fix react response

api/core/workflow/nodes/knowledge_retrieval/structed_multi_dataset_router_agent.py

@@ -14,6 +14,7 @@ from core.model_runtime.entities.llm_entities import LLMUsage
 from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageRole, PromptMessageTool
 from core.prompt.advanced_prompt_transform import AdvancedPromptTransform
 from core.prompt.entities.advanced_prompt_entities import ChatModelMessage
+from core.rag.retrieval.agent.output_parser.structured_chat import StructuredChatOutputParser
 from core.workflow.nodes.knowledge_retrieval.entities import KnowledgeRetrievalNodeData
 from core.workflow.nodes.llm.llm_node import LLMNode
 from pydantic import Field
@@ -92,7 +93,7 @@ class ReactMultiDatasetRouter:
             suffix: str = SUFFIX,
             human_message_template: str = HUMAN_MESSAGE_TEMPLATE,
             format_instructions: str = FORMAT_INSTRUCTIONS,
-    ) -> str:
+    ) -> Union[str, None]:
         if model_config.mode == "chat":
             prompt = self.create_chat_prompt(
                 query=query,
@@ -109,7 +110,7 @@ class ReactMultiDatasetRouter:
                 format_instructions=format_instructions,
                 input_variables=None
             )
-        stop = model_config.stop
+        stop = ['Observation:']
         # handle invoke result
         prompt_transform = AdvancedPromptTransform()
         prompt_messages = prompt_transform.get_prompt(
@@ -130,13 +131,11 @@ class ReactMultiDatasetRouter:
             user_id=user_id,
             tenant_id=tenant_id
         )
-        output_parser: AgentOutputParser = Field(
-            default_factory=StructuredChatOutputParserWithRetries
-        )
+        output_parser = StructuredChatOutputParser()
         agent_decision = output_parser.parse(result_text)
         if isinstance(agent_decision, AgentAction):
-            tool_inputs = agent_decision.tool_input
-        return tool_inputs
+            return agent_decision.tool
+        return None
 
     def _invoke_llm(self, node_data: KnowledgeRetrievalNodeData,
                     model_instance: ModelInstance,
@@ -207,7 +206,7 @@ class ReactMultiDatasetRouter:
     ) -> list[ChatModelMessage]:
         tool_strings = []
         for tool in tools:
-            tool_strings.append(f"dataset_{tool.name}: {tool.description}, args: {{'query': {{'title': 'Query', 'description': 'Query for the dataset to be used to retrieve the dataset.', 'type': 'string'}}}}")
+            tool_strings.append(f"{tool.name}: {tool.description}, args: {{'query': {{'title': 'Query', 'description': 'Query for the dataset to be used to retrieve the dataset.', 'type': 'string'}}}}")
         formatted_tools = "\n".join(tool_strings)
         unique_tool_names = set(tool.name for tool in tools)
         tool_names = ", ".join('"' + name + '"' for name in unique_tool_names)