fix: validate params assignment in custom_component_update endpoint (l…

…angflow-ai#2931)

* feat(RunFlow.py): update input and output definitions for RunFlowComponent

* refactor: update params assignment in custom_component_update endpoint

Simplify the params assignment in the custom_component_update endpoint by using a dictionary comprehension. This improves code readability and reduces the number of lines.

* feat(custom_component.py, flow.py): add support for specifying output type in run_flow method to filter outputs based on type

(cherry picked from commit 7d5ccb3)

src/backend/base/langflow/api/v1/endpoints.py

@@ -590,7 +590,9 @@ async def custom_component_update(
         )
         if hasattr(cc_instance, "set_attributes"):
             template = code_request.get_template()
-            params = {key: value_dict["value"] for key, value_dict in template.items() if isinstance(value_dict, dict)}
+            params = {
+                key: value_dict.get("value") for key, value_dict in template.items() if isinstance(value_dict, dict)
+            }
             load_from_db_fields = [
                 field_name
                 for field_name, field_dict in template.items()

src/backend/base/langflow/components/prototypes/RunFlow.py

@@ -1,13 +1,13 @@
 from typing import Any, List, Optional
 
 from langflow.base.flow_processing.utils import build_data_from_run_outputs
-from langflow.custom import CustomComponent
-from langflow.field_typing import NestedDict, Text
+from langflow.custom import Component
 from langflow.graph.schema import RunOutputs
+from langflow.io import DropdownInput, MessageTextInput, NestedDictInput, Output
 from langflow.schema import Data, dotdict
 
 
-class RunFlowComponent(CustomComponent):
+class RunFlowComponent(Component):
     display_name = "Run Flow"
     description = "A component to run a flow."
     name = "RunFlow"
@@ -23,27 +23,33 @@ def update_build_config(self, build_config: dotdict, field_value: Any, field_nam
 
         return build_config
 
-    def build_config(self):
-        return {
-            "input_value": {
-                "display_name": "Input Value",
-                "multiline": True,
-            },
-            "flow_name": {
-                "display_name": "Flow Name",
-                "info": "The name of the flow to run.",
-                "options": [],
-                "refresh_button": True,
-            },
-            "tweaks": {
-                "display_name": "Tweaks",
-                "info": "Tweaks to apply to the flow.",
-            },
-        }
-
-    async def build(self, input_value: Text, flow_name: str, tweaks: NestedDict) -> List[Data]:
+    inputs = [
+        MessageTextInput(
+            name="input_value",
+            display_name="Input Value",
+            info="The input value to be processed by the flow.",
+        ),
+        DropdownInput(
+            name="flow_name",
+            display_name="Flow Name",
+            info="The name of the flow to run.",
+            options=[],
+            refresh_button=True,
+        ),
+        NestedDictInput(
+            name="tweaks",
+            display_name="Tweaks",
+            info="Tweaks to apply to the flow.",
+        ),
+    ]
+
+    outputs = [
+        Output(display_name="Run Outputs", name="run_outputs", method="generate_results"),
+    ]
+
+    async def generate_results(self) -> List[Data]:
         results: List[Optional[RunOutputs]] = await self.run_flow(
-            inputs={"input_value": input_value}, flow_name=flow_name, tweaks=tweaks
+            inputs={"input_value": self.input_value}, flow_name=self.flow_name, tweaks=self.tweaks
         )
         if isinstance(results, list):
             data = []

src/backend/base/langflow/custom/custom_component/custom_component.py

@@ -480,9 +480,17 @@ async def run_flow(
         inputs: Optional[Union[dict, List[dict]]] = None,
         flow_id: Optional[str] = None,
         flow_name: Optional[str] = None,
+        output_type: Optional[str] = None,
         tweaks: Optional[dict] = None,
     ) -> Any:
-        return await run_flow(inputs=inputs, flow_id=flow_id, flow_name=flow_name, tweaks=tweaks, user_id=self._user_id)
+        return await run_flow(
+            inputs=inputs,
+            output_type=output_type,
+            flow_id=flow_id,
+            flow_name=flow_name,
+            tweaks=tweaks,
+            user_id=self._user_id,
+        )
 
     def list_flows(self) -> List[Data]:
         if not self._user_id:

src/backend/base/langflow/helpers/flow.py

@@ -71,6 +71,7 @@ async def run_flow(
     tweaks: Optional[dict] = None,
     flow_id: Optional[str] = None,
     flow_name: Optional[str] = None,
+    output_type: Optional[str] = None,
     user_id: Optional[str] = None,
 ) -> List[RunOutputs]:
     if user_id is None:
@@ -89,10 +90,23 @@ async def run_flow(
         inputs_components.append(input_dict.get("components", []))
         types.append(input_dict.get("type", "chat"))
 
+    outputs = [
+        vertex.id
+        for vertex in graph.vertices
+        if output_type == "debug"
+        or (
+            vertex.is_output and (output_type == "any" or output_type in vertex.id.lower())  # type: ignore
+        )
+    ]
+
     fallback_to_env_vars = get_settings_service().settings.fallback_to_env_var
 
     return await graph.arun(
-        inputs_list, inputs_components=inputs_components, types=types, fallback_to_env_vars=fallback_to_env_vars
+        inputs_list,
+        outputs=outputs,
+        inputs_components=inputs_components,
+        types=types,
+        fallback_to_env_vars=fallback_to_env_vars,
     )