remove bare list, dict, Sequence, None, Any (#25058)

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: -LAN- <laipz8200@outlook.com>

api/configs/remote_settings_sources/base.py

     def get_field_value(self, field: FieldInfo, field_name: str) -> tuple[Any, str, bool]:
         raise NotImplementedError
 
-    def prepare_field_value(self, field_name: str, field: FieldInfo, value: Any, value_is_complex: bool) -> Any:
+    def prepare_field_value(self, field_name: str, field: FieldInfo, value: Any, value_is_complex: bool):
         return value

api/configs/remote_settings_sources/nacos/__init__.py

             logger.exception("[get-access-token] exception occurred")
             raise
 
-    def _parse_config(self, content: str) -> dict:
+    def _parse_config(self, content: str):
         if not content:
             return {}
         try:

api/controllers/console/app/generator.py

     @setup_required
     @login_required
     @account_initialization_required
-    def post(self) -> dict:
+    def post(self):
         parser = reqparse.RequestParser()
         parser.add_argument("type", type=str, required=True, default=False, location="json")
         args = parser.parse_args()

api/controllers/console/app/workflow_draft_variable.py

 import logging
-from typing import Any, NoReturn
+from typing import NoReturn
 
 from flask import Response
 from flask_restx import Resource, fields, inputs, marshal, marshal_with, reqparse
 logger = logging.getLogger(__name__)
 
 
-def _convert_values_to_json_serializable_object(value: Segment) -> Any:
+def _convert_values_to_json_serializable_object(value: Segment):
     if isinstance(value, FileSegment):
         return value.value.model_dump()
     elif isinstance(value, ArrayFileSegment):
         return value.value
 
 
-def _serialize_var_value(variable: WorkflowDraftVariable) -> Any:
+def _serialize_var_value(variable: WorkflowDraftVariable):
     value = variable.get_value()
     # create a copy of the value to avoid affecting the model cache.
     value = value.model_copy(deep=True)

api/controllers/mcp/mcp.py

 
         return mcp_server, app
 
-    def _validate_server_status(self, mcp_server: AppMCPServer) -> None:
+    def _validate_server_status(self, mcp_server: AppMCPServer):
         """Validate MCP server status"""
         if mcp_server.status != AppMCPServerStatus.ACTIVE:
             raise MCPRequestError(mcp_types.INVALID_REQUEST, "Server is not active")

api/core/agent/base_agent_runner.py

         model_instance: ModelInstance,
         memory: Optional[TokenBufferMemory] = None,
         prompt_messages: Optional[list[PromptMessage]] = None,
-    ) -> None:
+    ):
         self.tenant_id = tenant_id
         self.application_generate_entity = application_generate_entity
         self.conversation = conversation

api/core/agent/cot_agent_runner.py

 
         return instruction
 
-    def _init_react_state(self, query) -> None:
+    def _init_react_state(self, query):
         """
         init agent scratchpad
         """

api/core/agent/entities.py

         action_name: str
         action_input: Union[dict, str]
 
-        def to_dict(self) -> dict:
+        def to_dict(self):
             """
             Convert to dictionary.
             """

api/core/app/app_config/easy_ui_based_app/dataset/manager.py

         return config, ["agent_mode", "dataset_configs", "dataset_query_variable"]
 
     @classmethod
-    def extract_dataset_config_for_legacy_compatibility(cls, tenant_id: str, app_mode: AppMode, config: dict) -> dict:
+    def extract_dataset_config_for_legacy_compatibility(cls, tenant_id: str, app_mode: AppMode, config: dict):
         """
         Extract dataset config for legacy compatibility
 

api/core/app/app_config/easy_ui_based_app/model_config/manager.py

         return dict(config), ["model"]
 
     @classmethod
-    def validate_model_completion_params(cls, cp: dict) -> dict:
+    def validate_model_completion_params(cls, cp: dict):
         # model.completion_params
         if not isinstance(cp, dict):
             raise ValueError("model.completion_params must be of object type")

api/core/app/app_config/easy_ui_based_app/prompt_template/manager.py

         return config, ["prompt_type", "pre_prompt", "chat_prompt_config", "completion_prompt_config"]
 
     @classmethod
-    def validate_post_prompt_and_set_defaults(cls, config: dict) -> dict:
+    def validate_post_prompt_and_set_defaults(cls, config: dict):
         """
         Validate post_prompt and set defaults for prompt feature
 

api/core/app/apps/advanced_chat/app_config_manager.py

         return app_config
 
     @classmethod
-    def config_validate(cls, tenant_id: str, config: dict, only_structure_validate: bool = False) -> dict:
+    def config_validate(cls, tenant_id: str, config: dict, only_structure_validate: bool = False):
         """
         Validate for advanced chat app model config
 

api/core/app/apps/advanced_chat/app_generator.py

         message_id: str,
         context: contextvars.Context,
         variable_loader: VariableLoader,
-    ) -> None:
+    ):
         """
         Generate worker in a new thread.
         :param flask_app: Flask app

api/core/app/apps/advanced_chat/app_runner.py

         workflow: Workflow,
         system_user_id: str,
         app: App,
-    ) -> None:
+    ):
         super().__init__(
             queue_manager=queue_manager,
             variable_loader=variable_loader,
         self.system_user_id = system_user_id
         self._app = app
 
-    def run(self) -> None:
+    def run(self):
         app_config = self.application_generate_entity.app_config
         app_config = cast(AdvancedChatAppConfig, app_config)
 
 
         return False
 
-    def _complete_with_stream_output(self, text: str, stopped_by: QueueStopEvent.StopBy) -> None:
+    def _complete_with_stream_output(self, text: str, stopped_by: QueueStopEvent.StopBy):
         """
         Direct output
         """

api/core/app/apps/advanced_chat/generate_task_pipeline.py

         workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         draft_var_saver_factory: DraftVariableSaverFactory,
-    ) -> None:
+    ):
         self._base_task_pipeline = BasedGenerateTaskPipeline(
             application_generate_entity=application_generate_entity,
             queue_manager=queue_manager,
                 session.rollback()
                 raise
 
-    def _ensure_workflow_initialized(self) -> None:
+    def _ensure_workflow_initialized(self):
         """Fluent validation for workflow state."""
         if not self._workflow_run_id:
             raise ValueError("workflow run not initialized.")
         if self._conversation_name_generate_thread:
             self._conversation_name_generate_thread.join()
 
-    def _save_message(self, *, session: Session, graph_runtime_state: Optional[GraphRuntimeState] = None) -> None:
+    def _save_message(self, *, session: Session, graph_runtime_state: Optional[GraphRuntimeState] = None):
         message = self._get_message(session=session)
 
         # If there are assistant files, remove markdown image links from answer

api/core/app/apps/agent_chat/app_config_manager.py

         return app_config
 
     @classmethod
-    def config_validate(cls, tenant_id: str, config: Mapping[str, Any]) -> dict:
+    def config_validate(cls, tenant_id: str, config: Mapping[str, Any]):
         """
         Validate for agent chat app model config
 

api/core/app/apps/agent_chat/app_generator.py

         queue_manager: AppQueueManager,
         conversation_id: str,
         message_id: str,
-    ) -> None:
+    ):
         """
         Generate worker in a new thread.
         :param flask_app: Flask app

api/core/app/apps/agent_chat/app_runner.py

         queue_manager: AppQueueManager,
         conversation: Conversation,
         message: Message,
-    ) -> None:
+    ):
         """
         Run assistant application
         :param application_generate_entity: application generate entity

api/core/app/apps/agent_chat/generate_response_converter.py

     _blocking_response_type = ChatbotAppBlockingResponse
 
     @classmethod
-    def convert_blocking_full_response(cls, blocking_response: ChatbotAppBlockingResponse) -> dict:  # type: ignore[override]
+    def convert_blocking_full_response(cls, blocking_response: ChatbotAppBlockingResponse):  # type: ignore[override]
         """
         Convert blocking full response.
         :param blocking_response: blocking response
         return response
 
     @classmethod
-    def convert_blocking_simple_response(cls, blocking_response: ChatbotAppBlockingResponse) -> dict:  # type: ignore[override]
+    def convert_blocking_simple_response(cls, blocking_response: ChatbotAppBlockingResponse):  # type: ignore[override]
         """
         Convert blocking simple response.
         :param blocking_response: blocking response

api/core/app/apps/base_app_generate_response_converter.py

         return metadata
 
     @classmethod
-    def _error_to_stream_response(cls, e: Exception) -> dict:
+    def _error_to_stream_response(cls, e: Exception):
         """
         Error to stream response.
         :param e: exception

api/core/app/apps/base_app_generator.py

 
         return value
 
-    def _sanitize_value(self, value: Any) -> Any:
+    def _sanitize_value(self, value: Any):
         if isinstance(value, str):
             return value.replace("\x00", "")
         return value

api/core/app/apps/base_app_queue_manager.py

 
 
 class AppQueueManager:
-    def __init__(self, task_id: str, user_id: str, invoke_from: InvokeFrom) -> None:
+    def __init__(self, task_id: str, user_id: str, invoke_from: InvokeFrom):
         if not user_id:
             raise ValueError("user is required")
 
                     self.publish(QueuePingEvent(), PublishFrom.TASK_PIPELINE)
                     last_ping_time = elapsed_time // 10
 
-    def stop_listen(self) -> None:
+    def stop_listen(self):
         """
         Stop listen to queue
         :return:
         """
         self._q.put(None)
 
-    def publish_error(self, e, pub_from: PublishFrom) -> None:
+    def publish_error(self, e, pub_from: PublishFrom):
         """
         Publish error
         :param e: error
         """
         self.publish(QueueErrorEvent(error=e), pub_from)
 
-    def publish(self, event: AppQueueEvent, pub_from: PublishFrom) -> None:
+    def publish(self, event: AppQueueEvent, pub_from: PublishFrom):
         """
         Publish event to queue
         :param event:
         self._publish(event, pub_from)
 
     @abstractmethod
-    def _publish(self, event: AppQueueEvent, pub_from: PublishFrom) -> None:
+    def _publish(self, event: AppQueueEvent, pub_from: PublishFrom):
         """
         Publish event to queue
         :param event:
         raise NotImplementedError
 
     @classmethod
-    def set_stop_flag(cls, task_id: str, invoke_from: InvokeFrom, user_id: str) -> None:
+    def set_stop_flag(cls, task_id: str, invoke_from: InvokeFrom, user_id: str):
         """
         Set task stop flag
         :return:

api/core/app/apps/base_app_runner.py

         text: str,
         stream: bool,
         usage: Optional[LLMUsage] = None,
-    ) -> None:
+    ):
         """
         Direct output
         :param queue_manager: application queue manager
         queue_manager: AppQueueManager,
         stream: bool,
         agent: bool = False,
-    ) -> None:
+    ):
         """
         Handle invoke result
         :param invoke_result: invoke result
         else:
             raise NotImplementedError(f"unsupported invoke result type: {type(invoke_result)}")
 
-    def _handle_invoke_result_direct(
-        self, invoke_result: LLMResult, queue_manager: AppQueueManager, agent: bool
-    ) -> None:
+    def _handle_invoke_result_direct(self, invoke_result: LLMResult, queue_manager: AppQueueManager, agent: bool):
         """
         Handle invoke result direct
         :param invoke_result: invoke result
 
     def _handle_invoke_result_stream(
         self, invoke_result: Generator[LLMResultChunk, None, None], queue_manager: AppQueueManager, agent: bool
-    ) -> None:
+    ):
         """
         Handle invoke result
         :param invoke_result: invoke result

api/core/app/apps/chat/app_config_manager.py

         return app_config
 
     @classmethod
-    def config_validate(cls, tenant_id: str, config: dict) -> dict:
+    def config_validate(cls, tenant_id: str, config: dict):
         """
         Validate for chat app model config
 

api/core/app/apps/chat/app_generator.py

         queue_manager: AppQueueManager,
         conversation_id: str,
         message_id: str,
-    ) -> None:
+    ):
         """
         Generate worker in a new thread.
         :param flask_app: Flask app

api/core/app/apps/chat/app_runner.py

         queue_manager: AppQueueManager,
         conversation: Conversation,
         message: Message,
-    ) -> None:
+    ):
         """
         Run application
         :param application_generate_entity: application generate entity

api/core/app/apps/chat/generate_response_converter.py

     _blocking_response_type = ChatbotAppBlockingResponse
 
     @classmethod
-    def convert_blocking_full_response(cls, blocking_response: ChatbotAppBlockingResponse) -> dict:  # type: ignore[override]
+    def convert_blocking_full_response(cls, blocking_response: ChatbotAppBlockingResponse):  # type: ignore[override]
         """
         Convert blocking full response.
         :param blocking_response: blocking response
         return response
 
     @classmethod
-    def convert_blocking_simple_response(cls, blocking_response: ChatbotAppBlockingResponse) -> dict:  # type: ignore[override]
+    def convert_blocking_simple_response(cls, blocking_response: ChatbotAppBlockingResponse):  # type: ignore[override]
         """
         Convert blocking simple response.
         :param blocking_response: blocking response

api/core/app/apps/common/workflow_response_converter.py

         *,
         application_generate_entity: Union[AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity],
         user: Union[Account, EndUser],
-    ) -> None:
+    ):
         self._application_generate_entity = application_generate_entity
         self._user = user
 

api/core/app/apps/completion/app_config_manager.py

         return app_config
 
     @classmethod
-    def config_validate(cls, tenant_id: str, config: dict) -> dict:
+    def config_validate(cls, tenant_id: str, config: dict):
         """
         Validate for completion app model config
 

api/core/app/apps/completion/app_generator.py

         application_generate_entity: CompletionAppGenerateEntity,
         queue_manager: AppQueueManager,
         message_id: str,
-    ) -> None:
+    ):
         """
         Generate worker in a new thread.
         :param flask_app: Flask app

api/core/app/apps/completion/app_runner.py

 
     def run(
         self, application_generate_entity: CompletionAppGenerateEntity, queue_manager: AppQueueManager, message: Message
-    ) -> None:
+    ):
         """
         Run application
         :param application_generate_entity: application generate entity

api/core/app/apps/completion/generate_response_converter.py

     _blocking_response_type = CompletionAppBlockingResponse
 
     @classmethod
-    def convert_blocking_full_response(cls, blocking_response: CompletionAppBlockingResponse) -> dict:  # type: ignore[override]
+    def convert_blocking_full_response(cls, blocking_response: CompletionAppBlockingResponse):  # type: ignore[override]
         """
         Convert blocking full response.
         :param blocking_response: blocking response
         return response
 
     @classmethod
-    def convert_blocking_simple_response(cls, blocking_response: CompletionAppBlockingResponse) -> dict:  # type: ignore[override]
+    def convert_blocking_simple_response(cls, blocking_response: CompletionAppBlockingResponse):  # type: ignore[override]
         """
         Convert blocking simple response.
         :param blocking_response: blocking response

api/core/app/apps/message_based_app_queue_manager.py

 class MessageBasedAppQueueManager(AppQueueManager):
     def __init__(
         self, task_id: str, user_id: str, invoke_from: InvokeFrom, conversation_id: str, app_mode: str, message_id: str
-    ) -> None:
+    ):
         super().__init__(task_id, user_id, invoke_from)
 
         self._conversation_id = str(conversation_id)
         self._app_mode = app_mode
         self._message_id = str(message_id)
 
-    def _publish(self, event: AppQueueEvent, pub_from: PublishFrom) -> None:
+    def _publish(self, event: AppQueueEvent, pub_from: PublishFrom):
         """
         Publish event to queue
         :param event:

api/core/app/apps/workflow/app_config_manager.py

         return app_config
 
     @classmethod
-    def config_validate(cls, tenant_id: str, config: dict, only_structure_validate: bool = False) -> dict:
+    def config_validate(cls, tenant_id: str, config: dict, only_structure_validate: bool = False):
         """
         Validate for workflow app model config
 

api/core/app/apps/workflow/app_generator.py

         context: contextvars.Context,
         variable_loader: VariableLoader,
         workflow_thread_pool_id: Optional[str] = None,
-    ) -> None:
+    ):
         """
         Generate worker in a new thread.
         :param flask_app: Flask app

api/core/app/apps/workflow/app_queue_manager.py

 
 
 class WorkflowAppQueueManager(AppQueueManager):
-    def __init__(self, task_id: str, user_id: str, invoke_from: InvokeFrom, app_mode: str) -> None:
+    def __init__(self, task_id: str, user_id: str, invoke_from: InvokeFrom, app_mode: str):
         super().__init__(task_id, user_id, invoke_from)
 
         self._app_mode = app_mode
 
-    def _publish(self, event: AppQueueEvent, pub_from: PublishFrom) -> None:
+    def _publish(self, event: AppQueueEvent, pub_from: PublishFrom):
         """
         Publish event to queue
         :param event:

api/core/app/apps/workflow/app_runner.py

         workflow_thread_pool_id: Optional[str] = None,
         workflow: Workflow,
         system_user_id: str,
-    ) -> None:
+    ):
         super().__init__(
             queue_manager=queue_manager,
             variable_loader=variable_loader,
         self._workflow = workflow
         self._sys_user_id = system_user_id
 
-    def run(self) -> None:
+    def run(self):
         """
         Run application
         """

api/core/app/apps/workflow/generate_response_converter.py

     _blocking_response_type = WorkflowAppBlockingResponse
 
     @classmethod
-    def convert_blocking_full_response(cls, blocking_response: WorkflowAppBlockingResponse) -> dict:  # type: ignore[override]
+    def convert_blocking_full_response(cls, blocking_response: WorkflowAppBlockingResponse):  # type: ignore[override]
         """
         Convert blocking full response.
         :param blocking_response: blocking response
         return dict(blocking_response.to_dict())
 
     @classmethod
-    def convert_blocking_simple_response(cls, blocking_response: WorkflowAppBlockingResponse) -> dict:  # type: ignore[override]
+    def convert_blocking_simple_response(cls, blocking_response: WorkflowAppBlockingResponse):  # type: ignore[override]
         """
         Convert blocking simple response.
         :param blocking_response: blocking response

api/core/app/apps/workflow/generate_task_pipeline.py

         workflow_execution_repository: WorkflowExecutionRepository,
         workflow_node_execution_repository: WorkflowNodeExecutionRepository,
         draft_var_saver_factory: DraftVariableSaverFactory,
-    ) -> None:
+    ):
         self._base_task_pipeline = BasedGenerateTaskPipeline(
             application_generate_entity=application_generate_entity,
             queue_manager=queue_manager,
                 session.rollback()
                 raise
 
-    def _ensure_workflow_initialized(self) -> None:
+    def _ensure_workflow_initialized(self):
         """Fluent validation for workflow state."""
         if not self._workflow_run_id:
             raise ValueError("workflow run not initialized.")
         if tts_publisher:
             tts_publisher.publish(None)
 
-    def _save_workflow_app_log(self, *, session: Session, workflow_execution: WorkflowExecution) -> None:
+    def _save_workflow_app_log(self, *, session: Session, workflow_execution: WorkflowExecution):
         invoke_from = self._application_generate_entity.invoke_from
         if invoke_from == InvokeFrom.SERVICE_API:
             created_from = WorkflowAppLogCreatedFrom.SERVICE_API

api/core/app/apps/workflow_app_runner.py

         queue_manager: AppQueueManager,
         variable_loader: VariableLoader = DUMMY_VARIABLE_LOADER,
         app_id: str,
-    ) -> None:
+    ):
         self._queue_manager = queue_manager
         self._variable_loader = variable_loader
         self._app_id = app_id
 
         return graph, variable_pool
 
-    def _handle_event(self, workflow_entry: WorkflowEntry, event: GraphEngineEvent) -> None:
+    def _handle_event(self, workflow_entry: WorkflowEntry, event: GraphEngineEvent):
         """
         Handle event
         :param workflow_entry: workflow entry
                 )
             )
 
-    def _publish_event(self, event: AppQueueEvent) -> None:
+    def _publish_event(self, event: AppQueueEvent):
         self._queue_manager.publish(event, PublishFrom.APPLICATION_MANAGER)

api/core/app/task_pipeline/based_generate_task_pipeline.py

         application_generate_entity: AppGenerateEntity,
         queue_manager: AppQueueManager,
         stream: bool,
-    ) -> None:
+    ):
         self._application_generate_entity = application_generate_entity
         self.queue_manager = queue_manager
         self._start_at = time.perf_counter()

api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py

         conversation: Conversation,
         message: Message,
         stream: bool,
-    ) -> None:
+    ):
         super().__init__(
             application_generate_entity=application_generate_entity,
             queue_manager=queue_manager,
         if self._conversation_name_generate_thread:
             self._conversation_name_generate_thread.join()
 
-    def _save_message(self, *, session: Session, trace_manager: Optional[TraceQueueManager] = None) -> None:
+    def _save_message(self, *, session: Session, trace_manager: Optional[TraceQueueManager] = None):
         """
         Save message.
         :return:
             application_generate_entity=self._application_generate_entity,
         )
 
-    def _handle_stop(self, event: QueueStopEvent) -> None:
+    def _handle_stop(self, event: QueueStopEvent):
         """
         Handle stop.
         :return:

api/core/app/task_pipeline/message_cycle_manager.py

             AdvancedChatAppGenerateEntity,
         ],
         task_state: Union[EasyUITaskState, WorkflowTaskState],
-    ) -> None:
+    ):
         self._application_generate_entity = application_generate_entity
         self._task_state = task_state
 
 
         return None
 
-    def handle_retriever_resources(self, event: QueueRetrieverResourcesEvent) -> None:
+    def handle_retriever_resources(self, event: QueueRetrieverResourcesEvent):
         """
         Handle retriever resources.
         :param event: event

api/core/callback_handler/agent_tool_callback_handler.py

     return f"\u001b[{color_str}m\033[1;3m{text}\u001b[0m"
 
 
-def print_text(text: str, color: Optional[str] = None, end: str = "", file: Optional[TextIO] = None) -> None:
+def print_text(text: str, color: Optional[str] = None, end: str = "", file: Optional[TextIO] = None):
     """Print text with highlighting and no end characters."""
     text_to_print = get_colored_text(text, color) if color else text
     print(text_to_print, end=end, file=file)
     color: Optional[str] = ""
     current_loop: int = 1
 
-    def __init__(self, color: Optional[str] = None) -> None:
+    def __init__(self, color: Optional[str] = None):
         super().__init__()
         """Initialize callback handler."""
         # use a specific color is not specified
         self,
         tool_name: str,
         tool_inputs: Mapping[str, Any],
-    ) -> None:
+    ):
         """Do nothing."""
         if dify_config.DEBUG:
             print_text("\n[on_tool_start] ToolCall:" + tool_name + "\n" + str(tool_inputs) + "\n", color=self.color)
         message_id: Optional[str] = None,
         timer: Optional[Any] = None,
         trace_manager: Optional[TraceQueueManager] = None,
-    ) -> None:
+    ):
         """If not the final action, print out observation."""
         if dify_config.DEBUG:
             print_text("\n[on_tool_end]\n", color=self.color)
                 )
             )
 
-    def on_tool_error(self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any) -> None:
+    def on_tool_error(self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any):
         """Do nothing."""
         if dify_config.DEBUG:
             print_text("\n[on_tool_error] Error: " + str(error) + "\n", color="red")
 
-    def on_agent_start(self, thought: str) -> None:
+    def on_agent_start(self, thought: str):
         """Run on agent start."""
         if dify_config.DEBUG:
             if thought:
             else:
                 print_text("\n[on_agent_start] \nCurrent Loop: " + str(self.current_loop) + "\n", color=self.color)
 
-    def on_agent_finish(self, color: Optional[str] = None, **kwargs: Any) -> None:
+    def on_agent_finish(self, color: Optional[str] = None, **kwargs: Any):
         """Run on agent end."""
         if dify_config.DEBUG:
             print_text("\n[on_agent_finish]\n Loop: " + str(self.current_loop) + "\n", color=self.color)

api/core/callback_handler/index_tool_callback_handler.py

 
     def __init__(
         self, queue_manager: AppQueueManager, app_id: str, message_id: str, user_id: str, invoke_from: InvokeFrom
-    ) -> None:
+    ):
         self._queue_manager = queue_manager
         self._app_id = app_id
         self._message_id = message_id
         self._user_id = user_id
         self._invoke_from = invoke_from
 
-    def on_query(self, query: str, dataset_id: str) -> None:
+    def on_query(self, query: str, dataset_id: str):
         """
         Handle query.
         """
         db.session.add(dataset_query)
         db.session.commit()
 
-    def on_tool_end(self, documents: list[Document]) -> None:
+    def on_tool_end(self, documents: list[Document]):
         """Handle tool end."""
         for document in documents:
             if document.metadata is not None:

api/core/entities/model_entities.py

     icon_large: Optional[I18nObject] = None
     supported_model_types: list[ModelType]
 
-    def __init__(self, provider_entity: ProviderEntity) -> None:
+    def __init__(self, provider_entity: ProviderEntity):
         """
         Init simple provider.
 
     load_balancing_enabled: bool = False
     has_invalid_load_balancing_configs: bool = False
 
-    def raise_for_status(self) -> None:
+    def raise_for_status(self):
         """
         Check model status and raise ValueError if not active.
 

api/core/entities/provider_configuration.py

             else [],
         )
 
-    def validate_provider_credentials(
-        self, credentials: dict, credential_id: str = "", session: Session | None = None
-    ) -> dict:
+    def validate_provider_credentials(self, credentials: dict, credential_id: str = "", session: Session | None = None):
         """
         Validate custom credentials.
         :param credentials: provider credentials
         :return:
         """
 
-        def _validate(s: Session) -> dict:
+        def _validate(s: Session):
             # Get provider credential secret variables
             provider_credential_secret_variables = self.extract_secret_variables(
                 self.provider.provider_credential_schema.credential_form_schemas
             logger.warning("Error generating next credential name: %s", str(e))
             return "API KEY 1"
 
-    def create_provider_credential(self, credentials: dict, credential_name: str | None) -> None:
+    def create_provider_credential(self, credentials: dict, credential_name: str | None):
         """
         Add custom provider credentials.
         :param credentials: provider credentials
         credentials: dict,
         credential_id: str,
         credential_name: str | None,
-    ) -> None:
+    ):
         """
         update a saved provider credential (by credential_id).
 
         credential_record: ProviderCredential | ProviderModelCredential,
         credential_source: str,
         session: Session,
-    ) -> None:
+    ):
         """
         Update load balancing configurations that reference the given credential_id.
 
 
         session.commit()
 
-    def delete_provider_credential(self, credential_id: str) -> None:
+    def delete_provider_credential(self, credential_id: str):
         """
         Delete a saved provider credential (by credential_id).
 
                 session.rollback()
                 raise
 
-    def switch_active_provider_credential(self, credential_id: str) -> None:
+    def switch_active_provider_credential(self, credential_id: str):
         """
         Switch active provider credential (copy the selected one into current active snapshot).
 
         credentials: dict,
         credential_id: str = "",
         session: Session | None = None,
-    ) -> dict:
+    ):
         """
         Validate custom model credentials.
 
         :return:
         """
 
-        def _validate(s: Session) -> dict:
+        def _validate(s: Session):
             # Get provider credential secret variables
             provider_credential_secret_variables = self.extract_secret_variables(
                 self.provider.model_credential_schema.credential_form_schemas
                 session.rollback()
                 raise
 
-    def delete_custom_model_credential(self, model_type: ModelType, model: str, credential_id: str) -> None:
+    def delete_custom_model_credential(self, model_type: ModelType, model: str, credential_id: str):
         """
         Delete a saved provider credential (by credential_id).
 
                 session.rollback()
                 raise
 
-    def add_model_credential_to_model(self, model_type: ModelType, model: str, credential_id: str) -> None:
+    def add_model_credential_to_model(self, model_type: ModelType, model: str, credential_id: str):
         """
         if model list exist this custom model, switch the custom model credential.
         if model list not exist this custom model, use the credential to add a new custom model record.
             session.add(provider_model_record)
             session.commit()
 
-    def switch_custom_model_credential(self, model_type: ModelType, model: str, credential_id: str) -> None:
+    def switch_custom_model_credential(self, model_type: ModelType, model: str, credential_id: str):
         """
         switch the custom model credential.
 
             session.add(provider_model_record)
             session.commit()
 
-    def delete_custom_model(self, model_type: ModelType, model: str) -> None:
+    def delete_custom_model(self, model_type: ModelType, model: str):
         """
         Delete custom model.
         :param model_type: model type
             provider=self.provider.provider, model_type=model_type, model=model, credentials=credentials
         )
 
-    def switch_preferred_provider_type(self, provider_type: ProviderType, session: Session | None = None) -> None:
+    def switch_preferred_provider_type(self, provider_type: ProviderType, session: Session | None = None):
         """
         Switch preferred provider type.
         :param provider_type:
         if provider_type == ProviderType.SYSTEM and not self.system_configuration.enabled:
             return
 
-        def _switch(s: Session) -> None:
+        def _switch(s: Session):
             # get preferred provider
             model_provider_id = ModelProviderID(self.provider.provider)
             provider_names = [self.provider.provider]
 
         return secret_input_form_variables
 
-    def obfuscated_credentials(self, credentials: dict, credential_form_schemas: list[CredentialFormSchema]) -> dict:
+    def obfuscated_credentials(self, credentials: dict, credential_form_schemas: list[CredentialFormSchema]):
         """
         Obfuscated credentials.
 

api/core/errors/error.py

 
     description: Optional[str] = None
 
-    def __init__(self, description: Optional[str] = None) -> None:
+    def __init__(self, description: Optional[str] = None):
         self.description = description
 
 

api/core/extension/api_based_extension_requestor.py

     timeout: tuple[int, int] = (5, 60)
     """timeout for request connect and read"""
 
-    def __init__(self, api_endpoint: str, api_key: str) -> None:
+    def __init__(self, api_endpoint: str, api_key: str):
         self.api_endpoint = api_endpoint
         self.api_key = api_key
 
-    def request(self, point: APIBasedExtensionPoint, params: dict) -> dict:
+    def request(self, point: APIBasedExtensionPoint, params: dict):
         """
         Request the api.
 

api/core/extension/extensible.py

     tenant_id: str
     config: Optional[dict] = None
 
-    def __init__(self, tenant_id: str, config: Optional[dict] = None) -> None:
+    def __init__(self, tenant_id: str, config: Optional[dict] = None):
         self.tenant_id = tenant_id
         self.config = config
 

api/core/external_data_tool/api/api.py

     """the unique name of external data tool"""
 
     @classmethod
-    def validate_config(cls, tenant_id: str, config: dict) -> None:
+    def validate_config(cls, tenant_id: str, config: dict):
         """
         Validate the incoming form config data.
 

api/core/external_data_tool/base.py

     variable: str
     """the tool variable name of app tool"""
 
-    def __init__(self, tenant_id: str, app_id: str, variable: str, config: Optional[dict] = None) -> None:
+    def __init__(self, tenant_id: str, app_id: str, variable: str, config: Optional[dict] = None):
         super().__init__(tenant_id, config)
         self.app_id = app_id
         self.variable = variable
 
     @classmethod
     @abstractmethod
-    def validate_config(cls, tenant_id: str, config: dict) -> None:
+    def validate_config(cls, tenant_id: str, config: dict):
         """
         Validate the incoming form config data.
 

api/core/external_data_tool/factory.py

 
 
 class ExternalDataToolFactory:
-    def __init__(self, name: str, tenant_id: str, app_id: str, variable: str, config: dict) -> None:
+    def __init__(self, name: str, tenant_id: str, app_id: str, variable: str, config: dict):
         extension_class = code_based_extension.extension_class(ExtensionModule.EXTERNAL_DATA_TOOL, name)
         self.__extension_instance = extension_class(
             tenant_id=tenant_id, app_id=app_id, variable=variable, config=config
         )
 
     @classmethod
-    def validate_config(cls, name: str, tenant_id: str, config: dict) -> None:
+    def validate_config(cls, name: str, tenant_id: str, config: dict):
         """
         Validate the incoming form config data.
 

api/core/file/tool_file_parser.py

 _tool_file_manager_factory: Callable[[], "ToolFileManager"] | None = None
 
 
-def set_tool_file_manager_factory(factory: Callable[[], "ToolFileManager"]) -> None:
+def set_tool_file_manager_factory(factory: Callable[[], "ToolFileManager"]):
     global _tool_file_manager_factory
     _tool_file_manager_factory = factory

api/core/helper/code_executor/code_node_provider.py

         pass
 
     @classmethod
-    def get_default_config(cls) -> dict:
+    def get_default_config(cls):
         return {
             "type": "code",
             "config": {

api/core/helper/code_executor/jinja2/jinja2_transformer.py

 
 class Jinja2TemplateTransformer(TemplateTransformer):
     @classmethod
-    def transform_response(cls, response: str) -> dict:
+    def transform_response(cls, response: str):
         """
         Transform response to dict
         :param response: response

api/core/helper/code_executor/python3/python3_code_provider.py

     def get_default_code(cls) -> str:
         return dedent(
             """
-            def main(arg1: str, arg2: str) -> dict:
+            def main(arg1: str, arg2: str):
                 return {
                     "result": arg1 + arg2,
                 }

api/core/helper/model_provider_cache.py

         else:
             return None
 
-    def set(self, credentials: dict) -> None:
+    def set(self, credentials: dict):
         """
         Cache model provider credentials.
 
         """
         redis_client.setex(self.cache_key, 86400, json.dumps(credentials))
 
-    def delete(self) -> None:
+    def delete(self):
         """
         Delete cached model provider credentials.
 

api/core/helper/provider_cache.py

                 return None
         return None
 
-    def set(self, config: dict[str, Any]) -> None:
+    def set(self, config: dict[str, Any]):
         """Cache provider credentials"""
         redis_client.setex(self.cache_key, 86400, json.dumps(config))
 
-    def delete(self) -> None:
+    def delete(self):
         """Delete cached provider credentials"""
         redis_client.delete(self.cache_key)
 
         """Get cached provider credentials"""
         return None
 
-    def set(self, config: dict[str, Any]) -> None:
+    def set(self, config: dict[str, Any]):
         """Cache provider credentials"""
         pass
 
-    def delete(self) -> None:
+    def delete(self):
         """Delete cached provider credentials"""
         pass

api/core/helper/tool_parameter_cache.py

         else:
             return None
 
-    def set(self, parameters: dict) -> None:
+    def set(self, parameters: dict):
         """Cache model provider credentials."""
         redis_client.setex(self.cache_key, 86400, json.dumps(parameters))
 
-    def delete(self) -> None:
+    def delete(self):
         """
         Delete cached model provider credentials.
 

api/core/helper/trace_id_helper.py

     return None
 
 
-def extract_external_trace_id_from_args(args: Mapping[str, Any]) -> dict:
+def extract_external_trace_id_from_args(args: Mapping[str, Any]):
     """
     Extract 'external_trace_id' from args.
 

api/core/hosting_configuration.py

     provider_map: dict[str, HostingProvider]
     moderation_config: Optional[HostedModerationConfig] = None
 
-    def __init__(self) -> None:
+    def __init__(self):
         self.provider_map = {}
         self.moderation_config = None
 
-    def init_app(self, app: Flask) -> None:
+    def init_app(self, app: Flask):
         if dify_config.EDITION != "CLOUD":
             return
 

api/core/indexing_runner.py

         dataset: Dataset,
         dataset_document: DatasetDocument,
         documents: list[Document],
-    ) -> None:
+    ):
         """
         insert index and update document/segment status to completed
         """
     @staticmethod
     def _update_document_index_status(
         document_id: str, after_indexing_status: str, extra_update_params: Optional[dict] = None
-    ) -> None:
+    ):
         """
         Update the document indexing status.
         """
         db.session.commit()
 
     @staticmethod
-    def _update_segments_by_document(dataset_document_id: str, update_params: dict) -> None:
+    def _update_segments_by_document(dataset_document_id: str, update_params: dict):
         """
         Update the document segment by document id.
         """

api/core/llm_generator/llm_generator.py

         return questions
 
     @classmethod
-    def generate_rule_config(cls, tenant_id: str, instruction: str, model_config: dict, no_variable: bool) -> dict:
+    def generate_rule_config(cls, tenant_id: str, instruction: str, model_config: dict, no_variable: bool):
         output_parser = RuleConfigGeneratorOutputParser()
 
         error = ""
         return rule_config
 
     @classmethod
-    def generate_code(
-        cls, tenant_id: str, instruction: str, model_config: dict, code_language: str = "javascript"
-    ) -> dict:
+    def generate_code(cls, tenant_id: str, instruction: str, model_config: dict, code_language: str = "javascript"):
         if code_language == "python":
             prompt_template = PromptTemplateParser(PYTHON_CODE_GENERATOR_PROMPT_TEMPLATE)
         else:
     @staticmethod
     def instruction_modify_legacy(
         tenant_id: str, flow_id: str, current: str, instruction: str, model_config: dict, ideal_output: str | None
-    ) -> dict:
+    ):
         last_run: Message | None = (
             db.session.query(Message).where(Message.app_id == flow_id).order_by(Message.created_at.desc()).first()
         )
         instruction: str,
         model_config: dict,
         ideal_output: str | None,
-    ) -> dict:
+    ):
         from services.workflow_service import WorkflowService
 
         app: App | None = db.session.query(App).where(App.id == flow_id).first()
                 return []
             parsed: Sequence[AgentLogEvent] = json.loads(raw_agent_log)
 
-            def dict_of_event(event: AgentLogEvent) -> dict:
+            def dict_of_event(event: AgentLogEvent):
                 return {
                     "status": event.status,
                     "error": event.error,
         instruction: str,
         node_type: str,
         ideal_output: str | None,
-    ) -> dict:
+    ):
         LAST_RUN = "{{#last_run#}}"
         CURRENT = "{{#current#}}"
         ERROR_MESSAGE = "{{#error_message#}}"

api/core/llm_generator/output_parser/rule_config_generator.py

-from typing import Any
-
 from core.llm_generator.output_parser.errors import OutputParserError
 from core.llm_generator.prompts import (
     RULE_CONFIG_PARAMETER_GENERATE_TEMPLATE,
             RULE_CONFIG_STATEMENT_GENERATE_TEMPLATE,
         )
 
-    def parse(self, text: str) -> Any:
+    def parse(self, text: str):
         try:
             expected_keys = ["prompt", "variables", "opening_statement"]
             parsed = parse_and_check_json_markdown(text, expected_keys)

api/core/llm_generator/output_parser/structured_output.py

     structured_output_schema: Mapping,
     model_parameters: dict,
     rules: list[ParameterRule],
-) -> dict:
+):
     """
     Handle structured output for models with native JSON schema support.
 
     return model_parameters
 
 
-def _set_response_format(model_parameters: dict, rules: list) -> None:
+def _set_response_format(model_parameters: dict, rules: list):
     """
     Set the appropriate response format parameter based on model rules.
 
     return structured_output
 
 
-def _prepare_schema_for_model(provider: str, model_schema: AIModelEntity, schema: Mapping) -> dict:
+def _prepare_schema_for_model(provider: str, model_schema: AIModelEntity, schema: Mapping):
     """
     Prepare JSON schema based on model requirements.
 
         return {"schema": processed_schema, "name": "llm_response"}
 
 
-def remove_additional_properties(schema: dict) -> None:
+def remove_additional_properties(schema: dict):
     """
     Remove additionalProperties fields from JSON schema.
     Used for models like Gemini that don't support this property.
                     remove_additional_properties(item)
 
 
-def convert_boolean_to_string(schema: dict) -> None:
+def convert_boolean_to_string(schema: dict):
     """
     Convert boolean type specifications to string in JSON schema.
 

api/core/llm_generator/output_parser/suggested_questions_after_answer.py

 import json
 import re
-from typing import Any
 
 from core.llm_generator.prompts import SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT
 
     def get_format_instructions(self) -> str:
         return SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT
 
-    def parse(self, text: str) -> Any:
+    def parse(self, text: str):
         action_match = re.search(r"\[.*?\]", text.strip(), re.DOTALL)
         if action_match is not None:
             json_obj = json.loads(action_match.group(0).strip())

api/core/mcp/auth/auth_provider.py

             return None
         return OAuthClientInformation.model_validate(client_information)
 
-    def save_client_information(self, client_information: OAuthClientInformationFull) -> None:
+    def save_client_information(self, client_information: OAuthClientInformationFull):
         """Saves client information after dynamic registration."""
         MCPToolManageService.update_mcp_provider_credentials(
             self.mcp_provider,
             refresh_token=credentials.get("refresh_token", ""),
         )
 
-    def save_tokens(self, tokens: OAuthTokens) -> None:
+    def save_tokens(self, tokens: OAuthTokens):
         """Stores new OAuth tokens for the current session."""
         # update mcp provider credentials
         token_dict = tokens.model_dump()
         MCPToolManageService.update_mcp_provider_credentials(self.mcp_provider, token_dict, authed=True)
 
-    def save_code_verifier(self, code_verifier: str) -> None:
+    def save_code_verifier(self, code_verifier: str):
         """Saves a PKCE code verifier for the current session."""
         MCPToolManageService.update_mcp_provider_credentials(self.mcp_provider, {"code_verifier": code_verifier})
 

api/core/mcp/client/sse_client.py

         headers: dict[str, Any] | None = None,
         timeout: float = 5.0,
         sse_read_timeout: float = 5 * 60,
-    ) -> None:
+    ):
         """Initialize the SSE transport.
 
         Args:
 
         return url_parsed.netloc == endpoint_parsed.netloc and url_parsed.scheme == endpoint_parsed.scheme
 
-    def _handle_endpoint_event(self, sse_data: str, status_queue: StatusQueue) -> None:
+    def _handle_endpoint_event(self, sse_data: str, status_queue: StatusQueue):
         """Handle an 'endpoint' SSE event.
 
         Args:
 
         status_queue.put(_StatusReady(endpoint_url))
 
-    def _handle_message_event(self, sse_data: str, read_queue: ReadQueue) -> None:
+    def _handle_message_event(self, sse_data: str, read_queue: ReadQueue):
         """Handle a 'message' SSE event.
 
         Args:
             logger.exception("Error parsing server message")
             read_queue.put(exc)
 
-    def _handle_sse_event(self, sse: ServerSentEvent, read_queue: ReadQueue, status_queue: StatusQueue) -> None:
+    def _handle_sse_event(self, sse: ServerSentEvent, read_queue: ReadQueue, status_queue: StatusQueue):
         """Handle a single SSE event.
 
         Args:
             case _:
                 logger.warning("Unknown SSE event: %s", sse.event)
 
-    def sse_reader(self, event_source: EventSource, read_queue: ReadQueue, status_queue: StatusQueue) -> None:
+    def sse_reader(self, event_source: EventSource, read_queue: ReadQueue, status_queue: StatusQueue):
         """Read and process SSE events.
 
         Args:
         finally:
             read_queue.put(None)
 
-    def _send_message(self, client: httpx.Client, endpoint_url: str, message: SessionMessage) -> None:
+    def _send_message(self, client: httpx.Client, endpoint_url: str, message: SessionMessage):
         """Send a single message to the server.
 
         Args:
         response.raise_for_status()
         logger.debug("Client message sent successfully: %s", response.status_code)
 
-    def post_writer(self, client: httpx.Client, endpoint_url: str, write_queue: WriteQueue) -> None:
+    def post_writer(self, client: httpx.Client, endpoint_url: str, write_queue: WriteQueue):
         """Handle writing messages to the server.
 
         Args:
                 write_queue.put(None)
 
 
-def send_message(http_client: httpx.Client, endpoint_url: str, session_message: SessionMessage) -> None:
+def send_message(http_client: httpx.Client, endpoint_url: str, session_message: SessionMessage):
     """
     Send a message to the server using the provided HTTP client.
 

api/core/mcp/client/streamable_client.py

         headers: dict[str, Any] | None = None,
         timeout: float | timedelta = 30,
         sse_read_timeout: float | timedelta = 60 * 5,
-    ) -> None:
+    ):
         """Initialize the StreamableHTTP transport.
 
         Args:
     def _maybe_extract_session_id_from_response(
         self,
         response: httpx.Response,
-    ) -> None:
+    ):
         """Extract and store session ID from response headers."""
         new_session_id = response.headers.get(MCP_SESSION_ID)
         if new_session_id:
         self,
         client: httpx.Client,
         server_to_client_queue: ServerToClientQueue,
-    ) -> None:
+    ):
         """Handle GET stream for server-initiated messages."""
         try:
             if not self.session_id:
         except Exception as exc:
             logger.debug("GET stream error (non-fatal): %s", exc)
 
-    def _handle_resumption_request(self, ctx: RequestContext) -> None:
+    def _handle_resumption_request(self, ctx: RequestContext):
         """Handle a resumption request using GET with SSE."""
         headers = self._update_headers_with_session(ctx.headers)
         if ctx.metadata and ctx.metadata.resumption_token:
                 if is_complete:
                     break
 
-    def _handle_post_request(self, ctx: RequestContext) -> None:
+    def _handle_post_request(self, ctx: RequestContext):
         """Handle a POST request with response processing."""
         headers = self._update_headers_with_session(ctx.headers)
         message = ctx.session_message.message
         self,
         response: httpx.Response,
         server_to_client_queue: ServerToClientQueue,
-    ) -> None:
+    ):
         """Handle JSON response from the server."""
         try:
             content = response.read()
         except Exception as exc:
             server_to_client_queue.put(exc)
 
-    def _handle_sse_response(self, response: httpx.Response, ctx: RequestContext) -> None:
+    def _handle_sse_response(self, response: httpx.Response, ctx: RequestContext):
         """Handle SSE response from the server."""
         try:
             event_source = EventSource(response)
         self,
         content_type: str,
         server_to_client_queue: ServerToClientQueue,
-    ) -> None:
+    ):
         """Handle unexpected content type in response."""
         error_msg = f"Unexpected content type: {content_type}"
         logger.error(error_msg)
         self,
         server_to_client_queue: ServerToClientQueue,
         request_id: RequestId,
-    ) -> None:
+    ):
         """Send a session terminated error response."""
         jsonrpc_error = JSONRPCError(
             jsonrpc="2.0",
         client_to_server_queue: ClientToServerQueue,
         server_to_client_queue: ServerToClientQueue,
         start_get_stream: Callable[[], None],
-    ) -> None:
+    ):
         """Handle writing requests to the server.
 
         This method processes messages from the client_to_server_queue and sends them to the server.
             except Exception as exc:
                 server_to_client_queue.put(exc)
 
-    def terminate_session(self, client: httpx.Client) -> None:
+    def terminate_session(self, client: httpx.Client):
         """Terminate the session by sending a DELETE request."""
         if not self.session_id:
             return
                 timeout=httpx.Timeout(transport.timeout, read=transport.sse_read_timeout),
             ) as client:
                 # Define callbacks that need access to thread pool
-                def start_get_stream() -> None:
+                def start_get_stream():
                     """Start a worker thread to handle server-initiated messages."""
                     executor.submit(transport.handle_get_stream, client, server_to_client_queue)
 

api/core/mcp/session/base_session.py

             ReceiveNotificationT
         ]""",
         on_complete: Callable[["RequestResponder[ReceiveRequestT, SendResultT]"], Any],
-    ) -> None:
+    ):
         self.request_id = request_id
         self.request_meta = request_meta
         self.request = request
         exc_type: type[BaseException] | None,
         exc_val: BaseException | None,
         exc_tb: TracebackType | None,
-    ) -> None:
+    ):
         """Exit the context manager, performing cleanup and notifying completion."""
         try:
             if self._completed:
         finally:
             self._entered = False
 
-    def respond(self, response: SendResultT | ErrorData) -> None:
+    def respond(self, response: SendResultT | ErrorData):
         """Send a response for this request.
 
         Must be called within a context manager block.
 
         self._session._send_response(request_id=self.request_id, response=response)
 
-    def cancel(self) -> None:
+    def cancel(self):
         """Cancel this request and mark it as completed."""
         if not self._entered:
             raise RuntimeError("RequestResponder must be used as a context manager")
         receive_notification_type: type[ReceiveNotificationT],
         # If none, reading will never time out
         read_timeout_seconds: timedelta | None = None,
-    ) -> None:
+    ):
         self._read_stream = read_stream
         self._write_stream = write_stream
         self._response_streams = {}
         self._receiver_future = self._executor.submit(self._receive_loop)
         return self
 
-    def check_receiver_status(self) -> None:
+    def check_receiver_status(self):
         """`check_receiver_status` ensures that any exceptions raised during the
         execution of `_receive_loop` are retrieved and propagated."""
         if self._receiver_future and self._receiver_future.done():
 
     def __exit__(
         self, exc_type: type[BaseException] | None, exc_val: BaseException | None, exc_tb: TracebackType | None
-    ) -> None:
+    ):
         self._read_stream.put(None)
         self._write_stream.put(None)
 
         self,
         notification: SendNotificationT,
         related_request_id: RequestId | None = None,
-    ) -> None:
+    ):
         """
         Emits a notification, which is a one-way message that does not expect
         a response.
         )
         self._write_stream.put(session_message)
 
-    def _send_response(self, request_id: RequestId, response: SendResultT | ErrorData) -> None:
+    def _send_response(self, request_id: RequestId, response: SendResultT | ErrorData):
         if isinstance(response, ErrorData):
             jsonrpc_error = JSONRPCError(jsonrpc="2.0", id=request_id, error=response)
             session_message = SessionMessage(message=JSONRPCMessage(jsonrpc_error))
             session_message = SessionMessage(message=JSONRPCMessage(jsonrpc_response))
             self._write_stream.put(session_message)
 
-    def _receive_loop(self) -> None:
+    def _receive_loop(self):
         """
         Main message processing loop.
         In a real synchronous implementation, this would likely run in a separate thread.
                 logger.exception("Error in message processing loop")
                 raise
 
-    def _received_request(self, responder: RequestResponder[ReceiveRequestT, SendResultT]) -> None:
+    def _received_request(self, responder: RequestResponder[ReceiveRequestT, SendResultT]):
         """
         Can be overridden by subclasses to handle a request without needing to
         listen on the message stream.
         forwarded on to the message stream.
         """
 
-    def _received_notification(self, notification: ReceiveNotificationT) -> None:
+    def _received_notification(self, notification: ReceiveNotificationT):
         """
         Can be overridden by subclasses to handle a notification without needing
         to listen on the message stream.
         """
 
-    def send_progress_notification(
-        self, progress_token: str | int, progress: float, total: float | None = None
-    ) -> None:
+    def send_progress_notification(self, progress_token: str | int, progress: float, total: float | None = None):
         """
         Sends a progress notification for a request that is currently being
         processed.
     def _handle_incoming(
         self,
         req: RequestResponder[ReceiveRequestT, SendResultT] | ReceiveNotificationT | Exception,
-    ) -> None:
+    ):
         """A generic handler for incoming messages. Overwritten by subclasses."""

api/core/mcp/session/client_session.py

     def __call__(
         self,
         params: types.LoggingMessageNotificationParams,
-    ) -> None: ...
+    ): ...
 
 
 class MessageHandlerFnT(Protocol):
     def __call__(
         self,
         message: RequestResponder[types.ServerRequest, types.ClientResult] | types.ServerNotification | Exception,
-    ) -> None: ...
+    ): ...
 
 
 def _default_message_handler(
     message: RequestResponder[types.ServerRequest, types.ClientResult] | types.ServerNotification | Exception,
-) -> None:
+):
     if isinstance(message, Exception):
         raise ValueError(str(message))
     elif isinstance(message, (types.ServerNotification | RequestResponder)):
 
 def _default_logging_callback(
     params: types.LoggingMessageNotificationParams,
-) -> None:
+):
     pass
 
 
         logging_callback: LoggingFnT | None = None,
         message_handler: MessageHandlerFnT | None = None,
         client_info: types.Implementation | None = None,
-    ) -> None:
+    ):
         super().__init__(
             read_stream,
             write_stream,
             types.EmptyResult,
         )
 
-    def send_progress_notification(
-        self, progress_token: str | int, progress: float, total: float | None = None
-    ) -> None:
+    def send_progress_notification(self, progress_token: str | int, progress: float, total: float | None = None):
         """Send a progress notification."""
         self.send_notification(
             types.ClientNotification(
             types.ListToolsResult,
         )
 
-    def send_roots_list_changed(self) -> None:
+    def send_roots_list_changed(self):
         """Send a roots/list_changed notification."""
         self.send_notification(
             types.ClientNotification(
             )
         )
 
-    def _received_request(self, responder: RequestResponder[types.ServerRequest, types.ClientResult]) -> None:
+    def _received_request(self, responder: RequestResponder[types.ServerRequest, types.ClientResult]):
         ctx = RequestContext[ClientSession, Any](
             request_id=responder.request_id,
             meta=responder.request_meta,
     def _handle_incoming(
         self,
         req: RequestResponder[types.ServerRequest, types.ClientResult] | types.ServerNotification | Exception,
-    ) -> None:
+    ):
         """Handle incoming messages by forwarding to the message handler."""
         self._message_handler(req)
 
-    def _received_notification(self, notification: types.ServerNotification) -> None:
+    def _received_notification(self, notification: types.ServerNotification):
         """Handle notifications from the server."""
         # Process specific notification types
         match notification.root:

api/core/memory/token_buffer_memory.py

         self,
         conversation: Conversation,
         model_instance: ModelInstance,
-    ) -> None:
+    ):
         self.conversation = conversation
         self.model_instance = model_instance
 

api/core/model_manager.py

     Model instance class
     """
 
-    def __init__(self, provider_model_bundle: ProviderModelBundle, model: str) -> None:
+    def __init__(self, provider_model_bundle: ProviderModelBundle, model: str):
         self.provider_model_bundle = provider_model_bundle
         self.model = model
         self.provider = provider_model_bundle.configuration.provider.provider
         )
 
     @staticmethod
-    def _fetch_credentials_from_bundle(provider_model_bundle: ProviderModelBundle, model: str) -> dict:
+    def _fetch_credentials_from_bundle(provider_model_bundle: ProviderModelBundle, model: str):
         """
         Fetch credentials from provider model bundle
         :param provider_model_bundle: provider model bundle
             ),
         )
 
-    def _round_robin_invoke(self, function: Callable[..., Any], *args, **kwargs) -> Any:
+    def _round_robin_invoke(self, function: Callable[..., Any], *args, **kwargs):
         """
         Round-robin invoke
         :param function: function to invoke
             except Exception as e:
                 raise e
 
-    def get_tts_voices(self, language: Optional[str] = None) -> list:
+    def get_tts_voices(self, language: Optional[str] = None):
         """
         Invoke large language tts model voices
 
 
 
 class ModelManager:
-    def __init__(self) -> None:
+    def __init__(self):
         self._provider_manager = ProviderManager()
 
     def get_model_instance(self, tenant_id: str, provider: str, model_type: ModelType, model: str) -> ModelInstance:
         model: str,
         load_balancing_configs: list[ModelLoadBalancingConfiguration],
         managed_credentials: Optional[dict] = None,
-    ) -> None:
+    ):
         """
         Load balancing model manager
         :param tenant_id: tenant_id
 
             return config
 
-    def cooldown(self, config: ModelLoadBalancingConfiguration, expire: int = 60) -> None:
+    def cooldown(self, config: ModelLoadBalancingConfiguration, expire: int = 60):
         """
         Cooldown model load balancing config
         :param config: model load balancing config

api/core/model_runtime/callbacks/base_callback.py

         stop: Optional[Sequence[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-    ) -> None:
+    ):
         """
         Before invoke callback
 
         stop: Optional[Sequence[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-    ) -> None:
+    ):
         """
         After invoke callback
 
         stop: Optional[Sequence[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-    ) -> None:
+    ):
         """
         Invoke error callback
 
         """
         raise NotImplementedError()
 
-    def print_text(self, text: str, color: Optional[str] = None, end: str = "") -> None:
+    def print_text(self, text: str, color: Optional[str] = None, end: str = ""):
         """Print text with highlighting and no end characters."""
         text_to_print = self._get_colored_text(text, color) if color else text
         print(text_to_print, end=end)

api/core/model_runtime/callbacks/logging_callback.py

         stop: Optional[Sequence[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-    ) -> None:
+    ):
         """
         Before invoke callback
 
         stop: Optional[Sequence[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-    ) -> None:
+    ):
         """
         After invoke callback
 
         stop: Optional[Sequence[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-    ) -> None:
+    ):
         """
         Invoke error callback
 

api/core/model_runtime/errors/invoke.py

 
     description: Optional[str] = None
 
-    def __init__(self, description: Optional[str] = None) -> None:
+    def __init__(self, description: Optional[str] = None):
         self.description = description
 
     def __str__(self):

api/core/model_runtime/model_providers/__base/ai_model.py

         """
         return None
 
-    def _get_default_parameter_rule_variable_map(self, name: DefaultParameterName) -> dict:
+    def _get_default_parameter_rule_variable_map(self, name: DefaultParameterName):
         """
         Get default parameter rule for given name
 

api/core/model_runtime/model_providers/__base/large_language_model.py

         stream: bool = True,
         user: Optional[str] = None,
         callbacks: Optional[list[Callback]] = None,
-    ) -> None:
+    ):
         """
         Trigger before invoke callbacks
 
         stream: bool = True,
         user: Optional[str] = None,
         callbacks: Optional[list[Callback]] = None,
-    ) -> None:
+    ):
         """
         Trigger new chunk callbacks
 
         stream: bool = True,
         user: Optional[str] = None,
         callbacks: Optional[list[Callback]] = None,
-    ) -> None:
+    ):
         """
         Trigger after invoke callbacks
 
         stream: bool = True,
         user: Optional[str] = None,
         callbacks: Optional[list[Callback]] = None,
-    ) -> None:
+    ):
         """
         Trigger invoke error callbacks
 

api/core/model_runtime/model_providers/__base/tokenizers/gpt2_tokenizer.py

         return GPT2Tokenizer._get_num_tokens_by_gpt2(text)
 
     @staticmethod
-    def get_encoder() -> Any:
+    def get_encoder():
         global _tokenizer, _lock
         if _tokenizer is not None:
             return _tokenizer

api/core/model_runtime/model_providers/__base/tts_model.py

         except Exception as e:
             raise self._transform_invoke_error(e)
 
-    def get_tts_model_voices(self, model: str, credentials: dict, language: Optional[str] = None) -> list[dict]:
+    def get_tts_model_voices(self, model: str, credentials: dict, language: Optional[str] = None):
         """
         Retrieves the list of voices supported by a given text-to-speech (TTS) model.
 

api/core/model_runtime/model_providers/model_provider_factory.py

 class ModelProviderFactory:
     provider_position_map: dict[str, int]
 
-    def __init__(self, tenant_id: str) -> None:
+    def __init__(self, tenant_id: str):
         self.provider_position_map = {}
 
         self.tenant_id = tenant_id
 
         return plugin_model_provider_entity
 
-    def provider_credentials_validate(self, *, provider: str, credentials: dict) -> dict:
+    def provider_credentials_validate(self, *, provider: str, credentials: dict):
         """
         Validate provider credentials
 
 
         return filtered_credentials
 
-    def model_credentials_validate(
-        self, *, provider: str, model_type: ModelType, model: str, credentials: dict
-    ) -> dict:
+    def model_credentials_validate(self, *, provider: str, model_type: ModelType, model: str, credentials: dict):
         """
         Validate model credentials
 

api/core/model_runtime/schema_validators/common_validator.py

 class CommonValidator:
     def _validate_and_filter_credential_form_schemas(
         self, credential_form_schemas: list[CredentialFormSchema], credentials: dict
-    ) -> dict:
+    ):
         need_validate_credential_form_schema_map = {}
         for credential_form_schema in credential_form_schemas:
             if not credential_form_schema.show_on:

api/core/model_runtime/schema_validators/model_credential_schema_validator.py

         self.model_type = model_type
         self.model_credential_schema = model_credential_schema
 
-    def validate_and_filter(self, credentials: dict) -> dict:
+    def validate_and_filter(self, credentials: dict):
         """
         Validate model credentials
 

api/core/model_runtime/schema_validators/provider_credential_schema_validator.py

     def __init__(self, provider_credential_schema: ProviderCredentialSchema):
         self.provider_credential_schema = provider_credential_schema
 
-    def validate_and_filter(self, credentials: dict) -> dict:
+    def validate_and_filter(self, credentials: dict):
         """
         Validate provider credentials
 

api/core/model_runtime/utils/encoders.py

 from pydantic_extra_types.color import Color
 
 
-def _model_dump(model: BaseModel, mode: Literal["json", "python"] = "json", **kwargs: Any) -> Any:
+def _model_dump(model: BaseModel, mode: Literal["json", "python"] = "json", **kwargs: Any):
     return model.model_dump(mode=mode, **kwargs)
 
 
     exclude_none: bool = False,
     custom_encoder: Optional[dict[Any, Callable[[Any], Any]]] = None,
     sqlalchemy_safe: bool = True,
-) -> Any:
+):
     custom_encoder = custom_encoder or {}
     if custom_encoder:
         if type(obj) in custom_encoder:

api/core/moderation/api/api.py

     name: str = "api"
 
     @classmethod
-    def validate_config(cls, tenant_id: str, config: dict) -> None:
+    def validate_config(cls, tenant_id: str, config: dict):
         """
         Validate the incoming form config data.
 
             flagged=flagged, action=ModerationAction.DIRECT_OUTPUT, preset_response=preset_response
         )
 
-    def _get_config_by_requestor(self, extension_point: APIBasedExtensionPoint, params: dict) -> dict:
+    def _get_config_by_requestor(self, extension_point: APIBasedExtensionPoint, params: dict):
         if self.config is None:
             raise ValueError("The config is not set.")
         extension = self._get_api_based_extension(self.tenant_id, self.config.get("api_based_extension_id", ""))

api/core/moderation/base.py

 
     module: ExtensionModule = ExtensionModule.MODERATION
 
-    def __init__(self, app_id: str, tenant_id: str, config: Optional[dict] = None) -> None:
+    def __init__(self, app_id: str, tenant_id: str, config: Optional[dict] = None):
         super().__init__(tenant_id, config)
         self.app_id = app_id
 
     @classmethod
     @abstractmethod
-    def validate_config(cls, tenant_id: str, config: dict) -> None:
+    def validate_config(cls, tenant_id: str, config: dict):
         """
         Validate the incoming form config data.
 
         raise NotImplementedError
 
     @classmethod
-    def _validate_inputs_and_outputs_config(cls, config: dict, is_preset_response_required: bool) -> None:
+    def _validate_inputs_and_outputs_config(cls, config: dict, is_preset_response_required: bool):
         # inputs_config
         inputs_config = config.get("inputs_config")
         if not isinstance(inputs_config, dict):

api/core/moderation/factory.py

 class ModerationFactory:
     __extension_instance: Moderation
 
-    def __init__(self, name: str, app_id: str, tenant_id: str, config: dict) -> None:
+    def __init__(self, name: str, app_id: str, tenant_id: str, config: dict):
         extension_class = code_based_extension.extension_class(ExtensionModule.MODERATION, name)
         self.__extension_instance = extension_class(app_id, tenant_id, config)
 
     @classmethod
-    def validate_config(cls, name: str, tenant_id: str, config: dict) -> None:
+    def validate_config(cls, name: str, tenant_id: str, config: dict):
         """
         Validate the incoming form config data.
 

api/core/moderation/keywords/keywords.py

     name: str = "keywords"
 
     @classmethod
-    def validate_config(cls, tenant_id: str, config: dict) -> None:
+    def validate_config(cls, tenant_id: str, config: dict):
         """
         Validate the incoming form config data.
 

api/core/moderation/openai_moderation/openai_moderation.py

     name: str = "openai_moderation"
 
     @classmethod
-    def validate_config(cls, tenant_id: str, config: dict) -> None:
+    def validate_config(cls, tenant_id: str, config: dict):
         """
         Validate the incoming form config data.
 

api/core/moderation/output_moderation.py

     def get_final_output(self) -> str:
         return self.final_output or ""
 
-    def append_new_token(self, token: str) -> None:
+    def append_new_token(self, token: str):
         self.buffer += token
 
         if not self.thread:

api/core/plugin/backwards_invocation/encrypt.py

 
 class PluginEncrypter:
     @classmethod
-    def invoke_encrypt(cls, tenant: Tenant, payload: RequestInvokeEncrypt) -> dict:
+    def invoke_encrypt(cls, tenant: Tenant, payload: RequestInvokeEncrypt):
         encrypter, cache = create_provider_encrypter(
             tenant_id=tenant.id,
             config=payload.config,

api/core/plugin/backwards_invocation/node.py

         model_config: ParameterExtractorModelConfig,
         instruction: str,
         query: str,
-    ) -> dict:
+    ):
         """
         Invoke parameter extractor node.
 
         classes: list[ClassConfig],
         instruction: str,
         query: str,
-    ) -> dict:
+    ):
         """
         Invoke question classifier node.
 

api/core/plugin/entities/plugin.py

 
     @model_validator(mode="before")
     @classmethod
-    def validate_category(cls, values: dict) -> dict:
+    def validate_category(cls, values: dict):
         # auto detect category
         if values.get("tool"):
             values["category"] = PluginCategory.Tool
     def __str__(self) -> str:
         return f"{self.organization}/{self.plugin_name}/{self.provider_name}"
 
-    def __init__(self, value: str, is_hardcoded: bool = False) -> None:
+    def __init__(self, value: str, is_hardcoded: bool = False):
         if not value:
             raise NotFound("plugin not found, please add plugin")
         # check if the value is a valid plugin id with format: $organization/$plugin_name/$provider_name
 
 
 class ModelProviderID(GenericProviderID):
-    def __init__(self, value: str, is_hardcoded: bool = False) -> None:
+    def __init__(self, value: str, is_hardcoded: bool = False):
         super().__init__(value, is_hardcoded)
         if self.organization == "langgenius" and self.provider_name == "google":
             self.plugin_name = "gemini"
 
 
 class ToolProviderID(GenericProviderID):
-    def __init__(self, value: str, is_hardcoded: bool = False) -> None:
+    def __init__(self, value: str, is_hardcoded: bool = False):
         super().__init__(value, is_hardcoded)
         if self.organization == "langgenius":
             if self.provider_name in ["jina", "siliconflow", "stepfun", "gitee_ai"]:

api/core/plugin/impl/agent.py

         Fetch agent providers for the given tenant.
         """
 
-        def transformer(json_response: dict[str, Any]) -> dict:
+        def transformer(json_response: dict[str, Any]):
             for provider in json_response.get("data", []):
                 declaration = provider.get("declaration", {}) or {}
                 provider_name = declaration.get("identity", {}).get("name")
         """
         agent_provider_id = GenericProviderID(provider)
 
-        def transformer(json_response: dict[str, Any]) -> dict:
+        def transformer(json_response: dict[str, Any]):
             # skip if error occurs
             if json_response.get("data") is None or json_response.get("data", {}).get("declaration") is None:
                 return json_response

api/core/plugin/impl/exc.py

 class PluginDaemonError(Exception):
     """Base class for all plugin daemon errors."""
 
-    def __init__(self, description: str) -> None:
+    def __init__(self, description: str):
         self.description = description
 
     def __str__(self) -> str:

api/core/plugin/impl/model.py

         model: str,
         credentials: dict,
         language: Optional[str] = None,
-    ) -> list[dict]:
+    ):
         """
         Get tts model voices
         """

api/core/plugin/impl/tool.py

         Fetch tool providers for the given tenant.
         """
 
-        def transformer(json_response: dict[str, Any]) -> dict:
+        def transformer(json_response: dict[str, Any]):
             for provider in json_response.get("data", []):
                 declaration = provider.get("declaration", {}) or {}
                 provider_name = declaration.get("identity", {}).get("name")
         """
         tool_provider_id = ToolProviderID(provider)
 
-        def transformer(json_response: dict[str, Any]) -> dict:
+        def transformer(json_response: dict[str, Any]):
             data = json_response.get("data")
             if data:
                 for tool in data.get("declaration", {}).get("tools", []):