fix: refactor all 'or []' and 'or {}' logic to make code more clear

api/core/agent/base_agent_runner.py

@@ -114,16 +114,9 @@ def __init__(
         # check if model supports stream tool call
         llm_model = cast(LargeLanguageModel, model_instance.model_type_instance)
         model_schema = llm_model.get_model_schema(model_instance.model, model_instance.credentials)
-        if model_schema and ModelFeature.STREAM_TOOL_CALL in (model_schema.features or []):
-            self.stream_tool_call = True
-        else:
-            self.stream_tool_call = False
-
-        # check if model supports vision
-        if model_schema and ModelFeature.VISION in (model_schema.features or []):
-            self.files = application_generate_entity.files
-        else:
-            self.files = []
+        features = model_schema.features if model_schema and model_schema.features else []
+        self.stream_tool_call = ModelFeature.STREAM_TOOL_CALL in features
+        self.files = application_generate_entity.files if ModelFeature.VISION in features else []
         self.query = None
         self._current_thoughts: list[PromptMessage] = []
 
@@ -250,7 +243,7 @@ def update_prompt_message_tool(self, tool: Tool, prompt_tool: PromptMessageTool)
         update prompt message tool
         """
         # try to get tool runtime parameters
-        tool_runtime_parameters = tool.get_runtime_parameters() or []
+        tool_runtime_parameters = tool.get_runtime_parameters()
 
         for parameter in tool_runtime_parameters:
             if parameter.form != ToolParameter.ToolParameterForm.LLM:

api/core/app/task_pipeline/workflow_cycle_manage.py

@@ -381,7 +381,7 @@ def _workflow_start_to_stream_response(
                 id=workflow_run.id,
                 workflow_id=workflow_run.workflow_id,
                 sequence_number=workflow_run.sequence_number,
-                inputs=workflow_run.inputs_dict or {},
+                inputs=workflow_run.inputs_dict,
                 created_at=int(workflow_run.created_at.timestamp()),
             ),
         )
@@ -428,7 +428,7 @@ def _workflow_finish_to_stream_response(
                 created_by=created_by,
                 created_at=int(workflow_run.created_at.timestamp()),
                 finished_at=int(workflow_run.finished_at.timestamp()),
-                files=self._fetch_files_from_node_outputs(workflow_run.outputs_dict or {}),
+                files=self._fetch_files_from_node_outputs(workflow_run.outputs_dict),
             ),
         )
 

api/core/model_runtime/model_providers/cohere/llm/llm.py

@@ -691,8 +691,8 @@ def get_customizable_model_schema(self, model: str, credentials: dict) -> AIMode
         base_model_schema = cast(AIModelEntity, base_model_schema)
 
         base_model_schema_features = base_model_schema.features or []
-        base_model_schema_model_properties = base_model_schema.model_properties or {}
-        base_model_schema_parameters_rules = base_model_schema.parameter_rules or []
+        base_model_schema_model_properties = base_model_schema.model_properties
+        base_model_schema_parameters_rules = base_model_schema.parameter_rules
 
         entity = AIModelEntity(
             model=model,

api/core/model_runtime/model_providers/openai/llm/llm.py

@@ -1178,8 +1178,8 @@ def get_customizable_model_schema(self, model: str, credentials: dict) -> AIMode
         base_model_schema = model_map[base_model]
 
         base_model_schema_features = base_model_schema.features or []
-        base_model_schema_model_properties = base_model_schema.model_properties or {}
-        base_model_schema_parameters_rules = base_model_schema.parameter_rules or []
+        base_model_schema_model_properties = base_model_schema.model_properties
+        base_model_schema_parameters_rules = base_model_schema.parameter_rules
 
         entity = AIModelEntity(
             model=model,

api/core/model_runtime/model_providers/openllm/llm/openllm_generate.py

@@ -37,13 +37,14 @@ def __init__(self, content: str, role: str = "user") -> None:
 class OpenLLMGenerate:
     def generate(
         self,
+        *,
         server_url: str,
         model_name: str,
         stream: bool,
         model_parameters: dict[str, Any],
-        stop: list[str],
+        stop: list[str] | None = None,
         prompt_messages: list[OpenLLMGenerateMessage],
-        user: str,
+        user: str | None = None,
     ) -> Union[Generator[OpenLLMGenerateMessage, None, None], OpenLLMGenerateMessage]:
         if not server_url:
             raise InvalidAuthenticationError("Invalid server URL")

api/core/tools/tool/tool.py

@@ -261,7 +261,7 @@ def get_all_runtime_parameters(self) -> list[ToolParameter]:
         """
         parameters = self.parameters or []
         parameters = parameters.copy()
-        user_parameters = self.get_runtime_parameters() or []
+        user_parameters = self.get_runtime_parameters()
         user_parameters = user_parameters.copy()
 
         # override parameters

api/core/tools/tool_engine.py

@@ -55,7 +55,7 @@ def agent_invoke(
             # check if this tool has only one parameter
             parameters = [
                 parameter
-                for parameter in tool.get_runtime_parameters() or []
+                for parameter in tool.get_runtime_parameters()
                 if parameter.form == ToolParameter.ToolParameterForm.LLM
             ]
             if parameters and len(parameters) == 1:

api/core/tools/utils/configuration.py

@@ -127,7 +127,7 @@ def _merge_parameters(self) -> list[ToolParameter]:
         # get tool parameters
         tool_parameters = self.tool_runtime.parameters or []
         # get tool runtime parameters
-        runtime_parameters = self.tool_runtime.get_runtime_parameters() or []
+        runtime_parameters = self.tool_runtime.get_runtime_parameters()
         # override parameters
         current_parameters = tool_parameters.copy()
         for runtime_parameter in runtime_parameters:

api/services/app_service.py

@@ -341,7 +341,7 @@ def get_app_meta(self, app_model: App) -> dict:
             if not app_model_config:
                 return meta
 
-            agent_config = app_model_config.agent_mode_dict or {}
+            agent_config = app_model_config.agent_mode_dict
 
             # get all tools
             tools = agent_config.get("tools", [])

api/services/tools/tools_transform_service.py

@@ -242,7 +242,7 @@ def tool_to_user_tool(
             # get tool parameters
             parameters = tool.parameters or []
             # get tool runtime parameters
-            runtime_parameters = tool.get_runtime_parameters() or []
+            runtime_parameters = tool.get_runtime_parameters()
             # override parameters
             current_parameters = parameters.copy()
             for runtime_parameter in runtime_parameters:

api/services/website_service.py

@@ -51,8 +51,8 @@ def crawl_url(cls, args: dict) -> dict:
                 excludes = options.get("excludes").split(",") if options.get("excludes") else []
                 params = {
                     "crawlerOptions": {
-                        "includes": includes or [],
-                        "excludes": excludes or [],
+                        "includes": includes,
+                        "excludes": excludes,
                         "generateImgAltText": True,
                         "limit": options.get("limit", 1),
                         "returnOnlyUrls": False,