Add session_id and component_id to ChatOutputResponse schema

src/backend/langflow/api/v1/schemas.py

@@ -232,7 +232,7 @@ class VertexBuildResponse(BaseModel):
     inactivated_vertices: Optional[List[str]] = None
     next_vertices_ids: Optional[List[str]] = None
     valid: bool
-    params: Optional[str]
+    params: Optional[Any] = Field(default_factory=dict)
     """JSON string of the params."""
     data: ResultDataResponse
     """Mapping of vertex ids to result dict containing the param name and result value."""

src/backend/langflow/components/utilities/RunFlow.py

@@ -0,0 +1,58 @@
+from typing import List, Optional
+
+from langflow import CustomComponent
+from langflow.field_typing import NestedDict, Text
+from langflow.graph.schema import ResultData
+from langflow.schema import Record
+
+
+class RunFlowComponent(CustomComponent):
+    display_name = "Run Flow"
+    description = "A component to run a flow."
+
+    def get_flow_names(self) -> List[str]:
+        flow_records = self.list_flows()
+        return [flow_record.data["name"] for flow_record in flow_records]
+
+    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": self.get_flow_names,
+            },
+            "tweaks": {
+                "display_name": "Tweaks",
+                "info": "Tweaks to apply to the flow.",
+            },
+        }
+
+    def build_records_from_result_data(self, result_data: ResultData) -> Record:
+        messages = result_data.messages
+        records = []
+        for message in messages:
+            record = Record(text=message.get("text", ""), data={"result": result_data})
+            records.append(record)
+        return records
+
+    async def build(
+        self, input_value: Text, flow_name: str, tweaks: NestedDict
+    ) -> Record:
+
+        results: List[Optional[ResultData]] = await self.run_flow(
+            input_value=input_value, flow_name=flow_name, tweaks=tweaks
+        )
+        if isinstance(results, list):
+            records = []
+            for result in results:
+                if result:
+                    records.extend(self.build_records_from_result_data(result))
+        else:
+            records = self.build_records_from_result_data(results)
+
+        self.status = records
+        return records

src/backend/langflow/graph/schema.py

@@ -4,12 +4,13 @@ from typing import Any, Optional
 from pydantic import BaseModel, Field, field_serializer
 
 from langflow.graph.utils import serialize_field
-from langflow.utils.schemas import ContainsEnumMeta
+from langflow.utils.schemas import ChatOutputResponse, ContainsEnumMeta
 
 
 class ResultData(BaseModel):
     results: Optional[Any] = Field(default_factory=dict)
     artifacts: Optional[Any] = Field(default_factory=dict)
+    messages: Optional[list[ChatOutputResponse]] = Field(default_factory=list)
     timedelta: Optional[float] = None
     duration: Optional[str] = None
 

src/backend/langflow/graph/vertex/base.py

@@ -28,6 +28,7 @@ from langflow.interface.initialize import loading
 from langflow.interface.listing import lazy_load_dict
 from langflow.services.deps import get_storage_service
 from langflow.utils.constants import DIRECT_TYPES
+from langflow.utils.schemas import ChatOutputResponse
 from langflow.utils.util import sync_to_async
 
 if TYPE_CHECKING:
@@ -411,15 +412,43 @@ class Vertex:
 
         self._built = True
 
+    def extract_messages_from_artifacts(self, artifacts: Dict[str, Any]) -> List[str]:
+        """
+        Extracts messages from the artifacts.
+
+        Args:
+            artifacts (Dict[str, Any]): The artifacts to extract messages from.
+
+        Returns:
+            List[str]: The extracted messages.
+        """
+        messages = []
+        for key, artifact in artifacts.items():
+            if not isinstance(artifact, dict):
+                continue
+            if "message" in artifact:
+                chat_output_response = ChatOutputResponse(
+                    message=artifact["message"],
+                    sender=artifact.get("sender"),
+                    sender_name=artifact.get("sender_name"),
+                    session_id=artifact.get("session_id"),
+                    component_id=self.id,
+                )
+                messages.append(chat_output_response.model_dump(exclude_none=True))
+
+        return messages
+
     def _finalize_build(self):
         result_dict = self.get_built_result()
         # We need to set the artifacts to pass information
         # to the frontend
         self.set_artifacts()
         artifacts = self.artifacts
+        messages = self.extract_messages_from_artifacts(artifacts)
         result_dict = ResultData(
             results=result_dict,
             artifacts=artifacts,
+            messages=messages,
         )
         self.set_result(result_dict)
 

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

@@ -132,7 +132,7 @@ class CustomComponent(Component):
             return yaml.dump(self.repr_value)
         if isinstance(self.repr_value, str):
             return self.repr_value
-        return str(self.repr_value)
+        return self.repr_value
 
     def build_config(self):
         return self.field_config

src/backend/langflow/schema/schema.py

@@ -1,4 +1,4 @@
-from typing import Any
+from typing import Any, Optional
 
 from langchain_core.documents import Document
 from pydantic import BaseModel
@@ -13,7 +13,7 @@ class Record(BaseModel):
         data (dict, optional): Additional data associated with the record.
     """
 
-    text: str
+    text: Optional[str] = ""
     data: dict = {}
 
     @classmethod
@@ -52,8 +52,6 @@ class Record(BaseModel):
         Returns the text of the record.
 
         Returns:
-            str: The text of the record.
+            str: The text and data of the record.
         """
-        return self.text
+        return self.model_dump_json(indent=2)
-
-

src/backend/langflow/utils/schemas.py

@@ -11,7 +11,9 @@ class ChatOutputResponse(BaseModel):
     message: Union[str, List[Union[str, Dict]]]
     sender: Optional[str] = "Machine"
     sender_name: Optional[str] = "AI"
+    session_id: Optional[str] = None
     stream_url: Optional[str] = None
+    component_id: Optional[str] = None
 
     @classmethod
     def from_message(

src/frontend/src/CustomNodes/GenericNode/index.tsx

@@ -9,6 +9,7 @@ import Loading from "../../components/ui/loading";
 import { Textarea } from "../../components/ui/textarea";
 import Xmark from "../../components/ui/xmark";
 import {
+  RUN_TIMESTAMP_PREFIX,
   STATUS_BUILD,
   STATUS_BUILDING,
   priorityFields,
@@ -59,6 +60,8 @@ export default function GenericNode({
     useState<validationStatusType | null>(null);
   const [handles, setHandles] = useState<number>(0);
 
+  const [validationString, setValidationString] = useState<string>("");
+
   const takeSnapshot = useFlowsManagerStore((state) => state.takeSnapshot);
 
   function countHandles(): void {
@@ -131,6 +134,18 @@ export default function GenericNode({
     }
   }, [flowPool[data.id], data.id]);
 
+  useEffect(() => {
+    if (validationStatus?.params) {
+      // if it is not a string turn it into a string
+      let newValidationString = validationStatus.params;
+      if (typeof newValidationString !== "string") {
+        newValidationString = JSON.stringify(validationStatus.params);
+      }
+
+      setValidationString(newValidationString);
+    }
+  }, [validationStatus, validationStatus?.params]);
+
   const showNode = data.showNode ?? true;
 
   const nameEditable = true;
@@ -493,14 +508,32 @@ export default function GenericNode({
                       ) : !validationStatus ? (
                         <span className="flex">{STATUS_BUILD}</span>
                       ) : (
-                        <div className="max-h-96 overflow-auto">
+                        <div className="max-h-100">
-                          {typeof validationStatus.params === "string"
+                          <div>
-                            ? `${durationString}\n${validationStatus.params}`
+                            {lastRunTime && (
-                                .split("\n")
+                              <div className="justify-left flex text-muted-foreground">
-                                .map((line, index) => (
+                                <div>{RUN_TIMESTAMP_PREFIX}</div>
+                                <div className="ml-1 text-status-blue">
+                                  {lastRunTime}
+                                </div>
+                              </div>
+                            )}
+                          </div>
+                          <div className="justify-left flex text-muted-foreground">
+                            <div>Duration:</div>
+                            <div className="ml-1 text-status-blue">
+                              {validationStatus?.data.duration}
+                            </div>
+                          </div>
+                          <hr />
+                          <span className="flex justify-center   text-muted-foreground ">
+                            Output
+                          </span>
+                          <div className="max-h-96 overflow-auto custom-scroll">
+                            {validationString.split("\n").map((line, index) => (
                               <div key={index}>{line}</div>
-                                ))
+                            ))}
-                            : durationString}
+                          </div>
                         </div>
                       )
                     }