此示例演示了如何在执行工具调用前要求用户确认,以实现人为干预(human-in-the-loop)功能。
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:
"""获取 Hacker News 的热门故事。
Args:
num_stories (int): 要检索的故事数量
Returns:
str: 包含故事详情的 JSON 字符串
"""
# 获取热门故事 IDs
response = httpx.get("https://hacker-news.firebaseio.com/v0/topstories.json")
story_ids = response.json()
# yield 故事详情
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,
)
agent.run("Fetch the top 2 hackernews stories.")
if agent.is_paused:
for tool in agent.run_response.tools_requiring_confirmation:
# 请求确认
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:
tool.confirmed = True
run_response = agent.continue_run()
pprint.pprint_run_response(run_response)
创建虚拟环境
打开 Terminal
并创建一个 python 虚拟环境。
python3 -m venv .venv
source .venv/bin/activate
设置您的 API 密钥
export OPENAI_API_KEY=xxx
安装库
pip install -U agno httpx rich openai
运行示例
python cookbook/agent_concepts/user_control_flows/confirmation_required.py
@tool(requires_confirmation=True)
标记需要用户确认的工具