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    "## 背景\n",
    "\n",
    "我有一个`postgresql`数据库,现在需要一个专业的数据库优化工程师,来帮我看下设计是否合理,以及如何优化.\n",
    "\n",
    "## 目标\n",
    "\n",
    "这个数据库优化工程师智能体应该具备以下能力:\n",
    "\n",
    "- [ ] 使用`claude3.7`作为模型(相当于拥有一个聪明的大脑,总是能够做出正确的决策)\n",
    "- [ ] 精通关系型数据库系统的理论知识以及`postgresql`的实现细节(知识库)\n",
    "- [ ] 能够使用`postgresql mcp server`来分析现有数据库设计(行为)\n"
   ]
  },
  {
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   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-30T15:44:44.236141Z",
     "start_time": "2025-03-30T15:44:44.223728Z"
    }
   },
   "outputs": [],
   "source": [
    "# 然后在notebook中加载\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "# 加载当前目录下的.env文件\n",
    "load_dotenv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-30T15:44:58.492402Z",
     "start_time": "2025-03-30T15:44:45.695125Z"
    }
   },
   "outputs": [],
   "source": [
    "from agno.agent import Agent, RunResponse  # noqa\n",
    "from agno.models.deepseek import DeepSeek\n",
    "\n",
    "agent = Agent(model=DeepSeek(id=\"deepseek-chat\"), markdown=True)\n",
    "\n",
    "# Get the response in a variable\n",
    "# run: RunResponse = agent.run(\"Share a 2 sentence horror story\")\n",
    "# print(run.content)\n",
    "\n",
    "# Print the response in the terminal\n",
    "agent.print_response(\"傻狗\")\n",
    "# 用jupyter的话输出有问题，妈的,转到py文件"
   ]
  }
 ],
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