"""🤝 Human-in-the-Loop: Execute a tool call outside of the agent
This example shows how to implement human-in-the-loop functionality in your Agno tools.
It shows how to:
- Use external tool execution to execute a tool call outside of the agent
Run `pip install openai agno` to install dependencies.
"""
import asyncio
import subprocess
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools import tool
from agno.utils import pprint
# We have to create a tool with the correct name, arguments and docstring for the agent to know what to call.
@tool(external_execution=True)
def execute_shell_command(command: str) -> str:
"""Execute a shell command.
Args:
command (str): The shell command to execute
Returns:
str: The output of the shell command
"""
if command.startswith("ls"):
return subprocess.check_output(command, shell=True).decode("utf-8")
else:
raise Exception(f"Unsupported command: {command}")
agent = Agent(
model=OpenAIChat(id="gpt-5-mini"),
tools=[execute_shell_command],
markdown=True,
)
run_response = asyncio.run(agent.arun("What files do I have in my current directory?"))
if run_response.is_paused:
for tool in run_response.tools_awaiting_external_execution:
if tool.tool_name == execute_shell_command.name:
print(f"Executing {tool.tool_name} with args {tool.tool_args} externally")
# We execute the tool ourselves. You can also execute something completely external here.
result = execute_shell_command.entrypoint(**tool.tool_args) # type: ignore
# We have to set the result on the tool execution object so that the agent can continue
tool.result = result
run_response = asyncio.run(agent.acontinue_run(run_response=run_response))
pprint.pprint_run_response(run_response)
# Or for simple debug flow
# agent.print_response("What files do I have in my current directory?")
Create a virtual environment
Terminal
and create a python virtual environment.python3 -m venv .venv
source .venv/bin/activate
Install libraries
pip install -U agno openai
Run Agent
python cookbook/agents/human_in_the_loop/external_tool_execution_async.py