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#
# Copyright 2024 The InfiniFlow 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 api.db import LLMType, UserTenantRole
from api.db.db_models import init_database_tables as init_web_db
from api.db.services import UserService
from api.db.services.llm_service import LLMFactoriesService, LLMService, TenantLLMService, LLMBundle
from api.db.services.user_service import TenantService, UserTenantService
from api.settings import CHAT_MDL, EMBEDDING_MDL, ASR_MDL, IMAGE2TEXT_MDL, PARSERS, LLM_FACTORY, API_KEY
def init_superuser():
user_info = {
"id": uuid.uuid1().hex,
"password": "admin",
"nickname": "admin",
"is_superuser": True,
"email": "[email protected]",
"creator": "system",
"status": "1",
}
tenant = {
"id": user_info["id"],
"name": user_info["nickname"] + "‘s Kingdom",
"llm_id": CHAT_MDL,
"embd_id": EMBEDDING_MDL,
"asr_id": ASR_MDL,
"parser_ids": PARSERS,
"img2txt_id": IMAGE2TEXT_MDL
}
usr_tenant = {
"tenant_id": user_info["id"],
"user_id": user_info["id"],
"invited_by": user_info["id"],
"role": UserTenantRole.OWNER
}
tenant_llm = []
for llm in LLMService.query(fid=LLM_FACTORY):
tenant_llm.append(
{"tenant_id": user_info["id"], "llm_factory": LLM_FACTORY, "llm_name": llm.llm_name, "model_type": llm.model_type,
"api_key": API_KEY})
if not UserService.save(**user_info):
print("\033[93m【ERROR】\033[0mcan't init admin.")
return
TenantService.insert(**tenant)
UserTenantService.insert(**usr_tenant)
TenantLLMService.insert_many(tenant_llm)
print("【INFO】Super user initialized. \033[93memail: [email protected], password: admin\033[0m. Changing the password after logining is strongly recomanded.")
chat_mdl = LLMBundle(tenant["id"], LLMType.CHAT, tenant["llm_id"])
msg = chat_mdl.chat(system="", history=[{"role": "user", "content": "Hello!"}], gen_conf={})
if msg.find("ERROR: ") == 0:
print("\33[91m【ERROR】\33[0m: ", "'{}' dosen't work. {}".format(tenant["llm_id"], msg))
embd_mdl = LLMBundle(tenant["id"], LLMType.EMBEDDING, tenant["embd_id"])
v, c = embd_mdl.encode(["Hello!"])
if c == 0:
print("\33[91m【ERROR】\33[0m:", " '{}' dosen't work!".format(tenant["embd_id"]))
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 = [
# ---------------------- OpenAI ------------------------
{
"fid": factory_infos[0]["name"],
"llm_name": "gpt-3.5-turbo",
"tags": "LLM,CHAT,4K",
"max_tokens": 4096,
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "gpt-3.5-turbo-16k-0613",
"tags": "LLM,CHAT,16k",
"max_tokens": 16385,
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "text-embedding-ada-002",
"tags": "TEXT EMBEDDING,8K",
"max_tokens": 8191,
"model_type": LLMType.EMBEDDING.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "whisper-1",
"tags": "SPEECH2TEXT",
"max_tokens": 25*1024*1024,
"model_type": LLMType.SPEECH2TEXT.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "gpt-4",
"tags": "LLM,CHAT,8K",
"max_tokens": 8191,
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "gpt-4-32k",
"tags": "LLM,CHAT,32K",
"max_tokens": 32768,
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[0]["name"],
"llm_name": "gpt-4-vision-preview",
"tags": "LLM,CHAT,IMAGE2TEXT",
"max_tokens": 765,
"model_type": LLMType.IMAGE2TEXT.value
},
# ----------------------- Qwen -----------------------
{
"fid": factory_infos[1]["name"],
"llm_name": "qwen-turbo",
"tags": "LLM,CHAT,8K",
"max_tokens": 8191,
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[1]["name"],
"llm_name": "qwen-plus",
"tags": "LLM,CHAT,32K",
"max_tokens": 32768,
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[1]["name"],
"llm_name": "text-embedding-v2",
"tags": "TEXT EMBEDDING,2K",
"max_tokens": 2048,
"model_type": LLMType.EMBEDDING.value
},{
"fid": factory_infos[1]["name"],
"llm_name": "paraformer-realtime-8k-v1",
"tags": "SPEECH2TEXT",
"max_tokens": 25*1024*1024,
"model_type": LLMType.SPEECH2TEXT.value
},{
"fid": factory_infos[1]["name"],
"llm_name": "qwen-vl-max",
"tags": "LLM,CHAT,IMAGE2TEXT",
"max_tokens": 765,
"model_type": LLMType.IMAGE2TEXT.value
},
# ---------------------- ZhipuAI ----------------------
{
"fid": factory_infos[2]["name"],
"llm_name": "glm-3-turbo",
"tags": "LLM,CHAT,",
"max_tokens": 128 * 1000,
"model_type": LLMType.CHAT.value
}, {
"fid": factory_infos[2]["name"],
"llm_name": "glm-4",
"tags": "LLM,CHAT,",
"max_tokens": 128 * 1000,
"model_type": LLMType.CHAT.value
}, {
"fid": factory_infos[2]["name"],
"llm_name": "glm-4v",
"tags": "LLM,CHAT,IMAGE2TEXT",
"max_tokens": 2000,
"model_type": LLMType.IMAGE2TEXT.value
},
{
"fid": factory_infos[2]["name"],
"llm_name": "embedding-2",
"tags": "TEXT EMBEDDING",
"max_tokens": 512,
"model_type": LLMType.EMBEDDING.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 LLMService.get_all().count():init_llm_factory()
if not UserService.get_all().count():
init_superuser()
print("init web data success:{}".format(time.time() - start_time))
if __name__ == '__main__':
init_web_db()
init_web_data() |