File size: 6,177 Bytes
3079197 484e5ab 3079197 9bf75d4 3079197 484e5ab 3079197 4a858d3 3079197 4a858d3 3079197 4a858d3 3079197 4a858d3 3079197 4a858d3 3079197 4a858d3 3079197 4a858d3 3079197 4a858d3 3079197 4a858d3 3079197 4a858d3 3079197 4a858d3 3079197 4a858d3 3079197 484e5ab 3079197 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 |
#
# 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
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
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": "Infiniflow",
"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",
"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
},{
"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_chat_v1",
"tags": "LLM,CHAT,IMAGE2TEXT",
"max_tokens": 765,
"model_type": LLMType.IMAGE2TEXT.value
},{
"fid": factory_infos[2]["name"],
"llm_name": "gpt-3.5-turbo",
"tags": "LLM,CHAT,4K",
"max_tokens": 4096,
"model_type": LLMType.CHAT.value
},{
"fid": factory_infos[2]["name"],
"llm_name": "text-embedding-ada-002",
"tags": "TEXT EMBEDDING,8K",
"max_tokens": 8191,
"model_type": LLMType.EMBEDDING.value
},{
"fid": factory_infos[2]["name"],
"llm_name": "whisper-1",
"tags": "SPEECH2TEXT",
"max_tokens": 25*1024*1024,
"model_type": LLMType.SPEECH2TEXT.value
},{
"fid": factory_infos[2]["name"],
"llm_name": "gpt-4-vision-preview",
"tags": "LLM,CHAT,IMAGE2TEXT",
"max_tokens": 765,
"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() |