Langchain-Chatchat/init_database.py
liunux4odoo d316efe8d3
release 0.2.6 (#1815)
## 🛠 新增功能

- 支持百川在线模型 (@hzg0601 @liunux4odoo in #1623)
- 支持 Azure OpenAI 与 claude 等 Langchain 自带模型 (@zRzRzRzRzRzRzR in #1808)
- Agent 功能大量更新,支持更多的工具、更换提示词、检索知识库 (@zRzRzRzRzRzRzR in #1626 #1666 #1785)
- 加长 32k 模型的历史记录 (@zRzRzRzRzRzRzR in #1629 #1630)
- *_chat 接口支持 max_tokens 参数 (@liunux4odoo in #1744)
- 实现 API 和 WebUI 的前后端分离 (@liunux4odoo in #1772)
- 支持 zlilliz 向量库 (@zRzRzRzRzRzRzR in #1785)
- 支持 metaphor 搜索引擎 (@liunux4odoo in #1792)
- 支持 p-tuning 模型 (@hzg0601 in #1810)
- 更新完善文档和 Wiki (@imClumsyPanda @zRzRzRzRzRzRzR @glide-the in #1680 #1811)

## 🐞 问题修复

- 修复 bge-* 模型匹配超过 1 的问题 (@zRzRzRzRzRzRzR in #1652)
- 修复系统代理为空的问题 (@glide-the in #1654)
- 修复重建知识库时 `d == self.d assert error` (@liunux4odoo in #1766)
- 修复对话历史消息错误 (@liunux4odoo in #1801)
- 修复 OpenAI 无法调用的 bug (@zRzRzRzRzRzRzR in #1808)
- 修复 windows下 BIND_HOST=0.0.0.0 时对话出错的问题 (@hzg0601 in #1810)
2023-10-20 23:16:06 +08:00

95 lines
3.0 KiB
Python

import sys
sys.path.append(".")
from server.knowledge_base.migrate import create_tables, reset_tables, folder2db, prune_db_docs, prune_folder_files
from configs.model_config import NLTK_DATA_PATH
import nltk
nltk.data.path = [NLTK_DATA_PATH] + nltk.data.path
from datetime import datetime
import sys
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(description="please specify only one operate method once time.")
parser.add_argument(
"-r",
"--recreate-vs",
action="store_true",
help=('''
recreate vector store.
use this option if you have copied document files to the content folder, but vector store has not been populated or DEFAUL_VS_TYPE/EMBEDDING_MODEL changed.
'''
)
)
parser.add_argument(
"-u",
"--update-in-db",
action="store_true",
help=('''
update vector store for files exist in database.
use this option if you want to recreate vectors for files exist in db and skip files exist in local folder only.
'''
)
)
parser.add_argument(
"-i",
"--increament",
action="store_true",
help=('''
update vector store for files exist in local folder and not exist in database.
use this option if you want to create vectors increamentally.
'''
)
)
parser.add_argument(
"--prune-db",
action="store_true",
help=('''
delete docs in database that not existed in local folder.
it is used to delete database docs after user deleted some doc files in file browser
'''
)
)
parser.add_argument(
"--prune-folder",
action="store_true",
help=('''
delete doc files in local folder that not existed in database.
is is used to free local disk space by delete unused doc files.
'''
)
)
parser.add_argument(
"--kb-name",
type=str,
nargs="+",
default=[],
help=("specify knowledge base names to operate on. default is all folders exist in KB_ROOT_PATH.")
)
if len(sys.argv) <= 1:
parser.print_help()
else:
args = parser.parse_args()
start_time = datetime.now()
create_tables() # confirm tables exist
if args.recreate_vs:
reset_tables()
print("database talbes reseted")
print("recreating all vector stores")
folder2db(kb_names=args.kb_name, mode="recreate_vs")
elif args.update_in_db:
folder2db(kb_names=args.kb_name, mode="update_in_db")
elif args.increament:
folder2db(kb_names=args.kb_name, mode="increament")
elif args.prune_db:
prune_db_docs(args.kb_name)
elif args.prune_folder:
prune_folder_files(args.kb_name)
end_time = datetime.now()
print(f"总计用时: {end_time-start_time}")