feat: add governed public knowledge retrieval

app/service/knowledge_authority.py

@@ -0,0 +1,100 @@
+import json
+from datetime import UTC, datetime
+
+from sqlalchemy import select
+from sqlalchemy.ext.asyncio import AsyncSession
+from sqlalchemy.sql.elements import ColumnElement
+
+from app.core.knowledge_contracts import KnowledgeHit, KnowledgeQuery
+from app.model.knowledge import FinKnowledgeMeta
+
+
+class KnowledgeMysqlAuthority:
+    def __init__(self, session: AsyncSession) -> None:
+        self._session = session
+
+    async def filter_published(self, hits: tuple[KnowledgeHit, ...]) -> list[KnowledgeHit]:
+        ids = tuple(int(hit.knowledge_id) for hit in hits if hit.knowledge_id.isdecimal())
+        if not ids:
+            return []
+        rows = await self._session.scalars(
+            select(FinKnowledgeMeta).where(
+                FinKnowledgeMeta.id.in_(ids), *self._published_filters()
+            )
+        )
+        approved = {str(row.id): row for row in rows}
+        result: list[KnowledgeHit] = []
+        for hit in hits:
+            row = approved.get(hit.knowledge_id)
+            if row is None:
+                continue
+            answer = self.extract_answer(row.content_text).strip()
+            if answer:
+                result.append(hit.model_copy(update={
+                    "answer": answer, "version": row.version, "title": row.title,
+                }))
+        return result
+
+    async def search_keyword(
+        self, query: KnowledgeQuery, collections: tuple[str, ...], top_k: int
+    ) -> list[KnowledgeHit]:
+        """向量服务不可用时，在原授权集合内执行受限的只读关键词检索。"""
+        keyword = self._keyword(query.query)
+        if not collections or not keyword:
+            return []
+        # 显式转义 LIKE 通配符，避免用户输入扩大关键词降级的匹配范围。
+        escaped_keyword = keyword.replace("\\", "\\\\").replace("%", "\\%").replace("_", "\\_")
+        rows = await self._session.scalars(
+            select(FinKnowledgeMeta)
+            .where(
+                FinKnowledgeMeta.milvus_collection.in_(collections),
+                *self._published_filters(),
+                FinKnowledgeMeta.content_text.like(f"%{escaped_keyword}%", escape="\\"),
+            )
+            .order_by(FinKnowledgeMeta.id.desc())
+            .limit(top_k)
+        )
+        result: list[KnowledgeHit] = []
+        for row in rows:
+            answer = self.extract_answer(row.content_text).strip()
+            if not answer:
+                continue
+            result.append(
+                KnowledgeHit(
+                    knowledge_id=str(row.id),
+                    collection=row.milvus_collection,
+                    title=row.title,
+                    snippet=answer[:300],
+                    answer=answer,
+                    version=row.version,
+                )
+            )
+        return result
+
+    @staticmethod
+    def _keyword(query: str) -> str:
+        """压缩空白并限制关键词长度，避免降级查询承载无界输入。"""
+        return "".join(query.split())[:64]
+
+    @staticmethod
+    def _published_filters() -> tuple[ColumnElement[bool], ...]:
+        today = datetime.now(UTC).date()
+        return (
+            FinKnowledgeMeta.review_status == "published",
+            FinKnowledgeMeta.status == "active",
+            (FinKnowledgeMeta.effective_date.is_(None))
+            | (FinKnowledgeMeta.effective_date <= today),
+            (FinKnowledgeMeta.expire_date.is_(None))
+            | (FinKnowledgeMeta.expire_date > today),
+        )
+
+    @staticmethod
+    def extract_answer(content_text: str) -> str:
+        try:
+            payload = json.loads(content_text)
+        except json.JSONDecodeError:
+            return content_text
+        answer = payload.get("answer") if isinstance(payload, dict) else None
+        if isinstance(answer, str):
+            return answer
+        return content_text