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Feat: allows setting multiple types of default models in service config (#9404)

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### What problem does this PR solve?

Allows set multiple types of default models in service config.

### Type of change

- [x] New Feature (non-breaking change which adds functionality)
This commit is contained in:
Yongteng Lei
2025-08-13 09:46:05 +08:00
committed by GitHub
parent 7ee5e0d152
commit 421657f64b
4 changed files with 154 additions and 45 deletions
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48
api/apps/user_app.py
View File

@ -620,18 +620,35 @@ def user_register(user_id, user):
"location": "",
}
tenant_llm = []
for llm in LLMService.query(fid=settings.LLM_FACTORY):
tenant_llm.append(
{
"tenant_id": user_id,
"llm_factory": settings.LLM_FACTORY,
"llm_name": llm.llm_name,
"model_type": llm.model_type,
"api_key": settings.API_KEY,
"api_base": settings.LLM_BASE_URL,
"max_tokens": llm.max_tokens if llm.max_tokens else 8192,
}
)
seen = set()
factory_configs = []
for factory_config in [
settings.CHAT_CFG,
settings.EMBEDDING_CFG,
settings.ASR_CFG,
settings.IMAGE2TEXT_CFG,
settings.RERANK_CFG,
]:
factory_name = factory_config["factory"]
if factory_name not in seen:
seen.add(factory_name)
factory_configs.append(factory_config)
for factory_config in factory_configs:
for llm in LLMService.query(fid=factory_config["factory"]):
tenant_llm.append(
{
"tenant_id": user_id,
"llm_factory": factory_config["factory"],
"llm_name": llm.llm_name,
"model_type": llm.model_type,
"api_key": factory_config["api_key"],
"api_base": factory_config["base_url"],
"max_tokens": llm.max_tokens if llm.max_tokens else 8192,
}
)
if settings.LIGHTEN != 1:
for buildin_embedding_model in settings.BUILTIN_EMBEDDING_MODELS:
mdlnm, fid = TenantLLMService.split_model_name_and_factory(buildin_embedding_model)
@ -647,6 +664,13 @@ def user_register(user_id, user):
}
)
unique = {}
for item in tenant_llm:
key = (item["tenant_id"], item["llm_factory"], item["llm_name"])
if key not in unique:
unique[key] = item
tenant_llm = list(unique.values())
if not UserService.save(**user):
return
TenantService.insert(**tenant)

44
api/db/init_data.py
View File

@ -63,12 +63,44 @@ def init_superuser():
"invited_by": user_info["id"],
"role": UserTenantRole.OWNER
}
user_id = user_info
tenant_llm = []
for llm in LLMService.query(fid=settings.LLM_FACTORY):
tenant_llm.append(
{"tenant_id": user_info["id"], "llm_factory": settings.LLM_FACTORY, "llm_name": llm.llm_name,
"model_type": llm.model_type,
"api_key": settings.API_KEY, "api_base": settings.LLM_BASE_URL})
seen = set()
factory_configs = []
for factory_config in [
settings.CHAT_CFG["factory"],
settings.EMBEDDING_CFG["factory"],
settings.ASR_CFG["factory"],
settings.IMAGE2TEXT_CFG["factory"],
settings.RERANK_CFG["factory"],
]:
factory_name = factory_config["factory"]
if factory_name not in seen:
seen.add(factory_name)
factory_configs.append(factory_config)
for factory_config in factory_configs:
for llm in LLMService.query(fid=factory_config["factory"]):
tenant_llm.append(
{
"tenant_id": user_id,
"llm_factory": factory_config["factory"],
"llm_name": llm.llm_name,
"model_type": llm.model_type,
"api_key": factory_config["api_key"],
"api_base": factory_config["base_url"],
"max_tokens": llm.max_tokens if llm.max_tokens else 8192,
}
)
unique = {}
for item in tenant_llm:
key = (item["tenant_id"], item["llm_factory"], item["llm_name"])
if key not in unique:
unique[key] = item
tenant_llm = list(unique.values())
if not UserService.save(**user_info):
logging.error("can't init admin.")
@ -103,7 +135,7 @@ def init_llm_factory():
except Exception:
pass
factory_llm_infos = settings.FACTORY_LLM_INFOS
factory_llm_infos = settings.FACTORY_LLM_INFOS
for factory_llm_info in factory_llm_infos:
info = deepcopy(factory_llm_info)
llm_infos = info.pop("llm")

89
api/settings.py
View File

@ -38,6 +38,11 @@ EMBEDDING_MDL = ""
RERANK_MDL = ""
ASR_MDL = ""
IMAGE2TEXT_MDL = ""
CHAT_CFG = ""
EMBEDDING_CFG = ""
RERANK_CFG = ""
ASR_CFG = ""
IMAGE2TEXT_CFG = ""
API_KEY = None
PARSERS = None
HOST_IP = None
@ -74,23 +79,22 @@ STRONG_TEST_COUNT = int(os.environ.get("STRONG_TEST_COUNT", "8"))
BUILTIN_EMBEDDING_MODELS = ["BAAI/bge-large-zh-v1.5@BAAI", "maidalun1020/bce-embedding-base_v1@Youdao"]
def get_or_create_secret_key():
secret_key = os.environ.get("RAGFLOW_SECRET_KEY")
if secret_key and len(secret_key) >= 32:
return secret_key
# Check if there's a configured secret key
configured_key = get_base_config(RAG_FLOW_SERVICE_NAME, {}).get("secret_key")
if configured_key and configured_key != str(date.today()) and len(configured_key) >= 32:
return configured_key
# Generate a new secure key and warn about it
import logging
new_key = secrets.token_hex(32)
logging.warning(
"SECURITY WARNING: Using auto-generated SECRET_KEY. "
f"Generated key: {new_key}"
)
logging.warning(f"SECURITY WARNING: Using auto-generated SECRET_KEY. Generated key: {new_key}")
return new_key
@ -99,10 +103,10 @@ def init_settings():
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")
LLM_BASE_URL = LLM.get("base_url")
LLM = get_base_config("user_default_llm", {}) or {}
LLM_DEFAULT_MODELS = LLM.get("default_models", {}) or {}
LLM_FACTORY = LLM.get("factory", "") or ""
LLM_BASE_URL = LLM.get("base_url", "") or ""
try:
REGISTER_ENABLED = int(os.environ.get("REGISTER_ENABLED", "1"))
except Exception:
@ -115,29 +119,34 @@ def init_settings():
FACTORY_LLM_INFOS = []
global CHAT_MDL, EMBEDDING_MDL, RERANK_MDL, ASR_MDL, IMAGE2TEXT_MDL
global CHAT_CFG, EMBEDDING_CFG, RERANK_CFG, ASR_CFG, IMAGE2TEXT_CFG
if not LIGHTEN:
EMBEDDING_MDL = BUILTIN_EMBEDDING_MODELS[0]
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,email:Email,tag:Tag"
)
chat_entry = _parse_model_entry(LLM_DEFAULT_MODELS.get("chat_model", CHAT_MDL))
embedding_entry = _parse_model_entry(LLM_DEFAULT_MODELS.get("embedding_model", EMBEDDING_MDL))
rerank_entry = _parse_model_entry(LLM_DEFAULT_MODELS.get("rerank_model", RERANK_MDL))
asr_entry = _parse_model_entry(LLM_DEFAULT_MODELS.get("asr_model", ASR_MDL))
image2text_entry = _parse_model_entry(LLM_DEFAULT_MODELS.get("image2text_model", IMAGE2TEXT_MDL))
CHAT_CFG = _resolve_per_model_config(chat_entry, LLM_FACTORY, API_KEY, LLM_BASE_URL)
EMBEDDING_CFG = _resolve_per_model_config(embedding_entry, LLM_FACTORY, API_KEY, LLM_BASE_URL)
RERANK_CFG = _resolve_per_model_config(rerank_entry, LLM_FACTORY, API_KEY, LLM_BASE_URL)
ASR_CFG = _resolve_per_model_config(asr_entry, LLM_FACTORY, API_KEY, LLM_BASE_URL)
IMAGE2TEXT_CFG = _resolve_per_model_config(image2text_entry, LLM_FACTORY, API_KEY, LLM_BASE_URL)
CHAT_MDL = CHAT_CFG.get("model", "") or ""
EMBEDDING_MDL = EMBEDDING_CFG.get("model", "") or ""
RERANK_MDL = RERANK_CFG.get("model", "") or ""
ASR_MDL = ASR_CFG.get("model", "") or ""
IMAGE2TEXT_MDL = IMAGE2TEXT_CFG.get("model", "") or ""
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")
@ -170,6 +179,7 @@ def init_settings():
retrievaler = search.Dealer(docStoreConn)
from graphrag import search as kg_search
kg_retrievaler = kg_search.KGSearch(docStoreConn)
if int(os.environ.get("SANDBOX_ENABLED", "0")):
@ -210,3 +220,34 @@ class RetCode(IntEnum, CustomEnum):
SERVER_ERROR = 500
FORBIDDEN = 403
NOT_FOUND = 404
def _parse_model_entry(entry):
if isinstance(entry, str):
return {"name": entry, "factory": None, "api_key": None, "base_url": None}
if isinstance(entry, dict):
name = entry.get("name") or entry.get("model") or ""
return {
"name": name,
"factory": entry.get("factory"),
"api_key": entry.get("api_key"),
"base_url": entry.get("base_url"),
}
return {"name": "", "factory": None, "api_key": None, "base_url": None}
def _resolve_per_model_config(entry_dict, backup_factory, backup_api_key, backup_base_url):
name = (entry_dict.get("name") or "").strip()
m_factory = entry_dict.get("factory") or backup_factory or ""
m_api_key = entry_dict.get("api_key") or backup_api_key or ""
m_base_url = entry_dict.get("base_url") or backup_base_url or ""
if name and "@" not in name and m_factory:
name = f"{name}@{m_factory}"
return {
"model": name,
"factory": m_factory,
"api_key": m_api_key,
"base_url": m_base_url,
}

18
conf/service_conf.yaml
View File

@ -64,9 +64,21 @@ redis:
# config:
# oss_table: 'opendal_storage'
# user_default_llm:
# factory: 'Tongyi-Qianwen'
# api_key: 'sk-xxxxxxxxxxxxx'
# base_url: ''
# factory: 'BAAI'
# api_key: 'backup'
# base_url: 'backup_base_url'
# default_models:
# chat_model:
# name: 'qwen2.5-7b-instruct'
# factory: 'xxxx'
# api_key: 'xxxx'
# base_url: 'https://api.xx.com'
# embedding_model:
# name: 'bge-m3'
# rerank_model: 'bge-reranker-v2'
# asr_model:
# model: 'whisper-large-v3' # alias of name
# image2text_model: ''
# oauth:
# oauth2:
# display_name: "OAuth2"