refactor: replace bare dict with dict[str, Any] in core tools and runtime (#35111)

api/core/indexing_runner.py

@@ -735,7 +735,9 @@ class IndexingRunner:
 
     @staticmethod
     def _update_document_index_status(
-        document_id: str, after_indexing_status: IndexingStatus, extra_update_params: dict | None = None
+        document_id: str,
+        after_indexing_status: IndexingStatus,
+        extra_update_params: dict[Any, Any] | None = None,
     ):
         """
         Update the document indexing status.
@@ -762,7 +764,7 @@ class IndexingRunner:
         db.session.commit()
 
     @staticmethod
-    def _update_segments_by_document(dataset_document_id: str, update_params: dict):
+    def _update_segments_by_document(dataset_document_id: str, update_params: dict[Any, Any]):
         """
         Update the document segment by document id.
         """

api/core/llm_generator/output_parser/structured_output.py

@@ -200,7 +200,7 @@ def _handle_native_json_schema(
     provider: str,
     model_schema: AIModelEntity,
     structured_output_schema: Mapping,
-    model_parameters: dict,
+    model_parameters: dict[str, Any],
     rules: list[ParameterRule],
 ):
     """
@@ -224,7 +224,7 @@ def _handle_native_json_schema(
     return model_parameters
 
 
-def _set_response_format(model_parameters: dict, rules: list):
+def _set_response_format(model_parameters: dict[str, Any], rules: list[ParameterRule]):
     """
     Set the appropriate response format parameter based on model rules.
 
@@ -326,7 +326,7 @@ def _prepare_schema_for_model(provider: str, model_schema: AIModelEntity, schema
         return {"schema": processed_schema, "name": "llm_response"}
 
 
-def remove_additional_properties(schema: dict):
+def remove_additional_properties(schema: dict[str, Any]):
     """
     Remove additionalProperties fields from JSON schema.
     Used for models like Gemini that don't support this property.

api/core/tools/__base/tool.py

@@ -198,7 +198,7 @@ class Tool(ABC):
             message=ToolInvokeMessage.TextMessage(text=text),
         )
 
-    def create_blob_message(self, blob: bytes, meta: dict | None = None) -> ToolInvokeMessage:
+    def create_blob_message(self, blob: bytes, meta: dict[str, Any] | None = None) -> ToolInvokeMessage:
         """
         create a blob message
 
@@ -212,7 +212,7 @@ class Tool(ABC):
             meta=meta,
         )
 
-    def create_json_message(self, object: dict, suppress_output: bool = False) -> ToolInvokeMessage:
+    def create_json_message(self, object: dict[str, Any], suppress_output: bool = False) -> ToolInvokeMessage:
         """
         create a json message
         """

api/core/tools/entities/tool_entities.py

@@ -149,7 +149,7 @@ class ToolInvokeMessage(BaseModel):
         text: str
 
     class JsonMessage(BaseModel):
-        json_object: dict | list
+        json_object: dict[str, Any] | list[Any]
         suppress_output: bool = Field(default=False, description="Whether to suppress JSON output in result string")
 
     class BlobMessage(BaseModel):
@@ -337,7 +337,7 @@ class ToolParameter(PluginParameter):
     form: ToolParameterForm = Field(..., description="The form of the parameter, schema/form/llm")
     llm_description: str | None = None
     # MCP object and array type parameters use this field to store the schema
-    input_schema: dict | None = None
+    input_schema: dict[str, Any] | None = None
 
     @classmethod
     def get_simple_instance(
@@ -463,7 +463,7 @@ class ToolInvokeMeta(BaseModel):
 
     time_cost: float = Field(..., description="The time cost of the tool invoke")
     error: str | None = None
-    tool_config: dict | None = None
+    tool_config: dict[str, Any] | None = None
 
     @classmethod
     def empty(cls) -> ToolInvokeMeta:

api/core/tools/tool_engine.py

@@ -85,7 +85,8 @@ class ToolEngine:
             invocation_meta_dict: dict[str, ToolInvokeMeta] = {}
 
             def message_callback(
-                invocation_meta_dict: dict, messages: Generator[ToolInvokeMessage | ToolInvokeMeta, None, None]
+                invocation_meta_dict: dict[str, Any],
+                messages: Generator[ToolInvokeMessage | ToolInvokeMeta, None, None],
             ):
                 for message in messages:
                     if isinstance(message, ToolInvokeMeta):
@@ -200,7 +201,7 @@ class ToolEngine:
     @staticmethod
     def _invoke(
         tool: Tool,
-        tool_parameters: dict,
+        tool_parameters: dict[str, Any],
         user_id: str,
         conversation_id: str | None = None,
         app_id: str | None = None,

api/core/tools/utils/dataset_retriever_tool.py

@@ -33,7 +33,7 @@ class DatasetRetrieverTool(Tool):
         invoke_from: InvokeFrom,
         hit_callback: DatasetIndexToolCallbackHandler,
         user_id: str,
-        inputs: dict,
+        inputs: dict[str, Any],
     ) -> list["DatasetRetrieverTool"]:
         """
         get dataset tool

api/core/tools/workflow_as_tool/tool.py

@@ -277,7 +277,7 @@ class WorkflowTool(Tool):
             session.expunge(app)
             return app
 
-    def _transform_args(self, tool_parameters: dict) -> tuple[dict, list[dict]]:
+    def _transform_args(self, tool_parameters: dict[str, Any]) -> tuple[dict[str, Any], list[dict[str, Any]]]:
         """
         transform the tool parameters
 
@@ -323,7 +323,7 @@ class WorkflowTool(Tool):
 
         return parameters_result, files
 
-    def _extract_files(self, outputs: dict) -> tuple[dict, list[File]]:
+    def _extract_files(self, outputs: dict[str, Any]) -> tuple[dict[str, Any], list[File]]:
         """
         extract files from the result
 
@@ -355,7 +355,7 @@ class WorkflowTool(Tool):
 
         return result, files
 
-    def _update_file_mapping(self, file_dict: dict):
+    def _update_file_mapping(self, file_dict: dict[str, Any]):
         file_id = resolve_file_record_id(file_dict.get("reference") or file_dict.get("related_id"))
         transfer_method = FileTransferMethod.value_of(file_dict.get("transfer_method"))
         match transfer_method: