# # 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 json 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 from api.utils.file_utils import get_project_base_directory 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 FACTORY_LLM_INFOS = 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 # user registration switch REGISTER_ENABLED = 1 def init_settings(): global LLM, LLM_FACTORY, LLM_BASE_URL, LIGHTEN, DATABASE_TYPE, DATABASE, FACTORY_LLM_INFOS, REGISTER_ENABLED 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") try: REGISTER_ENABLED = int(os.environ.get("REGISTER_ENABLED", "1")) except Exception: pass try: with open(os.path.join(get_project_base_directory(), "conf", "llm_factories.json"), "r") as f: FACTORY_LLM_INFOS = json.load(f)["factory_llm_infos"] except Exception: FACTORY_LLM_INFOS = [] 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