ragflow / web_server /db /init_data.py
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#
# Copyright 2019 The FATE Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import time
import uuid
from web_server.db import LLMType
from web_server.db.db_models import init_database_tables as init_web_db
from web_server.db.services import UserService
from web_server.db.services.llm_service import LLMFactoriesService, LLMService
def init_superuser():
user_info = {
"id": uuid.uuid1().hex,
"password": "admin",
"nickname": "admin",
"is_superuser": True,
"email": "[email protected]",
"creator": "system",
"status": "1",
}
UserService.save(**user_info)
def init_llm_factory():
factory_infos = [{
"name": "OpenAI",
"logo": "",
"tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
"status": "1",
},{
"name": "通义千问",
"logo": "",
"tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
"status": "1",
},{
"name": "智普AI",
"logo": "",
"tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
"status": "1",
},{
"name": "文心一言",
"logo": "",
"tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
"status": "1",
},
]
llm_infos = [{
"fid": factory_infos[0]["name"],
"llm_name": "gpt-3.5-turbo",
"tags": "LLM,CHAT,4K",
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "gpt-3.5-turbo-16k-0613",
"tags": "LLM,CHAT,16k",
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "text-embedding-ada-002",
"tags": "TEXT EMBEDDING,8K",
"model_type": LLMType.EMBEDDING.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "whisper-1",
"tags": "SPEECH2TEXT",
"model_type": LLMType.SPEECH2TEXT.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "gpt-4",
"tags": "LLM,CHAT,8K",
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "gpt-4-32k",
"tags": "LLM,CHAT,32K",
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "gpt-4-vision-preview",
"tags": "LLM,CHAT,IMAGE2TEXT",
"model_type": LLMType.IMAGE2TEXT.value
},{
"fid": factory_infos[1]["name"],
"llm_name": "qwen-turbo",
"tags": "LLM,CHAT,8K",
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[1]["name"],
"llm_name": "qwen-plus",
"tags": "LLM,CHAT,32K",
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[1]["name"],
"llm_name": "text-embedding-v2",
"tags": "TEXT EMBEDDING,2K",
"model_type": LLMType.EMBEDDING.value
},{
"fid": factory_infos[1]["name"],
"llm_name": "paraformer-realtime-8k-v1",
"tags": "SPEECH2TEXT",
"model_type": LLMType.SPEECH2TEXT.value
},{
"fid": factory_infos[1]["name"],
"llm_name": "qwen_vl_chat_v1",
"tags": "LLM,CHAT,IMAGE2TEXT",
"model_type": LLMType.IMAGE2TEXT.value
},
]
for info in factory_infos:
LLMFactoriesService.save(**info)
for info in llm_infos:
LLMService.save(**info)
def init_web_data():
start_time = time.time()
if not UserService.get_all().count():
init_superuser()
if not LLMService.get_all().count():init_llm_factory()
print("init web data success:{}".format(time.time() - start_time))
if __name__ == '__main__':
init_web_db()
init_web_data()