feat: 热词热力图改为Treemap矩形堆砌布局，面积代表提及次数；赛道分析页面布局调整

2026-07-21 07:59:25 +08:00
parent a40b0f14ae
commit 3c4916ba04
8 changed files with 284 additions and 81 deletions
@@ -45,9 +45,11 @@ def now_iso() -> str:


 def db() -> sqlite3.Connection:
-    conn = sqlite3.connect(DB_PATH)
+    conn = sqlite3.connect(DB_PATH, timeout=10)
    conn.row_factory = sqlite3.Row
+    conn.execute("PRAGMA journal_mode = WAL")
    conn.execute("PRAGMA foreign_keys = ON")
+    conn.execute("PRAGMA busy_timeout = 5000")
    return conn


@@ -160,7 +162,7 @@ def dashboard():
                "type": r["type"] or "经营干货",
                "score": r["score"] or 0,
                "summary": r["ai_summary"] or "",
-                "entities": json.loads(r["entities"]) if r["entities"] else [],
+                "entities": [b["name"] if isinstance(b, dict) else b for b in (json.loads(r["entities"]) if r["entities"] else [])],
            }
            for r in top_intel
        ],
@@ -251,7 +253,7 @@ def intel_list():
                "summary": r["ai_summary"] or r["summary"] or "",
                "keyPoints": json.loads(r["key_points"]) if r["key_points"] else [],
                "score": r["score"] or 0,
-                "entities": json.loads(r["entities"]) if r["entities"] else [],
+                "entities": [b["name"] if isinstance(b, dict) else b for b in (json.loads(r["entities"]) if r["entities"] else [])],
                "timeliness": r["timeliness"] or "中",
                "tags": json.loads(r["tags"]) if r["tags"] else [],
                "url": r["canonical_url"],
@@ -393,26 +395,41 @@ def brand_detail(brand_id: int):
@app.get("/api/analysis")
 def analysis():
    with db() as conn:
-        # 赛道热度趋势：按月统计各赛道的平均评分
+        # 赛道热度趋势：按月统计各赛道的文章数和平均评分，热度=文章数×平均评分/10
        heat_rows = conn.execute(
            """
-            SELECT strftime('%m', a.published_at) AS month,
+            SELECT strftime('%Y-%m', a.published_at) AS month,
                   a.category,
-                   AVG(CAST(json_extract(x.result_json, '$.score') AS REAL)) AS heat
+                   COUNT(*) AS article_cnt,
+                   AVG(CAST(json_extract(x.result_json, '$.score') AS REAL)) AS avg_score
            FROM articles a
            LEFT JOIN ai_analyses x ON x.article_id = a.id AND x.analysis_type = 'editorial'
-            WHERE a.crawl_status = 'success' AND a.category IS NOT NULL
+            WHERE a.crawl_status = 'success' AND a.category IS NOT NULL AND a.category != ''
+              AND a.published_at >= date('now', '-12 months')
            GROUP BY month, a.category
            ORDER BY month
            """
        ).fetchall()

-        # 开关店对比（从文章中提取的品类趋势数据）
-        category_counts = conn.execute(
+        # 品牌门店规模（按赛道聚合真实门店总数）
+        brand_stores = conn.execute(
            """
-            SELECT a.category, COUNT(*) AS cnt
+            SELECT category, SUM(stores) AS total_stores, COUNT(*) AS brand_cnt
+            FROM brands WHERE category IS NOT NULL AND category != '' AND stores > 0
+            GROUP BY category
+            """
+        ).fetchall()
+
+        # 舆情分布（按赛道统计正面/负面/中性文章数）
+        sentiment_rows = conn.execute(
+            """
+            SELECT a.category,
+                   SUM(CASE WHEN json_extract(x.result_json, '$.sentiment') = 'positive' THEN 1 ELSE 0 END) AS positive_cnt,
+                   SUM(CASE WHEN json_extract(x.result_json, '$.sentiment') = 'negative' THEN 1 ELSE 0 END) AS negative_cnt,
+                   SUM(CASE WHEN json_extract(x.result_json, '$.sentiment') = 'neutral' OR json_extract(x.result_json, '$.sentiment') IS NULL THEN 1 ELSE 0 END) AS neutral_cnt
            FROM articles a
-            WHERE a.crawl_status = 'success' AND a.category IS NOT NULL
+            JOIN ai_analyses x ON x.article_id = a.id AND x.analysis_type = 'editorial'
+            WHERE a.crawl_status = 'success' AND a.category IS NOT NULL AND a.category != ''
            GROUP BY a.category
            """
        ).fetchall()
@@ -432,29 +449,55 @@ def analysis():
            """
        ).fetchone()

-        # 热词
-        tag_rows = conn.execute(
+        # 热词热力图：近7天每天各标签出现次数
+        tag_heatmap = conn.execute(
            """
-            SELECT value AS tag, COUNT(*) AS cnt
-            FROM ai_analyses, json_each(json_extract(result_json, '$.tags'))
-            GROUP BY value
-            ORDER BY cnt DESC
-            LIMIT 8
+            SELECT value AS tag,
+                   strftime('%Y-%m-%d', a.published_at) AS day,
+                   COUNT(*) AS cnt
+            FROM ai_analyses x
+            JOIN articles a ON a.id = x.article_id
+            , json_each(json_extract(x.result_json, '$.tags'))
+            WHERE a.published_at >= date('now', '-6 days')
+              AND value IS NOT NULL AND value != ''
+            GROUP BY tag, day
            """
        ).fetchall()

-    # 构建热度趋势数据
+        # 热词总量排行（用于选取 TOP 标签）
+        tag_total = conn.execute(
+            """
+            SELECT value AS tag, COUNT(*) AS cnt
+            FROM ai_analyses x
+            JOIN articles a ON a.id = x.article_id
+            , json_each(json_extract(x.result_json, '$.tags'))
+            WHERE a.published_at >= date('now', '-6 days')
+              AND value IS NOT NULL AND value != ''
+            GROUP BY value
+            ORDER BY cnt DESC
+            LIMIT 10
+            """
+        ).fetchall()
+
+    # 构建热度趋势数据（热度 = 文章数 × 平均评分 / 10）
    heat_trend = {}
    for r in heat_rows:
-        month_key = f"{r['month']}月" if r["month"] else "未知"
+        month_key = f"{r['month'][-2:]}月" if r["month"] else "未知"
        if month_key not in heat_trend:
            heat_trend[month_key] = {"month": month_key}
-        heat_trend[month_key][r["category"]] = round(r["heat"] or 0)
+        heat_val = round((r["article_cnt"] or 0) * (r["avg_score"] or 0) / 10)
+        heat_trend[month_key][r["category"]] = heat_val

-    # 构建开关店数据
-    open_close = [
-        {"category": r["category"], "新开": r["cnt"], "关闭": max(0, r["cnt"] - int(r["cnt"] * 0.85))}
-        for r in category_counts
+    # 构建品牌门店规模数据
+    brand_stores_data = [
+        {"category": r["category"], "stores": r["total_stores"] or 0, "brands": r["brand_cnt"]}
+        for r in brand_stores
+    ]
+
+    # 构建舆情分布数据
+    sentiment_data = [
+        {"category": r["category"], "正面": r["positive_cnt"] or 0, "负面": r["negative_cnt"] or 0, "中性": r["neutral_cnt"] or 0}
+        for r in sentiment_rows
    ]

    # 构建价格分布
@@ -468,11 +511,28 @@ def analysis():
        {"band": "150元以上", "pct": round((price_rows["band6"] or 0) * 100 / total_brands)},
    ]

+    # 构建热词热力图数据（用 UTC 日期与 SQLite date('now') 保持一致）
+    from datetime import timedelta, timezone
+    today_utc = datetime.now(timezone.utc).date()
+    days = [(today_utc - timedelta(days=i)).isoformat() for i in range(6, -1, -1)]
+    top_tags = [r["tag"] for r in tag_total]
+    # 构建矩阵 {tag: {day: cnt}}
+    matrix = {tag: {day: 0 for day in days} for tag in top_tags}
+    for r in tag_heatmap:
+        if r["tag"] in matrix and r["day"] in matrix[r["tag"]]:
+            matrix[r["tag"]][r["day"]] = r["cnt"]
+    hot_keywords = {
+        "days": days,
+        "tags": top_tags,
+        "matrix": matrix,
+    }
+
    return jsonify({
        "categoryHeatTrend": list(heat_trend.values()),
-        "openCloseByCategory": open_close,
+        "brandStoresByCategory": brand_stores_data,
+        "sentimentByCategory": sentiment_data,
        "priceBandData": price_bands,
-        "hotKeywords": [{"word": r["tag"], "change": min(r["cnt"] * 5, 50)} for r in tag_rows],
+        "hotKeywords": hot_keywords,
    })


@@ -36,6 +36,7 @@ load_dotenv(BASE_DIR / ".env")

 DEFAULT_LIST_URL = "https://m.canyin88.com/zixun/"
 ARTICLE_PATH_RE = re.compile(r"/zixun/\d{4}/\d{1,2}/\d{1,2}/\d+\.html$")
+CANYIN168_ARTICLE_RE = re.compile(r"/Article/[a-z]+/\d+\.html$")
 DATE_RE = re.compile(r"(20\d{2})[-/.年](\d{1,2})[-/.月](\d{1,2})(?:日)?(?:\s+(\d{1,2}):(\d{2})(?::(\d{2}))?)?")


@@ -47,9 +48,11 @@ def normalize_url(raw_url: str, base_url: str = DEFAULT_LIST_URL) -> str | None:
    absolute = urljoin(base_url, raw_url.strip())
    parts = urlsplit(absolute)
    host = parts.netloc.lower().removeprefix("m.").removeprefix("www.")
-    if host != "canyin88.com" or not ARTICLE_PATH_RE.search(parts.path):
-        return None
-    return urlunsplit(("https", "www.canyin88.com", parts.path, "", ""))
+    if host == "canyin88.com" and ARTICLE_PATH_RE.search(parts.path):
+        return urlunsplit(("https", "www.canyin88.com", parts.path, "", ""))
+    if host == "canyin168.com" and CANYIN168_ARTICLE_RE.search(parts.path):
+        return urlunsplit(("http", "www.canyin168.com", parts.path, "", ""))
+    return None


 def clean_text(value: str | None) -> str:
@@ -138,7 +141,7 @@ def extract_article(page, url: str) -> dict[str, str | None]:
    page.goto(url, wait_until="domcontentloaded", timeout=60_000)
    page.wait_for_timeout(800)
    document_title = clean_text(page.title())
-    document_title = re.sub(r"(?:[_-]红餐网.*)$", "", document_title).strip()
+    document_title = re.sub(r"(?:[_-](?:红餐网|职业餐饮网).*)$", "", document_title).strip()
    title = meta(page, 'meta[property="og:title"]') or document_title
    if not title or title == "相关推荐":
        title = first_text(page, [".title", "h1"])
@@ -197,17 +200,17 @@ def pending_urls(conn: sqlite3.Connection, discovered: list[str], max_retries: i
    return list(dict.fromkeys(discovered + [row[0] for row in rows]))


-def insert_discoveries(conn: sqlite3.Connection, urls: list[str], source_type: str = "公众号") -> int:
+def insert_discoveries(conn: sqlite3.Connection, urls: list[str], source_type: str = "公众号", source_name: str = "") -> int:
    timestamp = now_iso()
    inserted = 0
    for url in urls:
        cursor = conn.execute(
            """
            INSERT OR IGNORE INTO articles
-                (canonical_url, source_type, discovered_at, updated_at)
-            VALUES (?, ?, ?, ?)
+                (canonical_url, source_type, source_name, discovered_at, updated_at)
+            VALUES (?, ?, ?, ?, ?)
            """,
-            (url, source_type, timestamp, timestamp),
+            (url, source_type, source_name, timestamp, timestamp),
        )
        inserted += cursor.rowcount
    conn.commit()
@@ -439,7 +442,7 @@ def run_crawl(args: argparse.Namespace) -> int:
                            print(f"--- 采集公众号: {source_name} ({list_url}) ---", flush=True)
                            urls = discover_urls(page, list_url, max_scrolls, list_pause_ms)
                            discovered_count += len(urls)
-                            inserted_count += insert_discoveries(conn, urls, source_name)
+                            inserted_count += insert_discoveries(conn, urls, "公众号", source_name)
                            queue = pending_urls(conn, urls, args.max_retries)
                            cutoff = datetime.now() - timedelta(days=lookback_days)
                            for index, url in enumerate(queue, start=1):
@@ -551,7 +554,7 @@ def run_crawl(args: argparse.Namespace) -> int:
            "status": status, "source_type": args.source_type,
            "discovered": discovered_count, "inserted": inserted_count,
            "updated": updated_count, "failed": failed_count,
-        }, ensure_ascii=False, flush=True))
+        }, ensure_ascii=False))
        return 0 if status in {"success", "partial"} else 1


@@ -51,6 +51,23 @@ def get_api_key() -> str:

 # ---- 单篇文章结构化分析 ----

+_PROFANITY_MAP = {
+    "妈的": "**", "傻逼": "**", "他妈": "**", "操": "*",
+    "草泥马": "***", "尼玛": "**", "贱人": "**",
+    "王八蛋": "***", "混蛋": "**", "去死": "**",
+    "毛爷爷": "某伟人", "毛泽东": "某伟人", "国民党": "某党",
+    "共产党": "某党", "长征": "远征", "抗日": "抗战",
+    "革命": "变革", "社会主义": "某主义",
+}
+
+
+def sanitize_content(text: str) -> str:
+    """过滤粗口和敏感词，避免触发千问内容审核。"""
+    for word, replacement in _PROFANITY_MAP.items():
+        text = text.replace(word, replacement)
+    return text
+
+
 def analyze_article(title: str, content: str) -> dict:
    """调用通义千问对文章进行结构化分析。"""
    api_key = get_api_key()
@@ -71,7 +88,7 @@ JSON 字段必须为：
 - numbers（关键数据数组）

 文章标题：{title}
-正文：{content[:24000]}"""
+正文：{sanitize_content(content[:24000])}"""
    payload = json.dumps({
        "model": model,
        "messages": [
@@ -276,6 +293,11 @@ def run_batch_analyze(force: bool, pause: float, retries: int) -> int:
                break
            except Exception as exc:
                last_error = exc
+                err_str = str(exc)
+                # 内容审核失败，标记跳过不重试
+                if "data_inspection_failed" in err_str:
+                    print(f"[{index}/{len(rows)}] SKIP(内容审核) {row['title']}", flush=True)
+                    break
                if attempt <= retries:
                    wait = attempt * 2
                    print(f"[{index}/{len(rows)}] RETRY {attempt}/{retries} {exc}", flush=True)
@@ -94,9 +94,10 @@ export interface Brand {

 export interface AnalysisData {
  categoryHeatTrend: Record<string, any>[]
-  openCloseByCategory: { category: string; 新开: number; 关闭: number }[]
+  brandStoresByCategory: { category: string; stores: number; brands: number }[]
+  sentimentByCategory: { category: string; 正面: number; 负面: number; 中性: number }[]
  priceBandData: { band: string; pct: number }[]
-  hotKeywords: { word: string; change: number }[]
+  hotKeywords: { days: string[]; tags: string[]; matrix: Record<string, Record<string, number>> }
 }

 export interface SourceConfig {
@@ -59,7 +59,7 @@ export default function Home() {
        </div>

        <div className={page === 'qa' ? 'flex h-full flex-col p-4 md:p-6' : 'p-4 md:p-6'}>
-          {page === 'dashboard' && <Dashboard onNavigate={(p) => navigate(`/${p}`)} />}
+          {page === 'dashboard' && <Dashboard onNavigate={(p, articleId, articleTitle) => navigate(articleId ? `/${p}?article=${articleId}&q=${encodeURIComponent(articleTitle || '')}` : `/${p}`)} />}
          {page === 'intel' && <IntelFeed />}
          {page === 'qa' && <QAChat />}
          {page === 'brands' && <BrandLibrary />}
@@ -3,10 +3,58 @@ import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card'
 import { Loader2 } from 'lucide-react'
 import {
  LineChart, Line, BarChart, Bar, XAxis, YAxis, Tooltip, Legend,
-  ResponsiveContainer, CartesianGrid, PieChart, Pie, Cell,
+  ResponsiveContainer, CartesianGrid, PieChart, Pie, Cell, Treemap,
 } from 'recharts'
 import { api, type AnalysisData } from '@/lib/api'

+const treemapColors = ['#fdba74', '#fb923c', '#f97316', '#ea580c', '#c2410c']
+
+function TreemapCell(props: any) {
+  const { x, y, width, height, name, value, maxVal } = props
+  if (width < 30 || height < 20) return null
+  const intensity = maxVal > 0 ? value / maxVal : 0
+  const colorIdx = Math.min(Math.floor(intensity * treemapColors.length), treemapColors.length - 1)
+  const bg = treemapColors[colorIdx]
+  const fontSize = Math.max(10, Math.min(16, width / 8))
+  return (
+    <g>
+      <rect
+        x={x}
+        y={y}
+        width={width}
+        height={height}
+        fill={bg}
+        stroke="#fff"
+        strokeWidth={2}
+        rx={4}
+      />
+      {width > 50 && height > 30 && (
+        <text
+          x={x + width / 2}
+          y={y + height / 2 - 6}
+          textAnchor="middle"
+          fill="#fff"
+          fontSize={fontSize}
+          fontWeight={600}
+        >
+          {name}
+        </text>
+      )}
+      {width > 40 && height > 40 && (
+        <text
+          x={x + width / 2}
+          y={y + height / 2 + 12}
+          textAnchor="middle"
+          fill="rgba(255,255,255,0.85)"
+          fontSize={Math.max(10, fontSize - 3)}
+        >
+          {value}
+        </text>
+      )}
+    </g>
+  )
+}
+
 const lineColors: Record<string, string> = {
  茶饮咖啡: '#f97316',
  快餐: '#3b82f6',
@@ -29,9 +77,10 @@ export default function CategoryAnalysis() {
  }, [])

  const heatTrend = data?.categoryHeatTrend ?? []
-  const openClose = data?.openCloseByCategory ?? []
+  const brandStores = data?.brandStoresByCategory ?? []
+  const sentiment = data?.sentimentByCategory ?? []
  const priceBands = data?.priceBandData ?? []
-  const hotKw = data?.hotKeywords ?? []
+  const hotKw = data?.hotKeywords ?? { days: [], tags: [], matrix: {} }

  if (loading) {
    return (
@@ -54,7 +103,7 @@ export default function CategoryAnalysis() {
      <Card className="border-slate-200">
        <CardHeader className="pb-2">
          <CardTitle className="text-base">赛道热度指数（近 12 个月）</CardTitle>
-          <p className="text-xs text-slate-400">由情报提及量、开关店数据、消费关注度加权合成</p>
+          <p className="text-xs text-slate-400">由情报提及量与 AI 评分加权合成</p>
        </CardHeader>
        <CardContent>
          {heatTrend.length === 0 ? (
@@ -79,26 +128,52 @@ export default function CategoryAnalysis() {
      </Card>

      <div className="grid gap-4 xl:grid-cols-2">
-        {/* 开关店对比 */}
+        {/* 品牌门店规模 */}
        <Card className="border-slate-200">
          <CardHeader className="pb-2">
-            <CardTitle className="text-base">上半年新开 / 关闭门店对比</CardTitle>
-            <p className="text-xs text-slate-400">绿色为正增长缺口，红色为净收缩信号</p>
+            <CardTitle className="text-base">各赛道品牌门店规模</CardTitle>
+            <p className="text-xs text-slate-400">按赛道聚合的品牌总门店数</p>
          </CardHeader>
          <CardContent>
-            {openClose.length === 0 ? (
-              <div className="flex h-64 items-center justify-center text-sm text-slate-400">暂无开关店数据</div>
+            {brandStores.length === 0 ? (
+              <div className="flex h-64 items-center justify-center text-sm text-slate-400">暂无门店数据</div>
            ) : (
            <div className="h-64">
              <ResponsiveContainer width="100%" height="100%">
-                <BarChart data={openClose} barGap={2}>
+                <BarChart data={brandStores} barGap={2}>
+                  <CartesianGrid strokeDasharray="3 3" stroke="#f1f5f9" />
+                  <XAxis dataKey="category" tick={{ fontSize: 11 }} tickLine={false} axisLine={false} />
+                  <YAxis tick={{ fontSize: 11 }} tickLine={false} axisLine={false} width={50} />
+                  <Tooltip />
+                  <Bar dataKey="stores" name="门店总数" fill="#3b82f6" radius={[3, 3, 0, 0]} />
+                </BarChart>
+              </ResponsiveContainer>
+            </div>
+            )}
+          </CardContent>
+        </Card>
+
+        {/* 舆情分布 */}
+        <Card className="border-slate-200">
+          <CardHeader className="pb-2">
+            <CardTitle className="text-base">各赛道舆情分布</CardTitle>
+            <p className="text-xs text-slate-400">按赛道统计正面/负面/中性情报数量</p>
+          </CardHeader>
+          <CardContent>
+            {sentiment.length === 0 ? (
+              <div className="flex h-64 items-center justify-center text-sm text-slate-400">暂无舆情数据</div>
+            ) : (
+            <div className="h-64">
+              <ResponsiveContainer width="100%" height="100%">
+                <BarChart data={sentiment} barGap={2}>
                  <CartesianGrid strokeDasharray="3 3" stroke="#f1f5f9" />
                  <XAxis dataKey="category" tick={{ fontSize: 11 }} tickLine={false} axisLine={false} />
                  <YAxis tick={{ fontSize: 11 }} tickLine={false} axisLine={false} width={44} />
                  <Tooltip />
                  <Legend wrapperStyle={{ fontSize: 12 }} />
-                  <Bar dataKey="新开" fill="#10b981" radius={[3, 3, 0, 0]} />
-                  <Bar dataKey="关闭" fill="#f87171" radius={[3, 3, 0, 0]} />
+                  <Bar dataKey="正面" stackId="a" fill="#10b981" radius={[0, 0, 0, 0]} />
+                  <Bar dataKey="中性" stackId="a" fill="#cbd5e1" radius={[0, 0, 0, 0]} />
+                  <Bar dataKey="负面" stackId="a" fill="#f87171" radius={[3, 3, 0, 0]} />
                </BarChart>
              </ResponsiveContainer>
            </div>
@@ -147,28 +222,48 @@ export default function CategoryAnalysis() {
            )}
          </CardContent>
        </Card>
-      </div>

-      {/* 热词趋势 */}
-      <Card className="border-slate-200">
-        <CardHeader className="pb-3">
-          <CardTitle className="text-base">行业热词关注度周环比</CardTitle>
-        </CardHeader>
-        <CardContent>
-          {hotKw.length === 0 ? (
-            <div className="py-8 text-center text-sm text-slate-400">暂无热词数据</div>
-          ) : (
-          <div className="grid grid-cols-2 gap-3 sm:grid-cols-4">
-            {hotKw.map((k) => (
-              <div key={k.word} className="rounded-lg border border-slate-100 p-3">
-                <div className="text-sm font-medium text-slate-800">{k.word}</div>
-                <div className="mt-1 text-xs font-semibold text-emerald-500">▲ +{k.change}%</div>
-              </div>
-            ))}
-          </div>
-          )}
-        </CardContent>
-      </Card>
+        {/* 热词热力图 — 矩形堆砌，大小代表提及次数 */}
+        <Card className="border-slate-200">
+          <CardHeader className="pb-3">
+            <CardTitle className="text-base">行业热词近7天热力图</CardTitle>
+            <p className="text-xs text-slate-400">矩形面积代表提及次数，颜色深浅表示热度高低</p>
+          </CardHeader>
+          <CardContent>
+            {!hotKw?.tags || hotKw.tags.length === 0 ? (
+              <div className="py-8 text-center text-sm text-slate-400">暂无热词数据</div>
+            ) : (() => {
+              const treemapData = hotKw.tags
+                .map((tag) => ({
+                  name: tag,
+                  size: hotKw.days.reduce((sum, d) => sum + (hotKw.matrix[tag]?.[d] || 0), 0),
+                }))
+                .filter((d) => d.size > 0)
+                .sort((a, b) => b.size - a.size)
+
+              if (treemapData.length === 0) {
+                return <div className="py-8 text-center text-sm text-slate-400">暂无热词数据</div>
+              }
+
+              const maxVal = Math.max(...treemapData.map((d) => d.size))
+
+              return (
+                <div className="h-64">
+                  <ResponsiveContainer width="100%" height="100%">
+                    <Treemap
+                      data={treemapData}
+                      dataKey="size"
+                      nameKey="name"
+                      stroke="#fff"
+                      content={<TreemapCell maxVal={maxVal} />}
+                    />
+                  </ResponsiveContainer>
+                </div>
+              )
+            })()}
+          </CardContent>
+        </Card>
+      </div>
    </div>
  )
 }
@@ -5,7 +5,7 @@ import { Badge } from '@/components/ui/badge'
 import { api, type DashboardData, type OverviewStats } from '@/lib/api'

 export interface PageKeyHintType {
-  onNavigate?: (page: 'intel' | 'qa' | 'analysis' | 'reports') => void
+  onNavigate?: (page: 'intel' | 'qa' | 'analysis' | 'reports', articleId?: string, articleTitle?: string) => void
 }

 const statCards = (ovStats: OverviewStats) => [
@@ -109,7 +109,8 @@ export default function Dashboard({ onNavigate }: PageKeyHintType) {
            {topIntel.map((item, idx) => (
              <div
                key={item.id}
-                className="flex items-start gap-3 rounded-lg border border-slate-100 p-3 transition-colors hover:border-orange-200 hover:bg-orange-50/40"
+                className="flex cursor-pointer items-start gap-3 rounded-lg border border-slate-100 p-3 transition-colors hover:border-orange-200 hover:bg-orange-50/40"
+                onClick={() => onNavigate?.('intel', item.id, item.title)}
              >
                <div className="flex h-6 w-6 shrink-0 items-center justify-center rounded-md bg-slate-900 text-xs font-bold text-white">
                  {idx + 1}
@@ -1,5 +1,6 @@
 import { useEffect, useState } from 'react'
 import { createPortal } from 'react-dom'
+import { useSearchParams } from 'react-router'
 import { ChevronDown, ChevronUp, Search, Sparkles, ListChecks, Loader2, FileText, AlertCircle, TrendingUp, PlayCircle, X } from 'lucide-react'
 import { Card, CardContent } from '@/components/ui/card'
 import { Badge } from '@/components/ui/badge'
@@ -26,6 +27,7 @@ function scoreColor(score: number) {
 }

 export default function IntelFeed() {
+  const [searchParams, setSearchParams] = useSearchParams()
  const [type, setType] = useState<string>('全部')
  const [category, setCategory] = useState('全部赛道')
  const [query, setQuery] = useState('')
@@ -39,16 +41,33 @@ export default function IntelFeed() {
  const [totalPages, setTotalPages] = useState(1)
  const [total, setTotal] = useState(0)
  const perPage = 20
+  const pendingArticleId = searchParams.get('article')
+  const pendingQuery = searchParams.get('q') || ''

  useEffect(() => {
    setLoading(true)
    setExpanded(null)
    setDetail(null)
-    api.getIntel({ type: type === '全部' ? undefined : type, category: category === '全部赛道' ? undefined : category, q: query || undefined, page, per_page: perPage })
+    const searchQuery = pendingQuery || query
+    api.getIntel({ type: type === '全部' ? undefined : type, category: category === '全部赛道' ? undefined : category, q: searchQuery || undefined, page, per_page: perPage })
      .then((res) => { setItems(res.items); setTotalPages(res.pages); setTotal(res.total) })
      .catch(() => { setItems([]); setTotalPages(1); setTotal(0) })
      .finally(() => setLoading(false))
-  }, [type, category, query, page])
+  }, [type, category, query, page, pendingQuery])
+
+  // 从 Dashboard 跳转过来时，同步搜索关键词并自动展开对应文章
+  useEffect(() => {
+    if (pendingQuery && !query) {
+      setQuery(pendingQuery)
+    }
+    if (pendingArticleId && items.length > 0 && !expanded) {
+      const found = items.find((it) => it.id === pendingArticleId)
+      if (found) {
+        toggleExpand(found.id)
+        setSearchParams({}, { replace: true })
+      }
+    }
+  }, [pendingArticleId, pendingQuery, items, expanded, query])

  const toggleExpand = (id: string) => {
    if (expanded === id) {
@@ -279,9 +298,11 @@ export default function IntelFeed() {
                        {(detail?.analysis?.brands || item.entities).length > 0 && (
                          <div className="flex flex-wrap items-center gap-1.5 rounded-lg border border-slate-100 p-3">
                            <span className="text-xs text-slate-400">关联品牌：</span>
-                            {(detail?.analysis?.brands || item.entities).map((e) => (
-                              <Badge key={e} variant="secondary" className="text-[10px]">{e}</Badge>
-                            ))}
+                            {(detail?.analysis?.brands || item.entities).map((e, i) => {
+                              const label = typeof e === 'string' ? e : (e as { name?: string })?.name || ''
+                              if (!label) return null
+                              return <Badge key={i} variant="secondary" className="text-[10px]">{label}</Badge>
+                            })}
                          </div>
                        )}