fix knowledge base management:

1. docs in database were note deleted when clear vector store
2. diable buttons when local doc file not exist.
This commit is contained in:
liunux4odoo 2023-08-14 19:09:02 +08:00
parent bb8331384f
commit ec984205ae
4 changed files with 49 additions and 16 deletions

View File

@ -49,6 +49,18 @@ def delete_file_from_db(session, kb_file: KnowledgeFile):
return True
@with_session
def delete_files_from_db(session, knowledge_base_name: str):
session.query(KnowledgeFileModel).filter_by(kb_name=knowledge_base_name).delete()
kb = session.query(KnowledgeBaseModel).filter_by(kb_name=knowledge_base_name).first()
if kb:
kb.file_count = 0
session.commit()
return True
@with_session
def doc_exists(session, kb_file: KnowledgeFile):
existing_file = session.query(KnowledgeFileModel).filter_by(file_name=kb_file.filename,

View File

@ -44,8 +44,12 @@ async def delete_kb(
if kb is None:
return BaseResponse(code=404, msg=f"未找到知识库 {knowledge_base_name}")
status = kb.drop_kb()
if status:
return BaseResponse(code=200, msg=f"成功删除知识库 {knowledge_base_name}")
else:
return BaseResponse(code=500, msg=f"删除知识库失败 {knowledge_base_name}")
try:
status = kb.clear_vs()
status = kb.drop_kb()
if status:
return BaseResponse(code=200, msg=f"成功删除知识库 {knowledge_base_name}")
except Exception as e:
print(e)
return BaseResponse(code=500, msg=f"删除知识库失败 {knowledge_base_name}")

View File

@ -9,8 +9,8 @@ from server.db.repository.knowledge_base_repository import (
load_kb_from_db, get_kb_detail,
)
from server.db.repository.knowledge_file_repository import (
add_doc_to_db, delete_file_from_db, doc_exists,
list_docs_from_db, get_file_detail
add_doc_to_db, delete_file_from_db, delete_files_from_db, doc_exists,
list_docs_from_db, get_file_detail, delete_file_from_db
)
from configs.model_config import (kbs_config, VECTOR_SEARCH_TOP_K,
@ -56,9 +56,12 @@ class KBService(ABC):
def clear_vs(self):
"""
用知识库中已上传文件重建向量库
删除向量库中所有内容
"""
self.do_clear_vs()
status = delete_files_from_db(self.kb_name)
return status
def drop_kb(self):
"""

View File

@ -1,5 +1,3 @@
import sqlite3
import streamlit as st
from webui_pages.utils import *
from st_aggrid import AgGrid, JsCode
@ -9,6 +7,9 @@ from server.knowledge_base.utils import get_file_path, LOADER_DICT
from server.knowledge_base.kb_service.base import get_kb_details, get_kb_doc_details
from typing import Literal, Dict, Tuple
from configs.model_config import embedding_model_dict, kbs_config, EMBEDDING_MODEL, DEFAULT_VS_TYPE
import os
import time
# SENTENCE_SIZE = 100
@ -33,6 +34,19 @@ def config_aggrid(
return gb
def file_exists(kb: str, selected_rows: List) -> Tuple[str, str]:
'''
check whether a doc file exists in local knowledge base folder.
return the file's name and path if it exists.
'''
if selected_rows:
file_name = selected_rows[0]["file_name"]
file_path = get_file_path(kb, file_name)
if os.path.isfile(file_path):
return file_name, file_path
return "", ""
def knowledge_base_page(api: ApiRequest):
try:
kb_list = get_kb_details()
@ -174,9 +188,8 @@ def knowledge_base_page(api: ApiRequest):
selected_rows = doc_grid.get("selected_rows", [])
cols = st.columns(4)
if selected_rows:
file_name = selected_rows[0]["file_name"]
file_path = get_file_path(kb, file_name)
file_name, file_path = file_exists(kb, selected_rows)
if file_path:
with open(file_path, "rb") as fp:
cols[0].download_button(
"下载选中文档",
@ -194,7 +207,7 @@ def knowledge_base_page(api: ApiRequest):
# 将文件分词并加载到向量库中
if cols[1].button(
"重新添加至向量库" if selected_rows and (pd.DataFrame(selected_rows)["in_db"]).any() else "添加至向量库",
disabled=len(selected_rows) == 0,
disabled=not file_exists(kb, selected_rows)[0],
use_container_width=True,
):
for row in selected_rows:
@ -204,7 +217,7 @@ def knowledge_base_page(api: ApiRequest):
# 将文件从向量库中删除,但不删除文件本身。
if cols[2].button(
"从向量库删除",
disabled=len(selected_rows) == 0,
disabled=not (selected_rows and selected_rows[0]["in_db"]),
use_container_width=True,
):
for row in selected_rows:
@ -245,5 +258,6 @@ def knowledge_base_page(api: ApiRequest):
use_container_width=True,
):
ret = api.delete_knowledge_base(kb)
st.experimental_rerun()
st.toast(ret["msg"])
time.sleep(1)
st.experimental_rerun()