fix: update model output type to message instead of string (#8489)

* Changed conversion methods to support the fact that LLM hint on a Message return type but return a string, causing a runtime error while converting types

* Convert to Message for model component text response

* [autofix.ci] apply automated fixes

* [autofix.ci] apply automated fixes

---------

Co-authored-by: Pedro Pacheco <pedro.pacheco@yahoo.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

src/backend/base/langflow/base/models/model.py

@@ -174,7 +174,7 @@ class LCModelComponent(Component):
         stream: bool,
         input_value: str | Message,
         system_message: str | None = None,
-    ):
+    ) -> Message:
         if getattr(self, "detailed_thinking", False):
             system_message = DETAILED_THINKING_PREFIX + (system_message or "")
 
@@ -192,7 +192,7 @@ class LCModelComponent(Component):
         stream: bool,
         input_value: str | Message,
         system_message: str | None = None,
-    ):
+    ) -> Message:
         messages: list[BaseMessage] = []
         if not input_value and not system_message:
             msg = "The message you want to send to the model is empty."
@@ -248,7 +248,7 @@ class LCModelComponent(Component):
                 raise ValueError(message) from e
             raise
 
-        return result
+        return Message(text=result)
 
     @abstractmethod
     def build_model(self) -> LanguageModel:  # type: ignore[type-var]

src/backend/base/langflow/components/processing/converter.py

@@ -68,7 +68,13 @@ class TypeConverterComponent(Component):
         ),
     ]
 
-    outputs = [Output(display_name="Message Output", name="message_output", method="convert_to_message")]
+    outputs = [
+        Output(
+            display_name="Message Output",
+            name="message_output",
+            method="convert_to_message",
+        )
+    ]
 
     def update_outputs(self, frontend_node: dict, field_name: str, field_value: Any) -> dict:
         """Dynamically show only the relevant output based on the selected output type."""
@@ -79,16 +85,26 @@ class TypeConverterComponent(Component):
             # Add only the selected output type
             if field_value == "Message":
                 frontend_node["outputs"].append(
-                    Output(display_name="Message Output", name="message_output", method="convert_to_message").to_dict()
+                    Output(
+                        display_name="Message Output",
+                        name="message_output",
+                        method="convert_to_message",
+                    ).to_dict()
                 )
             elif field_value == "Data":
                 frontend_node["outputs"].append(
-                    Output(display_name="Data Output", name="data_output", method="convert_to_data").to_dict()
+                    Output(
+                        display_name="Data Output",
+                        name="data_output",
+                        method="convert_to_data",
+                    ).to_dict()
                 )
             elif field_value == "DataFrame":
                 frontend_node["outputs"].append(
                     Output(
-                        display_name="DataFrame Output", name="dataframe_output", method="convert_to_dataframe"
+                        display_name="DataFrame Output",
+                        name="dataframe_output",
+                        method="convert_to_dataframe",
                     ).to_dict()
                 )
 
@@ -96,12 +112,30 @@ class TypeConverterComponent(Component):
 
     def convert_to_message(self) -> Message:
         """Convert input to Message type."""
-        return convert_to_message(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)
+        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data
+
+        # Handle string input by converting to Message first
+        if isinstance(input_value, str):
+            input_value = Message(text=input_value)
+
+        return convert_to_message(input_value)
 
     def convert_to_data(self) -> Data:
         """Convert input to Data type."""
-        return convert_to_data(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)
+        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data
+
+        # Handle string input by converting to Message first
+        if isinstance(input_value, str):
+            input_value = Message(text=input_value)
+
+        return convert_to_data(input_value)
 
     def convert_to_dataframe(self) -> DataFrame:
         """Convert input to DataFrame type."""
-        return convert_to_dataframe(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)
+        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data
+
+        # Handle string input by converting to Message first
+        if isinstance(input_value, str):
+            input_value = Message(text=input_value)
+
+        return convert_to_dataframe(input_value)

src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json

@@ -2954,7 +2954,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from typing import Any\n\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, Output, TabInput\nfrom langflow.schema import Data, DataFrame, Message\n\n\ndef convert_to_message(v) -> Message:\n    \"\"\"Convert input to Message type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Message: Converted Message object\n    \"\"\"\n    return v if isinstance(v, Message) else v.to_message()\n\n\ndef convert_to_data(v: DataFrame | Data | Message | dict) -> Data:\n    \"\"\"Convert input to Data type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Data: Converted Data object\n    \"\"\"\n    if isinstance(v, dict):\n        return Data(v)\n    return v if isinstance(v, Data) else v.to_data()\n\n\ndef convert_to_dataframe(v: DataFrame | Data | Message | dict) -> DataFrame:\n    \"\"\"Convert input to DataFrame type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        DataFrame: Converted DataFrame object\n    \"\"\"\n    if isinstance(v, dict):\n        return DataFrame([v])\n    return v if isinstance(v, DataFrame) else v.to_dataframe()\n\n\nclass TypeConverterComponent(Component):\n    display_name = \"Type Convert\"\n    description = \"Convert between different types (Message, Data, DataFrame)\"\n    icon = \"repeat\"\n\n    inputs = [\n        HandleInput(\n            name=\"input_data\",\n            display_name=\"Input\",\n            input_types=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Accept Message, Data or DataFrame as input\",\n            required=True,\n        ),\n        TabInput(\n            name=\"output_type\",\n            display_name=\"Output Type\",\n            options=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Select the desired output data type\",\n            real_time_refresh=True,\n            value=\"Message\",\n        ),\n    ]\n\n    outputs = [Output(display_name=\"Message Output\", name=\"message_output\", method=\"convert_to_message\")]\n\n    def update_outputs(self, frontend_node: dict, field_name: str, field_value: Any) -> dict:\n        \"\"\"Dynamically show only the relevant output based on the selected output type.\"\"\"\n        if field_name == \"output_type\":\n            # Start with empty outputs\n            frontend_node[\"outputs\"] = []\n\n            # Add only the selected output type\n            if field_value == \"Message\":\n                frontend_node[\"outputs\"].append(\n                    Output(display_name=\"Message Output\", name=\"message_output\", method=\"convert_to_message\").to_dict()\n                )\n            elif field_value == \"Data\":\n                frontend_node[\"outputs\"].append(\n                    Output(display_name=\"Data Output\", name=\"data_output\", method=\"convert_to_data\").to_dict()\n                )\n            elif field_value == \"DataFrame\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"DataFrame Output\", name=\"dataframe_output\", method=\"convert_to_dataframe\"\n                    ).to_dict()\n                )\n\n        return frontend_node\n\n    def convert_to_message(self) -> Message:\n        \"\"\"Convert input to Message type.\"\"\"\n        return convert_to_message(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)\n\n    def convert_to_data(self) -> Data:\n        \"\"\"Convert input to Data type.\"\"\"\n        return convert_to_data(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)\n\n    def convert_to_dataframe(self) -> DataFrame:\n        \"\"\"Convert input to DataFrame type.\"\"\"\n        return convert_to_dataframe(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)\n"
+                "value": "from typing import Any\n\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, Output, TabInput\nfrom langflow.schema import Data, DataFrame, Message\n\n\ndef convert_to_message(v) -> Message:\n    \"\"\"Convert input to Message type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Message: Converted Message object\n    \"\"\"\n    return v if isinstance(v, Message) else v.to_message()\n\n\ndef convert_to_data(v: DataFrame | Data | Message | dict) -> Data:\n    \"\"\"Convert input to Data type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Data: Converted Data object\n    \"\"\"\n    if isinstance(v, dict):\n        return Data(v)\n    return v if isinstance(v, Data) else v.to_data()\n\n\ndef convert_to_dataframe(v: DataFrame | Data | Message | dict) -> DataFrame:\n    \"\"\"Convert input to DataFrame type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        DataFrame: Converted DataFrame object\n    \"\"\"\n    if isinstance(v, dict):\n        return DataFrame([v])\n    return v if isinstance(v, DataFrame) else v.to_dataframe()\n\n\nclass TypeConverterComponent(Component):\n    display_name = \"Type Convert\"\n    description = \"Convert between different types (Message, Data, DataFrame)\"\n    icon = \"repeat\"\n\n    inputs = [\n        HandleInput(\n            name=\"input_data\",\n            display_name=\"Input\",\n            input_types=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Accept Message, Data or DataFrame as input\",\n            required=True,\n        ),\n        TabInput(\n            name=\"output_type\",\n            display_name=\"Output Type\",\n            options=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Select the desired output data type\",\n            real_time_refresh=True,\n            value=\"Message\",\n        ),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message Output\",\n            name=\"message_output\",\n            method=\"convert_to_message\",\n        )\n    ]\n\n    def update_outputs(self, frontend_node: dict, field_name: str, field_value: Any) -> dict:\n        \"\"\"Dynamically show only the relevant output based on the selected output type.\"\"\"\n        if field_name == \"output_type\":\n            # Start with empty outputs\n            frontend_node[\"outputs\"] = []\n\n            # Add only the selected output type\n            if field_value == \"Message\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"Message Output\",\n                        name=\"message_output\",\n                        method=\"convert_to_message\",\n                    ).to_dict()\n                )\n            elif field_value == \"Data\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"Data Output\",\n                        name=\"data_output\",\n                        method=\"convert_to_data\",\n                    ).to_dict()\n                )\n            elif field_value == \"DataFrame\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"DataFrame Output\",\n                        name=\"dataframe_output\",\n                        method=\"convert_to_dataframe\",\n                    ).to_dict()\n                )\n\n        return frontend_node\n\n    def convert_to_message(self) -> Message:\n        \"\"\"Convert input to Message type.\"\"\"\n        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data\n\n        # Handle string input by converting to Message first\n        if isinstance(input_value, str):\n            input_value = Message(text=input_value)\n\n        return convert_to_message(input_value)\n\n    def convert_to_data(self) -> Data:\n        \"\"\"Convert input to Data type.\"\"\"\n        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data\n\n        # Handle string input by converting to Message first\n        if isinstance(input_value, str):\n            input_value = Message(text=input_value)\n\n        return convert_to_data(input_value)\n\n    def convert_to_dataframe(self) -> DataFrame:\n        \"\"\"Convert input to DataFrame type.\"\"\"\n        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data\n\n        # Handle string input by converting to Message first\n        if isinstance(input_value, str):\n            input_value = Message(text=input_value)\n\n        return convert_to_dataframe(input_value)\n"
               },
               "input_data": {
                 "_input_type": "HandleInput",

src/backend/base/langflow/initial_setup/starter_projects/Meeting Summary.json

@@ -3964,7 +3964,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from typing import Any\n\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, Output, TabInput\nfrom langflow.schema import Data, DataFrame, Message\n\n\ndef convert_to_message(v) -> Message:\n    \"\"\"Convert input to Message type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Message: Converted Message object\n    \"\"\"\n    return v if isinstance(v, Message) else v.to_message()\n\n\ndef convert_to_data(v: DataFrame | Data | Message | dict) -> Data:\n    \"\"\"Convert input to Data type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Data: Converted Data object\n    \"\"\"\n    if isinstance(v, dict):\n        return Data(v)\n    return v if isinstance(v, Data) else v.to_data()\n\n\ndef convert_to_dataframe(v: DataFrame | Data | Message | dict) -> DataFrame:\n    \"\"\"Convert input to DataFrame type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        DataFrame: Converted DataFrame object\n    \"\"\"\n    if isinstance(v, dict):\n        return DataFrame([v])\n    return v if isinstance(v, DataFrame) else v.to_dataframe()\n\n\nclass TypeConverterComponent(Component):\n    display_name = \"Type Convert\"\n    description = \"Convert between different types (Message, Data, DataFrame)\"\n    icon = \"repeat\"\n\n    inputs = [\n        HandleInput(\n            name=\"input_data\",\n            display_name=\"Input\",\n            input_types=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Accept Message, Data or DataFrame as input\",\n            required=True,\n        ),\n        TabInput(\n            name=\"output_type\",\n            display_name=\"Output Type\",\n            options=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Select the desired output data type\",\n            real_time_refresh=True,\n            value=\"Message\",\n        ),\n    ]\n\n    outputs = [Output(display_name=\"Message Output\", name=\"message_output\", method=\"convert_to_message\")]\n\n    def update_outputs(self, frontend_node: dict, field_name: str, field_value: Any) -> dict:\n        \"\"\"Dynamically show only the relevant output based on the selected output type.\"\"\"\n        if field_name == \"output_type\":\n            # Start with empty outputs\n            frontend_node[\"outputs\"] = []\n\n            # Add only the selected output type\n            if field_value == \"Message\":\n                frontend_node[\"outputs\"].append(\n                    Output(display_name=\"Message Output\", name=\"message_output\", method=\"convert_to_message\").to_dict()\n                )\n            elif field_value == \"Data\":\n                frontend_node[\"outputs\"].append(\n                    Output(display_name=\"Data Output\", name=\"data_output\", method=\"convert_to_data\").to_dict()\n                )\n            elif field_value == \"DataFrame\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"DataFrame Output\", name=\"dataframe_output\", method=\"convert_to_dataframe\"\n                    ).to_dict()\n                )\n\n        return frontend_node\n\n    def convert_to_message(self) -> Message:\n        \"\"\"Convert input to Message type.\"\"\"\n        return convert_to_message(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)\n\n    def convert_to_data(self) -> Data:\n        \"\"\"Convert input to Data type.\"\"\"\n        return convert_to_data(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)\n\n    def convert_to_dataframe(self) -> DataFrame:\n        \"\"\"Convert input to DataFrame type.\"\"\"\n        return convert_to_dataframe(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)\n"
+                "value": "from typing import Any\n\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, Output, TabInput\nfrom langflow.schema import Data, DataFrame, Message\n\n\ndef convert_to_message(v) -> Message:\n    \"\"\"Convert input to Message type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Message: Converted Message object\n    \"\"\"\n    return v if isinstance(v, Message) else v.to_message()\n\n\ndef convert_to_data(v: DataFrame | Data | Message | dict) -> Data:\n    \"\"\"Convert input to Data type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Data: Converted Data object\n    \"\"\"\n    if isinstance(v, dict):\n        return Data(v)\n    return v if isinstance(v, Data) else v.to_data()\n\n\ndef convert_to_dataframe(v: DataFrame | Data | Message | dict) -> DataFrame:\n    \"\"\"Convert input to DataFrame type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        DataFrame: Converted DataFrame object\n    \"\"\"\n    if isinstance(v, dict):\n        return DataFrame([v])\n    return v if isinstance(v, DataFrame) else v.to_dataframe()\n\n\nclass TypeConverterComponent(Component):\n    display_name = \"Type Convert\"\n    description = \"Convert between different types (Message, Data, DataFrame)\"\n    icon = \"repeat\"\n\n    inputs = [\n        HandleInput(\n            name=\"input_data\",\n            display_name=\"Input\",\n            input_types=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Accept Message, Data or DataFrame as input\",\n            required=True,\n        ),\n        TabInput(\n            name=\"output_type\",\n            display_name=\"Output Type\",\n            options=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Select the desired output data type\",\n            real_time_refresh=True,\n            value=\"Message\",\n        ),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message Output\",\n            name=\"message_output\",\n            method=\"convert_to_message\",\n        )\n    ]\n\n    def update_outputs(self, frontend_node: dict, field_name: str, field_value: Any) -> dict:\n        \"\"\"Dynamically show only the relevant output based on the selected output type.\"\"\"\n        if field_name == \"output_type\":\n            # Start with empty outputs\n            frontend_node[\"outputs\"] = []\n\n            # Add only the selected output type\n            if field_value == \"Message\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"Message Output\",\n                        name=\"message_output\",\n                        method=\"convert_to_message\",\n                    ).to_dict()\n                )\n            elif field_value == \"Data\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"Data Output\",\n                        name=\"data_output\",\n                        method=\"convert_to_data\",\n                    ).to_dict()\n                )\n            elif field_value == \"DataFrame\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"DataFrame Output\",\n                        name=\"dataframe_output\",\n                        method=\"convert_to_dataframe\",\n                    ).to_dict()\n                )\n\n        return frontend_node\n\n    def convert_to_message(self) -> Message:\n        \"\"\"Convert input to Message type.\"\"\"\n        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data\n\n        # Handle string input by converting to Message first\n        if isinstance(input_value, str):\n            input_value = Message(text=input_value)\n\n        return convert_to_message(input_value)\n\n    def convert_to_data(self) -> Data:\n        \"\"\"Convert input to Data type.\"\"\"\n        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data\n\n        # Handle string input by converting to Message first\n        if isinstance(input_value, str):\n            input_value = Message(text=input_value)\n\n        return convert_to_data(input_value)\n\n    def convert_to_dataframe(self) -> DataFrame:\n        \"\"\"Convert input to DataFrame type.\"\"\"\n        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data\n\n        # Handle string input by converting to Message first\n        if isinstance(input_value, str):\n            input_value = Message(text=input_value)\n\n        return convert_to_dataframe(input_value)\n"
               },
               "input_data": {
                 "_input_type": "HandleInput",

src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json

@@ -1703,7 +1703,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from typing import Any\n\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, Output, TabInput\nfrom langflow.schema import Data, DataFrame, Message\n\n\ndef convert_to_message(v) -> Message:\n    \"\"\"Convert input to Message type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Message: Converted Message object\n    \"\"\"\n    return v if isinstance(v, Message) else v.to_message()\n\n\ndef convert_to_data(v: DataFrame | Data | Message | dict) -> Data:\n    \"\"\"Convert input to Data type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Data: Converted Data object\n    \"\"\"\n    if isinstance(v, dict):\n        return Data(v)\n    return v if isinstance(v, Data) else v.to_data()\n\n\ndef convert_to_dataframe(v: DataFrame | Data | Message | dict) -> DataFrame:\n    \"\"\"Convert input to DataFrame type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        DataFrame: Converted DataFrame object\n    \"\"\"\n    if isinstance(v, dict):\n        return DataFrame([v])\n    return v if isinstance(v, DataFrame) else v.to_dataframe()\n\n\nclass TypeConverterComponent(Component):\n    display_name = \"Type Convert\"\n    description = \"Convert between different types (Message, Data, DataFrame)\"\n    icon = \"repeat\"\n\n    inputs = [\n        HandleInput(\n            name=\"input_data\",\n            display_name=\"Input\",\n            input_types=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Accept Message, Data or DataFrame as input\",\n            required=True,\n        ),\n        TabInput(\n            name=\"output_type\",\n            display_name=\"Output Type\",\n            options=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Select the desired output data type\",\n            real_time_refresh=True,\n            value=\"Message\",\n        ),\n    ]\n\n    outputs = [Output(display_name=\"Message Output\", name=\"message_output\", method=\"convert_to_message\")]\n\n    def update_outputs(self, frontend_node: dict, field_name: str, field_value: Any) -> dict:\n        \"\"\"Dynamically show only the relevant output based on the selected output type.\"\"\"\n        if field_name == \"output_type\":\n            # Start with empty outputs\n            frontend_node[\"outputs\"] = []\n\n            # Add only the selected output type\n            if field_value == \"Message\":\n                frontend_node[\"outputs\"].append(\n                    Output(display_name=\"Message Output\", name=\"message_output\", method=\"convert_to_message\").to_dict()\n                )\n            elif field_value == \"Data\":\n                frontend_node[\"outputs\"].append(\n                    Output(display_name=\"Data Output\", name=\"data_output\", method=\"convert_to_data\").to_dict()\n                )\n            elif field_value == \"DataFrame\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"DataFrame Output\", name=\"dataframe_output\", method=\"convert_to_dataframe\"\n                    ).to_dict()\n                )\n\n        return frontend_node\n\n    def convert_to_message(self) -> Message:\n        \"\"\"Convert input to Message type.\"\"\"\n        return convert_to_message(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)\n\n    def convert_to_data(self) -> Data:\n        \"\"\"Convert input to Data type.\"\"\"\n        return convert_to_data(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)\n\n    def convert_to_dataframe(self) -> DataFrame:\n        \"\"\"Convert input to DataFrame type.\"\"\"\n        return convert_to_dataframe(self.input_data[0] if isinstance(self.input_data, list) else self.input_data)\n"
+                "value": "from typing import Any\n\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, Output, TabInput\nfrom langflow.schema import Data, DataFrame, Message\n\n\ndef convert_to_message(v) -> Message:\n    \"\"\"Convert input to Message type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Message: Converted Message object\n    \"\"\"\n    return v if isinstance(v, Message) else v.to_message()\n\n\ndef convert_to_data(v: DataFrame | Data | Message | dict) -> Data:\n    \"\"\"Convert input to Data type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        Data: Converted Data object\n    \"\"\"\n    if isinstance(v, dict):\n        return Data(v)\n    return v if isinstance(v, Data) else v.to_data()\n\n\ndef convert_to_dataframe(v: DataFrame | Data | Message | dict) -> DataFrame:\n    \"\"\"Convert input to DataFrame type.\n\n    Args:\n        v: Input to convert (Message, Data, DataFrame, or dict)\n\n    Returns:\n        DataFrame: Converted DataFrame object\n    \"\"\"\n    if isinstance(v, dict):\n        return DataFrame([v])\n    return v if isinstance(v, DataFrame) else v.to_dataframe()\n\n\nclass TypeConverterComponent(Component):\n    display_name = \"Type Convert\"\n    description = \"Convert between different types (Message, Data, DataFrame)\"\n    icon = \"repeat\"\n\n    inputs = [\n        HandleInput(\n            name=\"input_data\",\n            display_name=\"Input\",\n            input_types=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Accept Message, Data or DataFrame as input\",\n            required=True,\n        ),\n        TabInput(\n            name=\"output_type\",\n            display_name=\"Output Type\",\n            options=[\"Message\", \"Data\", \"DataFrame\"],\n            info=\"Select the desired output data type\",\n            real_time_refresh=True,\n            value=\"Message\",\n        ),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Message Output\",\n            name=\"message_output\",\n            method=\"convert_to_message\",\n        )\n    ]\n\n    def update_outputs(self, frontend_node: dict, field_name: str, field_value: Any) -> dict:\n        \"\"\"Dynamically show only the relevant output based on the selected output type.\"\"\"\n        if field_name == \"output_type\":\n            # Start with empty outputs\n            frontend_node[\"outputs\"] = []\n\n            # Add only the selected output type\n            if field_value == \"Message\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"Message Output\",\n                        name=\"message_output\",\n                        method=\"convert_to_message\",\n                    ).to_dict()\n                )\n            elif field_value == \"Data\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"Data Output\",\n                        name=\"data_output\",\n                        method=\"convert_to_data\",\n                    ).to_dict()\n                )\n            elif field_value == \"DataFrame\":\n                frontend_node[\"outputs\"].append(\n                    Output(\n                        display_name=\"DataFrame Output\",\n                        name=\"dataframe_output\",\n                        method=\"convert_to_dataframe\",\n                    ).to_dict()\n                )\n\n        return frontend_node\n\n    def convert_to_message(self) -> Message:\n        \"\"\"Convert input to Message type.\"\"\"\n        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data\n\n        # Handle string input by converting to Message first\n        if isinstance(input_value, str):\n            input_value = Message(text=input_value)\n\n        return convert_to_message(input_value)\n\n    def convert_to_data(self) -> Data:\n        \"\"\"Convert input to Data type.\"\"\"\n        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data\n\n        # Handle string input by converting to Message first\n        if isinstance(input_value, str):\n            input_value = Message(text=input_value)\n\n        return convert_to_data(input_value)\n\n    def convert_to_dataframe(self) -> DataFrame:\n        \"\"\"Convert input to DataFrame type.\"\"\"\n        input_value = self.input_data[0] if isinstance(self.input_data, list) else self.input_data\n\n        # Handle string input by converting to Message first\n        if isinstance(input_value, str):\n            input_value = Message(text=input_value)\n\n        return convert_to_dataframe(input_value)\n"
               },
               "input_data": {
                 "_input_type": "HandleInput",