ragflow / api /settings.py
Starowo's picture
Upload 1411 files
b9fe2b4 verified
#
# 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 os
from datetime import date
from enum import IntEnum, Enum
import rag.utils.es_conn
import rag.utils.infinity_conn
import rag.utils
from rag.nlp import search
from graphrag import search as kg_search
from api.utils import get_base_config, decrypt_database_config
from api.constants import RAG_FLOW_SERVICE_NAME
LIGHTEN = int(os.environ.get('LIGHTEN', "0"))
LLM = None
LLM_FACTORY = None
LLM_BASE_URL = None
CHAT_MDL = ""
EMBEDDING_MDL = ""
RERANK_MDL = ""
ASR_MDL = ""
IMAGE2TEXT_MDL = ""
API_KEY = None
PARSERS = None
HOST_IP = None
HOST_PORT = None
SECRET_KEY = None
DATABASE_TYPE = os.getenv("DB_TYPE", 'mysql')
DATABASE = decrypt_database_config(name=DATABASE_TYPE)
# authentication
AUTHENTICATION_CONF = None
# client
CLIENT_AUTHENTICATION = None
HTTP_APP_KEY = None
GITHUB_OAUTH = None
FEISHU_OAUTH = None
DOC_ENGINE = None
docStoreConn = None
retrievaler = None
kg_retrievaler = None
def init_settings():
global LLM, LLM_FACTORY, LLM_BASE_URL, LIGHTEN, DATABASE_TYPE, DATABASE
LIGHTEN = int(os.environ.get('LIGHTEN', "0"))
DATABASE_TYPE = os.getenv("DB_TYPE", 'mysql')
DATABASE = decrypt_database_config(name=DATABASE_TYPE)
LLM = get_base_config("user_default_llm", {})
LLM_DEFAULT_MODELS = LLM.get("default_models", {})
LLM_FACTORY = LLM.get("factory", "Tongyi-Qianwen")
LLM_BASE_URL = LLM.get("base_url")
global CHAT_MDL, EMBEDDING_MDL, RERANK_MDL, ASR_MDL, IMAGE2TEXT_MDL
if not LIGHTEN:
EMBEDDING_MDL = "BAAI/bge-large-zh-v1.5@BAAI"
if LLM_DEFAULT_MODELS:
CHAT_MDL = LLM_DEFAULT_MODELS.get("chat_model", CHAT_MDL)
EMBEDDING_MDL = LLM_DEFAULT_MODELS.get("embedding_model", EMBEDDING_MDL)
RERANK_MDL = LLM_DEFAULT_MODELS.get("rerank_model", RERANK_MDL)
ASR_MDL = LLM_DEFAULT_MODELS.get("asr_model", ASR_MDL)
IMAGE2TEXT_MDL = LLM_DEFAULT_MODELS.get("image2text_model", IMAGE2TEXT_MDL)
# factory can be specified in the config name with "@". LLM_FACTORY will be used if not specified
CHAT_MDL = CHAT_MDL + (f"@{LLM_FACTORY}" if "@" not in CHAT_MDL and CHAT_MDL != "" else "")
EMBEDDING_MDL = EMBEDDING_MDL + (f"@{LLM_FACTORY}" if "@" not in EMBEDDING_MDL and EMBEDDING_MDL != "" else "")
RERANK_MDL = RERANK_MDL + (f"@{LLM_FACTORY}" if "@" not in RERANK_MDL and RERANK_MDL != "" else "")
ASR_MDL = ASR_MDL + (f"@{LLM_FACTORY}" if "@" not in ASR_MDL and ASR_MDL != "" else "")
IMAGE2TEXT_MDL = IMAGE2TEXT_MDL + (
f"@{LLM_FACTORY}" if "@" not in IMAGE2TEXT_MDL and IMAGE2TEXT_MDL != "" else "")
global API_KEY, PARSERS, HOST_IP, HOST_PORT, SECRET_KEY
API_KEY = LLM.get("api_key", "")
PARSERS = LLM.get(
"parsers",
"naive:General,qa:Q&A,resume:Resume,manual:Manual,table:Table,paper:Paper,book:Book,laws:Laws,presentation:Presentation,picture:Picture,one:One,audio:Audio,knowledge_graph:Knowledge Graph,email:Email,tag:Tag")
HOST_IP = get_base_config(RAG_FLOW_SERVICE_NAME, {}).get("host", "127.0.0.1")
HOST_PORT = get_base_config(RAG_FLOW_SERVICE_NAME, {}).get("http_port")
SECRET_KEY = get_base_config(
RAG_FLOW_SERVICE_NAME,
{}).get("secret_key", str(date.today()))
global AUTHENTICATION_CONF, CLIENT_AUTHENTICATION, HTTP_APP_KEY, GITHUB_OAUTH, FEISHU_OAUTH
# authentication
AUTHENTICATION_CONF = get_base_config("authentication", {})
# client
CLIENT_AUTHENTICATION = AUTHENTICATION_CONF.get(
"client", {}).get(
"switch", False)
HTTP_APP_KEY = AUTHENTICATION_CONF.get("client", {}).get("http_app_key")
GITHUB_OAUTH = get_base_config("oauth", {}).get("github")
FEISHU_OAUTH = get_base_config("oauth", {}).get("feishu")
global DOC_ENGINE, docStoreConn, retrievaler, kg_retrievaler
DOC_ENGINE = os.environ.get('DOC_ENGINE', "elasticsearch")
lower_case_doc_engine = DOC_ENGINE.lower()
if lower_case_doc_engine == "elasticsearch":
docStoreConn = rag.utils.es_conn.ESConnection()
elif lower_case_doc_engine == "infinity":
docStoreConn = rag.utils.infinity_conn.InfinityConnection()
else:
raise Exception(f"Not supported doc engine: {DOC_ENGINE}")
retrievaler = search.Dealer(docStoreConn)
kg_retrievaler = kg_search.KGSearch(docStoreConn)
class CustomEnum(Enum):
@classmethod
def valid(cls, value):
try:
cls(value)
return True
except BaseException:
return False
@classmethod
def values(cls):
return [member.value for member in cls.__members__.values()]
@classmethod
def names(cls):
return [member.name for member in cls.__members__.values()]
class RetCode(IntEnum, CustomEnum):
SUCCESS = 0
NOT_EFFECTIVE = 10
EXCEPTION_ERROR = 100
ARGUMENT_ERROR = 101
DATA_ERROR = 102
OPERATING_ERROR = 103
CONNECTION_ERROR = 105
RUNNING = 106
PERMISSION_ERROR = 108
AUTHENTICATION_ERROR = 109
UNAUTHORIZED = 401
SERVER_ERROR = 500
FORBIDDEN = 403
NOT_FOUND = 404