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Fix: model selecton rule in get_model_config_by_type_and_name (#13569)

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### What problem does this PR solve?

Fix: model selecton rule in get_model_config_by_type_and_name

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)
This commit is contained in:
Magicbook1108
2026-03-13 19:46:13 +08:00
committed by GitHub
parent cb49cd30c4
commit 161659becc
5 changed files with 65 additions and 20 deletions
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17
api/db/joint_services/tenant_model_service.py
View File

@ -35,11 +35,12 @@ def get_model_config_by_id(tenant_model_id: int) -> dict:
def get_model_config_by_type_and_name(tenant_id: str, model_type: str, model_name: str):
if not model_name:
raise Exception("Model Name is required")
model_config = TenantLLMService.get_api_key(tenant_id, model_name)
model_type_val = model_type.value if hasattr(model_type, "value") else model_type
model_config = TenantLLMService.get_api_key(tenant_id, model_name, model_type_val)
if not model_config:
# model_name in format 'name@factory', split model_name and try again
pure_model_name, fid = TenantLLMService.split_model_name_and_factory(model_name)
if model_type == LLMType.EMBEDDING and fid == "Builtin" and "tei-" in os.getenv("COMPOSE_PROFILES", "") and pure_model_name == os.getenv("TEI_MODEL", ""):
if model_type_val == LLMType.EMBEDDING.value and fid == "Builtin" and "tei-" in os.getenv("COMPOSE_PROFILES", "") and pure_model_name == os.getenv("TEI_MODEL", ""):
# configured local embedding model
embedding_cfg = settings.EMBEDDING_CFG
config_dict = {
@ -47,16 +48,22 @@ def get_model_config_by_type_and_name(tenant_id: str, model_type: str, model_nam
"api_key": embedding_cfg["api_key"],
"llm_name": pure_model_name,
"api_base": embedding_cfg["base_url"],
"model_type": LLMType.EMBEDDING,
"model_type": LLMType.EMBEDDING.value,
}
else:
model_config = TenantLLMService.get_api_key(tenant_id, pure_model_name)
model_config = TenantLLMService.get_api_key(tenant_id, pure_model_name, model_type_val)
if not model_config:
raise LookupError(f"Tenant Model with name {model_name} not found")
raise LookupError(f"Tenant Model with name {model_name} and type {model_type_val} not found")
config_dict = model_config.to_dict()
else:
# model_name without @factory
config_dict = model_config.to_dict()
config_model_type = config_dict.get("model_type")
config_model_type = config_model_type.value if hasattr(config_model_type, "value") else config_model_type
if config_model_type != model_type_val:
raise LookupError(
f"Tenant Model with name {model_name} has type {config_model_type}, expected {model_type_val}"
)
llm = LLMService.query(llm_name=config_dict["llm_name"])
if llm:
config_dict["is_tools"] = llm[0].is_tools

17
api/db/services/tenant_llm_service.py
View File

@ -36,12 +36,16 @@ class TenantLLMService(CommonService):
@classmethod
@DB.connection_context()
def get_api_key(cls, tenant_id, model_name):
def get_api_key(cls, tenant_id, model_name, model_type=None):
mdlnm, fid = TenantLLMService.split_model_name_and_factory(model_name)
model_type_val = model_type.value if hasattr(model_type, "value") else model_type
query_kwargs = {"tenant_id": tenant_id, "llm_name": mdlnm}
if model_type_val is not None:
query_kwargs["model_type"] = model_type_val
if not fid:
objs = cls.query(tenant_id=tenant_id, llm_name=mdlnm)
objs = cls.query(**query_kwargs)
else:
objs = cls.query(tenant_id=tenant_id, llm_name=mdlnm, llm_factory=fid)
objs = cls.query(**query_kwargs, llm_factory=fid)
if (not objs) and fid:
if fid == "LocalAI":
@ -52,7 +56,8 @@ class TenantLLMService(CommonService):
mdlnm += "___OpenAI-API"
elif fid == "VLLM":
mdlnm += "___VLLM"
objs = cls.query(tenant_id=tenant_id, llm_name=mdlnm, llm_factory=fid)
query_kwargs["llm_name"] = mdlnm
objs = cls.query(**query_kwargs, llm_factory=fid)
if not objs:
return None
return objs[0]
@ -112,10 +117,10 @@ class TenantLLMService(CommonService):
else:
assert False, "LLM type error"
model_config = cls.get_api_key(tenant_id, mdlnm)
model_config = cls.get_api_key(tenant_id, mdlnm, llm_type)
mdlnm, fid = TenantLLMService.split_model_name_and_factory(mdlnm)
if not model_config: # for some cases seems fid mismatch
model_config = cls.get_api_key(tenant_id, mdlnm)
model_config = cls.get_api_key(tenant_id, mdlnm, llm_type)
if model_config:
model_config = model_config.to_dict()
elif llm_type == LLMType.EMBEDDING and fid == "Builtin" and "tei-" in os.getenv("COMPOSE_PROFILES", "") and mdlnm == os.getenv("TEI_MODEL", ""):