External Tool Execution Stream Async

import asyncio
import subprocess

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIChat
from agno.tools import tool


# 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-4o-mini"),
    tools=[execute_shell_command],
    markdown=True,
    db=SqliteDb(session_table="test_session", db_file="tmp/example.db"),
)


async def main():
    async for run_event in agent.arun(
        "What files do I have in my current directory?", stream=True
    ):
        if run_event.is_paused:
            for requirement in run_event.active_requirements:  # type: ignore
                if requirement.needs_external_execution:
                    if (
                        requirement.tool_execution.tool_name
                        == execute_shell_command.name
                    ):
                        print(
                            f"Executing {requirement.tool_execution.tool_name} with args {requirement.tool_execution.tool_args} externally"
                        )
                        # We execute the tool ourselves. You can also execute something completely external here.
                        result = execute_shell_command.entrypoint(
                            **requirement.tool_execution.tool_args  # type: ignore
                        )  # type: ignore
                        # We have to set the result on the tool execution object so that the agent can continue
                        requirement.set_external_execution_result(result)

            async for resp in agent.acontinue_run(  # type: ignore
                run_id=run_event.run_id,
                requirements=run_event.requirements,  # type: ignore
                stream=True,
            ):
                print(resp.content, end="")
        else:
            print(run_event.content, end="")

    # Or for simple debug flow
    # agent.print_response("What files do I have in my current directory?", stream=True)


if __name__ == "__main__":
    asyncio.run(main())