Code

cookbook/agent_concepts/user_control_flows/external_tool_execution_stream.py
import subprocess

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

@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-4o-mini"),
    tools=[execute_shell_command],
    markdown=True,
)

for run_response in agent.run(
    "What files do I have in my current directory?", stream=True
):
    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)
                # We have to set the result on the tool execution object so that the agent can continue
                tool.result = result

        run_response = agent.continue_run(run_response=run_response, stream=True)
        pprint.pprint_run_response(run_response)

Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.

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

Set your API key

export OPENAI_API_KEY=xxx
3

Install libraries

pip install -U agno openai
4

Run Example

python cookbook/agent_concepts/user_control_flows/external_tool_execution_stream.py

Key Features

  • Uses agent.run(stream=True) for streaming responses
  • Implements streaming continuation with agent.continue_run(stream=True)
  • Maintains real-time interaction with external tool execution
  • Demonstrates how to handle streaming responses with external tools

Use Cases

  • Real-time external tool execution
  • Streaming applications with external service calls
  • Interactive interfaces with external tool execution
  • Progressive response generation with external tools