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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 项目名称\n",
    "\n",
    "## 项目简介\n",
    "简要介绍项目的目标和功能\n",
    "\n",
    "## 作者信息\n",
    "- 姓名：XXX\n",
    "- GitHub：@XXX\n",
    "- 日期：2025-XX-XX"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第1部分：环境配置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 安装依赖（如果需要）\n",
    "# !pip install -q hello-agents[all]\n",
    "\n",
    "# 导入必要的库\n",
    "from hello_agents import SimpleAgent, HelloAgentsLLM\n",
    "from hello_agents.tools import BaseTool\n",
    "import os\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "# 加载环境变量\n",
    "load_dotenv()\n",
    "\n",
    "print(\"✅ 环境配置完成\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第2部分：工具定义"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class CustomTool(BaseTool):\n",
    "    \"\"\"自定义工具类\"\"\"\n",
    "    \n",
    "    name = \"tool_name\"\n",
    "    description = \"工具描述\"\n",
    "    \n",
    "    def run(self, query: str) -> str:\n",
    "        \"\"\"工具执行逻辑\"\"\"\n",
    "        # 实现你的工具逻辑\n",
    "        return f\"处理结果：{query}\"\n",
    "\n",
    "print(\"✅ 工具定义完成\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第3部分：智能体构建"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 创建LLM\n",
    "llm = HelloAgentsLLM()\n",
    "\n",
    "# 定义系统提示词\n",
    "system_prompt = \"\"\"你是一个智能助手。\n",
    "\n",
    "你的任务是：\n",
    "1. 理解用户的需求\n",
    "2. 使用合适的工具\n",
    "3. 提供有帮助的回答\n",
    "\"\"\"\n",
    "\n",
    "# 创建智能体\n",
    "agent = SimpleAgent(\n",
    "    name=\"示例智能体\",\n",
    "    llm=llm,\n",
    "    system_prompt=system_prompt\n",
    ")\n",
    "\n",
    "# 添加工具\n",
    "agent.add_tool(CustomTool())\n",
    "\n",
    "print(\"✅ 智能体构建完成\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第4部分：功能演示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 示例1：基础功能\n",
    "print(\"=== 示例1：基础功能 ===\")\n",
    "result = agent.run(\"你的测试输入\")\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 示例2：复杂场景\n",
    "print(\"\\n=== 示例2：复杂场景 ===\")\n",
    "result = agent.run(\"更复杂的测试输入\")\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第5部分：性能评估（可选）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 评估代码\n",
    "# 例如：测试准确率、响应时间等\n",
    "\n",
    "print(\"✅ 评估完成\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第6部分：总结与展望\n",
    "\n",
    "### 项目总结\n",
    "\n",
    "#### 实现的功能\n",
    "- 功能1\n",
    "- 功能2\n",
    "\n",
    "#### 遇到的挑战\n",
    "- 挑战1及解决方案\n",
    "- 挑战2及解决方案\n",
    "\n",
    "#### 未来改进方向\n",
    "- 改进1\n",
    "- 改进2"
   ]
  }
 ],
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