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src/promptflow-core/promptflow/executor/_script_executor.py

@@ -120,7 +120,7 @@ def _exec_line_preprocess(
         # Executor will add line_number to batch inputs if there is no line_number in the original inputs,
         # which should be removed, so, we only preserve the inputs that are contained in self._inputs.
         inputs = {k: inputs[k] for k in self._inputs if k in inputs}
-        FlowValidator.ensure_flow_inputs_type(self._inputs_sign, inputs)
+        FlowValidator._ensure_flow_inputs_type_inner(self._inputs_sign, inputs)
         return run_info, inputs, run_tracker, None, []
 
     def _exec_line(
@@ -458,9 +458,12 @@ def _init_input_sign(self):
             with open(self._working_dir / self._flow_file, "r", encoding="utf-8") as fin:
                 flow_dag = load_yaml(fin)
             flow = FlexFlow.deserialize(flow_dag)
+            # In the yaml file, user can define the inputs and init signature for the flow, also SDK may create
+            # the signature and add them to the yaml file. We need to get the signature from the yaml file and
+            # used for applying default value and ensuring input type.
             self._inputs_sign = flow.inputs
             self._init_sign = flow.init
         else:
-            # For function entry there is no yaml file to get the inputs and init signature.
+            # Since there is no yaml file for function entry, we set the inputs and init signature to empty dict.
             self._inputs_sign = {}
             self._init_sign = {}

src/promptflow-core/promptflow/executor/flow_executor.py

@@ -969,9 +969,7 @@ def _exec(
         aggregation_inputs = {}
         try:
             if validate_inputs:
-                inputs = FlowValidator.ensure_flow_inputs_type(
-                    flow_inputs=self._flow.inputs, inputs=inputs, idx=run_info.index
-                )
+                inputs = FlowValidator.ensure_flow_inputs_type(flow=self._flow, inputs=inputs, idx=run_info.index)
             inputs = self._multimedia_processor.load_multimedia_data(self._flow.inputs, inputs)
             # Inputs are assigned after validation and multimedia data loading, instead of at the start of the flow run.
             # This way, if validation or multimedia data loading fails, we avoid persisting invalid inputs.
@@ -1056,9 +1054,7 @@ async def _exec_async(
         aggregation_inputs = {}
         try:
             if validate_inputs:
-                inputs = FlowValidator.ensure_flow_inputs_type(
-                    flow_inputs=self._flow.inputs, inputs=inputs, idx=run_info.index
-                )
+                inputs = FlowValidator.ensure_flow_inputs_type(flow=self._flow, inputs=inputs, idx=run_info.index)
             # TODO: Consider async implementation for load_multimedia_data
             inputs = self._multimedia_processor.load_multimedia_data(self._flow.inputs, inputs)
             # Inputs are assigned after validation and multimedia data loading, instead of at the start of the flow run.

src/promptflow-core/promptflow/executor/flow_validator.py

@@ -182,9 +182,7 @@ def resolve_aggregated_flow_inputs_type(flow: Flow, inputs: Mapping[str, List[An
         return updated_inputs
 
     @staticmethod
-    def resolve_flow_inputs_type(
-        flow_inputs: FlowInputDefinition, inputs: Mapping[str, Any], idx: Optional[int] = None
-    ) -> Mapping[str, Any]:
+    def resolve_flow_inputs_type(flow: Flow, inputs: Mapping[str, Any], idx: Optional[int] = None) -> Mapping[str, Any]:
         """Resolve inputs by type if existing. Ignore missing inputs.
 
         :param flow: The `flow` parameter is of type `Flow` and represents a flow object
@@ -199,16 +197,20 @@ def resolve_flow_inputs_type(
             in the `flow` object.
         :rtype: Mapping[str, Any]
         """
+        return FlowValidator._resolve_flow_inputs_type_inner(flow.inputs, inputs, idx)
+
+    @staticmethod
+    def _resolve_flow_inputs_type_inner(
+        flow_inputs: FlowInputDefinition, inputs: Mapping[str, Any], idx: Optional[int] = None
+    ) -> Mapping[str, Any]:
         updated_inputs = {k: v for k, v in inputs.items()}
         for k, v in flow_inputs.items():
             if k in inputs:
                 updated_inputs[k] = FlowValidator._parse_input_value(k, inputs[k], v.type, idx)
         return updated_inputs
 
     @staticmethod
-    def ensure_flow_inputs_type(
-        flow_inputs: FlowInputDefinition, inputs: Mapping[str, Any], idx: Optional[int] = None
-    ) -> Mapping[str, Any]:
+    def ensure_flow_inputs_type(flow: Flow, inputs: Mapping[str, Any], idx: Optional[int] = None) -> Mapping[str, Any]:
         """Make sure the inputs are completed and in the correct type. Raise Exception if not valid.
 
         :param flow: The `flow` parameter is of type `Flow` and represents a flow object
@@ -223,6 +225,12 @@ def ensure_flow_inputs_type(
             type specified in the `flow` object.
         :rtype: Mapping[str, Any]
         """
+        return FlowValidator._ensure_flow_inputs_type_inner(flow.inputs, inputs, idx)
+
+    @staticmethod
+    def _ensure_flow_inputs_type_inner(
+        flow_inputs: FlowInputDefinition, inputs: Mapping[str, Any], idx: Optional[int] = None
+    ) -> Mapping[str, Any]:
         for k, _ in flow_inputs.items():
             if k not in inputs:
                 line_info = "in input data" if idx is None else f"in line {idx} of input data"
@@ -232,7 +240,7 @@ def ensure_flow_inputs_type(
                     "if it's no longer needed."
                 )
                 raise InputNotFound(message_format=msg_format, input_name=k, line_info=line_info)
-        return FlowValidator.resolve_flow_inputs_type(flow_inputs, inputs, idx)
+        return FlowValidator._resolve_flow_inputs_type_inner(flow_inputs, inputs, idx)
 
     @staticmethod
     def convert_flow_inputs_for_node(flow: Flow, node: Node, inputs: Mapping[str, Any]) -> Mapping[str, Any]:

src/promptflow-devkit/promptflow/batch/_batch_engine.py

@@ -575,8 +575,7 @@ def _get_aggregation_inputs(self, batch_inputs, line_results: List[LineResult]):
 
         succeeded_batch_inputs = [batch_inputs[i] for i in succeeded]
         resolved_succeeded_batch_inputs = [
-            FlowValidator.ensure_flow_inputs_type(flow_inputs=self._flow.inputs, inputs=input)
-            for input in succeeded_batch_inputs
+            FlowValidator.ensure_flow_inputs_type(flow=self._flow, inputs=input) for input in succeeded_batch_inputs
         ]
         succeeded_inputs = transpose(resolved_succeeded_batch_inputs, keys=list(self._flow.inputs.keys()))
         aggregation_inputs = transpose(

src/promptflow/tests/executor/unittests/executor/test_flow_validator.py

@@ -168,7 +168,7 @@ def test_resolve_flow_inputs_type_json_error_for_list_type(
     ):
         flow = get_flow_from_folder(flow_folder)
         with pytest.raises(error_type) as exe_info:
-            FlowValidator.resolve_flow_inputs_type(flow.inputs, inputs, idx=index)
+            FlowValidator.resolve_flow_inputs_type(flow, inputs, idx=index)
         assert error_message == exe_info.value.message
 
     @pytest.mark.parametrize(