feat: support volc fangzhou
This commit is contained in:
liunux4odoo
liunux4odoo
parent
3dde02be28
commit
745a105bae
|
|
@ -115,6 +115,14 @@ ONLINE_LLM_MODEL = {
|
|||
"secret_key": "",
|
||||
"provider": "QianFanWorker",
|
||||
},
|
||||
# 火山方舟 API
|
||||
"fangzhou-api": {
|
||||
"version": "chatglm-6b-model", # 当前支持 "chatglm-6b-model"， 更多的见文档模型支持列表中方舟部分。
|
||||
"version_url": "", # 可以不填写version，直接填写在方舟申请模型发布的API地址
|
||||
"api_key": "",
|
||||
"secret_key": "",
|
||||
"provider": "FangZhouWorker",
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -1,44 +1,92 @@
|
|||
from server.knowledge_base.migrate import create_tables, reset_tables, folder2db, recreate_all_vs, list_kbs_from_folder
|
||||
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 startup import dump_server_info
|
||||
from datetime import datetime
|
||||
import sys
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import argparse
|
||||
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.formatter_class = argparse.RawTextHelpFormatter
|
||||
parser = argparse.ArgumentParser(description="please specify only one operate method once time.")
|
||||
|
||||
parser.add_argument(
|
||||
"-r",
|
||||
"--recreate-vs",
|
||||
action="store_true",
|
||||
help=('''
|
||||
recreate all vector store.
|
||||
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.
|
||||
if your vector store is ready with the configs, just skip this option to fill info to database only.
|
||||
'''
|
||||
)
|
||||
)
|
||||
args = parser.parse_args()
|
||||
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.")
|
||||
)
|
||||
|
||||
dump_server_info()
|
||||
|
||||
start_time = datetime.now()
|
||||
|
||||
if args.recreate_vs:
|
||||
reset_tables()
|
||||
print("database talbes reseted")
|
||||
print("recreating all vector stores")
|
||||
recreate_all_vs()
|
||||
if len(sys.argv) <= 1:
|
||||
parser.print_help()
|
||||
else:
|
||||
create_tables()
|
||||
print("database talbes created")
|
||||
print("filling kb infos to database")
|
||||
for kb in list_kbs_from_folder():
|
||||
folder2db(kb, "fill_info_only")
|
||||
args = parser.parse_args()
|
||||
start_time = datetime.now()
|
||||
|
||||
end_time = datetime.now()
|
||||
print(f"总计用时： {end_time-start_time}")
|
||||
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}")
|
||||
|
|
|
|||
|
|
@ -22,9 +22,9 @@ class MilvusKBService(KBService):
|
|||
from pymilvus import Collection
|
||||
return Collection(milvus_name)
|
||||
|
||||
def save_vector_store(self):
|
||||
if self.milvus.col:
|
||||
self.milvus.col.flush()
|
||||
# def save_vector_store(self):
|
||||
# if self.milvus.col:
|
||||
# self.milvus.col.flush()
|
||||
|
||||
def get_doc_by_id(self, id: str) -> Optional[Document]:
|
||||
if self.milvus.col:
|
||||
|
|
|
|||
|
|
@ -3,7 +3,7 @@ from configs import (EMBEDDING_MODEL, DEFAULT_VS_TYPE, ZH_TITLE_ENHANCE,
|
|||
from server.knowledge_base.utils import (get_file_path, list_kbs_from_folder,
|
||||
list_files_from_folder,files2docs_in_thread,
|
||||
KnowledgeFile,)
|
||||
from server.knowledge_base.kb_service.base import KBServiceFactory, SupportedVSType
|
||||
from server.knowledge_base.kb_service.base import KBServiceFactory
|
||||
from server.db.repository.knowledge_file_repository import add_file_to_db
|
||||
from server.db.base import Base, engine
|
||||
import os
|
||||
|
|
@ -33,8 +33,8 @@ def file_to_kbfile(kb_name: str, files: List[str]) -> List[KnowledgeFile]:
|
|||
|
||||
|
||||
def folder2db(
|
||||
kb_name: str,
|
||||
mode: Literal["recreate_vs", "fill_info_only", "update_in_db", "increament"],
|
||||
kb_names: List[str],
|
||||
mode: Literal["recreate_vs", "update_in_db", "increament"],
|
||||
vs_type: Literal["faiss", "milvus", "pg", "chromadb"] = DEFAULT_VS_TYPE,
|
||||
embed_model: str = EMBEDDING_MODEL,
|
||||
chunk_size: int = -1,
|
||||
|
|
@ -45,21 +45,11 @@ def folder2db(
|
|||
use existed files in local folder to populate database and/or vector store.
|
||||
set parameter `mode` to:
|
||||
recreate_vs: recreate all vector store and fill info to database using existed files in local folder
|
||||
fill_info_only: do not create vector store, fill info to db using existed files only
|
||||
fill_info_only(disabled): do not create vector store, fill info to db using existed files only
|
||||
update_in_db: update vector store and database info using local files that existed in database only
|
||||
increament: create vector store and database info for local files that not existed in database only
|
||||
'''
|
||||
kb = KBServiceFactory.get_service(kb_name, vs_type, embed_model)
|
||||
kb.create_kb()
|
||||
|
||||
if mode == "recreate_vs":
|
||||
files_count = kb.count_files()
|
||||
print(f"知识库 {kb_name} 中共有 {files_count} 个文档。\n即将清除向量库。")
|
||||
kb.clear_vs()
|
||||
files_count = kb.count_files()
|
||||
print(f"清理后，知识库 {kb_name} 中共有 {files_count} 个文档。")
|
||||
|
||||
kb_files = file_to_kbfile(kb_name, list_files_from_folder(kb_name))
|
||||
def files2vs(kb_name: str, kb_files: List[KnowledgeFile]):
|
||||
for success, result in files2docs_in_thread(kb_files,
|
||||
chunk_size=chunk_size,
|
||||
chunk_overlap=chunk_overlap,
|
||||
|
|
@ -68,84 +58,77 @@ def folder2db(
|
|||
_, filename, docs = result
|
||||
print(f"正在将 {kb_name}/{filename} 添加到向量库，共包含{len(docs)}条文档")
|
||||
kb_file = KnowledgeFile(filename=filename, knowledge_base_name=kb_name)
|
||||
kb.add_doc(kb_file=kb_file, docs=docs, not_refresh_vs_cache=True)
|
||||
kb_file.splited_docs = docs
|
||||
kb.add_doc(kb_file=kb_file, not_refresh_vs_cache=True)
|
||||
else:
|
||||
print(result)
|
||||
kb.save_vector_store()
|
||||
elif mode == "fill_info_only":
|
||||
files = list_files_from_folder(kb_name)
|
||||
kb_files = file_to_kbfile(kb_name, files)
|
||||
|
||||
for kb_file in kb_files:
|
||||
add_file_to_db(kb_file)
|
||||
print(f"已将 {kb_name}/{kb_file.filename} 添加到数据库")
|
||||
elif mode == "update_in_db":
|
||||
files = kb.list_files()
|
||||
kb_files = file_to_kbfile(kb_name, files)
|
||||
kb_names = kb_names or list_kbs_from_folder()
|
||||
for kb_name in kb_names:
|
||||
kb = KBServiceFactory.get_service(kb_name, vs_type, embed_model)
|
||||
kb.create_kb()
|
||||
|
||||
for kb_file in kb_files:
|
||||
kb.update_doc(kb_file, not_refresh_vs_cache=True)
|
||||
kb.save_vector_store()
|
||||
elif mode == "increament":
|
||||
db_files = kb.list_files()
|
||||
folder_files = list_files_from_folder(kb_name)
|
||||
files = list(set(folder_files) - set(db_files))
|
||||
kb_files = file_to_kbfile(kb_name, files)
|
||||
|
||||
for success, result in files2docs_in_thread(kb_files,
|
||||
chunk_size=chunk_size,
|
||||
chunk_overlap=chunk_overlap,
|
||||
zh_title_enhance=zh_title_enhance):
|
||||
if success:
|
||||
_, filename, docs = result
|
||||
print(f"正在将 {kb_name}/{filename} 添加到向量库")
|
||||
kb_file = KnowledgeFile(filename=filename, knowledge_base_name=kb_name)
|
||||
kb.add_doc(kb_file=kb_file, docs=docs, not_refresh_vs_cache=True)
|
||||
else:
|
||||
print(result)
|
||||
kb.save_vector_store()
|
||||
else:
|
||||
print(f"unspported migrate mode: {mode}")
|
||||
# 清除向量库，从本地文件重建
|
||||
if mode == "recreate_vs":
|
||||
kb.clear_vs()
|
||||
kb_files = file_to_kbfile(kb_name, list_files_from_folder(kb_name))
|
||||
files2vs(kb_name, kb_files)
|
||||
kb.save_vector_store()
|
||||
# # 不做文件内容的向量化，仅将文件元信息存到数据库
|
||||
# # 由于现在数据库存了很多与文本切分相关的信息，单纯存储文件信息意义不大，该功能取消。
|
||||
# elif mode == "fill_info_only":
|
||||
# files = list_files_from_folder(kb_name)
|
||||
# kb_files = file_to_kbfile(kb_name, files)
|
||||
# for kb_file in kb_files:
|
||||
# add_file_to_db(kb_file)
|
||||
# print(f"已将 {kb_name}/{kb_file.filename} 添加到数据库")
|
||||
# 以数据库中文件列表为基准，利用本地文件更新向量库
|
||||
elif mode == "update_in_db":
|
||||
files = kb.list_files()
|
||||
kb_files = file_to_kbfile(kb_name, files)
|
||||
files2vs(kb_name, kb_files)
|
||||
kb.save_vector_store()
|
||||
# 对比本地目录与数据库中的文件列表，进行增量向量化
|
||||
elif mode == "increament":
|
||||
db_files = kb.list_files()
|
||||
folder_files = list_files_from_folder(kb_name)
|
||||
files = list(set(folder_files) - set(db_files))
|
||||
kb_files = file_to_kbfile(kb_name, files)
|
||||
files2vs(kb_name, kb_files)
|
||||
kb.save_vector_store()
|
||||
else:
|
||||
print(f"unspported migrate mode: {mode}")
|
||||
|
||||
|
||||
def recreate_all_vs(
|
||||
vs_type: Literal["faiss", "milvus", "pg", "chromadb"] = DEFAULT_VS_TYPE,
|
||||
embed_mode: str = EMBEDDING_MODEL,
|
||||
**kwargs: Any,
|
||||
):
|
||||
def prune_db_docs(kb_names: List[str]):
|
||||
'''
|
||||
used to recreate a vector store or change current vector store to another type or embed_model
|
||||
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
|
||||
'''
|
||||
for kb_name in list_kbs_from_folder():
|
||||
folder2db(kb_name, "recreate_vs", vs_type, embed_mode, **kwargs)
|
||||
for kb_name in kb_names:
|
||||
kb = KBServiceFactory.get_service_by_name(kb_name)
|
||||
if kb and kb.exists():
|
||||
files_in_db = kb.list_files()
|
||||
files_in_folder = list_files_from_folder(kb_name)
|
||||
files = list(set(files_in_db) - set(files_in_folder))
|
||||
kb_files = file_to_kbfile(kb_name, files)
|
||||
for kb_file in kb_files:
|
||||
kb.delete_doc(kb_file, not_refresh_vs_cache=True)
|
||||
print(f"success to delete docs for file: {kb_name}/{kb_file.filename}")
|
||||
kb.save_vector_store()
|
||||
|
||||
|
||||
def prune_db_files(kb_name: str):
|
||||
'''
|
||||
delete files in database that not existed in local folder.
|
||||
it is used to delete database files after user deleted some doc files in file browser
|
||||
'''
|
||||
kb = KBServiceFactory.get_service_by_name(kb_name)
|
||||
if kb.exists():
|
||||
files_in_db = kb.list_files()
|
||||
files_in_folder = list_files_from_folder(kb_name)
|
||||
files = list(set(files_in_db) - set(files_in_folder))
|
||||
kb_files = file_to_kbfile(kb_name, files)
|
||||
for kb_file in kb_files:
|
||||
kb.delete_doc(kb_file, not_refresh_vs_cache=True)
|
||||
kb.save_vector_store()
|
||||
return kb_files
|
||||
|
||||
def prune_folder_files(kb_name: str):
|
||||
def prune_folder_files(kb_names: List[str]):
|
||||
'''
|
||||
delete doc files in local folder that not existed in database.
|
||||
is is used to free local disk space by delete unused doc files.
|
||||
'''
|
||||
kb = KBServiceFactory.get_service_by_name(kb_name)
|
||||
if kb.exists():
|
||||
files_in_db = kb.list_files()
|
||||
files_in_folder = list_files_from_folder(kb_name)
|
||||
files = list(set(files_in_folder) - set(files_in_db))
|
||||
for file in files:
|
||||
os.remove(get_file_path(kb_name, file))
|
||||
return files
|
||||
for kb_name in kb_names:
|
||||
kb = KBServiceFactory.get_service_by_name(kb_name)
|
||||
if kb and kb.exists():
|
||||
files_in_db = kb.list_files()
|
||||
files_in_folder = list_files_from_folder(kb_name)
|
||||
files = list(set(files_in_folder) - set(files_in_db))
|
||||
for file in files:
|
||||
os.remove(get_file_path(kb_name, file))
|
||||
print(f"success to delete file: {kb_name}/{file}")
|
||||
|
|
|
|||
|
|
@ -0,0 +1,91 @@
|
|||
from server.model_workers.base import ApiModelWorker
|
||||
from configs.model_config import TEMPERATURE
|
||||
from fastchat import conversation as conv
|
||||
import sys
|
||||
import json
|
||||
from typing import List, Literal, Dict
|
||||
|
||||
|
||||
class FangZhouWorker(ApiModelWorker):
|
||||
"""
|
||||
火山方舟
|
||||
"""
|
||||
SUPPORT_MODELS = ["chatglm-6b-model"]
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
version: Literal["chatglm-6b-model"] = "chatglm-6b-model",
|
||||
model_names: List[str] = ["fangzhou-api"],
|
||||
controller_addr: str,
|
||||
worker_addr: str,
|
||||
**kwargs,
|
||||
):
|
||||
kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr)
|
||||
kwargs.setdefault("context_len", 16384)
|
||||
super().__init__(**kwargs)
|
||||
|
||||
config = self.get_config()
|
||||
self.version = version
|
||||
self.api_key = config.get("api_key")
|
||||
self.secret_key = config.get("secret_key")
|
||||
|
||||
from volcengine.maas import ChatRole
|
||||
self.conv = conv.Conversation(
|
||||
name=self.model_names[0],
|
||||
system_message="你是一个聪明、对人类有帮助的人工智能，你可以对人类提出的问题给出有用、详细、礼貌的回答。",
|
||||
messages=[],
|
||||
roles=[ChatRole.USER, ChatRole.ASSISTANT, ChatRole.SYSTEM],
|
||||
sep="\n### ",
|
||||
stop_str="###",
|
||||
)
|
||||
|
||||
def generate_stream_gate(self, params):
|
||||
super().generate_stream_gate(params)
|
||||
from volcengine.maas import MaasService, MaasException, ChatRole
|
||||
maas = MaasService('maas-api.ml-platform-cn-beijing.volces.com', 'cn-beijing')
|
||||
|
||||
maas.set_ak(self.api_key)
|
||||
maas.set_sk(self.secret_key)
|
||||
|
||||
# document: "https://www.volcengine.com/docs/82379/1099475"
|
||||
req = {
|
||||
"model": {
|
||||
"name": self.version,
|
||||
},
|
||||
"parameters": {
|
||||
# 这里的参数仅为示例，具体可用的参数请参考具体模型的 API 说明
|
||||
# "max_new_tokens": 1000,
|
||||
"temperature": params.get("temperature", TEMPERATURE),
|
||||
},
|
||||
"messages": [{"role": ChatRole.USER, "content": params["prompt"]}]
|
||||
}
|
||||
text = ""
|
||||
try:
|
||||
|
||||
resps = maas.stream_chat(req)
|
||||
for resp in resps:
|
||||
text += resp.choice.message.content
|
||||
yield json.dumps({"error_code": 0, "text": text},
|
||||
ensure_ascii=False).encode() + b"\0"
|
||||
except MaasException as e:
|
||||
print(e)
|
||||
|
||||
|
||||
def get_embeddings(self, params):
|
||||
# TODO: 支持embeddings
|
||||
print("embedding")
|
||||
print(params)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import uvicorn
|
||||
from server.utils import MakeFastAPIOffline
|
||||
from fastchat.serve.model_worker import app
|
||||
|
||||
worker = FangZhouWorker(
|
||||
controller_addr="http://127.0.0.1:20001",
|
||||
worker_addr="http://127.0.0.1:20006",
|
||||
)
|
||||
sys.modules["fastchat.serve.model_worker"].worker = worker
|
||||
MakeFastAPIOffline(app)
|
||||
uvicorn.run(app, port=20006)
|
||||
|
|
@ -0,0 +1,139 @@
|
|||
from pathlib import Path
|
||||
from pprint import pprint
|
||||
import os
|
||||
import shutil
|
||||
import sys
|
||||
root_path = Path(__file__).parent.parent
|
||||
sys.path.append(str(root_path))
|
||||
|
||||
from server.knowledge_base.kb_service.base import KBServiceFactory
|
||||
from server.knowledge_base.utils import get_kb_path, get_doc_path, KnowledgeFile
|
||||
from server.knowledge_base.migrate import folder2db, prune_db_docs, prune_folder_files
|
||||
|
||||
|
||||
# setup test knowledge base
|
||||
kb_name = "test_kb_for_migrate"
|
||||
test_files = {
|
||||
"faq.md": str(root_path / "docs" / "faq.md"),
|
||||
"install.md": str(root_path / "docs" / "install.md"),
|
||||
}
|
||||
|
||||
|
||||
kb_path = get_kb_path(kb_name)
|
||||
doc_path = get_doc_path(kb_name)
|
||||
|
||||
if not os.path.isdir(doc_path):
|
||||
os.makedirs(doc_path)
|
||||
|
||||
for k, v in test_files.items():
|
||||
shutil.copy(v, os.path.join(doc_path, k))
|
||||
|
||||
|
||||
def test_recreate_vs():
|
||||
folder2db([kb_name], "recreate_vs")
|
||||
|
||||
kb = KBServiceFactory.get_service_by_name(kb_name)
|
||||
assert kb.exists()
|
||||
|
||||
files = kb.list_files()
|
||||
print(files)
|
||||
for name in test_files:
|
||||
assert name in files
|
||||
path = os.path.join(doc_path, name)
|
||||
|
||||
# list docs based on file name
|
||||
docs = kb.list_docs(file_name=name)
|
||||
assert len(docs) > 0
|
||||
pprint(docs[0])
|
||||
for doc in docs:
|
||||
assert doc.metadata["source"] == path
|
||||
|
||||
# list docs base on metadata
|
||||
docs = kb.list_docs(metadata={"source": path})
|
||||
assert len(docs) > 0
|
||||
|
||||
for doc in docs:
|
||||
assert doc.metadata["source"] == path
|
||||
|
||||
|
||||
def test_increament():
|
||||
kb = KBServiceFactory.get_service_by_name(kb_name)
|
||||
kb.clear_vs()
|
||||
assert kb.list_files() == []
|
||||
assert kb.list_docs() == []
|
||||
|
||||
folder2db([kb_name], "increament")
|
||||
|
||||
files = kb.list_files()
|
||||
print(files)
|
||||
for f in test_files:
|
||||
assert f in files
|
||||
|
||||
docs = kb.list_docs(file_name=f)
|
||||
assert len(docs) > 0
|
||||
pprint(docs[0])
|
||||
|
||||
for doc in docs:
|
||||
assert doc.metadata["source"] == os.path.join(doc_path, f)
|
||||
|
||||
|
||||
def test_prune_db():
|
||||
del_file, keep_file = list(test_files)[:2]
|
||||
os.remove(os.path.join(doc_path, del_file))
|
||||
|
||||
prune_db_docs([kb_name])
|
||||
|
||||
kb = KBServiceFactory.get_service_by_name(kb_name)
|
||||
files = kb.list_files()
|
||||
print(files)
|
||||
assert del_file not in files
|
||||
assert keep_file in files
|
||||
|
||||
docs = kb.list_docs(file_name=del_file)
|
||||
assert len(docs) == 0
|
||||
|
||||
docs = kb.list_docs(file_name=keep_file)
|
||||
assert len(docs) > 0
|
||||
pprint(docs[0])
|
||||
|
||||
shutil.copy(test_files[del_file], os.path.join(doc_path, del_file))
|
||||
|
||||
|
||||
def test_prune_folder():
|
||||
del_file, keep_file = list(test_files)[:2]
|
||||
kb = KBServiceFactory.get_service_by_name(kb_name)
|
||||
|
||||
# delete docs for file
|
||||
kb.delete_doc(KnowledgeFile(del_file, kb_name))
|
||||
files = kb.list_files()
|
||||
print(files)
|
||||
assert del_file not in files
|
||||
assert keep_file in files
|
||||
|
||||
docs = kb.list_docs(file_name=del_file)
|
||||
assert len(docs) == 0
|
||||
|
||||
docs = kb.list_docs(file_name=keep_file)
|
||||
assert len(docs) > 0
|
||||
|
||||
docs = kb.list_docs(file_name=del_file)
|
||||
assert len(docs) == 0
|
||||
|
||||
assert os.path.isfile(os.path.join(doc_path, del_file))
|
||||
|
||||
# prune folder
|
||||
prune_folder_files([kb_name])
|
||||
|
||||
# check result
|
||||
assert not os.path.isfile(os.path.join(doc_path, del_file))
|
||||
assert os.path.isfile(os.path.join(doc_path, keep_file))
|
||||
|
||||
|
||||
def test_drop_kb():
|
||||
kb = KBServiceFactory.get_service_by_name(kb_name)
|
||||
kb.drop_kb()
|
||||
assert not kb.exists()
|
||||
assert not os.path.isdir(kb_path)
|
||||
|
||||
kb = KBServiceFactory.get_service_by_name(kb_name)
|
||||
assert kb is None
|
||||
Loading…
Reference in New Issue