlEJ3X" data-idx=""><span class="text_M6NWU bold_fKI8G J-lemma-content-lemma-text" data-text="true">门票价格</span></div></th><td width="621" align="" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3eCjKHQtEi"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3eDLHMAXPw" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">旅游</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E6%97%BA%E5%AD%A3/62269?fromModule=lemma_inlink" target="_blank" data-from-module="">旺季</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">（3月1日-11月30日）</span></div><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="umnhvUpCfMAc" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">旺季门票全价票：120元/人；旺季门票半价票：60元/人；旺季观光车票：40元/人</span></div><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="umnhqXCMYHwj" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">旅游</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E6%B7%A1%E5%AD%A3/3978931?fromModule=lemma_inlink" target="_blank" data-from-module="">淡季</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">（12月1日-次年2月最后一日）</span></div><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="umnhUl11XQ5h" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">淡季门票全价票：100元/人；淡季门票半价票：50元/人；淡季观光车票：40元/人</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [2]<em id="sup-2" data-ctrid="umni1zjuRz5g"></em></sup></span></div></td></tr><tr><th width="107" align="center" rowspan="3" colSpan="1" class="tableTh_OcWQF"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3eCjKD5aOr" data-idx=""><span class="text_M6NWU bold_fKI8G J-lemma-content-lemma-text" data-text="true">交通指引</span></div></th><td width="621" align="" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3eCjKhJBOD"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3eMexxtk2b" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">自驾游</span></div><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3eMexYba5T" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">路线：贵州-</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E9%83%BD%E5%8C%80/2235890?fromModule=lemma_inlink" target="_blank" data-from-module="">都匀</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">-荔波-荔波大小七孔景区</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [3]<em id="sup-3" data-ctrid="umnI4fKd2HeM"></em></sup></span></div></td></tr><tr><td width="621" align="" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3eKJPU4AdC"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3eNr5KDAFh" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">火车</span></div><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3eNr5FtTcK" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">从</span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true"><a class="innerLink_e3eFR" href="/item/%E8%B4%B5%E9%98%B3%E5%8C%97%E7%AB%99/7720628?fromModule=lemma_inlink" target="_blank" data-from-module="">贵阳北站</a></span><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">乘坐高铁抵达荔波站，大约需要1小时。下车后再乘坐景区巴士或公交车可直接到达小七孔景区，车程大约25分钟</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [4]<em id="sup-4" data-ctrid="umniYpYCY8ch"></em></sup></span></div></td></tr><tr><td width="621" align="" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="tO3eKDndne3Z"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3eOk8TRrBd" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">大巴</span></div><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="tO3eOk9F9xyV" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">坐贵阳大巴抵达荔波县，再在县城新汽车站到小七孔东门乘坐11路公交车</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [21]<em id="sup-21" data-ctrid="umszuGUBoete"></em></sup></span></div></td></tr><tr><th width="107" align="center" rowspan="1" colSpan="1" class="tableTh_OcWQF"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="umnj7xGeNwHU" data-idx=""><span class="text_M6NWU bold_fKI8G J-lemma-content-lemma-text" data-text="true">注意事项</span></div></th><td width="621" align="left" rowspan="1" colSpan="1" class="tableTd_KaYot" data-uuid="umnj7xGDUdMy"><div class="para_Y8Vvn table_CfNwA MARK_MODULE" data-tag="paragraph" data-uuid="umnj7xGEpTGc" data-idx=""><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">小七孔景区内全程步行所需时间较长，建议穿着舒适的鞋子和服装。景区内部分路段较为陡峭或潮湿，需要注意安全。此外，游客在夏季游玩时需要注意防晒和补水</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [4]<em id="sup-4" data-ctrid="umnjQC5OQW8i"></em></sup></span></div></td></tr></tbody></table></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="uYq5tP7Qi7Zi" data-idx="11-2"><div style="display:inline" data-tag="module" data-module-type="video" data-uuid="uYq5tP7ZH4ht" data-style="inline"><div></div><div style="display:none" class="value-video" data-module-value="{&quot;data&quot;:[{&quot;form&quot;:2,&quot;mountType&quot;:1,&quot;nid&quot;:&quot;5173328588939337234&quot;,&quot;secondId&quot;:0,&quot;source&quot;:101,&quot;style&quot;:1,&quot;title&quot;:&quot;&quot;,&quot;uuid&quot;:&quot;uYvNNSccQJYy&quot;}]}"></div></div></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="13" data-tag="header" data-uuid="uMnLgw0MOpym" data-level="1" data-name="公开通报"><h2>公开通报</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="13" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div class="para_Y8Vvn content_oFocR MARK_MODULE" data-tag="paragraph" data-uuid="uMnLg3Ml86sn" data-idx="12-1"><span class="text_M6NWU J-lemma-content-lemma-text" data-text="true">2025年5月消息，文化和旅游部组织多个暗访小组对贵州等8个省（区）开展暗访抽查，发现一批安全生产隐患和市场秩序问题，现将有关情况予以通报。包括黔南荔波大小七孔景区有工作人员在林区抽烟，断桥飞瀑打卡点无安全提示，防护绳形同虚设。</span><span class="supWrap_wdN1f J-supWrap J-lemma-content-lemma-sup-item"><sup data-tag="ref"> [36]<em id="sup-36"></em></sup></span></div><div class="paraTitle_Mg50n level-1_NbeoA" data-index="14" data-tag="header" data-uuid="i2xrgjuj6k" data-level="1" data-name="地图信息"><h2>地图信息</h2><div class="titleLine_Jlbs6"></div><span><span data-tts-catalog="14" data-tts-from="paragraph" class="ttsBtn_ozw4g paragraph_zXXdl"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="M7.878 14.133c-.3 0-.7-.1-.9-.3l-2.8-2.5h-1.6c-.8 0-1.4-.7-1.4-1.4v-3.8c0-.8.6-1.4 1.4-1.4h1.6l2.7-2.4c.6-.5 1.4-.5 1.9.1.3.2.4.5.4.9v9.5c0 .7-.6 1.3-1.3 1.3zm-5.3-8.2c-.1 0-.2.1-.2.2v3.8c0 .1.1.2.2.2h1.4c.3 0 .6.1.9.3l2.8 2.5c.1.1.4 0 .4-.2v-9.4c0-.1 0-.1-.1-.2s-.2-.1-.3 0l-2.7 2.4c-.3.3-.6.4-.9.4h-1.5zm10.3 6.8c-.1 0-.3 0-.4-.2-.2-.2-.2-.6 0-.8.9-1 1.4-2.3 1.4-3.7 0-1.4-.5-2.7-1.4-3.7-.2-.2-.2-.6 0-.8.2-.2.6-.2.8 0 1.1 1.2 1.7 2.8 1.7 4.4s-.6 3.3-1.7 4.4c-.1.3-.2.4-.4.4z"></path><path d="M11.378 10.733c-.1 0-.2 0-.3-.1-.3-.2-.3-.6-.2-.8.4-.5.6-1.1.6-1.8s-.2-1.3-.6-1.8c-.1-.2-.1-.6.2-.8.2-.2.6-.1.8.2.5.7.8 1.5.8 2.4 0 .9-.3 1.7-.8 2.4-.1.2-.3.3-.5.3z"></path></svg><span>播报</span></span></span><div class="editLemma_zXIfg"><svg viewBox="0 0 16 16" fill="currentColor" width="1em" height="1em"><path d="m14 3.8-1.9-1.9c-.3-.3-.7-.4-1.1-.4-.4 0-.8.2-1.1.4l-8.4 8.4c-.3.3-.4.7-.4 1.1v1.9c0 .8.7 1.5 1.5 1.5h1.9c.4 0 .8-.2 1.1-.4L14 5.9c.6-.6.6-1.6 0-2.1zm-9.1 9.7c-.1.1-.2.1-.3.1H2.7c-.2 0-.4-.2-.4-.4v-1.9c0-.1 0-.2.1-.3l6.1-6 2.4 2.4-6 6.1zm8.3-8.4-1.5 1.5-2.4-2.4 1.5-1.5c.1-.1.2-.1.3-.1s.2 0 .3.1l1.9 1.9c.1.1.1.3-.1.5z"></path></svg><span class="text_HXKLQ">编辑</span></div></div><div data-tag="module" data-module-type="map" data-uuid="i2xrgjuj4m"><div class="lemmaMap_RKhjo big_LafRJ"><div class="mapBig_fMU3m"><div 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data-module-value="{&quot;address&quot;:&quot;贵州省黔南布依族苗族自治州荔波县206省道&quot;,&quot;city&quot;:&quot;黔南布依族苗族自治州&quot;,&quot;lat&quot;:25.260091,&quot;lng&quot;:107.714306,&quot;markerUrl&quot;:&quot;https://api.map.baidu.com/place/detail?uid=1f25a32375ad39fd08ccdd10&amp;output=html&amp;source=jsapi&quot;,&quot;title&quot;:&quot;小七孔景区&quot;,&quot;type&quot;:&quot;big&quot;,&quot;uid&quot;:&quot;1f25a32375ad39fd08ccdd10&quot;,&quot;url&quot;:&quot;centerX=107.714306&amp;centerY=25.260091&amp;city=%E9%BB%94%E5%8D%97%E5%B8%83%E4%BE%9D%E6%97%8F%E8%8B%97%E6%97%8F%E8%87%AA%E6%B2%BB%E5%B7%9E&amp;containerPrefix=container&amp;desc=%E5%B0%8F%E4%B8%83%E5%AD%94%E6%99%AF%E5%8C%BA&amp;markerAddress=%E8%B4%B5%E5%B7%9E%E7%9C%81%E9%BB%94%E5%8D%97%E5%B8%83%E4%BE%9D%E6%97%8F%E8%8B%97%E6%97%8F%E8%87%AA%E6%B2%BB%E5%B7%9E%E8%8D%94%E6%B3%A2%E5%8E%BF206%E7%9C%81%E9%81%93&amp;markerPosX=107.714306&amp;markerPosY=25.260091&amp;markerTitle=%E5%B0%8F%E4%B8%83%E5%AD%94%E6%99%AF%E5%8C%BA&amp;markerUid=1f25a32375ad39fd08ccdd10&amp;markerUrl=https%3A%2F%2Fapi.map.baidu.com%2Fplace%2Fdetail%3Fuid%3D1f25a32375ad39fd08ccdd10%26output%3Dhtml%26source%3Djsapi&amp;nomark=false&amp;query=%E5%B0%8F%E4%B8%83%E5%AD%94%E6%99%AF%E5%8C%BA&amp;zoom=15&quot;}"></div></div><div 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diff --git a/scripts/import_yunyou_libo_food_hotel_enrichment.py b/scripts/import_yunyou_libo_food_hotel_enrichment.py
new file mode 100644
index 0000000..99f63c4
--- /dev/null
+++ b/scripts/import_yunyou_libo_food_hotel_enrichment.py
@@ -0,0 +1,1156 @@
+#!/usr/bin/env python3
+"""Publish the latest Yunyou Libo food/hotel fusion CSVs to FalkorDB and PG schema.
+
+Safety and idempotency:
+- hard-scoped to tenant/project/graph ``yunyou_libo``;
+- defaults to dry-run; graph and PostgreSQL writes require ``--apply``;
+- exports the current FoodPlace/Hotel graph slice and PG schema/release rows;
+- MERGE/upsert by AMap element_id, so reruns do not duplicate entities;
+- only clears properties managed by this importer before refreshing them;
+- never deletes unrelated scenic, transit, bus, area, or grid data.
+"""
+from __future__ import annotations
+
+import argparse
+import csv
+import hashlib
+import json
+import os
+import re
+import sys
+from collections import Counter
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+from urllib.parse import urlsplit, urlunsplit
+
+import h3
+import psycopg
+from falkordb import FalkorDB
+from psycopg.rows import dict_row
+from psycopg.types.json import Jsonb
+
+ROOT = Path(__file__).resolve().parents[1]
+if str(ROOT) not in sys.path:
+    sys.path.insert(0, str(ROOT))
+
+from app.config import settings  # noqa: E402
+
+TENANT_ID = "yunyou_libo"
+PROJECT_ID = "yunyou_libo"
+GRAPH_NAME = "yunyou_libo"
+SCHEMA_NAMESPACE = "yunyou_libo"
+SCHEMA_VERSION = 1
+SCHEMA_DISPLAY_NAME = "云游荔波旅游POI融合知识图谱 Schema v1"
+SCHEMA_DSL_PATH = ROOT / "schema搭建/yunyou_libo/yunyou_libo_schema.current.dsl.md"
+
+FOOD_CSV = Path(
+    "/Users/xuexue/Desktop/荔波小七孔源数据/高德/"
+    "云游荔波_高德POI_美食_细网格.csv"
+)
+HOTEL_CSV = Path(
+    "/Users/xuexue/Desktop/荔波小七孔源数据/高德/"
+    "云游荔波_高德POI_酒店_细网格.csv"
+)
+OUTPUT_ROOT = Path(
+    "/Users/xuexue/Documents/云游荔波/outputs/"
+    "knowledge_graph_publish_20260729"
+)
+
+COMMON_FIELD_MAP: dict[str, tuple[str, str]] = {
+    "高德POI_ID": ("gaode_poi_id", "text"),
+    "POI名称": ("name", "text"),
+    "数据分类": ("type_label", "text"),
+    "Schema类型": ("schema_type", "text"),
+    "业务细分类": ("business_subcategory", "text"),
+    "高德一级分类": ("amap_category_l1", "text"),
+    "高德二级分类": ("amap_category_l2", "text"),
+    "高德三级分类": ("amap_category_l3", "text"),
+    "高德完整分类": ("amap_type", "text"),
+    "高德分类编码": ("typecode", "text"),
+    "省": ("province", "text"),
+    "地级市/自治州": ("city", "text"),
+    "区县": ("district", "text"),
+    "行政区划代码": ("adcode", "text"),
+    "详细地址": ("address", "text"),
+    "商圈": ("business_area", "text"),
+    "经度(GCJ-02)": ("lng", "float"),
+    "纬度(GCJ-02)": ("lat", "float"),
+    "电话": ("tel", "text"),
+    "评分": ("amap_rating", "float"),
+    "人均消费/参考价格": ("amap_cost_text", "text"),
+    "营业时间": ("open_time", "text"),
+    "图片数量": ("amap_image_count", "int"),
+    "首图URL": ("cover_image_url", "text"),
+    "全部图片URL": ("photo_urls", "text"),
+    "高德地图URL": ("amap_url", "text"),
+    "去重键": ("dedup_key", "text"),
+    "采集网格序号": ("collection_grid_no", "text"),
+    "网格中心经度": ("grid_center_lng", "float"),
+    "网格中心纬度": ("grid_center_lat", "float"),
+    "扫描半径(m)": ("scan_radius_m", "float"),
+    "采集时间": ("collected_at", "text"),
+    "数据来源": ("source_name", "text"),
+    "数据质量标记": ("data_quality", "text"),
+    "命中扫描类型": ("scan_hit_types", "text"),
+    "扫描命中次数": ("scan_hit_count", "int"),
+    "采集轮次": ("collection_rounds", "text"),
+}
+
+FOOD_FIELD_MAP: dict[str, tuple[str, str]] = {
+    "融合状态": ("food_fusion_status", "text"),
+    "匹配置信度": ("food_match_confidence", "text"),
+    "匹配规则": ("food_match_rule", "text"),
+    "匹配综合分": ("food_match_score", "float"),
+    "名称完全一致": ("food_name_exact_match", "bool"),
+    "名称相似度": ("food_name_similarity", "float"),
+    "地址相似度": ("food_address_similarity", "float"),
+    "坐标距离(m)": ("food_coordinate_distance_m", "float"),
+    "融合来源说明": ("food_fusion_source_note", "text"),
+    "大众点评源POI_ID": ("dianping_source_poi_id", "text"),
+    "大众点评店铺ID": ("dianping_shop_id", "text"),
+    "大众点评店铺UUID": ("dianping_shop_uuid", "text"),
+    "大众点评店铺名称": ("dianping_name", "text"),
+    "大众点评地址": ("dianping_address", "text"),
+    "大众点评经度": ("dianping_lng", "float"),
+    "大众点评纬度": ("dianping_lat", "float"),
+    "大众点评URL": ("dianping_url", "text"),
+    "大众点评评分": ("dianping_rating", "float"),
+    "大众点评评论数": ("dianping_review_count_text", "text"),
+    "大众点评评论数(数值)": ("dianping_review_count", "int"),
+    "大众点评人均消费": ("dianping_avg_price_text", "text"),
+    "大众点评人均消费(元)": ("dianping_avg_price", "float"),
+    "大众点评区域": ("dianping_area", "text"),
+    "大众点评分类": ("dianping_category", "text"),
+    "大众点评详细评分": ("dianping_score_details", "text"),
+    "大众点评排名": ("dianping_ranking", "text"),
+    "大众点评营业状态": ("dianping_business_status", "text"),
+    "大众点评营业时间": ("dianping_business_hours", "text"),
+    "大众点评特色标签": ("dianping_tags", "text"),
+    "大众点评交通信息": ("dianping_transportation", "text"),
+    "大众点评图片数量": ("dianping_image_count", "int"),
+    "大众点评店铺图片": ("dianping_shop_image", "text"),
+    "大众点评评论标签": ("dianping_review_tags", "text"),
+    "大众点评页面评论数量": ("dianping_page_review_count", "int"),
+    "大众点评更新时间": ("dianping_updated_at", "text"),
+    "推荐菜采集条数": ("recommended_dish_count", "int"),
+    "推荐菜名称摘要": ("recommended_dish_names", "text"),
+    "推荐菜最高推荐人数": ("recommended_dish_max_recommendations", "int"),
+    "推荐菜图片URL样例": ("recommended_dish_image_samples", "text"),
+    "团购采集条数": ("group_buy_count", "int"),
+    "团购最低价": ("group_buy_min_price", "float"),
+    "团购最高价": ("group_buy_max_price", "float"),
+    "团购标题摘要": ("group_buy_titles", "text"),
+    "团购包含菜品摘要": ("group_buy_items", "text"),
+    "评论采集条数": ("review_sample_count", "int"),
+    "评论样本平均星级": ("review_sample_avg_stars", "float"),
+    "评论时间摘要": ("review_sample_times", "text"),
+    "评论内容摘要": ("review_sample_summary", "text"),
+    "评论图片URL样例": ("review_image_samples", "text"),
+    "菜单图片采集条数": ("menu_image_count", "int"),
+    "菜单图片URL样例": ("menu_image_samples", "text"),
+    "候选点评源POI_ID": ("candidate_dianping_source_poi_id", "text"),
+    "候选点评店铺ID": ("candidate_dianping_shop_id", "text"),
+    "候选点评店铺名": ("candidate_dianping_name", "text"),
+    "候选名称相似度": ("food_candidate_name_similarity", "float"),
+    "候选地址相似度": ("food_candidate_address_similarity", "float"),
+    "候选坐标距离(m)": ("food_candidate_coordinate_distance_m", "float"),
+}
+
+HOTEL_FIELD_MAP: dict[str, tuple[str, str]] = {
+    "融合状态": ("hotel_fusion_status", "text"),
+    "匹配置信度": ("hotel_match_confidence", "text"),
+    "匹配规则": ("hotel_match_rule", "text"),
+    "名称相似度": ("hotel_name_similarity", "float"),
+    "地址相似度": ("hotel_address_similarity", "float"),
+    "电话一致": ("hotel_phone_exact_match", "bool"),
+    "融合来源说明": ("hotel_fusion_source_note", "text"),
+    "携程酒店ID": ("ctrip_hotel_id", "text"),
+    "携程酒店中文名": ("ctrip_name_cn", "text"),
+    "携程酒店英文名": ("ctrip_name_en", "text"),
+    "携程地址": ("ctrip_address", "text"),
+    "携程电话": ("ctrip_phone", "text"),
+    "携程星级": ("ctrip_star_level", "text"),
+    "携程钻级": ("ctrip_diamond_level", "text"),
+    "携程开业时间": ("ctrip_opened_year", "text"),
+    "携程客房数": ("ctrip_room_count", "int"),
+    "携程酒店类型": ("ctrip_hotel_type", "text"),
+    "携程榜单/排名": ("ctrip_ranking", "text"),
+    "携程评分": ("ctrip_rating", "float"),
+    "携程评分描述": ("ctrip_rating_description", "text"),
+    "携程点评总数": ("ctrip_review_count", "int"),
+    "携程图片总数": ("ctrip_image_count", "int"),
+    "携程交通信息": ("ctrip_transportation", "text"),
+    "携程特色标签": ("ctrip_tags", "text"),
+    "携程热门设施": ("ctrip_popular_facilities", "text"),
+    "携程评分明细": ("ctrip_score_details", "text"),
+    "携程卫生评分": ("ctrip_cleanliness_score", "float"),
+    "携程设施评分": ("ctrip_facilities_score", "float"),
+    "携程环境评分": ("ctrip_environment_score", "float"),
+    "携程服务评分": ("ctrip_service_score", "float"),
+    "携程酒店简介": ("ctrip_description", "text"),
+    "携程详情URL": ("ctrip_url", "text"),
+    "携程房型数": ("room_type_count", "int"),
+    "房型名称摘要": ("room_type_names", "text"),
+    "房型最低价": ("room_min_price", "float"),
+    "房型最高价": ("room_max_price", "float"),
+    "售卖方案数": ("offer_count", "int"),
+    "方案最低现价": ("offer_min_price", "float"),
+    "方案最高现价": ("offer_max_price", "float"),
+    "设施服务条数": ("facility_service_count", "int"),
+    "设施分类数": ("facility_category_count", "int"),
+    "设施分类统计": ("facility_category_stats", "text"),
+    "设施摘要": ("facility_summary", "text"),
+    "设施分类明细JSON": ("facility_category_items_json", "text"),
+    "酒店政策条数": ("policy_count", "int"),
+    "政策分类统计": ("policy_category_stats", "text"),
+    "政策摘要": ("policy_summary", "text"),
+    "住客点评样本数": ("guest_review_sample_count", "int"),
+    "样本平均评分": ("guest_review_sample_avg_score", "float"),
+    "最新点评时间": ("latest_review_at", "text"),
+    "点评出行类型": ("review_travel_types", "text"),
+    "酒店图片条数": ("hotel_image_record_count", "int"),
+    "图片类型统计": ("hotel_image_type_stats", "text"),
+    "图片URL样例": ("hotel_image_samples", "text"),
+    "周边地点条数": ("nearby_place_count", "int"),
+    "周边地点类型统计": ("nearby_place_type_stats", "text"),
+    "周边地点摘要": ("nearby_place_summary", "text"),
+    "周边分类明细JSON": ("nearby_category_items_json", "text"),
+    "候选携程酒店ID": ("candidate_ctrip_hotel_id", "text"),
+    "候选携程酒店名": ("candidate_ctrip_name", "text"),
+    "候选名称相似度": ("hotel_candidate_name_similarity", "float"),
+    "候选地址相似度": ("hotel_candidate_address_similarity", "float"),
+}
+
+SYSTEM_FIELDS: dict[str, str] = {
+    "element_id": "text",
+    "place_id": "text",
+    "place_type": "text",
+    "source": "text",
+    "h3_r6": "text",
+    "h3_r7": "text",
+    "h3_r8": "text",
+    "h3_r9": "text",
+    "h3_r10": "text",
+    "first_seen_at": "datetime",
+    "updated_at": "datetime",
+    "data_version": "text",
+    "enrichment_source": "text",
+    "enrichment_updated_at": "datetime",
+    "fusion_status": "text",
+}
+
+LEGACY_SHARED_FUSION_FIELDS = {
+    "match_confidence",
+    "match_rule",
+    "match_score",
+    "name_exact_match",
+    "name_similarity",
+    "address_similarity",
+    "coordinate_distance_m",
+    "phone_exact_match",
+    "fusion_source_note",
+    "candidate_name_similarity",
+    "candidate_address_similarity",
+    "candidate_coordinate_distance_m",
+}
+
+
+def now_iso() -> str:
+    return datetime.now(timezone.utc).isoformat()
+
+
+def clean(value: Any) -> str:
+    return "" if value is None else str(value).strip()
+
+
+def parse_number(value: Any, integer: bool = False) -> int | float | None:
+    match = re.search(r"-?\d+(?:\.\d+)?", clean(value).replace(",", ""))
+    if not match:
+        return None
+    number = float(match.group(0))
+    return int(round(number)) if integer else number
+
+
+def parse_bool(value: Any) -> bool | None:
+    normalized = clean(value).lower()
+    if normalized in {"是", "true", "1", "yes", "一致"}:
+        return True
+    if normalized in {"否", "false", "0", "no", "不一致"}:
+        return False
+    return None
+
+
+def coerce(value: Any, kind: str) -> str | int | float | bool | None:
+    if kind == "text":
+        normalized = clean(value)
+        return normalized or None
+    if kind == "int":
+        return parse_number(value, integer=True)
+    if kind == "float":
+        return parse_number(value)
+    if kind == "bool":
+        return parse_bool(value)
+    raise ValueError(f"Unsupported kind: {kind}")
+
+
+def normalize_ctrip_diamond_level(value: Any) -> str | None:
+    normalized = clean(value)
+    if not normalized:
+        return None
+    if re.fullmatch(r"\d+(?:\.\d+)?钻", normalized):
+        return normalized
+    matched = re.fullmatch(
+        r"(\d+(?:\.\d+)?)\s+out\s+of\s+5\s+(?:rating|diamonds?)",
+        normalized,
+        flags=re.IGNORECASE,
+    )
+    return f"{matched.group(1)}钻" if matched else None
+
+
+def sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def load_csv(path: Path) -> tuple[list[str], list[dict[str, str]]]:
+    with path.open("r", encoding="utf-8-sig", newline="") as stream:
+        reader = csv.DictReader(stream)
+        rows = [dict(row) for row in reader]
+        return list(reader.fieldnames or []), rows
+
+
+def h3_props(lat: float, lng: float) -> dict[str, str]:
+    return {f"h3_r{resolution}": h3.latlng_to_cell(lat, lng, resolution) for resolution in range(6, 11)}
+
+
+def row_props(
+    row: dict[str, str],
+    field_map: dict[str, tuple[str, str]],
+    *,
+    place_type: str,
+    data_version: str,
+    run_at: str,
+) -> dict[str, Any]:
+    props: dict[str, Any] = {}
+    for source_field, (target_field, kind) in {**COMMON_FIELD_MAP, **field_map}.items():
+        value = coerce(row.get(source_field), kind)
+        if target_field == "ctrip_diamond_level":
+            value = normalize_ctrip_diamond_level(value)
+        if value is not None:
+            props[target_field] = value
+
+    poi_id = clean(row.get("高德POI_ID"))
+    element_id = clean(row.get("去重键")) or f"amap:{poi_id}"
+    props.update(
+        {
+            "element_id": element_id,
+            "place_id": element_id,
+            "place_type": place_type,
+            "source": "amap",
+            "source_cell_id": (
+                f"amap-js-grid:{clean(row.get('采集网格序号'))}"
+                if clean(row.get("采集网格序号"))
+                else ""
+            ),
+            "source_resolution": 0,
+            "data_version": data_version,
+            "enrichment_source": (
+                "amap+dianping" if place_type == "eat" else "amap+ctrip"
+            ),
+            "enrichment_updated_at": run_at,
+            "updated_at": run_at,
+        }
+    )
+    lng = parse_number(row.get("经度(GCJ-02)"))
+    lat = parse_number(row.get("纬度(GCJ-02)"))
+    if lng is None or lat is None:
+        raise ValueError(f"{poi_id} missing coordinates")
+    props.update(h3_props(lat, lng))
+    return {key: value for key, value in props.items() if value not in (None, "")}
+
+
+def validate_rows(
+    *,
+    kind: str,
+    headers: list[str],
+    rows: list[dict[str, str]],
+    expected_schema_type: str,
+    expected_min_rows: int,
+) -> dict[str, Any]:
+    required = {
+        "高德POI_ID",
+        "POI名称",
+        "Schema类型",
+        "区县",
+        "行政区划代码",
+        "经度(GCJ-02)",
+        "纬度(GCJ-02)",
+        "融合状态",
+    }
+    missing = sorted(required - set(headers))
+    if missing:
+        raise ValueError(f"{kind} missing columns: {missing}")
+    if len(rows) < expected_min_rows:
+        raise ValueError(f"{kind} row count too small: {len(rows)}")
+    ids = [clean(row.get("高德POI_ID")) for row in rows]
+    if any(not poi_id for poi_id in ids):
+        raise ValueError(f"{kind} contains empty AMap POI ID")
+    duplicate_ids = [poi_id for poi_id, count in Counter(ids).items() if count > 1]
+    if duplicate_ids:
+        raise ValueError(f"{kind} duplicate AMap POI IDs: {duplicate_ids[:10]}")
+    foreign_rows = [
+        row for row in rows
+        if clean(row.get("行政区划代码")) != "522722"
+        or clean(row.get("区县")) != "荔波县"
+    ]
+    if foreign_rows:
+        raise ValueError(f"{kind} contains {len(foreign_rows)} non-Libo rows")
+    wrong_schema = [
+        row for row in rows
+        if clean(row.get("Schema类型")) != expected_schema_type
+    ]
+    if wrong_schema:
+        raise ValueError(f"{kind} contains {len(wrong_schema)} unexpected schema types")
+    return {
+        "rows": len(rows),
+        "columns": len(headers),
+        "unique_amap_ids": len(set(ids)),
+        "fusion_status": dict(Counter(clean(row.get("融合状态")) for row in rows)),
+        "match_confidence": dict(Counter(clean(row.get("匹配置信度")) for row in rows)),
+    }
+
+
+def schema_fields(field_map: dict[str, tuple[str, str]]) -> tuple[list[str], dict[str, str]]:
+    field_types = {
+        **SYSTEM_FIELDS,
+        **{target: kind for target, kind in COMMON_FIELD_MAP.values()},
+        **{target: kind for target, kind in field_map.values()},
+    }
+    fields = list(dict.fromkeys(field_types))
+    return fields, field_types
+
+
+def build_schema_payload() -> dict[str, Any]:
+    food_fields, food_types = schema_fields(FOOD_FIELD_MAP)
+    hotel_fields, hotel_types = schema_fields(HOTEL_FIELD_MAP)
+    return {
+        "namespace": SCHEMA_NAMESPACE,
+        "version": str(SCHEMA_VERSION),
+        "display_name": SCHEMA_DISPLAY_NAME,
+        "purpose": (
+            "支持荔波县地图展示、餐饮与住宿检索、游客决策和多来源证据追溯；"
+            "高德POI作为空间锚点，大众点评与携程详情只在同实体确认后融合。"
+        ),
+        "entity_types": {
+            "Place": {
+                "cn": "空间地点",
+                "primary_key": "element_id",
+                "fields": [
+                    "element_id", "place_id", "name", "place_type", "type_label",
+                    "business_subcategory", "amap_type", "typecode", "address",
+                    "district", "adcode", "lng", "lat", "h3_r9", "source",
+                ],
+            },
+            "FoodPlace": {
+                "cn": "美食店铺",
+                "primary_key": "element_id",
+                "description": "高德POI锚点及经审核融合的大众点评店铺详情。",
+                "fields": food_fields,
+                "field_types": food_types,
+            },
+            "Hotel": {
+                "cn": "酒店住宿",
+                "primary_key": "element_id",
+                "description": "高德POI锚点及经审核融合的携程酒店详情。",
+                "fields": hotel_fields,
+                "field_types": hotel_types,
+            },
+            "ScenicSpot": {
+                "cn": "景点",
+                "primary_key": "element_id",
+                "fields": [
+                    "element_id", "name", "scenic_type", "scenic_level",
+                    "parent_scenic", "visitor_value", "audit_result", "lng", "lat",
+                ],
+            },
+            "ScenicArea": {
+                "cn": "景区",
+                "primary_key": "element_id",
+                "fields": ["element_id", "name", "scenic_grade", "lng", "lat"],
+            },
+            "TransitFacility": {
+                "cn": "交通设施",
+                "primary_key": "element_id",
+                "fields": ["element_id", "name", "business_subcategory", "address", "lng", "lat"],
+            },
+            "BusStop": {
+                "cn": "公交站",
+                "primary_key": "element_id",
+                "fields": ["element_id", "name", "lng", "lat"],
+            },
+            "BusLine": {
+                "cn": "公交线路",
+                "primary_key": "element_id",
+                "fields": ["element_id", "name", "color"],
+            },
+            "BusRoute": {
+                "cn": "公交行驶方向",
+                "primary_key": "element_id",
+                "fields": ["element_id", "name", "direction", "polyline"],
+            },
+            "Area": {
+                "cn": "行政区域",
+                "primary_key": "element_id",
+                "fields": ["element_id", "name", "level", "adcode"],
+            },
+            "GeoCell": {
+                "cn": "片区",
+                "primary_key": "h3_id",
+                "fields": ["h3_id", "resolution"],
+            },
+        },
+        "relation_types": {
+            "LOCATED_IN": {
+                "from": "Place|BusStop|GeoCell",
+                "to": "Area",
+                "description": "地点或片区位于荔波县行政区域。",
+            },
+            "IN_H3_R9": {
+                "from": "Place|BusStop",
+                "to": "GeoCell",
+                "description": "地点落入H3九级网格。",
+            },
+            "PART_OF_SCENIC_AREA": {
+                "from": "ScenicSpot",
+                "to": "ScenicArea",
+                "description": "景区内部子景点归属。",
+            },
+            "PART_OF": {
+                "from": "Area",
+                "to": "Area",
+                "description": "行政区层级关系。",
+            },
+            "STOPS_AT": {
+                "from": "BusRoute",
+                "to": "BusStop",
+                "description": "公交线路方向停靠站点。",
+            },
+            "NEXT_STOP": {
+                "from": "BusStop",
+                "to": "BusStop",
+                "description": "同一公交方向的站点顺序。",
+            },
+        },
+        "fusion_policy": {
+            "anchor": "AMap POI",
+            "food_detail_source": "Dianping public shop detail",
+            "hotel_detail_source": "Ctrip public hotel detail",
+            "confirmed_rows_write_detail": True,
+            "candidate_rows_only_write_candidate_fields": True,
+            "source_tables_immutable": True,
+        },
+        "data_versions": {
+            "food": "2026-07-28-food-dianping-fusion",
+            "hotel": "2026-07-28-hotel-ctrip-fusion",
+        },
+    }
+
+
+def replace_port(database_url: str, port: int) -> str:
+    parts = urlsplit(database_url)
+    host = parts.hostname or "localhost"
+    userinfo = ""
+    if parts.username:
+        userinfo = parts.username
+        if parts.password:
+            userinfo += f":{parts.password}"
+        userinfo += "@"
+    netloc = f"{userinfo}{host}:{port}"
+    return urlunsplit((parts.scheme, netloc, parts.path, parts.query, parts.fragment))
+
+
+def pg_connect() -> psycopg.Connection:
+    candidates = []
+    explicit = os.environ.get("YUNYOU_DATABASE_URL", "").strip()
+    if explicit:
+        candidates.append(explicit)
+    candidates.append(settings.database_url)
+    candidates.append(replace_port(settings.database_url, 16433))
+    errors = []
+    for url in dict.fromkeys(candidates):
+        try:
+            return psycopg.connect(url, connect_timeout=3, row_factory=dict_row)
+        except psycopg.OperationalError as exc:
+            errors.append(str(exc).splitlines()[0])
+    raise RuntimeError(f"PostgreSQL unavailable: {errors}")
+
+
+def graph_client():
+    db = FalkorDB(
+        host=settings.falkordb_host,
+        port=settings.falkordb_port,
+        password=settings.falkordb_password or None,
+    )
+    return db.select_graph(GRAPH_NAME)
+
+
+def graph_scalar(graph, query: str, params: dict[str, Any] | None = None) -> int:
+    rows = graph.query(query, params or {}).result_set
+    return int(rows[0][0]) if rows else 0
+
+
+def graph_snapshot(graph) -> dict[str, Any]:
+    nodes = {}
+    for label in ("FoodPlace", "Hotel"):
+        rows = graph.query(f"MATCH (n:{label}) RETURN properties(n)").result_set
+        nodes[label] = [dict(row[0]) for row in rows]
+    outgoing = [
+        {
+            "source_element_id": row[0],
+            "relation_type": row[1],
+            "relation_properties": dict(row[2]),
+            "target_labels": list(row[3]),
+            "target_properties": dict(row[4]),
+        }
+        for row in graph.query(
+            "MATCH (n)-[r]->(m) "
+            "WHERE n:FoodPlace OR n:Hotel "
+            "RETURN n.element_id, type(r), properties(r), labels(m), properties(m)"
+        ).result_set
+    ]
+    incoming = [
+        {
+            "source_labels": list(row[0]),
+            "source_properties": dict(row[1]),
+            "relation_type": row[2],
+            "relation_properties": dict(row[3]),
+            "target_element_id": row[4],
+        }
+        for row in graph.query(
+            "MATCH (m)-[r]->(n) "
+            "WHERE n:FoodPlace OR n:Hotel "
+            "RETURN labels(m), properties(m), type(r), properties(r), n.element_id"
+        ).result_set
+    ]
+    return {"nodes": nodes, "outgoing_relations": outgoing, "incoming_relations": incoming}
+
+
+def pg_snapshot(conn: psycopg.Connection) -> dict[str, Any]:
+    schema = settings.db_schema
+    with conn.cursor() as cur:
+        cur.execute(
+            f"SELECT * FROM {schema}.ontology_schemas "
+            "WHERE tenant_id=%s AND project_id=%s ORDER BY version",
+            (TENANT_ID, PROJECT_ID),
+        )
+        schemas = [dict(row) for row in cur.fetchall()]
+        cur.execute(
+            f"SELECT * FROM {schema}.graph_releases "
+            "WHERE tenant_id=%s AND project_id=%s ORDER BY updated_at DESC",
+            (TENANT_ID, PROJECT_ID),
+        )
+        releases = [dict(row) for row in cur.fetchall()]
+        cur.execute(
+            f"SELECT * FROM {schema}.projects "
+            "WHERE tenant_id=%s AND project_id=%s",
+            (TENANT_ID, PROJECT_ID),
+        )
+        projects = [dict(row) for row in cur.fetchall()]
+    return {"schemas": schemas, "graph_releases": releases, "projects": projects}
+
+
+def json_write(path: Path, payload: Any) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    path.write_text(
+        json.dumps(payload, ensure_ascii=False, indent=2, default=str) + "\n",
+        encoding="utf-8",
+    )
+
+
+def batched(values: list[Any], size: int = 100):
+    for index in range(0, len(values), size):
+        yield values[index:index + size]
+
+
+def clear_managed_properties(graph, label: str, fields: set[str]) -> None:
+    if not fields:
+        return
+    remove_clause = ", ".join(f"n.{field}" for field in sorted(fields))
+    graph.query(f"MATCH (n:{label}) REMOVE {remove_clause}")
+
+
+def upsert_nodes(graph, label: str, rows: list[dict[str, Any]], run_at: str) -> None:
+    query = (
+        "UNWIND $rows AS row "
+        "MERGE (n:Place {element_id: row.element_id}) "
+        "ON CREATE SET n.first_seen_at = $run_at "
+        f"SET n:{label} "
+        "SET n += row.props"
+    )
+    for chunk in batched(rows):
+        graph.query(query, {"rows": chunk, "run_at": run_at})
+
+
+def upsert_spatial_relations(graph, rows: list[dict[str, Any]]) -> None:
+    cell_rows = [
+        {"h3_id": row["props"]["h3_r9"], "element_id": row["element_id"]}
+        for row in rows
+    ]
+    for chunk in batched(cell_rows):
+        graph.query(
+            "UNWIND $rows AS row "
+            "MERGE (cell:GeoCell {h3_id: row.h3_id}) "
+            "SET cell.resolution = 9",
+            {"rows": chunk},
+        )
+        graph.query(
+            "UNWIND $rows AS row "
+            "MATCH (cell:GeoCell {h3_id: row.h3_id}) "
+            "MATCH (area:Area {adcode: '522722'}) "
+            "MERGE (cell)-[:LOCATED_IN]->(area)",
+            {"rows": chunk},
+        )
+        graph.query(
+            "UNWIND $rows AS row "
+            "MATCH (n:Place {element_id: row.element_id}) "
+            "MATCH (area:Area {adcode: '522722'}) "
+            "MERGE (n)-[:LOCATED_IN]->(area)",
+            {"rows": chunk},
+        )
+        graph.query(
+            "UNWIND $rows AS row "
+            "MATCH (n:Place {element_id: row.element_id}) "
+            "MATCH (cell:GeoCell {h3_id: row.h3_id}) "
+            "MERGE (n)-[:IN_H3_R9]->(cell)",
+            {"rows": chunk},
+        )
+
+
+def update_compatibility_fusion_status(graph) -> None:
+    """Keep one readable legacy status while preserving per-business truth."""
+    graph.query(
+        "MATCH (n:FoodPlace) WHERE NOT n:Hotel "
+        "SET n.fusion_status = n.food_fusion_status"
+    )
+    graph.query(
+        "MATCH (n:Hotel) WHERE NOT n:FoodPlace "
+        "SET n.fusion_status = n.hotel_fusion_status"
+    )
+    graph.query(
+        "MATCH (n:FoodPlace:Hotel) "
+        "SET n.fusion_status = "
+        "'美食:' + n.food_fusion_status + '|酒店:' + n.hotel_fusion_status"
+    )
+
+
+def publish_pg(
+    conn: psycopg.Connection,
+    *,
+    schema_payload: dict[str, Any],
+    food_hash: str,
+    hotel_hash: str,
+    food_rows: int,
+    hotel_rows: int,
+    report_summary: dict[str, Any],
+) -> dict[str, Any]:
+    schema = settings.db_schema
+    with conn.cursor() as cur:
+        cur.execute(
+            f"UPDATE {schema}.ontology_schemas "
+            "SET status='archived', updated_at=now() "
+            "WHERE tenant_id=%s AND project_id=%s AND namespace=%s "
+            "AND status='active' AND version<>%s",
+            (TENANT_ID, PROJECT_ID, SCHEMA_NAMESPACE, SCHEMA_VERSION),
+        )
+        cur.execute(
+            f"""
+            INSERT INTO {schema}.ontology_schemas (
+                tenant_id, project_id, namespace, version, display_name,
+                description, status, schema_jsonb, created_by,
+                published_by, published_at, updated_at
+            )
+            VALUES (%s, %s, %s, %s, %s, %s, 'active', %s, 'codex',
+                    'codex', now(), now())
+            ON CONFLICT (tenant_id, project_id, namespace, version)
+            DO UPDATE SET
+                display_name=EXCLUDED.display_name,
+                description=EXCLUDED.description,
+                status='active',
+                schema_jsonb=EXCLUDED.schema_jsonb,
+                published_by='codex',
+                published_at=now(),
+                updated_at=now()
+            RETURNING id
+            """,
+            (
+                TENANT_ID,
+                PROJECT_ID,
+                SCHEMA_NAMESPACE,
+                SCHEMA_VERSION,
+                SCHEMA_DISPLAY_NAME,
+                schema_payload["purpose"],
+                Jsonb(schema_payload),
+            ),
+        )
+        schema_id = int(cur.fetchone()["id"])
+        dataset_version = "food-dianping+hotel-ctrip-2026-07-28"
+        release_metadata = {
+            "business": "yunyou_libo_tourism_poi",
+            "schema_version": SCHEMA_VERSION,
+            "food_rows": food_rows,
+            "hotel_rows": hotel_rows,
+            "food_sha256": food_hash,
+            "hotel_sha256": hotel_hash,
+            "published_at": now_iso(),
+            "publish_summary": report_summary,
+        }
+        cur.execute(
+            f"""
+            UPDATE {schema}.graph_releases
+            SET schema_id=%s,
+                source_dataset_version=%s,
+                metadata_jsonb=COALESCE(metadata_jsonb, '{{}}'::jsonb) || %s,
+                updated_at=now()
+            WHERE tenant_id=%s AND project_id=%s AND graph_name=%s
+              AND status='active'
+            RETURNING id
+            """,
+            (
+                schema_id,
+                dataset_version,
+                Jsonb(release_metadata),
+                TENANT_ID,
+                PROJECT_ID,
+                GRAPH_NAME,
+            ),
+        )
+        release = cur.fetchone()
+        if not release:
+            raise RuntimeError("Active yunyou_libo graph release not found")
+        cur.execute(
+            f"""
+            UPDATE {schema}.projects
+            SET default_namespace=%s,
+                metadata_jsonb=COALESCE(metadata_jsonb, '{{}}'::jsonb) || %s,
+                updated_at=now()
+            WHERE tenant_id=%s AND project_id=%s
+            """,
+            (
+                SCHEMA_NAMESPACE,
+                Jsonb(
+                    {
+                        "business": "yunyou_libo_tourism_poi",
+                        "graph_name": GRAPH_NAME,
+                        "schema_version": SCHEMA_VERSION,
+                        "schema_file": str(SCHEMA_DSL_PATH),
+                        "latest_food_rows": food_rows,
+                        "latest_hotel_rows": hotel_rows,
+                    }
+                ),
+                TENANT_ID,
+                PROJECT_ID,
+            ),
+        )
+
+        batches = []
+        for template_id, source_name, file_path, file_hash, row_count in (
+            (
+                "yunyou_libo_food_enriched_v1",
+                "高德美食POI+大众点评详情融合",
+                FOOD_CSV,
+                food_hash,
+                food_rows,
+            ),
+            (
+                "yunyou_libo_hotel_enriched_v1",
+                "高德酒店POI+携程详情融合",
+                HOTEL_CSV,
+                hotel_hash,
+                hotel_rows,
+            ),
+        ):
+            cur.execute(
+                f"""
+                SELECT id FROM {schema}.import_batches
+                WHERE tenant_id=%s AND project_id=%s AND template_id=%s
+                  AND file_hash=%s
+                ORDER BY id DESC LIMIT 1
+                """,
+                (TENANT_ID, PROJECT_ID, template_id, file_hash),
+            )
+            existing = cur.fetchone()
+            if existing:
+                batch_id = int(existing["id"])
+                cur.execute(
+                    f"""
+                    UPDATE {schema}.import_batches
+                    SET status='published', total_rows=%s, success_rows=%s,
+                        failed_rows=0, updated_at=now()
+                    WHERE id=%s
+                    """,
+                    (row_count, row_count, batch_id),
+                )
+            else:
+                cur.execute(
+                    f"""
+                    INSERT INTO {schema}.import_batches (
+                        tenant_id, project_id, graph_name, template_id,
+                        source_name, file_name, file_hash, status,
+                        total_rows, success_rows, failed_rows, created_by,
+                        updated_at
+                    )
+                    VALUES (%s, %s, %s, %s, %s, %s, %s, 'published',
+                            %s, %s, 0, 'codex', now())
+                    RETURNING id
+                    """,
+                    (
+                        TENANT_ID,
+                        PROJECT_ID,
+                        GRAPH_NAME,
+                        template_id,
+                        source_name,
+                        file_path.name,
+                        file_hash,
+                        row_count,
+                        row_count,
+                    ),
+                )
+                batch_id = int(cur.fetchone()["id"])
+            batches.append(batch_id)
+    conn.commit()
+    return {"schema_id": schema_id, "graph_release_id": int(release["id"]), "batch_ids": batches}
+
+
+def graph_summary(graph) -> dict[str, Any]:
+    return {
+        "nodes": graph_scalar(graph, "MATCH (n) RETURN count(n)"),
+        "relations": graph_scalar(graph, "MATCH ()-[r]->() RETURN count(r)"),
+        "food": graph_scalar(graph, "MATCH (n:FoodPlace) RETURN count(n)"),
+        "hotel": graph_scalar(graph, "MATCH (n:Hotel) RETURN count(n)"),
+        "food_fused": graph_scalar(
+            graph,
+            "MATCH (n:FoodPlace {food_fusion_status:'已融合'}) RETURN count(n)",
+        ),
+        "food_pending": graph_scalar(
+            graph,
+            "MATCH (n:FoodPlace {food_fusion_status:'待人工确认'}) RETURN count(n)",
+        ),
+        "food_with_dianping": graph_scalar(
+            graph,
+            "MATCH (n:FoodPlace) WHERE n.dianping_shop_id IS NOT NULL RETURN count(n)",
+        ),
+        "hotel_fused": graph_scalar(
+            graph,
+            "MATCH (n:Hotel {hotel_fusion_status:'已融合'}) RETURN count(n)",
+        ),
+        "hotel_pending": graph_scalar(
+            graph,
+            "MATCH (n:Hotel {hotel_fusion_status:'待人工确认'}) RETURN count(n)",
+        ),
+        "hotel_with_ctrip": graph_scalar(
+            graph,
+            "MATCH (n:Hotel) WHERE n.ctrip_hotel_id IS NOT NULL RETURN count(n)",
+        ),
+        "food_located_in": graph_scalar(
+            graph,
+            "MATCH (:FoodPlace)-[:LOCATED_IN]->(:Area {adcode:'522722'}) RETURN count(*)",
+        ),
+        "hotel_located_in": graph_scalar(
+            graph,
+            "MATCH (:Hotel)-[:LOCATED_IN]->(:Area {adcode:'522722'}) RETURN count(*)",
+        ),
+        "food_h3": graph_scalar(
+            graph,
+            "MATCH (:FoodPlace)-[:IN_H3_R9]->(:GeoCell) RETURN count(*)",
+        ),
+        "hotel_h3": graph_scalar(
+            graph,
+            "MATCH (:Hotel)-[:IN_H3_R9]->(:GeoCell) RETURN count(*)",
+        ),
+    }
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--apply",
+        action="store_true",
+        help="Perform scoped FalkorDB and PostgreSQL writes. Without this flag, dry-run only.",
+    )
+    return parser.parse_args()
+
+
+def main() -> None:
+    args = parse_args()
+    run_at = now_iso()
+    run_slug = datetime.now().strftime("%Y%m%d_%H%M%S")
+    run_dir = OUTPUT_ROOT / run_slug
+    run_dir.mkdir(parents=True, exist_ok=True)
+
+    food_headers, food_csv_rows = load_csv(FOOD_CSV)
+    hotel_headers, hotel_csv_rows = load_csv(HOTEL_CSV)
+    food_validation = validate_rows(
+        kind="food",
+        headers=food_headers,
+        rows=food_csv_rows,
+        expected_schema_type="FoodPlace",
+        expected_min_rows=1000,
+    )
+    hotel_validation = validate_rows(
+        kind="hotel",
+        headers=hotel_headers,
+        rows=hotel_csv_rows,
+        expected_schema_type="Hotel",
+        expected_min_rows=1200,
+    )
+    food_hash = sha256(FOOD_CSV)
+    hotel_hash = sha256(HOTEL_CSV)
+
+    food_nodes = [
+        {
+            "element_id": clean(row.get("去重键")) or f"amap:{clean(row.get('高德POI_ID'))}",
+            "props": row_props(
+                row,
+                FOOD_FIELD_MAP,
+                place_type="eat",
+                data_version="2026-07-28-food-dianping-fusion",
+                run_at=run_at,
+            ),
+        }
+        for row in food_csv_rows
+    ]
+    hotel_nodes = [
+        {
+            "element_id": clean(row.get("去重键")) or f"amap:{clean(row.get('高德POI_ID'))}",
+            "props": row_props(
+                row,
+                HOTEL_FIELD_MAP,
+                place_type="hotel",
+                data_version="2026-07-28-hotel-ctrip-fusion",
+                run_at=run_at,
+            ),
+        }
+        for row in hotel_csv_rows
+    ]
+
+    graph = graph_client()
+    before = graph_summary(graph)
+    dry_run_report = {
+        "mode": "apply" if args.apply else "dry-run",
+        "run_at": run_at,
+        "scope": {
+            "tenant_id": TENANT_ID,
+            "project_id": PROJECT_ID,
+            "graph_name": GRAPH_NAME,
+        },
+        "sources": {
+            "food": {"path": str(FOOD_CSV), "sha256": food_hash, **food_validation},
+            "hotel": {"path": str(HOTEL_CSV), "sha256": hotel_hash, **hotel_validation},
+        },
+        "schema": {
+            "namespace": SCHEMA_NAMESPACE,
+            "version": SCHEMA_VERSION,
+            "dsl_path": str(SCHEMA_DSL_PATH),
+            "entity_types": list(build_schema_payload()["entity_types"]),
+            "relation_types": list(build_schema_payload()["relation_types"]),
+        },
+        "graph_before": before,
+    }
+    json_write(run_dir / "preflight.json", dry_run_report)
+
+    if not args.apply:
+        print(json.dumps(dry_run_report, ensure_ascii=False, indent=2))
+        print("DRY-RUN ONLY: rerun with --apply after reviewing preflight.json")
+        return
+
+    if not SCHEMA_DSL_PATH.exists():
+        raise FileNotFoundError(f"Schema DSL missing: {SCHEMA_DSL_PATH}")
+
+    with pg_connect() as conn:
+        json_write(run_dir / "postgres_before.json", pg_snapshot(conn))
+        json_write(run_dir / "graph_food_hotel_before.json", graph_snapshot(graph))
+
+        enrichment_system_fields = {
+            "data_version",
+            "enrichment_source",
+            "enrichment_updated_at",
+            "fusion_status",
+        }
+        clear_managed_properties(
+            graph,
+            "FoodPlace",
+            enrichment_system_fields | LEGACY_SHARED_FUSION_FIELDS | {
+                target for target, _kind in FOOD_FIELD_MAP.values()
+            },
+        )
+        clear_managed_properties(
+            graph,
+            "Hotel",
+            enrichment_system_fields | LEGACY_SHARED_FUSION_FIELDS | {
+                target for target, _kind in HOTEL_FIELD_MAP.values()
+            },
+        )
+        upsert_nodes(graph, "FoodPlace", food_nodes, run_at)
+        upsert_nodes(graph, "Hotel", hotel_nodes, run_at)
+        update_compatibility_fusion_status(graph)
+        upsert_spatial_relations(graph, food_nodes)
+        upsert_spatial_relations(graph, hotel_nodes)
+
+        after = graph_summary(graph)
+        expected = {
+            "food": len(food_nodes),
+            "hotel": len(hotel_nodes),
+            "food_fused": food_validation["fusion_status"].get("已融合", 0),
+            "food_pending": food_validation["fusion_status"].get("待人工确认", 0),
+            "food_with_dianping": food_validation["fusion_status"].get("已融合", 0),
+            "hotel_fused": hotel_validation["fusion_status"].get("已融合", 0),
+            "hotel_pending": hotel_validation["fusion_status"].get("待人工确认", 0),
+            "hotel_with_ctrip": hotel_validation["fusion_status"].get("已融合", 0),
+            "food_located_in": len(food_nodes),
+            "hotel_located_in": len(hotel_nodes),
+            "food_h3": len(food_nodes),
+            "hotel_h3": len(hotel_nodes),
+        }
+        mismatches = {
+            key: {"expected": value, "actual": after.get(key)}
+            for key, value in expected.items()
+            if after.get(key) != value
+        }
+        if mismatches:
+            raise RuntimeError(f"Graph verification failed: {mismatches}")
+
+        pg_result = publish_pg(
+            conn,
+            schema_payload=build_schema_payload(),
+            food_hash=food_hash,
+            hotel_hash=hotel_hash,
+            food_rows=len(food_nodes),
+            hotel_rows=len(hotel_nodes),
+            report_summary=after,
+        )
+        postgres_after = pg_snapshot(conn)
+
+    report = {
+        **dry_run_report,
+        "mode": "applied",
+        "graph_after": after,
+        "graph_expected": expected,
+        "verification_mismatches": {},
+        "postgres_result": pg_result,
+        "postgres_after": postgres_after,
+        "backup_files": {
+            "graph": str(run_dir / "graph_food_hotel_before.json"),
+            "postgres": str(run_dir / "postgres_before.json"),
+        },
+    }
+    json_write(run_dir / "publish_report.json", report)
+    json_write(OUTPUT_ROOT / "latest_publish_report.json", report)
+    print(json.dumps(report, ensure_ascii=False, indent=2, default=str))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/server_rootless_docker.sh b/scripts/server_rootless_docker.sh
index 6710490..c9897a5 100755
--- a/scripts/server_rootless_docker.sh
+++ b/scripts/server_rootless_docker.sh
@@ -37,7 +37,11 @@ compose() {
   ensure_docker
   export DOCKER_HOST="unix://$DOCKER_SOCK"
   cd "$PROJECT_DIR"
-  docker compose "$@"
+  local compose_files=(-f docker-compose.yml)
+  if [ -f docker-compose.server.yml ]; then
+    compose_files+=(-f docker-compose.server.yml)
+  fi
+  docker compose "${compose_files[@]}" "$@"
 }
 
 case "${1:-up}" in
diff --git a/scripts/test_ocr_passport.py b/scripts/test_ocr_passport.py
new file mode 100644
index 0000000..6bf7d89
--- /dev/null
+++ b/scripts/test_ocr_passport.py
@@ -0,0 +1,59 @@
+"""阿里云护照 OCR 联调脚本。
+
+用法:
+    # 测本地图片
+    python3 scripts/test_ocr_passport.py /path/to/passport.jpg
+
+    # 测公网 URL
+    python3 scripts/test_ocr_passport.py --url https://example.com/passport.jpg
+
+前置:
+    pip install -r requirements.txt
+    在项目根目录的 .env 填好:
+        ALIYUN_OCR_ACCESS_KEY_ID=
+        ALIYUN_OCR_ACCESS_KEY_SECRET=
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+# 让脚本能在仓库根目录直接运行
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
+
+from app.aliyun_ocr import OcrCallError, OcrConfigError, recognize_passport  # noqa: E402
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="阿里云护照 OCR 自检")
+    parser.add_argument("image", nargs="?", help="本地图片路径")
+    parser.add_argument("--url", help="公网图片 URL")
+    args = parser.parse_args()
+
+    if not args.image and not args.url:
+        parser.error("请提供本地图片路径或 --url")
+
+    try:
+        if args.image:
+            path = Path(args.image).expanduser().resolve()
+            if not path.is_file():
+                print(f"[FAIL] 文件不存在: {path}", file=sys.stderr)
+                return 2
+            data = recognize_passport(image_bytes=path.read_bytes())
+        else:
+            data = recognize_passport(image_url=args.url)
+    except OcrConfigError as exc:
+        print(f"[CONFIG] {exc}", file=sys.stderr)
+        return 3
+    except OcrCallError as exc:
+        print(f"[CALL]   {exc}", file=sys.stderr)
+        return 4
+
+    print(json.dumps(data, ensure_ascii=False, indent=2))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/scripts/test_qwen_vl.py b/scripts/test_qwen_vl.py
new file mode 100644
index 0000000..8e8fe4f
--- /dev/null
+++ b/scripts/test_qwen_vl.py
@@ -0,0 +1,57 @@
+"""测试通义千问多模态：URL 图片 + 本地图片 两种用法。
+
+用法:
+    export DASHSCOPE_API_KEY=sk-xxxx
+    python scripts/test_qwen_vl.py                       # 跑 URL 用例
+    python scripts/test_qwen_vl.py /path/to/local.jpg    # 跑本地图片用例
+"""
+
+import os
+import sys
+from pathlib import Path
+
+from dashscope import MultiModalConversation
+
+
+def call(image_ref: str, prompt: str = "详细描述这张图片，并提取里面所有可见文字。") -> None:
+    resp = MultiModalConversation.call(
+        model="qwen-vl-max",
+        messages=[
+            {
+                "role": "user",
+                "content": [
+                    {"image": image_ref},
+                    {"text": prompt},
+                ],
+            }
+        ],
+    )
+    if resp.status_code != 200:
+        print(f"FAIL  status={resp.status_code}  code={resp.code}  msg={resp.message}")
+        sys.exit(1)
+
+    # 兼容两种返回结构
+    content = resp.output.choices[0].message.content
+    if isinstance(content, list):
+        text = "".join(seg.get("text", "") for seg in content)
+    else:
+        text = content
+    print("OK\n" + text)
+    print(f"\n[usage] {resp.usage}")
+
+
+def main() -> None:
+    if not os.getenv("DASHSCOPE_API_KEY"):
+        sys.exit("ERROR: 请先 export DASHSCOPE_API_KEY=sk-xxxx")
+
+    if len(sys.argv) > 1:
+        path = Path(sys.argv[1]).expanduser().resolve()
+        if not path.is_file():
+            sys.exit(f"文件不存在: {path}")
+        call(f"file://{path}")
+    else:
+        call("https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/snapshots/postgres/kg_admin_new2.dump b/snapshots/postgres/kg_admin_new2.dump
deleted file mode 100644
index f18719f..0000000
Binary files a/snapshots/postgres/kg_admin_new2.dump and /dev/null differ
diff --git a/小王洁居头像/avatar_v1.svg b/小王洁居头像/avatar_v1.svg
new file mode 100644
index 0000000..02f9955
--- /dev/null
+++ b/小王洁居头像/avatar_v1.svg
@@ -0,0 +1,30 @@
+<svg xmlns="http://www.w3.org/2000/svg" width="1024" height="1024" viewBox="0 0 1024 1024">
+  <defs>
+    <linearGradient id="bg" x1="0" y1="0" x2="1" y2="1">
+      <stop offset="0%" stop-color="#2BB8A3"/>
+      <stop offset="100%" stop-color="#1E8E7E"/>
+    </linearGradient>
+  </defs>
+  <!-- 背景：圆角方形（微信会裁成圆形，主体内容居中） -->
+  <rect width="1024" height="1024" rx="220" fill="url(#bg)"/>
+
+  <!-- 房子轮廓 -->
+  <g transform="translate(512,470)">
+    <path d="M -230 -40 L 0 -230 L 230 -40 L 230 200 Q 230 240 190 240 L -190 240 Q -230 240 -230 200 Z"
+          fill="#FFFFFF"/>
+    <!-- 门 -->
+    <rect x="-55" y="90" width="110" height="150" rx="20" fill="#1E8E7E"/>
+    <!-- 屋顶烟囱小方块 -->
+    <rect x="120" y="-190" width="60" height="90" rx="14" fill="#FFFFFF"/>
+  </g>
+
+  <!-- 闪亮星光（洁净感） -->
+  <g fill="#FFF9C9">
+    <path d="M 760 200 l 14 44 44 14 -44 14 -14 44 -14 -44 -44 -14 44 -14 Z"/>
+    <path d="M 240 260 l 10 30 30 10 -30 10 -10 30 -10 -30 -30 -10 30 -10 Z"/>
+  </g>
+
+  <!-- 文字 -->
+  <text x="512" y="850" text-anchor="middle" font-family="PingFang SC, Hiragino Sans GB, sans-serif"
+        font-size="150" font-weight="700" fill="#FFFFFF">小王洁居</text>
+</svg>
diff --git a/小王洁居头像/avatar_v2.svg b/小王洁居头像/avatar_v2.svg
new file mode 100644
index 0000000..32a2554
--- /dev/null
+++ b/小王洁居头像/avatar_v2.svg
@@ -0,0 +1,24 @@
+<svg xmlns="http://www.w3.org/2000/svg" width="1024" height="1024" viewBox="0 0 1024 1024">
+  <defs>
+    <linearGradient id="bg2" x1="0" y1="0" x2="0" y2="1">
+      <stop offset="0%" stop-color="#4FA8FF"/>
+      <stop offset="100%" stop-color="#2E6FE0"/>
+    </linearGradient>
+  </defs>
+  <rect width="1024" height="1024" rx="220" fill="url(#bg2)"/>
+
+  <!-- 白色圆形底 -->
+  <circle cx="512" cy="450" r="300" fill="#FFFFFF"/>
+
+  <!-- 房子 + 水滴（清洁） -->
+  <g transform="translate(512,440)">
+    <path d="M -180 -20 L 0 -170 L 180 -20 L 180 160 Q 180 195 145 195 L -145 195 Q -180 195 -180 160 Z"
+          fill="#2E6FE0"/>
+    <rect x="-42" y="75" width="84" height="120" rx="16" fill="#FFFFFF"/>
+    <!-- 水滴 -->
+    <path d="M 235 -120 Q 300 -30 300 20 A 65 65 0 0 1 170 20 Q 170 -30 235 -120 Z" fill="#7BC8FF"/>
+  </g>
+
+  <text x="512" y="880" text-anchor="middle" font-family="PingFang SC, Hiragino Sans GB, sans-serif"
+        font-size="130" font-weight="700" fill="#FFFFFF">小王洁居</text>
+</svg>
diff --git a/小王洁居头像/avatar_v3.svg b/小王洁居头像/avatar_v3.svg
new file mode 100644
index 0000000..776afa0
--- /dev/null
+++ b/小王洁居头像/avatar_v3.svg
@@ -0,0 +1,23 @@
+<svg xmlns="http://www.w3.org/2000/svg" width="1024" height="1024" viewBox="0 0 1024 1024">
+  <defs>
+    <linearGradient id="bg3" x1="0" y1="0" x2="1" y2="1">
+      <stop offset="0%" stop-color="#FF9A5A"/>
+      <stop offset="100%" stop-color="#F2703B"/>
+    </linearGradient>
+  </defs>
+  <rect width="1024" height="1024" rx="220" fill="url(#bg3)"/>
+
+  <!-- 大字「洁」为主视觉 -->
+  <circle cx="512" cy="470" r="310" fill="#FFFFFF"/>
+  <text x="512" y="580" text-anchor="middle" font-family="PingFang SC, Hiragino Sans GB, sans-serif"
+        font-size="360" font-weight="800" fill="#F2703B">洁</text>
+
+  <!-- 星光点缀 -->
+  <g fill="#FFFFFF">
+    <path d="M 790 230 l 12 38 38 12 -38 12 -12 38 -12 -38 -38 -12 38 -12 Z"/>
+    <path d="M 220 700 l 9 28 28 9 -28 9 -9 28 -9 -28 -28 -9 28 -9 Z"/>
+  </g>
+
+  <text x="512" y="900" text-anchor="middle" font-family="PingFang SC, Hiragino Sans GB, sans-serif"
+        font-size="120" font-weight="700" fill="#FFFFFF">小王洁居</text>
+</svg>
diff --git a/小王洁居头像/头像-橙色洁字.png b/小王洁居头像/头像-橙色洁字.png
new file mode 100644
index 0000000..bf7cb6d
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diff --git a/小王洁居头像/头像-绿色房子.png b/小王洁居头像/头像-绿色房子.png
new file mode 100644
index 0000000..6201170
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diff --git a/小王洁居头像/头像-蓝色水滴.png b/小王洁居头像/头像-蓝色水滴.png
new file mode 100644
index 0000000..49c7fbb
Binary files /dev/null and b/小王洁居头像/头像-蓝色水滴.png differ
diff --git a/荔波美食采集/荔波美食采集_字段说明.csv b/荔波美食采集/荔波美食采集_字段说明.csv
new file mode 100644
index 0000000..e998562
--- /dev/null
+++ b/荔波美食采集/荔波美食采集_字段说明.csv
@@ -0,0 +1,47 @@
+"分组","字段名(英文)","中文名","说明","示例","是否必填","数据来源"
+"标识","id","记录ID","唯一主键,建议 平台缩写_note_id_序号","xhs_6612aef_01","是","系统生成"
+"标识","record_level","记录粒度","这条是菜品还是店铺","菜品","是","采集判断"
+"美食本体","name","名称","菜品名或店铺名","荔波精华卷粉","是","笔记正文"
+"美食本体","category","类别","特色菜 / 小吃 / 正餐 / 夜市 / 饮品 / 伴手礼","小吃","是","规则+人工"
+"美食本体","cuisine_type","菜系风味","布依 / 水族 / 瑶族 / 苗族 / 贵州酸汤 / 黔南本地 / 融合","黔南本地","否","笔记"
+"美食本体","ethnic_tag","民族特色","关联的少数民族(荔波多民族聚居)","水族","否","笔记"
+"美食本体","signature_items","招牌菜品","店铺粒度时填必点菜,多值用分号","虾酸牛肉;风猪","否","笔记"
+"美食本体","taste_profile","口味标签","酸 / 辣 / 鲜 / 香 / 发酵 / 清淡,多值用分号","酸;发酵","否","笔记"
+"美食本体","spicy_level","辣度","不辣 / 微辣 / 中辣 / 重辣 / 可选","中辣","否","笔记"
+"位置","area","所在区域","小七孔景区内 / 景区门口 / 荔波县城 / 大七孔 / 瑶山古寨 / 其他","荔波县城","是","笔记+地图"
+"位置","address","详细地址","文字地址","荔波县向阳路XX号","否","笔记+地图"
+"位置","distance_to_xqk","距小七孔","到小七孔景区的距离或车程","县城约30km / 40分钟","否","地图计算"
+"位置","lng","经度","高德/百度坐标","107.88","否","地图"
+"位置","lat","纬度","高德/百度坐标","25.41","否","地图"
+"价格","price_per_person","人均","人均消费(元)","45","否","笔记+点评"
+"价格","price_level","价格档","¥便宜 / ¥¥适中 / ¥¥¥偏贵","¥","否","推算"
+"价格","signature_price","招牌单价","招牌菜价格","卷粉8元/份","否","笔记"
+"推荐场景","suitable_for","适合人群","家庭 / 情侣 / 朋友聚会 / 独自 / 亲子,多值用分号","家庭;朋友聚会","否","推算"
+"推荐场景","meal_time","适合餐次","早餐 / 午餐 / 晚餐 / 夜宵,多值用分号","早餐;夜宵","否","推算"
+"推荐场景","scene_tag","场景标签","正餐 / 打卡拍照 / 快速解决 / 宵夜 / 伴手礼","快速解决","否","推算"
+"推荐场景","recommend_reason","推荐语","一句话推荐理由(直接给游客看)","荔波人从小吃到大的早餐,酸辣开胃","否","生成+摘录"
+"热度口碑","popularity_score","综合热度","0-100,由点赞/收藏/提及归一化","82","否","计算"
+"热度口碑","likes_count","点赞数","来源笔记点赞","1203","否","平台"
+"热度口碑","collects_count","收藏数","来源笔记收藏","890","否","平台"
+"热度口碑","comments_count","评论数","来源笔记评论","156","否","平台"
+"热度口碑","mention_count","提及笔记数","去重后被多少条采集笔记提到","14","否","计算"
+"热度口碑","rating","评分","若有点评评分(5分制)","4.6","否","点评"
+"热度口碑","sentiment","口碑倾向","正面 / 中性 / 负面 / 褒贬不一","正面","否","情感分析"
+"实用信息","business_hours","营业时间","","07:00-14:00","否","笔记+点评"
+"实用信息","need_reservation","是否需预约","是 / 否 / 旺季需要","旺季需要","否","笔记"
+"实用信息","phone","联系电话","","0854-XXXXXXX","否","点评"
+"实用信息","queue_level","排队情况","无需排队 / 小排 / 大排长龙","小排","否","笔记"
+"采集溯源","source_platform","来源平台","小红书 / 抖音 / 大众点评 / 携程","小红书","是","系统"
+"采集溯源","source_keyword","采集关键词","命中的搜索词(对应上一轮的关键词表)","荔波卷粉","是","系统"
+"采集溯源","note_id","笔记ID","平台内容唯一ID(核心去重键)","66120aef000000001f00abcd","是","平台"
+"采集溯源","note_url","笔记链接","原始链接,便于回溯核实","https://www.xiaohongshu.com/...","是","平台"
+"采集溯源","note_title","笔记标题","","荔波必吃!本地人私藏卷粉","否","平台"
+"采集溯源","author","作者","博主昵称","贵州吃货小李","否","平台"
+"采集溯源","publish_date","发布时间","YYYY-MM-DD","2025-06-12","否","平台"
+"采集溯源","collect_date","采集时间","YYYY-MM-DD","2026-07-27","是","系统"
+"采集溯源","image_urls","图片链接","多张用分号分隔","https://a.jpg;https://b.jpg","否","平台"
+"采集溯源","raw_excerpt","原文摘录","关键原文片段,留证防杜撰","这家卷粉是本地人早餐首选...","否","平台"
+"质量审核","data_quality","数据质量","已核实 / 待核实 / 存疑","待核实","是","人工+规则"
+"质量审核","is_ad","疑似广告","是 / 否(过滤软广探店)","否","否","规则"
+"质量审核","dedup_key","去重键","名称+区域归一后的键","荔波精华卷粉|县城","是","计算"
+"质量审核","notes","备注","自由备注","","否","人工"
diff --git a/荔波美食采集/荔波美食采集_数据模板.csv b/荔波美食采集/荔波美食采集_数据模板.csv
new file mode 100644
index 0000000..3a80ead
--- /dev/null
+++ b/荔波美食采集/荔波美食采集_数据模板.csv
@@ -0,0 +1,6 @@
+id,record_level,name,category,cuisine_type,ethnic_tag,signature_items,taste_profile,spicy_level,area,address,distance_to_xqk,lng,lat,price_per_person,price_level,signature_price,suitable_for,meal_time,scene_tag,recommend_reason,popularity_score,likes_count,collects_count,comments_count,mention_count,rating,sentiment,business_hours,need_reservation,phone,queue_level,source_platform,source_keyword,note_id,note_url,note_title,author,publish_date,collect_date,image_urls,raw_excerpt,data_quality,is_ad,dedup_key,notes
+xhs_sample_01,菜品,荔波精华卷粉,小吃,黔南本地,,,酸;鲜,微辣,荔波县城,荔波县向阳路(示例),县城约30km,,,10,¥,8元/份,家庭;独自,早餐;夜宵,快速解决,荔波人从小吃到大的早餐卷粉,酸辣开胃份量足,80,1203,890,156,14,4.6,正面,06:30-13:00,否,,小排,小红书,荔波卷粉,66120aef000000001f00sample,https://www.xiaohongshu.com/explore/sample01,荔波必吃本地人私藏卷粉,示例博主A,2025-06-12,2026-07-27,,示例原文摘录:这家卷粉是本地人早餐首选,待核实,否,荔波精华卷粉|县城,样例数据请替换
+xhs_sample_02,菜品,虾酸牛肉,特色菜,黔南本地,布依,,酸;发酵;鲜,中辣,荔波县城,,,,,75,¥¥,,朋友聚会;家庭,午餐;晚餐,正餐,黔南招牌发酵酸味牛肉锅越煮越香,85,2100,1500,300,22,4.7,正面,10:30-21:30,旺季需要,,大排长龙,小红书,荔波虾酸,66120bff000000001f00sample,https://www.xiaohongshu.com/explore/sample02,荔波虾酸牛肉封神了,示例博主B,2025-07-01,2026-07-27,,示例原文摘录:第一次吃虾酸有点冲吃惯了会上瘾,待核实,否,虾酸牛肉|县城,样例数据请替换
+xhs_sample_03,菜品,荔波风猪,特色菜,黔南本地,布依,,香;咸鲜,不辣,荔波县城,,,,,60,¥¥,,家庭;情侣,午餐;晚餐,正餐,荔波头号招牌腌制小乳猪皮脆肉香可做伴手礼,78,980,760,88,9,4.5,褒贬不一,,否,,小排,小红书,荔波风猪,66120cff000000001f00sample,https://www.xiaohongshu.com/explore/sample03,来荔波一定要试的风猪,示例博主C,2025-05-20,2026-07-27,,示例原文摘录:风猪偏咸配米饭绝了,待核实,否,荔波风猪|县城,样例数据请替换
+xhs_sample_04,店铺,瑶山鸡(某农家乐),正餐,瑶族,瑶山鸡;土鸡汤,鲜;香,微辣,瑶山古寨,荔波瑶山古寨内(示例),距小七孔约15km,,,90,¥¥,,家庭;朋友聚会,午餐;晚餐,正餐,瑶寨土养走地鸡鸡汤清甜适合家庭聚餐,72,650,430,70,6,4.4,正面,10:00-20:00,建议预约,,无需排队,小红书,荔波瑶山鸡,66120dff000000001f00sample,https://www.xiaohongshu.com/explore/sample04,瑶山古寨吃土鸡,示例博主D,2025-08-03,2026-07-27,,示例原文摘录:环境好鸡很嫩就是要开车过去,待核实,否,瑶山鸡|瑶山古寨,样例数据请替换
+xhs_sample_05,菜品,樟江烤鱼,夜市,黔南本地,,,鲜;辣;香,中辣,荔波县城,樟江边夜市(示例),县城约30km,,,55,¥¥,,情侣;朋友聚会,夜宵,宵夜,樟江河鲜现烤配啤酒夏夜氛围感拉满,70,820,540,95,8,4.3,正面,18:00-次日01:00,否,,小排,小红书,荔波夜市,66120eff000000001f00sample,https://www.xiaohongshu.com/explore/sample05,荔波夜市烤鱼摊,示例博主E,2025-07-18,2026-07-27,,示例原文摘录:夜市沿江一排烤鱼摊人均五十多,待核实,否,樟江烤鱼|县城,样例数据请替换
diff --git a/荔波美食采集/采集关键词计划表.csv b/荔波美食采集/采集关键词计划表.csv
new file mode 100644
index 0000000..ce251fb
--- /dev/null
+++ b/荔波美食采集/采集关键词计划表.csv
@@ -0,0 +1,32 @@
+"关键词","优先级","关键词类型","预期产出","对应区域","消歧/备注"
+"荔波美食","P0","广度发现","综合美食笔记","荔波全域","量大但杂,需过滤风景帖"
+"荔波小七孔美食","P0","广度发现","景区周边美食","小七孔","游客搜索高频组合"
+"荔波特色美食","P0","广度发现","特色/招牌菜","荔波全域","直接命中'特色美食'需求"
+"荔波必吃","P0","广度发现","必吃清单","荔波全域",""
+"荔波好吃的","P0","广度发现","综合","荔波全域","口语词,召回不同人群"
+"荔波美食攻略","P0","广度发现","攻略合集","荔波全域","一篇多店,提及量高,性价比好"
+"荔波小吃","P0","广度发现","小吃","荔波全域",""
+"小七孔美食","P0","广度发现","景区美食","小七孔",""
+"小七孔附近美食","P0","广度发现","景区周边","小七孔",""
+"荔波古镇美食","P1","广度发现","古镇/夜市","荔波古镇",""
+"荔波夜市","P1","广度发现","夜市/宵夜","荔波县城","补 meal_time=夜宵 场景"
+"荔波探店","P1","广度发现","探店","荔波全域","软广多,配合 is_ad 过滤"
+"荔波风猪","P1","具体菜名","菜品(特色菜/伴手礼)","荔波全域","荔波头号招牌"
+"荔波臭酸","P1","具体菜名","菜品","荔波全域","强地方特色,长尾价值高"
+"荔波虾酸","P1","具体菜名","菜品(虾酸牛肉)","荔波全域","黔南招牌发酵菜"
+"荔波卷粉","P1","具体菜名","菜品(小吃)","荔波全域","必带'荔波'前缀,否则混凯里/都匀"
+"荔波瑶山鸡","P1","具体菜名","菜品/店铺","瑶山古寨",""
+"荔波酸肉","P2","具体菜名","菜品","荔波全域",""
+"樟江鱼","P2","具体菜名","河鲜","樟江/县城","变体:樟江河鱼、樟江烤鱼"
+"荔波酸汤鱼","P2","具体菜名","菜品","荔波全域","贵州通用,必带'荔波'"
+"荔波杨梅汤","P2","具体菜名","饮品","荔波全域","季节性(夏季)"
+"布依族美食 荔波","P2","民族菜","民族特色","荔波全域",""
+"水族美食 荔波","P2","民族菜","民族特色","荔波全域","荔波是全国水族聚居地"
+"瑶族美食 荔波","P2","民族菜","民族特色","瑶山古寨",""
+"荔波美食推荐","P1","意图词","推荐清单","荔波全域",""
+"荔波本地人推荐","P1","意图词","本地视角","荔波全域","信噪比高,优质来源"
+"荔波必吃清单","P1","意图词","清单","荔波全域",""
+"小七孔景区里面吃什么","P1","意图词","景区内餐饮","小七孔","游客高频问,景区内选择少/价格敏感"
+"荔波美食避坑","P2","意图词","避坑/负面","荔波全域","补充 sentiment 负面样本,防踩雷"
+"荔波三天两晚美食","P2","意图词","行程含美食","荔波全域",""
+"荔波伴手礼","P2","意图词","伴手礼","荔波全域","风猪/杨梅等可带走类"