diff --git a/api/core/workflow/nodes/knowledge_retrieval/entities.py b/api/core/workflow/nodes/knowledge_retrieval/entities.py
index cdbce3ce14..37ed5b8385 100644
--- a/api/core/workflow/nodes/knowledge_retrieval/entities.py
+++ b/api/core/workflow/nodes/knowledge_retrieval/entities.py
@@ -10,7 +10,7 @@ class RerankingModelConfig(BaseModel):
     Reranking Model Config.
     """
     provider: str
-    mode: str
+    model: str
 
 
 class MultipleRetrievalConfig(BaseModel):
diff --git a/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py b/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py
index 87ba4239f8..0534695adb 100644
--- a/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py
+++ b/api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py
@@ -5,11 +5,12 @@ from flask import Flask, current_app
 
 from core.app.app_config.entities import DatasetRetrieveConfigEntity
 from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
+from core.entities.agent_entities import PlanningStrategy
 from core.entities.model_entities import ModelStatus
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_manager import ModelInstance, ModelManager
 from core.model_runtime.entities.message_entities import PromptMessageTool, SystemPromptMessage, UserPromptMessage
-from core.model_runtime.entities.model_entities import ModelType
+from core.model_runtime.entities.model_entities import ModelType, ModelFeature
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.rag.datasource.retrieval_service import RetrievalService
 from core.rerank.rerank import RerankRunner
@@ -192,6 +193,25 @@ class KnowledgeRetrievalNode(BaseNode):
             tools.append(message_tool)
         # fetch model config
         model_instance, model_config = self._fetch_model_config(node_data)
+        # check model is support tool calling
+        model_type_instance = model_config.provider_model_bundle.model_type_instance
+        model_type_instance = cast(LargeLanguageModel, model_type_instance)
+        # get model schema
+        model_schema = model_type_instance.get_model_schema(
+            model=model_config.model,
+            credentials=model_config.credentials
+        )
+
+        if not model_schema:
+            return None
+        planning_strategy = PlanningStrategy.REACT_ROUTER
+        features = model_schema.features
+        if features:
+            if ModelFeature.TOOL_CALL in features \
+                    or ModelFeature.MULTI_TOOL_CALL in features:
+                planning_strategy = PlanningStrategy.ROUTER
+
+
         prompt_messages = [
             SystemPromptMessage(content='You are a helpful AI assistant.'),
             UserPromptMessage(content=query)
@@ -328,7 +348,7 @@ class KnowledgeRetrievalNode(BaseNode):
             tenant_id=self.tenant_id,
             provider=node_data.multiple_retrieval_config.reranking_model.provider,
             model_type=ModelType.RERANK,
-            model=node_data.multiple_retrieval_config.reranking_model.name
+            model=node_data.multiple_retrieval_config.reranking_model.model
         )
 
         rerank_runner = RerankRunner(rerank_model_instance)
@@ -374,3 +394,4 @@ class KnowledgeRetrievalNode(BaseNode):
                                                           )
 
                     all_documents.extend(documents)
+