diff --git a/data_chain/apps/service/chunk_service.py b/data_chain/apps/service/chunk_service.py
index a1c352de77b4287724c7a14b224edcceb29623f5..3e2896f278bba0e185184d98ae8663a24bb323fb 100644
--- a/data_chain/apps/service/chunk_service.py
+++ b/data_chain/apps/service/chunk_service.py
@@ -4,6 +4,7 @@ import random
 import time
 import jieba
 import traceback
+import asyncio
 from data_chain.logger.logger import logger as logging
 from data_chain.apps.service.llm_service import get_question_chunk_relation
 from data_chain.models.constant import ChunkRelevance
@@ -155,14 +156,24 @@ async def get_similar_chunks(content, kb_id=None, temporary_document_ids=None, m
         st = time.time()
         target_vector = await Vectorize.vectorize_embedding(content)
         logging.info(f"向量化耗时: {time.time()-st}")
+        retry_times = 3
         if target_vector is not None:
             st = time.time()
             if temporary_document_ids:
-                chunk_id_list = await TemporaryVectorItemsManager.find_top_k_similar_temporary_vectors(
-                    target_vector,
-                    temporary_document_ids,
-                    topk-len(chunk_tuple_list)
-                    )
+                chunk_id_list=[]
+                for i in range(retry_times):
+                    try:
+                        chunk_id_list = await asyncio.wait_for(TemporaryVectorItemsManager.find_top_k_similar_temporary_vectors(
+                            target_vector,
+                            temporary_document_ids,
+                            topk-len(chunk_tuple_list)
+                            ),
+                            timeout=1
+                            )
+                        break
+                    except Exception as e:
+                        logging.error(f"检索临时向量时出错: {e}")
+                        continue
                 chunk_entity_list = await TemporaryChunkManager.select_by_temporary_chunk_ids(chunk_id_list)
             elif kb_id:
                 kb_entity = await KnowledgeBaseManager.select_by_id(kb_id)
@@ -172,7 +183,14 @@ async def get_similar_chunks(content, kb_id=None, temporary_document_ids=None, m
                 vector_items_id = kb_entity.vector_items_id
                 dim = embedding_model_out_dimensions[embedding_model]
                 vector_items_table = await PostgresDB.get_dynamic_vector_items_table(vector_items_id, dim)
-                chunk_id_list = await VectorItemsManager.find_top_k_similar_vectors(vector_items_table, target_vector, kb_id, topk-len(chunk_tuple_list))
+                chunk_id_list=[]
+                for i in range(retry_times):
+                    try:
+                        chunk_id_list = await asyncio.wait_for(VectorItemsManager.find_top_k_similar_vectors(vector_items_table, target_vector, kb_id, topk-len(chunk_tuple_list)),timeout=1)
+                        break
+                    except Exception as e:
+                        logging.error(f"检索向量时出错: {e}")
+                        continue
                 chunk_entity_list = await ChunkManager.select_by_chunk_ids(chunk_id_list)
             logging.info(f"向量化检索耗时: {time.time()-st}")
             st = time.time()
diff --git a/data_chain/manager/vector_items_manager.py b/data_chain/manager/vector_items_manager.py
index 22f4a4c61b40bde15a26f446a1760ef27045f45e..a602501ece69e95bde9b7110eb9b6688cd67d793 100644
--- a/data_chain/manager/vector_items_manager.py
+++ b/data_chain/manager/vector_items_manager.py
@@ -125,7 +125,6 @@ class VectorItemsManager:
                     f"WHERE v.kb_id = :kb_id AND v.enabled = true AND document.enabled = true "
                     f"ORDER BY v.vector <=> :target_vector "
                     f"LIMIT :topk")
-            # 获取会话并执行查询
             async with await PostgresDB.get_session() as session:
                 # 使用execute执行原始SQL语句，并传递参数
                 result = await session.execute(