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1

Create a Python file

Create a Python file for the example.
touch confirmation_required.py
2

Add the following code to your Python file

confirmation_required.py
import json
import httpx
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
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-5-mini"),
    tools=[get_top_hackernews_stories],
    markdown=True,
    db=SqliteDb(session_table="test_session", db_file="tmp/example.db"),
)

run_response = agent.run("Fetch the top 2 hackernews stories.")
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_response=run_response)
# Or
# run_response = agent.continue_run(run_id=run_response.run_id, updated_tools=run_response.tools)

pprint.pprint_run_response(run_response)


# Or for simple debug flow
# agent.print_response("Fetch the top 2 hackernews stories")
3

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
4

Install libraries

pip install -U agno openai httpx rich
5

Export your OpenAI API key

  export OPENAI_API_KEY="your_openai_api_key_here"
6

Run Agent

python confirmation_required.py
7

Find All Cookbooks

Explore all the available cookbooks in the Agno repository. Click the link below to view the code on GitHub:Agno Cookbooks on GitHub