[Feature Request] Integration of Agent Protocol from AI-Engineer-Foundation into Langflow about langflow HOT 2 OPEN

Hey

That's a good idea!

We have created a new way building a Component and we could adapt the components we have now to support this.

Here's how the ChatInput looks in the new format. What do you think?

from langflow.base.io.chat import ChatComponent
from langflow.field_typing import Text
from langflow.schema import Record
from langflow.template import Input, Output


class ChatInput(ChatComponent):
    display_name = "Chat Input"
    description = "Get chat inputs from the Playground."
    icon = "ChatInput"

    inputs = [
        Input(
            name="input_value",
            type=str,
            display_name="Message",
            multiline=True,
            input_types=[],
            info="Message to be passed as input.",
        ),
        Input(
            name="sender",
            type=str,
            display_name="Sender Type",
            options=["Machine", "User"],
            value="User",
            info="Type of sender.",
            advanced=True,
        ),
        Input(name="sender_name", type=str, display_name="Sender Name", info="Name of the sender.", value="User"),
        Input(
            name="session_id", type=str, display_name="Session ID", info="Session ID for the message.", advanced=True
        ),
    ]
    outputs = [
        Output(display_name="Message", name="message", method="text_response"),
        Output(display_name="Record", name="record", method="record_response"),
    ]

    def text_response(self) -> Text:
        result = self.input_value
        if self.session_id and isinstance(result, (Record, str)):
            self.store_message(result, self.session_id, self.sender, self.sender_name)
        return result

    def record_response(self) -> Record:
        record = Record(
            data={
                "text": self.input_value,
                "sender": self.sender,
                "sender_name": self.sender_name,
                "session_id": self.session_id,
            },
        )
        if self.session_id and isinstance(record, (Record, str)):
            self.store_message(record, self.session_id, self.sender, self.sender_name)
        return record

from langflow.

Hey

That's a good idea!

We have created a new way building a Component and we could adapt the components we have now to support this.

Here's how the ChatInput looks in the new format. What do you think?

from langflow.base.io.chat import ChatComponent
from langflow.field_typing import Text
from langflow.schema import Record
from langflow.template import Input, Output


class ChatInput(ChatComponent):
    display_name = "Chat Input"
    description = "Get chat inputs from the Playground."
    icon = "ChatInput"

    inputs = [
        Input(
            name="input_value",
            type=str,
            display_name="Message",
            multiline=True,
            input_types=[],
            info="Message to be passed as input.",
        ),
        Input(
            name="sender",
            type=str,
            display_name="Sender Type",
            options=["Machine", "User"],
            value="User",
            info="Type of sender.",
            advanced=True,
        ),
        Input(name="sender_name", type=str, display_name="Sender Name", info="Name of the sender.", value="User"),
        Input(
            name="session_id", type=str, display_name="Session ID", info="Session ID for the message.", advanced=True
        ),
    ]
    outputs = [
        Output(display_name="Message", name="message", method="text_response"),
        Output(display_name="Record", name="record", method="record_response"),
    ]

    def text_response(self) -> Text:
        result = self.input_value
        if self.session_id and isinstance(result, (Record, str)):
            self.store_message(result, self.session_id, self.sender, self.sender_name)
        return result

    def record_response(self) -> Record:
        record = Record(
            data={
                "text": self.input_value,
                "sender": self.sender,
                "sender_name": self.sender_name,
                "session_id": self.session_id,
            },
        )
        if self.session_id and isinstance(record, (Record, str)):
            self.store_message(record, self.session_id, self.sender, self.sender_name)
        return record

@ogabrielluiz Hello!,

Thank you for the response. I was in the middle of development, and this is exactly the structure I was looking for!

Managing INPUT and OUTPUT as templates in this manner should make it easy to connect with various solutions, not just Agent Protocol.

It seems like there's someone trying to integrate Agent Protocol with Langchain and is currently working on it, but instead of waiting for that work, considering future integration with solutions like Lammaindex, Langflow itself will need IO templates that are integrated as templates.

(You came up with a great idea at the perfect time!)

Additionally, in the case of Agent Protocol, there is a concept of adding or downloading files as artifacts. This structure should also be predefined in the parent ChatComponent.

At this stage, since it seems like only the AUTOGPT team is actively integrating the Agent Protocol client, the structure needed for the artifact concept might not be immediately necessary.

from langflow.