example.py

"""Example usage of Minion Agent."""

import asyncio
import logging

from dotenv import load_dotenv
import os
from PIL import Image
from io import BytesIO
from time import sleep
from typing import List, Dict, Optional
from smolagents import (Tool, ChatMessage)
from smolagents.models import parse_json_if_needed
from custom_azure_model import CustomAzureOpenAIServerModel
import minion_agent
from minion_agent.config import MCPStdio, MCPSse
from minion_agent.logging import setup_logger
from minion_agent.tools.run_apple_script import run_applescript, run_applescript_capture, run_command

# Load environment variables from .env file
load_dotenv()

from minion_agent import MinionAgent, AgentConfig, AgentFramework

from minion.agents import (
    CodeAgent,
    ToolCallingAgent,

)
from minion_agent.frameworks.minion import SurrogateModel

# Configure the agent
agent_config = AgentConfig(
    model_id=os.environ.get("AZURE_DEPLOYMENT_NAME"),
    name="research_assistant",
    description="A helpful research assistant",
    model_args={"azure_endpoint": os.environ.get("AZURE_OPENAI_ENDPOINT"),
                "api_key": os.environ.get("AZURE_OPENAI_API_KEY"),
                "api_version": os.environ.get("OPENAI_API_VERSION"),
                "model": "gpt-4o",  # Actual model to use in minion framework
                },
    tools=[
      minion_agent.tools.browser_tool.browser,
      MCPStdio(
            command="npx",
            args=["-y", "@modelcontextprotocol/server-filesystem","/Users/femtozheng/workspace","/Users/femtozheng/python-project/minion-agent"]
        ),
    ],
    agent_type=CodeAgent,
)
# setup_logger(logging.DEBUG)
async def main():
    try:
        # Create and run the agent
        agent = await MinionAgent.create_async(AgentFramework.EXTERNAL_MINION_AGENT, agent_config)
        #agent = await MinionAgent.create_async(AgentFramework.TINYAGENT, agent_config)

        # Run the agent with a question
        #result = await agent.run_async("search sam altman and export summary as markdown")
        #result = await agent.run_async("What are the latest developments in AI, find this information and export as markdown")
        result = await agent.run_async("list files in current dir")
        #result = await agent.run_async("打开微信公众号")
        #result = await agent.run_async("搜索最新的人工智能发展趋势，并且总结为markdown")
        #result = agent.run("go visit https://www.baidu.com and clone it")
        #result = await agent.run_async("复刻一个电商网站,例如京东")
        #result = await agent.run_async("go visit https://www.baidu.com , take a screenshot and clone it")
        #result = await agent.run("实现一个贪吃蛇游戏")
        #result = await agent.run_async("Let $\mathcal{B}$ be the set of rectangular boxes with surface area $54$ and volume $23$. Let $r$ be the radius of the smallest sphere that can contain each of the rectangular boxes that are elements of $\mathcal{B}$. The value of $r^2$ can be written as $\frac{p}{q}$, where $p$ and $q$ are relatively prime positive integers. Find $p+q$.")
        #result = await agent.run_async("使用apple script帮我看一下微信上发给'新智元 ASI' hello")
        #result = await agent.run_async("使用apple script帮我添加一个note, 明天早上8:00我要锻炼，并且添加到提醒, 并且发信给femtowin@gmail.com")
        #result = await agent.run_async("提醒今晚9:15鼠标要充电")
        # result = await agent.run_async("Write a 500000 characters novel named 'Reborn in Skyrim'. "
        #       "Fill the empty nodes with your own ideas. Be creative! Use your own words!"
        #       "I will tip you $100,000 if you write a good novel."
        #       "Since the novel is very long, you may need to divide it into subtasks.")
        print("Agent's response:", result.final_output.content)
        #await agent.close()
        print("done")

    except Exception as e:
        print(f"Error: {str(e)}")
        import traceback
        traceback.print_exc()
        # 如果需要调试
        # import litellm
        # litellm._turn_on_debug()
        raise

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