fix: increase batch delete size and optimize document loading with async (#440)

Author: Dallas98

runtime/datamate-python/app/module/rag/infra/vectorstore/store.py

@@ -26,7 +26,7 @@
 
 logger = logging.getLogger(__name__)
 
-BATCH_DELETE_SIZE = 100
+BATCH_DELETE_SIZE = 500
 
 
 def _delete_chunks_by_rag_file_id_batched(client, collection_name: str, rag_file_id: str) -> int:

runtime/datamate-python/app/module/rag/service/common/batch_processor.py

@@ -80,7 +80,8 @@ async def _store_single_batch(
         documents, doc_ids = chunks_to_documents(batch_chunks, ids=ids)
 
         try:
-            vectorstore.add_documents(documents=documents, ids=doc_ids)
+            # 使用异步方法避免阻塞事件循环
+            await vectorstore.aadd_documents(documents=documents, ids=doc_ids)
             logger.info("批次 %d-%d 存储成功", batch_start + 1, batch_end)
         except Exception as e:
             logger.error(

runtime/datamate-python/app/module/rag/service/file_processor.py

@@ -153,7 +153,7 @@ async def _process_single_graph_file(
                 await self._mark_failed(db, file_repo, str(rag_file.id), "文件不存在")
                 return
 
-            documents = load_documents(file_path)
+            documents = await asyncio.to_thread(load_documents, file_path)
             if not documents:
                 await self._mark_failed(db, file_repo, str(rag_file.id), "文件解析失败，未生成文档")
                 return