diff --git a/configs/kb_config.py.exmaple b/configs/kb_config.py.exmaple
index 7df3f38..1c2deb9 100644
--- a/configs/kb_config.py.exmaple
+++ b/configs/kb_config.py.exmaple
@@ -8,7 +8,7 @@ DEFAULT_VS_TYPE = "faiss"
 CACHED_VS_NUM = 1
 
 # 知识库中单段文本长度(不适用MarkdownHeaderTextSplitter)
-CHUNK_SIZE = 500
+CHUNK_SIZE = 250
 
 # 知识库中相邻文本重合长度(不适用MarkdownHeaderTextSplitter)
 OVERLAP_SIZE = 50
@@ -104,4 +104,4 @@ text_splitter_dict = {
 }
 
 # TEXT_SPLITTER 名称
-TEXT_SPLITTER_NAME = "SpacyTextSplitter"
+TEXT_SPLITTER_NAME = "ChineseRecursiveTextSplitter"
diff --git a/server/knowledge_base/utils.py b/server/knowledge_base/utils.py
index c804a6a..033b48d 100644
--- a/server/knowledge_base/utils.py
+++ b/server/knowledge_base/utils.py
@@ -10,10 +10,9 @@ from configs import (
     ZH_TITLE_ENHANCE,
     logger, 
     log_verbose, 
-    text_splitter_dict, 
-    llm_model_dict, 
-    LLM_MODEL, 
-    TEXT_SPLITTER
+    text_splitter_dict,
+    LLM_MODEL,
+    TEXT_SPLITTER_NAME,
 )
 import importlib
 from text_splitter import zh_title_enhance
@@ -182,7 +181,7 @@ def get_loader(loader_name: str, file_path_or_content: Union[str, bytes, io.Stri
 
 
 def make_text_splitter(
-    splitter_name: str = TEXT_SPLITTER,
+    splitter_name: str = TEXT_SPLITTER_NAME,
     chunk_size: int = CHUNK_SIZE,
     chunk_overlap: int = OVERLAP_SIZE,
     llm_model: str = LLM_MODEL,
@@ -275,7 +274,7 @@ class KnowledgeFile:
         self.docs = None
         self.splited_docs = None
         self.document_loader_name = get_LoaderClass(self.ext)
-        self.text_splitter_name = TEXT_SPLITTER
+        self.text_splitter_name = TEXT_SPLITTER_NAME
 
     def file2docs(self, refresh: bool=False):
         if self.docs is None or refresh:
diff --git a/startup.py b/startup.py
index d5be6e5..838e588 100644
--- a/startup.py
+++ b/startup.py
@@ -479,7 +479,7 @@ def dump_server_info(after_start=False, args=None):
     if args and args.model_name:
         models = args.model_name
 
-    print(f"当前使用的分词器：{TEXT_SPLITTER}")
+    print(f"当前使用的分词器：{TEXT_SPLITTER_NAME}")
     print(f"当前启动的LLM模型：{models} @ {llm_device()}")
 
     for model in models: