diff --git a/app/models/base.py b/app/models/base.py
index 2d4c256..1c08a58 100644
--- a/app/models/base.py
+++ b/app/models/base.py
@@ -37,20 +37,24 @@ class KnowledgePage(Base, TimestampMixin):
     id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
     title: Mapped[str] = mapped_column(String(500), nullable=False, comment="页面标题")
     content: Mapped[str] = mapped_column(Text, nullable=False, comment="页面内容")
-    source: Mapped[str | None] = mapped_column(String(200), nullable=True, comment="来源文件名")
+    source_file: Mapped[str | None] = mapped_column(String(500), nullable=True, comment="来源文件路径")
     page_number: Mapped[int | None] = mapped_column(Integer, nullable=True, comment="原文件页码")
-    # 向量嵌入（JSON 格式存储）
+    course_name: Mapped[str | None] = mapped_column(String(200), nullable=True, comment="课程名称")
+    teacher_name: Mapped[str | None] = mapped_column(String(100), nullable=True, comment="讲师名称")
+    live_date: Mapped[str | None] = mapped_column(String(20), nullable=True, comment="直播日期")
+    metadata_json: Mapped[str | None] = mapped_column(Text, nullable=True, comment="额外元数据（JSON）")
     embedding: Mapped[str | None] = mapped_column(Text, nullable=True, comment="向量嵌入（JSON）")
 
-    @property
-    def embedding_vector(self) -> list[float] | None:
-        if self.embedding is None:
-            return None
-        return json.loads(self.embedding)
 
-    @embedding_vector.setter
-    def embedding_vector(self, value: list[float] | None):
-        self.embedding = json.dumps(value) if value else None
+class KnowledgeChunk(Base, TimestampMixin):
+    """知识页面分块"""
+    __tablename__ = "knowledge_chunks"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    page_id: Mapped[int] = mapped_column(Integer, nullable=False, comment="关联页面 ID")
+    chunk_index: Mapped[int] = mapped_column(Integer, nullable=False, comment="分块索引")
+    content: Mapped[str] = mapped_column(Text, nullable=False, comment="分块内容")
+    embedding: Mapped[str | None] = mapped_column(Text, nullable=True, comment="向量嵌入（JSON）")
 
 
 class OCRImage(Base, TimestampMixin):
diff --git a/app/services/page_service.py b/app/services/page_service.py
index 5ebd795..c484272 100644
--- a/app/services/page_service.py
+++ b/app/services/page_service.py
@@ -181,22 +181,15 @@ class PageService:
             if embedding:
                 embedding_str = "[" + ",".join(str(x) for x in embedding) + "]"
 
-            await self.db.execute(text("""
-                INSERT INTO knowledge_chunks (page_id, chunk_index, content, embedding)
-                VALUES (:page_id, :chunk_index, :content, :embedding::vector)
-            """), {
+            await self.db.execute(text(
+                "INSERT INTO knowledge_chunks (page_id, chunk_index, content, embedding) "
+                "VALUES (:page_id, :chunk_index, :content, :embedding)"
+            ), {
                 "page_id": page_id,
                 "chunk_index": idx,
                 "content": chunk_text,
                 "embedding": embedding_str,
             })
 
-        # 更新全文搜索向量
-        await self.db.execute(text("""
-            UPDATE knowledge_chunks
-            SET search_vector = to_tsvector('chinese_zh', content)
-            WHERE page_id = :page_id
-        """), {"page_id": page_id})
-
         await self.db.flush()
         return {"page_id": page_id, "chunks": len(chunks)}