diff --git a/webui_st.py b/webui_st.py
index 1584a55..8309210 100644
--- a/webui_st.py
+++ b/webui_st.py
@@ -1,6 +1,8 @@
 import streamlit as st
 from streamlit_chatbox import st_chatbox
 import tempfile
+from pathlib import Path
+
 ###### 从webui借用的代码 #####
 ######   做了少量修改    #####
 import os
@@ -101,23 +103,23 @@ def get_answer(query, vs_path, history, mode, score_threshold=VECTOR_SEARCH_SCOR
 
 
 def get_vector_store(vs_id, files, sentence_size, history, one_conent, one_content_segmentation):
-    vs_path = os.path.join(KB_ROOT_PATH, vs_id, "vector_store")
-    filelist = []
-    if not os.path.exists(os.path.join(KB_ROOT_PATH, vs_id, "content")):
-        os.makedirs(os.path.join(KB_ROOT_PATH, vs_id, "content"))
+    vs_path = Path(KB_ROOT_PATH) / vs_id / "vector_store"
+    con_path = Path(KB_ROOT_PATH) / vs_id / "content"
+    con_path.mkdir(parents=True, exist_ok=True)
+
     qa = st.session_state.local_doc_qa
     if qa.llm_model_chain and qa.embeddings:
+        filelist = []
         if isinstance(files, list):
             for file in files:
                 filename = os.path.split(file.name)[-1]
-                shutil.move(file.name, os.path.join(
-                    KB_ROOT_PATH, vs_id, "content", filename))
-                filelist.append(os.path.join(
-                    KB_ROOT_PATH, vs_id, "content", filename))
+                target = con_path / filename
+                shutil.move(file.name, target)
+                filelist.append(str(target))
             vs_path, loaded_files = qa.init_knowledge_vector_store(
-                filelist, vs_path, sentence_size)
+                filelist, str(vs_path), sentence_size)
         else:
-            vs_path, loaded_files = qa.one_knowledge_add(vs_path, files, one_conent, one_content_segmentation,
+            vs_path, loaded_files = qa.one_knowledge_add(str(vs_path), files, one_conent, one_content_segmentation,
                                                                    sentence_size)
         if len(loaded_files):
             file_status = f"已添加 {'、'.join([os.path.split(i)[-1] for i in loaded_files if i])} 内容至知识库，并已加载知识库，请开始提问"
@@ -322,7 +324,8 @@ with st.sidebar:
             sentence_size = st.slider('文本入库分句长度限制', 1, 1000, SENTENCE_SIZE)
             files = st.file_uploader('上传知识文件',
                                      ['docx', 'txt', 'md', 'csv', 'xlsx', 'pdf'],
-                                     accept_multiple_files=True)
+                                     accept_multiple_files=True,
+                                     )
             if st.button('添加文件到知识库'):
                 temp_dir = tempfile.mkdtemp()
                 file_list = []
@@ -331,8 +334,8 @@ with st.sidebar:
                     with open(file, 'wb') as fp:
                         fp.write(f.getvalue())
                     file_list.append(TempFile(file))
-                    _, _, history = get_vector_store(
-                    vs_path, file_list, sentence_size, [], None, None)
+                _, _, history = get_vector_store(
+                vs_path, file_list, sentence_size, [], None, None)
                 st.session_state.files = []