deepdata: core product code (backend, frontend, runtime, deepflow module)

runtime/deepdata-python/app/module/rag/service/common/metadata_builder.py

@@ -0,0 +1,42 @@
+"""
+元数据构建工具
+
+提供构建和管理分块元数据的工具方法。
+"""
+from typing import Dict, Any
+from app.db.models.knowledge_gen import KnowledgeBase, RagFile
+
+
+class MetadataBuilder:
+    """元数据构建工具类"""
+    
+    @staticmethod
+    def build_chunk_metadata(rag_file: RagFile, knowledge_base: KnowledgeBase) -> Dict[str, Any]:
+        """构建分块基础元数据
+        
+        Args:
+            rag_file: RAG 文件实体
+            knowledge_base: 知识库实体
+            
+        Returns:
+            元数据字典
+        """
+        return {
+            "rag_file_id": str(rag_file.id),
+            "original_file_id": str(rag_file.file_id),
+            "knowledge_base_id": str(knowledge_base.id),
+            "file_name": rag_file.file_name,
+            "knowledge_base_name": knowledge_base.name,
+        }
+    
+    @staticmethod
+    def add_to_chunks(chunks: list, base_metadata: Dict[str, Any]) -> None:
+        """为基础元数据添加到分块列表
+        
+        Args:
+            chunks: 分块列表
+            base_metadata: 基础元数据
+        """
+        for chunk in chunks:
+            if hasattr(chunk, 'metadata') and isinstance(chunk.metadata, dict):
+                chunk.metadata.update(base_metadata)