fix: stream never ruff

api/core/agent/base_agent_runner.py

@@ -253,9 +253,11 @@ class BaseAgentRunner(AppRunner):
             # save tool entity
             tool_instances[dataset_tool.entity.identity.name] = dataset_tool
 
-        output_tools = build_agent_output_tools(tenant_id=self.tenant_id,
-                                                invoke_from=self.application_generate_entity.invoke_from,
-                                                tool_invoke_from=ToolInvokeFrom.AGENT)
+        output_tools = build_agent_output_tools(
+            tenant_id=self.tenant_id,
+            invoke_from=self.application_generate_entity.invoke_from,
+            tool_invoke_from=ToolInvokeFrom.AGENT,
+        )
         for tool in output_tools:
             tool_instances[tool.entity.identity.name] = tool
 

api/core/agent/entities.py

@@ -194,6 +194,7 @@ class AgentResult(BaseModel):
     """
     Agent execution result.
     """
+
     output: str | dict = Field(default="", description="The generated output")
     files: list[Any] = Field(default_factory=list, description="Files produced during execution")
     usage: Any | None = Field(default=None, description="LLM usage statistics")

api/core/agent/output_tools.py

@@ -101,6 +101,7 @@ def build_agent_output_tools(
             message_id: str | None = None,
         ) -> ToolInvokeMessage:
             return ToolInvokeMessage(message=ToolInvokeMessage.TextMessage(text=TERMINAL_OUTPUT_MESSAGE))
+
         raw_tool._invoke = invoke_tool  # pyright: ignore[reportPrivateUsage]
         tools.append(raw_tool)
 

api/core/agent/patterns/base.py

@@ -57,10 +57,7 @@ class AgentPattern(ABC):
 
     @abstractmethod
     def run(
-        self,
-        prompt_messages: list[PromptMessage],
-        model_parameters: dict[str, Any],
-        stop: list[str]
+        self, prompt_messages: list[PromptMessage], model_parameters: dict[str, Any], stop: list[str]
     ) -> Generator[LLMResultChunk | AgentLog, None, AgentResult]:
         """Execute the agent strategy."""
         pass

api/core/agent/patterns/function_call.py

@@ -30,10 +30,7 @@ class FunctionCallStrategy(AgentPattern):
     """Function Call strategy using model's native tool calling capability."""
 
     def run(
-        self,
-        prompt_messages: list[PromptMessage],
-        model_parameters: dict[str, Any],
-        stop: list[str]
+        self, prompt_messages: list[PromptMessage], model_parameters: dict[str, Any], stop: list[str]
     ) -> Generator[LLMResultChunk | AgentLog, None, AgentResult]:
         """Execute the function call agent strategy."""
         # Convert tools to prompt format
@@ -144,9 +141,7 @@ class FunctionCallStrategy(AgentPattern):
                 output_files.extend(tool_files)
                 if tool_response == TERMINAL_OUTPUT_MESSAGE:
                     function_call_state = False
-                    final_tool_args = tool_entity.transform_tool_parameters_type(
-                        tool_args
-                    )
+                    final_tool_args = tool_entity.transform_tool_parameters_type(tool_args)
 
             yield self._finish_log(
                 round_log,

api/core/agent/patterns/react.py

@@ -59,11 +59,7 @@ class ReActStrategy(AgentPattern):
         self.instruction = instruction
 
     def run(
-        self,
-        prompt_messages:
-        list[PromptMessage],
-        model_parameters: dict[str, Any],
-        stop: list[str]
+        self, prompt_messages: list[PromptMessage], model_parameters: dict[str, Any], stop: list[str]
     ) -> Generator[LLMResultChunk | AgentLog, None, AgentResult]:
         """Execute the ReAct agent strategy."""
         # Initialize tracking

api/core/agent/patterns/strategy_factory.py

@@ -43,7 +43,7 @@ class StrategyFactory:
         agent_strategy: AgentEntity.Strategy | None = None,
         tool_invoke_hook: ToolInvokeHook | None = None,
         instruction: str = "",
-        structured_output_schema: Mapping[str, Any] | None = None
+        structured_output_schema: Mapping[str, Any] | None = None,
     ) -> AgentPattern:
         """
         Create an appropriate strategy based on model features.
@@ -71,7 +71,7 @@ class StrategyFactory:
             tenant_id=tenant_id,
             invoke_from=invoke_from,
             tool_invoke_from=tool_invoke_from,
-            structured_output_schema=structured_output_schema
+            structured_output_schema=structured_output_schema,
         )
 
         tools.extend(output_tools)