Does DevUI accept HITL input from the UI?

[TWebster]

I tried a simple example to find out if the UI can take HITL input from a step in the middle of workflow instead of the start, and wasn’t able to do this. Is this something supported by DevUI? Please see example, a slightly modified in memory example. When it runs, the user is prompted from command line, not the UI. Please note the get_human_input executor added.
Thanks

"""Example of using Agent Framework DevUI with in-memory entity registration.

This demonstrates the simplest way to serve agents and workflows as OpenAI-compatible API endpoints.
Includes both agents and a basic workflow to showcase different entity types.
"""

import logging
import os
from typing import Annotated

from dotenv import load_dotenv

from agent_framework import ChatAgent, Executor, WorkflowBuilder, WorkflowContext, executor, handler
from agent_framework.azure import AzureOpenAIChatClient
from agent_framework.devui import serve
from agent_framework._workflows._agent_executor import AgentExecutorResponse
from typing_extensions import Never

class UpperCase(Executor):
    """Convert text to uppercase."""

    @handler
    async def to_upper(self, text: str, ctx: WorkflowContext[str]) -> None:
        """Convert input to uppercase and forward to next executor."""
        result = text.upper()
        await ctx.send_message(result)


class AddExclamation(Executor):
    """Add exclamation mark to text."""

    @handler
    async def add_exclamation(self, text: str, ctx: WorkflowContext[str]) -> None:
        """Add exclamation and send to next executor."""
        result = f"{text}!"
        await ctx.send_message(result)


@executor(id="human_input")
async def get_human_input(text: str, ctx: WorkflowContext[str]) -> None:
    """Get user input to continue the conversation.

    Prompts the user to provide text input and sends it downstream.
    """
    user_input = input(f"Agent response: {text}\nEnter your response: ")  # noqa: ASYNC250
    if user_input.strip():
        await ctx.send_message(user_input)
    else:
        await ctx.send_message(text)


@executor(id="parse_agent_response")
async def parse_agent_response(response: AgentExecutorResponse, ctx: WorkflowContext[str]) -> None:
    """Parse AgentExecutorResponse into a string for human input."""
    text = response.agent_run_response.text
    await ctx.send_message(text)


    simple_agent = ChatAgent(
        name="general-assistant",
        description="A simple conversational agent",
        instructions="You are a helpful assistant.",
        chat_client=model_client,
    )

    # Create a basic workflow: Input -> UpperCase -> AddExclamation -> SimpleAgent -> ParseResponse -> HumanInput -> SimpleAgent (loop)
    basic_workflow = (
        WorkflowBuilder(
            name="Text Transformer",
            description="Workflow that converts text to uppercase, adds exclamation, then processes with agent with human feedback loop",
        )
        .register_executor(lambda: UpperCase(id="upper_case"), name="upper_case")
        .register_executor(lambda: AddExclamation(id="add_exclamation"), name="add_exclamation")
        .register_agent(lambda: simple_agent, name="simple_agent")
        .register_executor(lambda: parse_agent_response, name="parse_agent_response")
        .register_executor(lambda: get_human_input, name="human_input")
        .set_start_executor("upper_case")
        .add_edge("upper_case", "add_exclamation")
        .add_edge("add_exclamation", "simple_agent")
        .add_edge("simple_agent", "parse_agent_response")
        .add_edge("parse_agent_response", "human_input")
        .add_edge("human_input", "simple_agent")
        .build()
    )

    # Collect entities for serving
    entities = [weather_agent, simple_agent, basic_workflow]

    # Launch server with auto-generated entity IDs
    serve(entities=entities, port=8090, auto_open=True)


if __name__ == "__main__":
    main()

[moonbox3]

Hi @TWebster, thanks for the question. Your current code relies on input(), which is a blocking console operation and won't work with DevUI's web interface. For human-in-the-loop scenarios, you'll want to use our request/response pattern instead. See our "Requests and Responses" documentation for how to implement this.

[pjirsa]

The spam_workflow sample gives an example of HITL with DevUI.