diff --git a/api/apps/sdk/doc.py b/api/apps/sdk/doc.py
index 998e4abaa..74b2e6c95 100644
--- a/api/apps/sdk/doc.py
+++ b/api/apps/sdk/doc.py
@@ -20,7 +20,7 @@ from api.db.services.dialog_service import keyword_extraction
 from rag.app.qa import rmPrefix, beAdoc
 from rag.nlp import rag_tokenizer
 from api.db import LLMType, ParserType
-from api.db.services.llm_service import TenantLLMService
+from api.db.services.llm_service import TenantLLMService, LLMBundle
 from api import settings
 import xxhash
 import re
@@ -1331,18 +1331,14 @@ def retrieval_test(tenant_id):
         e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
         if not e:
             return get_error_data_result(message="Dataset not found!")
-        embd_mdl = TenantLLMService.model_instance(
-            kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id
-        )
+        embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING, llm_name=kb.embd_id)
 
         rerank_mdl = None
         if req.get("rerank_id"):
-            rerank_mdl = TenantLLMService.model_instance(
-                kb.tenant_id, LLMType.RERANK.value, llm_name=req["rerank_id"]
-            )
+            rerank_mdl = LLMBundle(kb.tenant_id, LLMType.RERANK, llm_name=req["rerank_id"])
 
         if req.get("keyword", False):
-            chat_mdl = TenantLLMService.model_instance(kb.tenant_id, LLMType.CHAT)
+            chat_mdl = LLMBundle(kb.tenant_id, LLMType.CHAT)
             question += keyword_extraction(chat_mdl, question)
 
         retr = settings.retrievaler if kb.parser_id != ParserType.KG else settings.kg_retrievaler