> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc-agui.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Agentic User Input with Control Flow

> This example demonstrates how to use UserControlFlowTools to allow agents to dynamically request user input when they need additional information to complete tasks.

<Steps>
  <Step title="Create a Python file">
    ```python agentic_user_input.py theme={null}
    from typing import Any, Dict, List

    from agno.agent import Agent
    from agno.db.sqlite import SqliteDb
    from agno.models.openai import OpenAIResponses
    from agno.tools import Toolkit
    from agno.tools.function import UserInputField
    from agno.tools.user_control_flow import UserControlFlowTools
    from agno.utils import pprint


    class EmailTools(Toolkit):
        def __init__(self, *args, **kwargs):
            super().__init__(
                name="EmailTools", tools=[self.send_email, self.get_emails], *args, **kwargs
            )

        def send_email(self, subject: str, body: str, to_address: str) -> str:
            """Send an email to the given address with the given subject and body.

            Args:
                subject (str): The subject of the email.
                body (str): The body of the email.
                to_address (str): The address to send the email to.
            """
            return f"Sent email to {to_address} with subject {subject} and body {body}"

        def get_emails(self, date_from: str, date_to: str) -> list[dict[str, str]]:
            """Get all emails between the given dates.

            Args:
                date_from (str): The start date (in YYYY-MM-DD format).
                date_to (str): The end date (in YYYY-MM-DD format).
            """
            return [
                {
                    "subject": "Hello",
                    "body": "Hello, world!",
                    "to_address": "test@test.com",
                    "date": date_from,
                },
                {
                    "subject": "Random other email",
                    "body": "This is a random other email",
                    "to_address": "john@doe.com",
                    "date": date_to,
                },
            ]


    agent = Agent(
        model=OpenAIResponses(id="gpt-5.2"),
        tools=[EmailTools(), UserControlFlowTools()],
        markdown=True,
        db=SqliteDb(db_file="tmp/agentic_user_input.db"),
    )

    run_response = agent.run("Send an email with the body 'What is the weather in Tokyo?'")

    # We use a while loop to continue the running until the agent is satisfied with the user input
    while run_response.is_paused:
        for requirement in run_response.active_requirements:
            if requirement.needs_user_input:
                input_schema: List[UserInputField] = requirement.user_input_schema  # type: ignore

                for field in input_schema:
                    # Get user input for each field in the schema
                    field_type = field.field_type  # type: ignore
                    field_description = field.description  # type: ignore

                    # Display field information to the user
                    print(f"\nField: {field.name}")  # type: ignore
                    print(f"Description: {field_description}")
                    print(f"Type: {field_type}")

                    # Get user input
                    if field.value is None:  # type: ignore
                        user_value = input(f"Please enter a value for {field.name}: ")  # type: ignore
                    else:
                        print(f"Value: {field.value}")  # type: ignore
                        user_value = field.value  # type: ignore

                    # Update the field value
                    field.value = user_value  # type: ignore

        run_response = agent.continue_run(
            run_id=run_response.run_id,
            requirements=run_response.requirements,
        )
        if not run_response.is_paused:
            pprint.pprint_run_response(run_response)
            break


    run_response = agent.run("Get me all my emails")

    while run_response.is_paused:
        for requirement in run_response.active_requirements:
            if requirement.needs_user_input:
                input_schema: Dict[str, Any] = requirement.user_input_schema  # type: ignore

                for field in input_schema:
                    # Get user input for each field in the schema
                    field_type = field.field_type  # type: ignore
                    field_description = field.description  # type: ignore

                    # Display field information to the user
                    print(f"\nField: {field.name}")  # type: ignore
                    print(f"Description: {field_description}")
                    print(f"Type: {field_type}")

                    # Get user input
                    if field.value is None:  # type: ignore
                        user_value = input(f"Please enter a value for {field.name}: ")  # type: ignore
                    else:
                        print(f"Value: {field.value}")  # type: ignore
                        user_value = field.value  # type: ignore

                    # Update the field value
                    field.value = user_value  # type: ignore

        run_response = agent.continue_run(
            run_id=run_response.run_id,
            requirements=run_response.requirements,
        )

        if not run_response.is_paused:
            pprint.pprint_run_response(run_response)
            break
    ```
  </Step>

  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
        export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
        $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run Agent">
    ```bash theme={null}
    python agentic_user_input.py
    ```
  </Step>
</Steps>