feat(search): 智能搜索建议 - 固化候选词表 (search_keywords + search_title_suggestions)

后端:
- alembic 0009: 两张固化表 + GIN prefix_keys 索引 + articles trigger
- /api/v1/search/suggestions: 混合 A(高频词 ts_stat) + B(真实标题) + 冷启动 fallback
- worker 每日 03:00 + 启动时刷新 search_keywords
- 顺便填 commit 11 TODO: articles.title_zh_tsv + GIN 索引(未来 FTS 基础)

前端:
- NInput -> NAutoComplete + debounce 250ms
- 选标题 -> 跳详情;选关键词 -> 填入 + 触发搜索
- AbortController 防 race condition

性能: prefix_keys @> ARRAY[prefix] 走 GIN 亚毫秒,100w 行也稳

backend/app/models/__init__.py

@@ -7,6 +7,8 @@ from app.models.article import Article  # noqa: F401
 from app.models.article_read import ArticleRead  # noqa: F401
 from app.models.bookmark import Bookmark  # noqa: F401
 from app.models.llm_setting import LlmSetting  # noqa: F401
+from app.models.search_keyword import SearchKeyword  # noqa: F401
+from app.models.search_title_suggestion import SearchTitleSuggestion  # noqa: F401
 from app.models.source import Source, SourceKind  # noqa: F401
 from app.models.subscription import Subscription  # noqa: F401
 from app.models.user import User, UserRole  # noqa: F401
@@ -17,6 +19,8 @@ __all__ = [
     "ArticleRead",
     "Bookmark",
     "LlmSetting",
+    "SearchKeyword",
+    "SearchTitleSuggestion",
     "Source",
     "SourceKind",
     "Subscription",

backend/app/models/search_keyword.py

@@ -0,0 +1,45 @@
+"""搜索建议候选词表(固化,worker 每日 ts_stat 刷新)。
+
+- 数据源:articles.title_zh + body_zh_text + commentary + commentary_meituan
+- 用途:/api/v1/search/suggestions 返回"高频词"建议(A 方案)
+- 刷新:每日凌晨 worker 调 refresh_search_keywords() 全量重建
+- 查询:prefix_keys @> ARRAY['美'] 走 GIN 索引(亚毫秒)
+"""
+from __future__ import annotations
+
+from datetime import datetime
+
+from sqlalchemy import BigInteger, DateTime, Integer, String, Text, func
+from sqlalchemy.dialects.postgresql import ARRAY
+from sqlalchemy.orm import Mapped, mapped_column
+
+from app.database import Base
+
+
+class SearchKeyword(Base):
+    __tablename__ = "search_keywords"
+
+    id: Mapped[int] = mapped_column(BigInteger, primary_key=True)
+
+    keyword: Mapped[str] = mapped_column(Text, nullable=False)
+    # ts_stat / title_extract / manual
+    source: Mapped[str] = mapped_column(String(32), nullable=False)
+    # 词频或文章数(权重,排序用)
+    weight: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+    # 预计算前缀数组,['美','美联储','美联储宣'] for '美联储宣布...'
+    prefix_keys: Mapped[list[str]] = mapped_column(ARRAY(Text), nullable=False)
+
+    last_seen_at: Mapped[datetime] = mapped_column(
+        DateTime(timezone=True), server_default=func.now(), nullable=False
+    )
+    created_at: Mapped[datetime] = mapped_column(
+        DateTime(timezone=True), server_default=func.now(), nullable=False
+    )
+
+    __table_args__ = (
+        # db-level unique 留给 alembic 迁移创建(__table_args__ 只是 ORM 侧参考)
+        # 实际 UNIQUE 约束在 0009 迁移里建
+    )
+
+    def __repr__(self) -> str:
+        return f"<SearchKeyword {self.keyword!r} src={self.source} weight={self.weight}>"

backend/app/models/search_title_suggestion.py

@@ -0,0 +1,43 @@
+"""搜索建议 - 真实文章标题片段表(articles 写入 trigger 自动维护)。
+
+- 数据源:articles.title_zh(优先)/ articles.title(短新闻回退)
+- 用途:/api/v1/search/suggestions 返回"真实文章标题"建议(B 方案)
+- 维护:PG trigger(articles INSERT/UPDATE OF title_zh/title/published_at 触发)
+- 查询:prefix_keys @> ARRAY['美'] 走 GIN 索引,按 published_at DESC 排序
+"""
+from __future__ import annotations
+
+from datetime import datetime
+
+from sqlalchemy import BigInteger, DateTime, ForeignKey, String, func
+from sqlalchemy.dialects.postgresql import ARRAY, TEXT
+from sqlalchemy.orm import Mapped, mapped_column
+
+from app.database import Base
+
+
+class SearchTitleSuggestion(Base):
+    __tablename__ = "search_title_suggestions"
+
+    id: Mapped[int] = mapped_column(BigInteger, primary_key=True)
+
+    article_id: Mapped[int] = mapped_column(
+        BigInteger,
+        ForeignKey("articles.id", ondelete="CASCADE"),
+        nullable=False,
+    )
+
+    # 该条用的是哪边的文本:'zh' (title_zh) / 'src' (title 短新闻回退)
+    title_lang: Mapped[str] = mapped_column(String(8), nullable=False, default="zh")
+
+    # 预计算前缀数组(从第 1 字到全词)
+    prefix_keys: Mapped[list[str]] = mapped_column(ARRAY(TEXT), nullable=False)
+
+    published_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
+
+    created_at: Mapped[datetime] = mapped_column(
+        DateTime(timezone=True), server_default=func.now(), nullable=False
+    )
+
+    def __repr__(self) -> str:
+        return f"<SearchTitleSuggestion article_id={self.article_id} lang={self.title_lang}>"