Tool Confirmation Required

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()


# This tool will require user confirmation before execution
@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,
    db=SqliteDb(session_table="test_session", db_file="tmp/example.db"),
)

run_response = agent.run("Fetch the top 2 hackernews stories.")

for requirement in run_response.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()
        )

        # Confirm or reject the requirement
        if message == "n":
            requirement.reject()
        else:
            requirement.confirm()


run_response = agent.continue_run(
    run_id=run_response.run_id,
    requirements=run_response.requirements,
)

# You can also pass the updated tools when continuing the run:
# run_response = agent.continue_run(
#     run_id=run_response.run_id,
#     updated_tools=run_response.tools,
# )

pprint.pprint_run_response(run_response)