> ## 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.

# Confirmation Required with Async Streaming

> This example demonstrates human-in-the-loop functionality with asynchronous streaming responses. It shows how to handle user confirmation during tool execution in an async environment while maintaining real-time streaming.

<Steps>
  <Step title="Create a Python file">
    ```python confirmation_required_stream_async.py theme={null}
    import asyncio
    import json

    import httpx
    from agno.agent import Agent
    from agno.db.sqlite import SqliteDb
    from agno.models.openai import OpenAIResponses
    from agno.tools import tool
    from rich.console import Console
    from rich.prompt import Prompt

    console = Console()


    @tool(requires_confirmation=True)
    def get_top_hackernews_stories(num_stories: int) -> str:
        """Fetch top stories from Hacker News.

        Args:
            num_stories (int): Number of stories to retrieve

        Returns:
            str: JSON string containing story details
        """
        # Fetch top story IDs
        response = httpx.get("https://hacker-news.firebaseio.com/v0/topstories.json")
        story_ids = response.json()

        # Yield story details
        all_stories = []
        for story_id in story_ids[:num_stories]:
            story_response = httpx.get(
                f"https://hacker-news.firebaseio.com/v0/item/{story_id}.json"
            )
            story = story_response.json()
            if "text" in story:
                story.pop("text", None)
            all_stories.append(story)
        return json.dumps(all_stories)


    agent = Agent(
        model=OpenAIResponses(id="gpt-5.2"),
        tools=[get_top_hackernews_stories],
        db=SqliteDb(session_table="test_session", db_file="tmp/example.db"),
        markdown=True,
    )


    async def main():
        async for run_event in agent.arun(
            "Fetch the top 2 hackernews stories", stream=True
        ):
            if run_event.is_paused:
                for requirement in run_event.active_requirements:
                    if requirement.needs_confirmation:
                        # Ask for confirmation
                        console.print(
                            f"Tool name [bold blue]{requirement.tool_execution.tool_name}({requirement.tool_execution.tool_args})[/] requires confirmation."
                        )
                        message = (
                            Prompt.ask(
                                "Do you want to continue?", choices=["y", "n"], default="y"
                            )
                            .strip()
                            .lower()
                        )

                        if message == "n":
                            requirement.reject()
                        else:
                            requirement.confirm()

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

        # Or for simple debug flow
        # await agent.aprint_response("Fetch the top 2 hackernews stories", stream=True)


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

    ```
  </Step>

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

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai httpx rich
    ```
  </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 confirmation_required_stream_async.py
    ```
  </Step>
</Steps>