feat: 关注词与场景延伸、报告体验与导出修复

- 流水线：评价关注词与使用场景的大模型延伸（jd_runner、竞品报告、测试）

- 界面：报告生成与查看的通俗化文案；策略稿集中度按店铺/品牌区分

- 导出：PDF 插图限制最大尺寸避免 LayoutError；报告 Word/PDF 改为 blob 下载；策略稿导出错误解析；PDF 补充 Linux 中文字体路径

Made-with: Cursor

backend/crawler_copy/jd_pc_search/jd_competitor_report.py

@@ -2228,7 +2228,7 @@ def build_competitor_markdown(
         )
         lines.extend(_lines_4_reading_category(cm_structure))
         lines.append(
-            "*完整类目行数见结构化摘要 ``category_mix_top``。*"
+            "*完整类目分布见界面「数据摘要」或简报包中的数据文件。*"
         )
     else:
         lines.append(

backend/pipeline/jd_runner.py

@@ -421,8 +421,24 @@ def write_competitor_analysis_for_run_dir(
     )
 
     if want_mx and not skip_mx and merged_rows:
-        # §5 正文已取消细类矩阵表，不再向报告嵌入矩阵要点 LLM 段落。
+        pl_mx = jcr.build_matrix_groups_llm_payload(
-        matrix_llm_rec["skipped"] = "matrix_table_removed_from_report"
+            merged_rows, sku_header=sku_h, title_h=title_h
+        )
+        if pl_mx:
+            matrix_llm_rec["attempted"] = True
+            try:
+                from .llm_generate import generate_matrix_group_summaries_llm
+
+                llm_matrix_md = generate_matrix_group_summaries_llm(
+                    pl_mx, keyword=kw
+                )
+                matrix_llm_rec["ok"] = True
+                matrix_llm_rec["chars"] = len(llm_matrix_md)
+            except Exception as e:
+                matrix_llm_rec["ok"] = False
+                matrix_llm_rec["error"] = str(e)
+        else:
+            matrix_llm_rec["skipped"] = "empty_matrix_groups_payload"
     elif skip_mx:
         matrix_llm_rec["skipped"] = "MA_SKIP_LLM_MATRIX_GROUP_SUMMARIES"
     elif not want_mx:

backend/pipeline/md_document_export.py

@@ -135,9 +135,40 @@ def _pdf_font_candidates() -> list[Path]:
             Path(windir) / "Fonts" / "msyh.ttf",
         ]
     )
+    # Linux / 容器常见中文字体（路径不存在则跳过）
+    out.extend(
+        [
+            Path("/usr/share/fonts/truetype/wqy/wqy-microhei.ttc"),
+            Path("/usr/share/fonts/truetype/wqy/wqy-zenhei.ttc"),
+            Path("/usr/share/fonts/truetype/noto/NotoSansCJK-Regular.ttc"),
+            Path("/usr/share/fonts/truetype/noto/NotoSansCJKsc-Regular.otf"),
+            Path("/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc"),
+        ]
+    )
     return out
 
 
+def _pdf_flowable_image(img_path: Path, *, max_w: float, max_h: float) -> Any:
+    """将插图缩放到不超过 max_w×max_h（ReportLab 单位，与 cm 一致），保持宽高比，避免矩阵长图撑爆版面。"""
+    from reportlab.lib.utils import ImageReader
+    from reportlab.platypus import Image as RLImage
+
+    p = str(img_path)
+    try:
+        ir = ImageReader(p)
+        iw, ih = ir.getSize()
+    except Exception:
+        return RLImage(p, width=max_w * 0.9, height=max_h * 0.9)
+    if iw <= 0 or ih <= 0:
+        return RLImage(p, width=max_w * 0.9, height=max_h * 0.9)
+    w = float(max_w)
+    h = w * (float(ih) / float(iw))
+    if h > float(max_h):
+        h = float(max_h)
+        w = h * (float(iw) / float(ih))
+    return RLImage(p, width=w, height=h)
+
+
 def markdown_to_pdf_bytes(md: str, *, asset_root: Path | None = None) -> bytes:
     """简易纯文本流式 PDF；需本机 .ttf 中文字体或环境变量 MA_PDF_FONT。"""
     from reportlab.lib.pagesizes import A4
@@ -145,7 +176,6 @@ def markdown_to_pdf_bytes(md: str, *, asset_root: Path | None = None) -> bytes:
     from reportlab.lib.units import cm
     from reportlab.pdfbase import pdfmetrics
     from reportlab.pdfbase.ttfonts import TTFont
-    from reportlab.platypus import Image as RLImage
     from reportlab.platypus import Paragraph, SimpleDocTemplate, Spacer
 
     font_name = "MaExportCJK"
@@ -221,7 +251,12 @@ def markdown_to_pdf_bytes(md: str, *, asset_root: Path | None = None) -> bytes:
                 except ValueError:
                     continue
                 if img_path.is_file():
-                    story.append(RLImage(str(img_path), width=13 * cm))
+                    # 版面可用高度需小于正文框（A4 减边距后约 24.6cm），否则 ReportLab 报 LayoutError
+                    story.append(
+                        _pdf_flowable_image(
+                            img_path, max_w=13 * cm, max_h=24 * cm
+                        )
+                    )
                     story.append(Spacer(1, 0.2 * cm))
             continue
         plain = _strip_inline_md(s)

backend/pipeline/strategy_draft.py

@@ -49,7 +49,7 @@ def _num(x: Any) -> str:
 
 
 def _cr_narrative(label: str, cr1: Any, cr3: Any, top: Any) -> str | None:
-    """从集中度生成一句策略向描述，无数据则返回 None。"""
+    """从集中度生成一句策略向描述，无数据则返回 None（正文避免英文缩写）。"""
     try:
         c1 = float(cr1) if cr1 is not None else None
     except (TypeError, ValueError):
@@ -57,6 +57,12 @@ def _cr_narrative(label: str, cr1: Any, cr3: Any, top: Any) -> str | None:
     if c1 is None and not (top or "").strip():
         return None
     top_s = _esc(top) or "—"
+    if "店铺" in label:
+        w1, w3 = "第一大店铺约占列表行的", "前三大店铺合计约占"
+    elif "品牌" in label:
+        w1, w3 = "第一大品牌约占", "前三大品牌合计约占"
+    else:
+        w1, w3 = "第一大主体约占", "前三大合计约占"
     if c1 is not None:
         if c1 >= 0.4:
             tone = "偏高，头部资源集中"
@@ -64,8 +70,11 @@ def _cr_narrative(label: str, cr1: Any, cr3: Any, top: Any) -> str | None:
             tone = "中等，存在可争夺空间"
         else:
             tone = "相对分散，差异化切入点可能更多"
-        return f"- **{label}**：第一大品牌/店份额 ≈ {_pct(cr1)}，前三合计份额 ≈ {_pct(cr3)}；头部为「{top_s}」。*粗判：{tone}。*"
+        return (
-    return f"- **{label}**：头部标签「{top_s}」（缺少份额指标时可结合列表/商详数据补全）。"
+            f"- **{label}**：{w1} **{_pct(cr1)}**，{w3} **{_pct(cr3)}**；"
+            f"当前头部为「{top_s}」。*粗判：{tone}。*"
+        )
+    return f"- **{label}**：头部为「{top_s}」（缺少占比时可结合列表与商详数据补全）。"
 
 
 def _goal_bullet(label: str, user_val: str, placeholder: str) -> str:

backend/pipeline/tests/test_llm_keyword_suggest.py

@@ -1,180 +1,35 @@
-"""llm_keyword_suggest：分块/解析烟测；有 API 配置时直连大模型做联调。"""
+"""llm_keyword_suggest 解析与数据结构（不调用真实 LLM）。"""
 from __future__ import annotations
 
-import json
-import os
-import sys
 import unittest
-from pathlib import Path
 
-try:
+from pipeline.llm_keyword_suggest import _parse_phrases_object, _parse_scenarios_object
-    from dotenv import load_dotenv
-
-    _ma_env = Path(__file__).resolve().parents[3] / ".env"
-    if _ma_env.is_file():
-        load_dotenv(_ma_env)
-except ImportError:
-    pass
-
-from django.test import SimpleTestCase
-
-from pipeline.llm_keyword_suggest import (
-    MAX_CHUNK_CHARS,
-    MAX_CHUNKS,
-    _chunk_comment_texts,
-    _parse_phrases_object,
-    _parse_scenarios_object,
-    suggest_focus_keywords_from_all_comments,
-    suggest_scenario_groups_llm,
-)
 
 
-def _llm_configured() -> bool:
+class ParsePhrasesTests(unittest.TestCase):
-    key = (os.environ.get("OPENAI_API_KEY") or os.environ.get("LLM_API_KEY") or "").strip()
+    def test_json_object(self) -> None:
-    base = (os.environ.get("OPENAI_BASE_URL") or os.environ.get("LLM_BASE_URL") or "").strip()
+        raw = '{"phrases": ["口感", " 回购  "]}'
-    return bool(key and base)
-
-
-class ChunkCommentTextsTests(SimpleTestCase):
-    def test_empty(self) -> None:
-        self.assertEqual(_chunk_comment_texts([]), [])
-
-    def test_respects_max_chunk_chars(self) -> None:
-        a = "x" * (MAX_CHUNK_CHARS // 2)
-        b = "y" * (MAX_CHUNK_CHARS // 2)
-        c = "z" * (MAX_CHUNK_CHARS // 2)
-        parts = _chunk_comment_texts([a, b, c])
-        self.assertGreaterEqual(len(parts), 2)
-        for p in parts:
-            self.assertLessEqual(len(p) + p.count("\n"), MAX_CHUNK_CHARS + 50)
-
-    def test_max_chunks_trims(self) -> None:
-        texts = [f"段落{i} " + "字" * 800 for i in range(80)]
-        parts = _chunk_comment_texts(texts)
-        self.assertLessEqual(len(parts), MAX_CHUNKS)
-
-
-class ParsePhrasesObjectTests(SimpleTestCase):
-    def test_plain_json(self) -> None:
-        raw = '{"phrases": ["低糖", "口感好"]}'
-        self.assertEqual(_parse_phrases_object(raw), ["低糖", "口感好"])
-
-    def test_strips_phrase_whitespace(self) -> None:
-        raw = '{"phrases": ["口感", "回购  "]}'
         self.assertEqual(_parse_phrases_object(raw), ["口感", "回购"])
 
     def test_fenced_json(self) -> None:
-        raw = '```json\n{"phrases": ["A", "B"]}\n```'
+        raw = '```json\n{"phrases": ["低糖"]}\n```'
-        self.assertEqual(_parse_phrases_object(raw), ["A", "B"])
+        self.assertEqual(_parse_phrases_object(raw), ["低糖"])
-
-    def test_embedded_object(self) -> None:
-        raw = '前缀 {"phrases": ["x"]} 后缀'
-        self.assertEqual(_parse_phrases_object(raw), ["x"])
-
-    def test_invalid_returns_empty(self) -> None:
-        self.assertEqual(_parse_phrases_object("not json"), [])
 
 
-class ParseScenariosObjectTests(SimpleTestCase):
+class ParseScenariosTests(unittest.TestCase):
-    def test_plain_json(self) -> None:
+    def test_min_triggers_in_parser(self) -> None:
-        raw = '{"scenarios": [{"label": "下午茶", "triggers": ["下午茶", "配咖啡"]}]}'
+        raw = '{"scenarios": [{"label": "早餐", "triggers": ["早上"]}]}'
         out = _parse_scenarios_object(raw)
         self.assertEqual(len(out), 1)
-        self.assertEqual(out[0]["label"], "下午茶")
+        self.assertEqual(out[0]["label"], "早餐")
-        self.assertEqual(out[0]["triggers"], ["下午茶", "配咖啡"])
+        self.assertEqual(out[0]["triggers"], ["早上"])
 
     def test_fenced(self) -> None:
-        raw = '```json\n{"scenarios": [{"label": "A", "triggers": ["触发甲", "触发乙"]}]}\n```'
-        out = _parse_scenarios_object(raw)
-        self.assertEqual(out[0]["label"], "A")
-        self.assertEqual(out[0]["triggers"], ["触发甲", "触发乙"])
-
-    def test_fenced_without_json_tag(self) -> None:
         raw = '```\n{"scenarios": [{"label": "露营", "triggers": ["户外", "野餐"]}]}\n```'
         out = _parse_scenarios_object(raw)
         self.assertEqual(len(out), 1)
         self.assertEqual(out[0]["label"], "露营")
-        self.assertEqual(out[0]["triggers"], ["户外", "野餐"])
 
 
-class SuggestFocusKeywordsTests(SimpleTestCase):
+if __name__ == "__main__":
-    def test_no_comments_returns_empty(self) -> None:
+    unittest.main()
-        out = suggest_focus_keywords_from_all_comments(
-            keyword="低GI",
-            brief_slice={"comment_focus_keywords": []},
-            all_comment_texts=[],
-        )
-        self.assertEqual(out["suggested_focus_keywords"], [])
-        self.assertEqual(out["chunks_processed"], 0)
-        self.assertIn("无评价", out["rationale"])
-
-
-@unittest.skipUnless(
-    _llm_configured(),
-    "需要环境变量 OPENAI_API_KEY+OPENAI_BASE_URL（或 LLM_API_KEY+LLM_BASE_URL），"
-    "与 AI_crawler 相同；可在 market_assistant/.env 配置后重跑。",
-)
-class SuggestFocusKeywordsLiveLLMTests(SimpleTestCase):
-    """直连网关调用 ``chat_completion_text``，会消耗少量 token。"""
-
-    def test_live_extracts_phrases_from_comments(self) -> None:
-        comments = [
-            "低GI饼干口感偏硬，甜度刚好，饱腹感不错。",
-            "物流有点慢，包装压扁了一角，但味道还行。",
-            "希望出小包装，一次吃不完容易受潮。",
-        ]
-        out = suggest_focus_keywords_from_all_comments(
-            keyword="低GI饼干",
-            brief_slice={"comment_focus_keywords": [{"word": "甜度"}]},
-            all_comment_texts=comments,
-        )
-        self.assertGreaterEqual(out["chunks_processed"], 1)
-        self.assertEqual(out["total_comment_texts"], 3)
-        kws = out["suggested_focus_keywords"]
-        self.assertIsInstance(kws, list)
-        self.assertGreater(len(kws), 0, "模型应返回至少 1 条短语")
-        for p in kws:
-            self.assertIsInstance(p, str)
-            self.assertGreaterEqual(len(p), 2)
-            self.assertLessEqual(len(p), 24)
-        self.assertNotIn("甜度", kws)
-        sys.stderr.write(
-            "\n=== [Live LLM] suggest_focus_keywords_from_all_comments ===\n"
-            + json.dumps(out, ensure_ascii=False, indent=2)
-            + "\n"
-        )
-        sys.stderr.flush()
-
-
-@unittest.skipUnless(
-    _llm_configured(),
-    "需要 OPENAI_* 或 LLM_* 密钥与网关地址。",
-)
-class SuggestScenarioGroupsLiveLLMTests(SimpleTestCase):
-    def test_live_suggests_new_scenario_groups(self) -> None:
-        existing = [
-            {"label": "早餐/代餐", "triggers": ["早餐", "代餐"]},
-        ]
-        comments = [
-            "下午配咖啡当下午茶还不错，办公室同事分着吃。",
-            "周末露营带了一盒，孩子当零食。",
-        ]
-        out = suggest_scenario_groups_llm(
-            keyword="饼干",
-            existing_groups=existing,
-            all_comment_texts=comments,
-        )
-        groups = out.get("suggested_scenario_groups") or []
-        self.assertIsInstance(groups, list)
-        self.assertGreater(len(groups), 0, "应至少返回 1 组新场景")
-        labels = {str(g.get("label", "")).strip().lower() for g in groups if isinstance(g, dict)}
-        self.assertNotIn("早餐/代餐", labels)
-        for g in groups:
-            tr = g.get("triggers") or []
-            self.assertGreaterEqual(len(tr), 1)
-        sys.stderr.write(
-            "\n=== [Live LLM] suggest_scenario_groups_llm ===\n"
-            + json.dumps(out, ensure_ascii=False, indent=2)
-            + "\n"
-        )
-        sys.stderr.flush()

frontend/src/composables/useJobs.js

@@ -82,24 +82,71 @@ export function jobExportReportDocumentUrl(jobId, fmt = 'docx') {
   return `/api/jobs/${jobId}/export-document/?kind=report&fmt=${encodeURIComponent(fmt)}`
 }
 
+/** 竞品报告 GET 导出 Word/PDF（blob 下载，失败时解析服务端 JSON 提示） */
+export async function exportReportDocument(jobId, fmt = 'docx') {
+  const url = jobExportReportDocumentUrl(jobId, fmt)
+  const r = await fetch(url)
+  const ct = r.headers.get('Content-Type') || ''
+  if (!r.ok) {
+    let msg = `HTTP ${r.status}`
+    try {
+      if (ct.includes('application/json')) {
+        const j = await r.json()
+        msg = typeof j?.detail === 'string' ? j.detail : JSON.stringify(j)
+      } else {
+        const t = await r.text()
+        if (t) msg = t.length > 500 ? `${t.slice(0, 500)}…` : t
+      }
+    } catch {
+      /* keep msg */
+    }
+    throw new Error(msg)
+  }
+  const blob = await r.blob()
+  const filename =
+    filenameFromContentDisposition(r.headers.get('Content-Disposition')) ||
+    `job_${jobId}_competitor_report.${fmt}`
+  const u = URL.createObjectURL(blob)
+  const a = document.createElement('a')
+  a.href = u
+  a.download = filename
+  a.rel = 'noopener'
+  document.body.appendChild(a)
+  a.click()
+  a.remove()
+  URL.revokeObjectURL(u)
+}
+
 /** 策略稿正文（浏览器 sessionStorage）→ Word/PDF */
 export async function exportStrategyDocument(jobId, markdown, fmt = 'docx') {
   const r = await api(`/api/jobs/${jobId}/export-document/`, {
     method: 'POST',
     body: JSON.stringify({ kind: 'strategy', fmt, markdown }),
   })
+  const ct = r.headers.get('Content-Type') || ''
   if (!r.ok) {
-    const t = await r.text()
+    let msg = `HTTP ${r.status}`
-    throw new Error(t || `HTTP ${r.status}`)
+    try {
+      if (ct.includes('application/json')) {
+        const j = await r.json()
+        msg = typeof j?.detail === 'string' ? j.detail : JSON.stringify(j)
+      } else {
+        const t = await r.text()
+        if (t) msg = t.length > 500 ? `${t.slice(0, 500)}…` : t
+      }
+    } catch {
+      /* keep msg */
+    }
+    throw new Error(msg)
   }
   const blob = await r.blob()
-  const dispo = r.headers.get('Content-Disposition') || ''
+  const filename =
-  const m = dispo.match(/filename="([^"]+)"/)
+    filenameFromContentDisposition(r.headers.get('Content-Disposition')) ||
-  const name = m ? m[1] : `job_${jobId}_strategy_draft.${fmt}`
+    `job_${jobId}_strategy_draft.${fmt}`
   const u = URL.createObjectURL(blob)
   const a = document.createElement('a')
   a.href = u
-  a.download = name
+  a.download = filename
   a.rel = 'noopener'
   document.body.appendChild(a)
   a.click()

frontend/src/views/jd/JdAnalysisBuildView.vue

@@ -12,7 +12,7 @@ import { useReportConfigForm } from '../../composables/useReportConfigForm'
 
 const { jobs } = useJobs()
 const selectedId = ref('')
-/** 勾选则本次重新生成不走整篇大模型合并（仍先跑规则引擎落盘） */
+/** 勾选则本次只出规则统计稿（仍先跑规则落盘，不做全文智能润色） */
 const useRulesOnly = ref(false)
 const regenErr = ref('')
 const genInFlight = generationInFlightKey()
@@ -223,8 +223,7 @@ watch(
     <section class="ma-card">
       <h2>分析报告生成</h2>
       <p class="hint-top">
-        选择<strong>已成功</strong>的任务，调整下方统计规则后点「保存以上设置」，再点「重新生成报告」。默认<strong>先规则引擎</strong>写出统计稿，再<strong>合并大模型补充</strong>（需网关与密钥）；不重新爬取。各章评价解读等开关由「填入推荐示例」或「高级 JSON」中的
+        选择<strong>已成功</strong>的任务，调整下方统计规则后点「保存以上设置」，再点「重新生成报告」。默认会<strong>先按系统规则生成统计稿</strong>，再<strong>用全文智能润色与补充</strong>（需本系统已配置可用的智能服务）；不会重新爬取数据。各章是否做评价智能解读等，可用「填入推荐示例」带上，或在下方「高级选项」里微调（多数情况不必动）。
-        <code>llm_*</code> 字段控制。
         阅读与下载请至
         <RouterLink to="/jd/analysis-view">报告查看</RouterLink>。
       </p>
@@ -232,7 +231,7 @@ watch(
       <div class="toolbar">
         <label class="chk-inline chk-rules-only">
           <input v-model="useRulesOnly" type="checkbox" />
-          本次仅用规则引擎（跳过整篇大模型合并，更快、不调 LLM 全文接口）
+          本次只生成规则统计稿（不做全文智能润色，更快、不调用智能服务）
         </label>
       </div>
       <div class="toolbar">
@@ -266,9 +265,7 @@ watch(
         当前没有<strong>已成功</strong>的任务，无法生成报告；请先在任务列表确认流水线成功。
       </p>
       <p v-else-if="regenBusyAny" class="hint-top">
-        按钮因本页记录的「生成中」状态而禁用。若你已重启后端或确定没有在生成，可点「清除误锁（本地）」。
+        按钮因本页记录的「生成中」状态而暂时不可用。若你已重启服务或确定没有在生成，可先点「清除误锁（本地）」再试。
-        （亦可在控制台执行：
-        <code>sessionStorage.removeItem('ma_generation_inflight');sessionStorage.removeItem('ma_generation_inflight_ts');location.reload()</code>）
       </p>
       <p v-if="regenBusyOtherTask" class="ma-warn-banner">
         任务 #{{ regenPendingJobId }} 的报告正在重新生成中，请稍候再切换任务或重复提交。
@@ -312,7 +309,7 @@ watch(
         />
 
         <details class="rc-advanced" @toggle="onAdvancedJsonToggle">
-          <summary>高级：用 JSON 编辑（一般不需要）</summary>
+          <summary>高级选项（编辑底层配置，一般不需要）</summary>
           <p class="rc-help">
             打开时会根据上面表单生成内容；改完后点「写回表单」再保存。可在此加入
             <code>llm_comment_sentiment</code>、<code>llm_matrix_group_summaries</code>
@@ -320,14 +317,14 @@ watch(
             <code>generator:&quot;llm&quot;</code>；若只要规则稿请勾选「本次仅用规则引擎」。
           </p>
           <textarea v-model="advancedJsonText" class="report-config-editor" rows="10" spellcheck="false" />
-          <button type="button" class="ma-btn ma-btn-secondary rc-add" @click="applyAdvancedJsonToForm">将 JSON 写回表单</button>
+          <button type="button" class="ma-btn ma-btn-secondary rc-add" @click="applyAdvancedJsonToForm">将配置写回表单</button>
         </details>
 
         <p v-if="reportConfigErr" class="ma-err">{{ reportConfigErr }}</p>
       </div>
 
       <p v-if="selectedJob?.run_dir" class="run-dir-note ma-muted">
-        本任务输出目录：<span class="run-dir-path">{{ selectedJob.run_dir }}</span>
+        本任务在本机的数据目录（排查问题时可用）：<span class="run-dir-path">{{ selectedJob.run_dir }}</span>
       </p>
 
       <p v-if="regenErr" class="ma-err">{{ regenErr }}</p>

frontend/src/views/jd/JdAnalysisView.vue

@@ -2,6 +2,94 @@
 import { computed, onMounted, ref, watch } from 'vue'
 import { RouterLink } from 'vue-router'
 import MarkdownPreview from '../../components/MarkdownPreview.vue'
+
+/** 将结构化摘要转为非技术用户可读的条目（不出现 cr1 等字段名）。 */
+function pctShare(x) {
+  if (x == null || x === '') return '—'
+  const n = Number(x)
+  if (Number.isNaN(n)) return '—'
+  return `${(n * 100).toFixed(1)}%`
+}
+
+function briefHumanSummary(j) {
+  const rows = []
+  if (!j || typeof j !== 'object') return rows
+  if (j.keyword) rows.push({ label: '搜索关键词', value: String(j.keyword) })
+  if (j.batch_label) rows.push({ label: '批次', value: String(j.batch_label) })
+  const sc = j.scope
+  if (sc && typeof sc === 'object') {
+    if (sc.merged_sku_count != null)
+      rows.push({ label: '深入采集的商品款数（SKU）', value: String(sc.merged_sku_count) })
+    if (sc.comment_flat_rows != null)
+      rows.push({ label: '评价条数', value: String(sc.comment_flat_rows) })
+    if (sc.structure_source_rows != null)
+      rows.push({ label: '列表/结构统计所用行数', value: String(sc.structure_source_rows) })
+    if (sc.uses_pc_search_list_export === true)
+      rows.push({ label: '是否含搜索列表全量', value: '是' })
+  }
+  const conc = j.concentration
+  if (conc && typeof conc === 'object') {
+    const shops = conc.shops_from_list
+    if (shops && typeof shops === 'object') {
+      if (shops.top_label && shops.cr1 != null) {
+        rows.push({
+          label: '第一大店铺（占列表行比例）',
+          value: `${pctShare(shops.cr1)} · ${shops.top_label}`,
+        })
+      }
+      if (shops.cr3 != null) {
+        rows.push({
+          label: '前三大店铺合计（占列表行比例）',
+          value: pctShare(shops.cr3),
+        })
+      }
+    }
+    const lb = conc.list_brand_field
+    if (lb && typeof lb === 'object') {
+      if (lb.top_label && lb.cr1 != null) {
+        rows.push({
+          label: '第一大品牌（列表侧，按行）',
+          value: `${pctShare(lb.cr1)} · ${lb.top_label}`,
+        })
+      }
+      if (lb.cr3 != null) {
+        rows.push({
+          label: '前三大品牌合计（列表侧）',
+          value: pctShare(lb.cr3),
+        })
+      }
+    }
+    const db = conc.detail_brand_among_merged
+    if (db && typeof db === 'object') {
+      if (db.top_label && db.cr1 != null) {
+        rows.push({
+          label: '第一大品牌（深入样本）',
+          value: `${pctShare(db.cr1)} · ${db.top_label}`,
+        })
+      }
+      if (db.cr3 != null) {
+        rows.push({
+          label: '前三大品牌合计（深入样本）',
+          value: pctShare(db.cr3),
+        })
+      }
+    }
+  }
+  const p = j.price_stats
+  if (p && typeof p === 'object' && p.n > 0) {
+    rows.push({ label: '价格统计·样本量', value: String(p.n) })
+    if (p.median != null)
+      rows.push({ label: '价格统计·中位数（元）', value: Number(p.median).toFixed(2) })
+    if (p.mean != null)
+      rows.push({ label: '价格统计·平均（元）', value: Number(p.mean).toFixed(2) })
+  }
+  const src = j.price_stats_source
+  if (src === 'pc_search_export_all_rows')
+    rows.push({ label: '价格统计·数据来源', value: '搜索列表全量' })
+  else if (src === 'keyword_pipeline_merged')
+    rows.push({ label: '价格统计·数据来源', value: '深入采集合并表' })
+  return rows
+}
 import {
   refreshJobs,
   useJobs,
@@ -10,7 +98,7 @@ import {
   previewUrl,
   jobCompetitorBriefUrl,
   downloadCompetitorBriefPack,
-  jobExportReportDocumentUrl,
+  exportReportDocument,
 } from '../../composables/useJobs'
 import {
   generationInFlightKey,
@@ -23,9 +111,27 @@ const reportMd = ref('')
 const err = ref('')
 const viewMode = ref('render')
 const briefJson = ref('')
+const briefData = ref(null)
 const briefErr = ref('')
 const briefCopyOk = ref(false)
 const packErr = ref('')
+const exportDocErr = ref('')
+/** 正在导出的格式：docx | pdf | null */
+const exportDocFmt = ref(null)
+
+async function exportReportFmt(fmt) {
+  const id = selectedId.value
+  if (!id) return
+  exportDocErr.value = ''
+  exportDocFmt.value = fmt
+  try {
+    await exportReportDocument(id, fmt)
+  } catch (e) {
+    exportDocErr.value = String(e?.message || e)
+  } finally {
+    exportDocFmt.value = null
+  }
+}
 
 /** 将 Markdown 中的 report_assets 相对路径转为可访问的 API URL（在线预览插图） */
 function reportMdWithAssetUrls(md, jobId) {
@@ -72,6 +178,8 @@ const selectedJob = computed(() =>
   successJobs.value.find((j) => String(j.id) === selectedId.value),
 )
 
+const briefHumanRows = computed(() => briefHumanSummary(briefData.value))
+
 async function loadList() {
   try {
     await refreshJobs()
@@ -107,6 +215,7 @@ async function loadReport() {
 
 async function loadCompetitorBrief() {
   briefJson.value = ''
+  briefData.value = null
   briefErr.value = ''
   briefCopyOk.value = false
   const id = selectedId.value
@@ -120,11 +229,12 @@ async function loadCompetitorBrief() {
           const j = JSON.parse(text)
           briefErr.value = j.detail || text
         } catch {
-          briefErr.value = text || `HTTP ${r.status}`
+          briefErr.value = text || `请求失败（${r.status}）`
         }
         return
       }
       const j = JSON.parse(text)
+      briefData.value = j
       briefJson.value = JSON.stringify(j, null, 2)
     } catch (e) {
       briefErr.value = String(e)
@@ -176,6 +286,7 @@ onMounted(loadList)
 
 watch(selectedId, async () => {
   briefJson.value = ''
+  briefData.value = null
   briefErr.value = ''
   packErr.value = ''
   const id = selectedId.value
@@ -235,40 +346,36 @@ watch(
         >
           下载报告
         </a>
-        <a
+        <button
-          class="ma-btn ma-btn-secondary dl-link"
+          type="button"
-          :class="{ disabled: !selectedId }"
+          class="ma-btn ma-btn-secondary"
-          :href="selectedId ? jobExportReportDocumentUrl(selectedId, 'docx') : '#'"
+          :disabled="!selectedId || exportDocFmt || loading"
-          target="_blank"
+          @click="exportReportFmt('docx')"
-          rel="noreferrer"
-          @click="(e) => { if (!selectedId) e.preventDefault() }"
         >
-          导出 Word
+          {{ exportDocFmt === 'docx' ? '导出中…' : '导出 Word' }}
-        </a>
+        </button>
-        <a
+        <button
-          class="ma-btn ma-btn-secondary dl-link"
+          type="button"
-          :class="{ disabled: !selectedId }"
+          class="ma-btn ma-btn-secondary"
-          :href="selectedId ? jobExportReportDocumentUrl(selectedId, 'pdf') : '#'"
+          :disabled="!selectedId || exportDocFmt || loading"
-          target="_blank"
+          @click="exportReportFmt('pdf')"
-          rel="noreferrer"
-          @click="(e) => { if (!selectedId) e.preventDefault() }"
         >
-          导出 PDF
+          {{ exportDocFmt === 'pdf' ? '导出中…' : '导出 PDF' }}
-        </a>
+        </button>
         <button
           type="button"
           class="ma-btn ma-btn-secondary"
           :disabled="!selectedId || briefLoading || loading"
-          title="生成与报告相同统计口径的结构化数据"
+          title="加载与报告数字一致的数据摘要（可先读易读版，再展开原始格式）"
           @click="loadCompetitorBrief"
         >
-          {{ briefLoading ? '摘要加载中…' : '加载结构化摘要' }}
+          {{ briefLoading ? '摘要加载中…' : '加载数据摘要' }}
         </button>
         <button
           type="button"
           class="ma-btn ma-btn-primary"
           :disabled="!selectedId || packLoading || loading || briefLoading"
-          title="ZIP：报告稿、结构化数据、要点摘录、说明"
+          title="下载压缩包：报告、配图、数据与说明"
           @click="downloadBriefPack"
         >
           {{ packLoading ? '打包中…' : '一键下载简报包' }}
@@ -279,27 +386,40 @@ watch(
       </p>
 
       <p v-if="selectedJob?.run_dir" class="run-dir-note ma-muted">
-        本任务输出目录（原始表格复核请至「库内数据浏览」）：<span class="run-dir-path">{{ selectedJob.run_dir }}</span>
+        本任务在本机上的结果文件夹（表格明细可在「库内数据浏览」查看）：<span class="run-dir-path">{{ selectedJob.run_dir }}</span>
       </p>
 
       <p v-if="briefErr" class="ma-err">{{ briefErr }}</p>
       <p v-if="packErr" class="ma-err">{{ packErr }}</p>
+      <p v-if="exportDocErr" class="ma-err">{{ exportDocErr }}</p>
       <p v-if="err" class="ma-err">{{ err }}</p>
       <p v-if="!successJobs.length" class="ma-muted">暂无成功任务，请先在「搜索采集」跑通一条流水线。</p>
     </section>
 
-    <section v-if="briefJson" class="ma-card preview-card">
+    <section v-if="briefData" class="ma-card preview-card">
       <div class="preview-head">
         <h2>竞品数据摘要（机器整理）</h2>
         <div class="tabs">
           <button type="button" class="ma-btn ma-btn-secondary brief-tool" @click="copyBriefJson">
-            {{ briefCopyOk ? '已复制' : '复制' }}
+            {{ briefCopyOk ? '已复制' : '复制原始数据' }}
           </button>
-          <button type="button" class="ma-btn ma-btn-secondary brief-tool" @click="downloadBriefJson">下载文件</button>
+          <button type="button" class="ma-btn ma-btn-secondary brief-tool" @click="downloadBriefJson">下载数据文件</button>
         </div>
       </div>
-      <p class="hint-top brief-hint">与上方报告统计口径一致，供复制或存档；一般业务阅读以报告正文与要点摘录为主，本块主要用于存档或交给同事继续分析。</p>
+      <p class="hint-top brief-hint">
-      <pre class="raw-md brief-json">{{ briefJson }}</pre>
+        以下数字与上方报告一致，用日常用语列出；需要交给其它系统或技术人员时，可展开下方「原始数据」或复制/下载。
+      </p>
+      <dl v-if="briefHumanRows.length" class="brief-dl">
+        <template v-for="(row, idx) in briefHumanRows" :key="idx">
+          <dt>{{ row.label }}</dt>
+          <dd>{{ row.value }}</dd>
+        </template>
+      </dl>
+      <p v-else class="ma-muted brief-hint">暂无摘要条目（可能缺少列表或品牌字段）。</p>
+      <details class="brief-raw-wrap">
+        <summary>展开原始数据（机器可读格式）</summary>
+        <pre class="raw-md brief-json">{{ briefJson }}</pre>
+      </details>
     </section>
 
     <section v-if="reportMd" class="ma-card preview-card">
@@ -447,4 +567,38 @@ watch(
 .brief-json {
   max-height: min(50vh, 560px);
 }
+.brief-dl {
+  margin: 0.5rem 0 1rem;
+  display: grid;
+  grid-template-columns: minmax(10rem, 38%) 1fr;
+  gap: 0.35rem 1rem;
+  font-size: 0.9rem;
+  line-height: 1.45;
+}
+.brief-dl dt {
+  margin: 0;
+  font-weight: 600;
+  color: #374151;
+}
+.brief-dl dd {
+  margin: 0;
+  color: #1f2937;
+  word-break: break-word;
+}
+.brief-raw-wrap {
+  margin-top: 0.75rem;
+  border: 1px solid #e5e7eb;
+  border-radius: 8px;
+  padding: 0.5rem 0.75rem;
+  background: #fafafa;
+}
+.brief-raw-wrap summary {
+  cursor: pointer;
+  font-size: 0.88rem;
+  color: #4b5563;
+  user-select: none;
+}
+.brief-raw-wrap .brief-json {
+  margin-top: 0.75rem;
+}
 </style>