diff --git a/server/knowledge_base/kb_service/base.py b/server/knowledge_base/kb_service/base.py
index e221e438..fa079f62 100644
--- a/server/knowledge_base/kb_service/base.py
+++ b/server/knowledge_base/kb_service/base.py
@@ -172,15 +172,15 @@ class KBService(ABC):
         docs = self.do_search(query, top_k, score_threshold)
         return docs
 
-    def get_doc_by_id(self, id: str) -> Optional[Document]:
-        return None
+    def get_doc_by_ids(self, ids: List[str]) -> List[Document]:
+        return []
 
     def list_docs(self, file_name: str = None, metadata: Dict = {}) -> List[Document]:
         '''
         通过file_name或metadata检索Document
         '''
         doc_infos = list_docs_from_db(kb_name=self.kb_name, file_name=file_name, metadata=metadata)
-        docs = [self.get_doc_by_id(x["id"]) for x in doc_infos]
+        docs = self.get_doc_by_ids([x["id"] for x in doc_infos])
         return docs
 
     @abstractmethod
diff --git a/server/knowledge_base/kb_service/faiss_kb_service.py b/server/knowledge_base/kb_service/faiss_kb_service.py
index 07c57e05..a444f038 100644
--- a/server/knowledge_base/kb_service/faiss_kb_service.py
+++ b/server/knowledge_base/kb_service/faiss_kb_service.py
@@ -32,9 +32,9 @@ class FaissKBService(KBService):
     def save_vector_store(self):
         self.load_vector_store().save(self.vs_path)
 
-    def get_doc_by_id(self, id: str) -> Optional[Document]:
+    def get_doc_by_ids(self, ids: List[str]) -> List[Document]:
         with self.load_vector_store().acquire() as vs:
-            return vs.docstore._dict.get(id)
+            return [vs.docstore._dict.get(id) for id in ids]
 
     def do_init(self):
         self.vector_name = self.vector_name or self.embed_model
diff --git a/server/knowledge_base/kb_service/milvus_kb_service.py b/server/knowledge_base/kb_service/milvus_kb_service.py
index 5e270400..97c5913e 100644
--- a/server/knowledge_base/kb_service/milvus_kb_service.py
+++ b/server/knowledge_base/kb_service/milvus_kb_service.py
@@ -22,13 +22,14 @@ class MilvusKBService(KBService):
     #     if self.milvus.col:
     #         self.milvus.col.flush()
 
-    def get_doc_by_id(self, id: str) -> Optional[Document]:
+    def get_doc_by_ids(self, ids: List[str]) -> List[Document]:
+        result = []
         if self.milvus.col:
-            data_list = self.milvus.col.query(expr=f'pk == {id}', output_fields=["*"])
-            if len(data_list) > 0:
-                data = data_list[0]
+            data_list = self.milvus.col.query(expr=f'pk in {ids}', output_fields=["*"])
+            for data in data_list:
                 text = data.pop("text")
-                return Document(page_content=text, metadata=data)
+                result.append(Document(page_content=text, metadata=data))
+        return result
 
     @staticmethod
     def search(milvus_name, content, limit=3):
@@ -99,7 +100,7 @@ if __name__ == '__main__':
     milvusService = MilvusKBService("test")
     # milvusService.add_doc(KnowledgeFile("README.md", "test"))
 
-    print(milvusService.get_doc_by_id("444022434274215486"))
+    print(milvusService.get_doc_by_ids(["444022434274215486"]))
     # milvusService.delete_doc(KnowledgeFile("README.md", "test"))
     # milvusService.do_drop_kb()
     # print(milvusService.search_docs("如何启动api服务"))
diff --git a/server/knowledge_base/kb_service/pg_kb_service.py b/server/knowledge_base/kb_service/pg_kb_service.py
index 3a6bab0b..cf58ce37 100644
--- a/server/knowledge_base/kb_service/pg_kb_service.py
+++ b/server/knowledge_base/kb_service/pg_kb_service.py
@@ -22,13 +22,12 @@ class PGKBService(KBService):
                                   distance_strategy=DistanceStrategy.EUCLIDEAN,
                                   connection_string=kbs_config.get("pg").get("connection_uri"))
 
-    def get_doc_by_id(self, id: str) -> Optional[Document]:
+    def get_doc_by_ids(self, ids: List[str]) -> List[Document]:
         with self.pg_vector.connect() as connect:
-            stmt = text("SELECT document, cmetadata FROM langchain_pg_embedding WHERE collection_id=:id")
+            stmt = text("SELECT document, cmetadata FROM langchain_pg_embedding WHERE collection_id in :ids")
             results = [Document(page_content=row[0], metadata=row[1]) for row in
-                       connect.execute(stmt, parameters={'id': id}).fetchall()]
-            if len(results) > 0:
-                return results[0]
+                       connect.execute(stmt, parameters={'ids': ids}).fetchall()]
+            return results
 
     def do_init(self):
         self._load_pg_vector()
@@ -88,5 +87,5 @@ if __name__ == '__main__':
     # pGKBService.add_doc(KnowledgeFile("README.md", "test"))
     # pGKBService.delete_doc(KnowledgeFile("README.md", "test"))
     # pGKBService.drop_kb()
-    print(pGKBService.get_doc_by_id("f1e51390-3029-4a19-90dc-7118aaa25772"))
+    print(pGKBService.get_doc_by_ids(["f1e51390-3029-4a19-90dc-7118aaa25772"]))
     # print(pGKBService.search_docs("如何启动api服务"))
diff --git a/server/knowledge_base/kb_service/zilliz_kb_service.py b/server/knowledge_base/kb_service/zilliz_kb_service.py
index bd8b3e9f..d82f8734 100644
--- a/server/knowledge_base/kb_service/zilliz_kb_service.py
+++ b/server/knowledge_base/kb_service/zilliz_kb_service.py
@@ -20,13 +20,14 @@ class ZillizKBService(KBService):
     #     if self.zilliz.col:
     #         self.zilliz.col.flush()
 
-    def get_doc_by_id(self, id: str) -> Optional[Document]:
+    def get_doc_by_ids(self, ids: List[str]) -> List[Document]:
+        result = []
         if self.zilliz.col:
-            data_list = self.zilliz.col.query(expr=f'pk == {id}', output_fields=["*"])
-            if len(data_list) > 0:
-                data = data_list[0]
+            data_list = self.zilliz.col.query(expr=f'pk in {ids}', output_fields=["*"])
+            for data in data_list:
                 text = data.pop("text")
-                return Document(page_content=text, metadata=data)
+                result.append(Document(page_content=text, metadata=data))
+        return result
 
     @staticmethod
     def search(zilliz_name, content, limit=3):