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Code

cookbook/agent_concepts/user_control_flows/confirmation_required_stream.py
import json

import httpx
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools import tool
from agno.utils import pprint
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=OpenAIChat(id="gpt-4o-mini"),
    tools=[get_top_hackernews_stories],
    markdown=True,
)

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

            if message == "n":
                tool.confirmed = False
            else:
                # We update the tools in place
                tool.confirmed = True
        run_response = agent.continue_run(
            run_id=agent.run_response.run_id,
            updated_tools=agent.run_response.tools,
            stream=True,
        )
        pprint.pprint_run_response(run_response)

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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 httpx rich openai
4

Run Example

python cookbook/agent_concepts/user_control_flows/confirmation_required_stream.py

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Key Features

  • Uses agent.run(stream=True) for streaming responses
  • Implements streaming continuation with agent.continue_run(stream=True)
  • Maintains real-time interaction with user confirmation
  • Demonstrates how to handle streaming responses with user input

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Use Cases

  • Real-time user interaction
  • Streaming applications requiring user input
  • Interactive chat interfaces
  • Progressive response generation