User Input Required All Fields

This example demonstrates how to use the requires_user_input parameter to collect input for all fields in a tool. It shows how to handle user input schema and collect values for each required field.

Code

user_input_required_all_fields.py

"""🤝 Human-in-the-Loop: Allowing users to provide input externally

This example shows how to use the `requires_user_input` parameter to allow users to provide input externally.
"""

from typing import List

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools import tool
from agno.tools.function import UserInputField
from agno.utils import pprint


@tool(requires_user_input=True)
def send_email(subject: str, body: str, to_address: str) -> str:
    """
    Send an email.

    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}"


agent = Agent(
    model=OpenAIChat(id="gpt-5-mini"),
    tools=[send_email],
    markdown=True,
)

run_response = agent.run("Send an email please")
if run_response.is_paused:  # Or agent.run_response.is_paused
    for tool in run_response.tools_requiring_user_input:  # type: ignore
        input_schema: List[UserInputField] = tool.user_input_schema  # type: ignore

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

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

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

            # Update the field value
            field.value = user_value

    run_response = agent.continue_run(run_response=run_response)
    pprint.pprint_run_response(run_response)

# Or for simple debug flow
# agent.print_response("Send an email please")

Usage

1. Create a virtual environment

   Open the Terminal and create a python virtual environment.

   Mac

   python3 -m venv .venv
   source .venv/bin/activate
   
2. Install libraries

   pip install -U agno openai
   
3. Export your OpenAI API key

   Mac/Linux

     export OPENAI_API_KEY="your_openai_api_key_here"
   
4. Create a Python file

   Create a Python file and add the above code.

   touch user_input_required_all_fields.py
   
5. Run Agent

   Mac

   python user_input_required_all_fields.py
   
6. Find All Cookbooks

   Explore all the available cookbooks in the Agno repository. Click the link below to view the code on GitHub:

   Agno Cookbooks on GitHub