3.基于MetaGPT构建单Agent.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 环境配置\n",
    "我们clone MetaGPT项目到本地进行研究：\n",
    "```bash\n",
    "!git clone https://github.com/geekan/MetaGPT.git\n",
    "!cd MetaGPT\n",
    "!pip install -e .\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cloning into 'MetaGPT'...\n",
      "remote: Enumerating objects: 32223, done.\u001b[K\n",
      "remote: Counting objects: 100% (41/41), done.\u001b[K\n",
      "remote: Compressing objects: 100% (33/33), done.\u001b[K\n",
      "remote: Total 32223 (delta 20), reused 13 (delta 8), pack-reused 32182\u001b[K\n",
      "Receiving objects: 100% (32223/32223), 92.49 MiB | 12.40 MiB/s, done.\n",
      "Resolving deltas: 100% (24132/24132), done.\n"
     ]
    }
   ],
   "source": [
    "!git clone https://github.com/geekan/MetaGPT.git\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dockerfile   README.md\t  docs\t    requirements.txt  tests\n",
      "LICENSE      SECURITY.md  examples  ruff.toml\n",
      "MANIFEST.in  config\t  metagpt   setup.py\n"
     ]
    }
   ],
   "source": [
    "!cd ./MetaGPT/\n",
    "!dir ./MetaGPT/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Obtaining file:///workspaces/MetaGPT-Learn/MetaGPT\n",
      "  Installing build dependencies ... \u001b[?25ldone\n",
      "\u001b[?25h  Checking if build backend supports build_editable ... \u001b[?25ldone\n",
      "\u001b[?25h  Getting requirements to build editable ... \u001b[?25ldone\n",
      "\u001b[?25h  Installing backend dependencies ... \u001b[?25ldone\n",
      "\u001b[?25h  Preparing editable metadata (pyproject.toml) ... \u001b[?25ldone\n",
      "\u001b[?25hRequirement already satisfied: aiohttp==3.8.6 in /usr/local/python/3.10.13/lib/python3.10/site-packages (from metagpt==0.8.1) (3.8.6)\n",
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      "Collecting typer==0.9.0 (from metagpt==0.8.1)\n",
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      "Requirement already satisfied: MarkupSafe>=2.1.1 in /home/codespace/.local/lib/python3.10/site-packages (from werkzeug->openapi_core<0.19.0,>=0.18.0->semantic-kernel==0.4.3.dev0->metagpt==0.8.1) (2.1.5)\n",
      "Using cached typer-0.9.0-py3-none-any.whl (45 kB)\n",
      "Using cached urllib3-1.26.18-py2.py3-none-any.whl (143 kB)\n",
      "Building wheels for collected packages: metagpt\n",
      "  Building editable for metagpt (pyproject.toml) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for metagpt: filename=metagpt-0.8.1-0.editable-py3-none-any.whl size=9177 sha256=8c056108c85398c0646c5eb8e3171908b336cda7d67259075748d9b71ce66dc1\n",
      "  Stored in directory: /tmp/pip-ephem-wheel-cache-8b_d3_k3/wheels/fc/8a/52/7a1c7d27adf6344504c52041d73fee26e3453f0630f1631db9\n",
      "Successfully built metagpt\n",
      "Installing collected packages: urllib3, typer, metagpt\n",
      "  Attempting uninstall: urllib3\n",
      "    Found existing installation: urllib3 2.2.1\n",
      "    Uninstalling urllib3-2.2.1:\n",
      "      Successfully uninstalled urllib3-2.2.1\n",
      "  Attempting uninstall: typer\n",
      "    Found existing installation: typer 0.12.3\n",
      "    Uninstalling typer-0.12.3:\n",
      "      Successfully uninstalled typer-0.12.3\n",
      "  Attempting uninstall: metagpt\n",
      "    Found existing installation: metagpt 0.8.1\n",
      "    Uninstalling metagpt-0.8.1:\n",
      "      Successfully uninstalled metagpt-0.8.1\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "fastapi-cli 0.0.3 requires typer>=0.12.3, but you have typer 0.9.0 which is incompatible.\n",
      "types-requests 2.31.0.20240406 requires urllib3>=2, but you have urllib3 1.26.18 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0mSuccessfully installed metagpt-0.8.1 typer-0.9.0 urllib3-1.26.18\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install --upgrade -e ./MetaGPT/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 配置API Key,打开/MetaGPT/config/config2.yaml\n",
    "- 然后填写自己的请求接口和API Key，作者这里使用的是deepseek的模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Hello! How can I assist you today? If you have any questions or need information on a specific topic, feel free to ask.\n"
     ]
    }
   ],
   "source": [
    "# 测试一下接口\n",
    "from openai import OpenAI\n",
    "\n",
    "client = OpenAI(api_key=\"sk-6XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX74\", base_url=\"https://api.deepseek.com\")\n",
    "\n",
    "response = client.chat.completions.create(\n",
    "    model=\"deepseek-chat\",\n",
    "    messages=[\n",
    "        {\"role\": \"system\", \"content\": \"You are a helpful assistant\"},\n",
    "        {\"role\": \"user\", \"content\": \"Hello\"},\n",
    "    ],\n",
    "    stream=False\n",
    ")\n",
    "\n",
    "# 运行正常没有问题\n",
    "print(response.choices[0].message.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  编写CodeWrite动作\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-05-15 18:11:36.284 | INFO     | metagpt.const:get_metagpt_package_root:29 - Package root set to /workspaces/MetaGPT-Learn/MetaGPT\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "import asyncio\n",
    "from metagpt.actions import Action\n",
    "\n",
    "class CodeWrite(Action):\n",
    "    PROMPT_TEMPLATE: str = \"\"\"\n",
    "    根据以下需求，编写一个能够实现{requirements}的Python函数，并提供两个可运行的测试用例。\n",
    "    返回的格式为：```python\\n你的代码\\n```，请不要包含其他的文本。\n",
    "    ```python\n",
    "    # your code here\n",
    "    ```\n",
    "    \"\"\"\n",
    "\n",
    "    name: str = \"CodeWriter\"\n",
    "\n",
    "    async def run(self, requirements: str):\n",
    "        prompt = self.PROMPT_TEMPLATE.format(requirements=requirements)\n",
    "        rsp = await self._aask(prompt)\n",
    "        code_text = CodeWrite.parse_code(rsp)\n",
    "        return code_text\n",
    "\n",
    "    @staticmethod\n",
    "    def parse_code(rsp): # 从模型生成中字符串匹配提取生成的代码\n",
    "        pattern = r'```python(.*?)```'  # 使用非贪婪匹配\n",
    "        match = re.search(pattern, rsp, re.DOTALL)\n",
    "        code_text = match.group(1) if match else rsp\n",
    "        return code_text"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 设计CodeWriterAgent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from metagpt.roles import Role\n",
    "from metagpt.schema import Message\n",
    "from metagpt.logs import logger\n",
    "\n",
    "class CodeWriter(Role):\n",
    "    \"\"\"\n",
    "    CodeWriter 角色类，继承自 Role 基类\n",
    "    \"\"\"\n",
    "\n",
    "    name: str = \"Cheems\"  # 角色昵称\n",
    "    profile: str = \"CodeWriter\"  # 角色人设\n",
    "\n",
    "    def __init__(self, **kwargs):\n",
    "        \"\"\"\n",
    "        初始化 CodeWriter 角色\n",
    "        \"\"\"\n",
    "        super().__init__(**kwargs)  # 调用基类构造函数\n",
    "        self.set_actions([CodeWrite])  # 为角色配备 CodeWrite 动作\n",
    "\n",
    "    async def _act(self) -> Message:\n",
    "        \"\"\"\n",
    "        定义角色行动逻辑\n",
    "        \"\"\"\n",
    "        logger.info(f\"{self._setting}: ready to {self.rc.todo}\")  # 记录日志\n",
    "        todo = self.rc.todo  # 获取待执行的动作 (CodeWriter)\n",
    "\n",
    "        msg = self.get_memories(k=1)[0]  # 获取最近一条记忆 (用户输入)\n",
    "\n",
    "        code_text = await todo.run(msg.content)  # 执行 CodeWrite 动作，获取生成的代码\n",
    "        msg = Message(content=code_text, role=self.profile, cause_by=type(todo))  # 构造 Message 对象\n",
    "\n",
    "        return msg  # 返回生成的 Message"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 运行测试CodeWriterAgent调用效果\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/codespace/.python/current/lib/python3.10/ast.py:50: RuntimeWarning: coroutine 'main' was never awaited\n",
      "  return compile(source, filename, mode, flags,\n",
      "RuntimeWarning: Enable tracemalloc to get the object allocation traceback\n"
     ]
    },
    {
     "ename": "RuntimeError",
     "evalue": "Cannot close a running event loop",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[7], line 14\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;66;03m# asyncio.run(main()) # 异步运行main函数 # 正常python文件使用\u001b[39;00m\n\u001b[1;32m     11\u001b[0m \n\u001b[1;32m     12\u001b[0m \u001b[38;5;66;03m# 获取当前事件循环\u001b[39;00m\n\u001b[1;32m     13\u001b[0m loop \u001b[38;5;241m=\u001b[39m asyncio\u001b[38;5;241m.\u001b[39mget_event_loop() \u001b[38;5;66;03m# jupyter notebook中使用\u001b[39;00m\n\u001b[0;32m---> 14\u001b[0m \u001b[43mloop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclose\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     16\u001b[0m \u001b[38;5;66;03m# 在当前事件循环中运行协程\u001b[39;00m\n\u001b[1;32m     17\u001b[0m \u001b[38;5;66;03m#loop.run_until_complete(main()) # jupyter notebook中使用\u001b[39;00m\n\u001b[1;32m     18\u001b[0m \n\u001b[1;32m     19\u001b[0m \u001b[38;5;66;03m# 创建一个新的事件循环\u001b[39;00m\n\u001b[1;32m     20\u001b[0m new_loop \u001b[38;5;241m=\u001b[39m asyncio\u001b[38;5;241m.\u001b[39mnew_event_loop()\n",
      "File \u001b[0;32m~/.python/current/lib/python3.10/asyncio/unix_events.py:68\u001b[0m, in \u001b[0;36m_UnixSelectorEventLoop.close\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     67\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mclose\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m---> 68\u001b[0m     \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclose\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     69\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m sys\u001b[38;5;241m.\u001b[39mis_finalizing():\n\u001b[1;32m     70\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m sig \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mlist\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_signal_handlers):\n",
      "File \u001b[0;32m~/.python/current/lib/python3.10/asyncio/selector_events.py:84\u001b[0m, in \u001b[0;36mBaseSelectorEventLoop.close\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     82\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mclose\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m     83\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mis_running():\n\u001b[0;32m---> 84\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCannot close a running event loop\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     85\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mis_closed():\n\u001b[1;32m     86\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m\n",
      "\u001b[0;31mRuntimeError\u001b[0m: Cannot close a running event loop"
     ]
    }
   ],
   "source": [
    "import asyncio\n",
    "\n",
    "async def main():\n",
    "    msg = \"如何用python获取最新的股票统计数据？\"\n",
    "    role = CodeWriter() # 实例化CodeWrite\n",
    "    logger.info(msg) # 记录日志信息\n",
    "    result = await role.run(msg) # 得到运行结果\n",
    "    logger.info(result) # 记录运行结果\n",
    "\n",
    "asyncio.run(main()) # 异步运行main函数 # 正常python文件使用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-05-15 18:21:09.414 | INFO     | metagpt.const:get_metagpt_package_root:29 - Package root set to /workspaces/MetaGPT-Learn/MetaGPT\n"
     ]
    },
    {
     "ename": "RuntimeError",
     "evalue": "asyncio.run() cannot be called from a running event loop",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[1], line 72\u001b[0m\n\u001b[1;32m     69\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m role\u001b[38;5;241m.\u001b[39mrun(msg) \u001b[38;5;66;03m# 得到运行结果\u001b[39;00m\n\u001b[1;32m     70\u001b[0m     logger\u001b[38;5;241m.\u001b[39minfo(result) \u001b[38;5;66;03m# 记录运行结果\u001b[39;00m\n\u001b[0;32m---> 72\u001b[0m \u001b[43masyncio\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmain\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# 异步运行main函数 # 正常python文件使用\u001b[39;00m\n",
      "File \u001b[0;32m~/.python/current/lib/python3.10/asyncio/runners.py:33\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(main, debug)\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Execute the coroutine and return the result.\u001b[39;00m\n\u001b[1;32m     10\u001b[0m \n\u001b[1;32m     11\u001b[0m \u001b[38;5;124;03mThis function runs the passed coroutine, taking care of\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     30\u001b[0m \u001b[38;5;124;03m    asyncio.run(main())\u001b[39;00m\n\u001b[1;32m     31\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m     32\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m events\u001b[38;5;241m.\u001b[39m_get_running_loop() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 33\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m     34\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124masyncio.run() cannot be called from a running event loop\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     36\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m coroutines\u001b[38;5;241m.\u001b[39miscoroutine(main):\n\u001b[1;32m     37\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma coroutine was expected, got \u001b[39m\u001b[38;5;132;01m{!r}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(main))\n",
      "\u001b[0;31mRuntimeError\u001b[0m: asyncio.run() cannot be called from a running event loop"
     ]
    }
   ],
   "source": [
    "import re\n",
    "import asyncio\n",
    "from metagpt.actions import Action\n",
    "from metagpt.roles import Role\n",
    "from metagpt.schema import Message\n",
    "from metagpt.logs import logger\n",
    "\n",
    "class CodeWrite(Action):\n",
    "    PROMPT_TEMPLATE: str = \"\"\"\n",
    "    根据以下需求，编写一个能够实现{requirements}的Python函数，并提供两个可运行的测试用例。\n",
    "    返回的格式为：```python\\n你的代码\\n```，请不要包含其他的文本。\n",
    "    ```python\n",
    "    # your code here\n",
    "    ```\n",
    "    \"\"\"\n",
    "\n",
    "    name: str = \"CodeWriter\"\n",
    "\n",
    "    async def run(self, requirements: str):\n",
    "        prompt = self.PROMPT_TEMPLATE.format(requirements=requirements)\n",
    "        rsp = await self._aask(prompt)\n",
    "        code_text = CodeWrite.parse_code(rsp)\n",
    "        return code_text\n",
    "\n",
    "    @staticmethod\n",
    "    def parse_code(rsp): # 从模型生成中字符串匹配提取生成的代码\n",
    "        pattern = r'```python(.*?)```'  # 使用非贪婪匹配\n",
    "        match = re.search(pattern, rsp, re.DOTALL)\n",
    "        code_text = match.group(1) if match else rsp\n",
    "        return code_text\n",
    "\n",
    "class CodeWriter(Role):\n",
    "    \"\"\"\n",
    "    CodeWriter 角色类，继承自 Role 基类\n",
    "    \"\"\"\n",
    "\n",
    "    name: str = \"Cheems\"  # 角色昵称\n",
    "    profile: str = \"CodeWriter\"  # 角色人设\n",
    "\n",
    "    def __init__(self, **kwargs):\n",
    "        \"\"\"\n",
    "        初始化 CodeWriter 角色\n",
    "        \"\"\"\n",
    "        super().__init__(**kwargs)  # 调用基类构造函数\n",
    "        self.set_actions([CodeWrite])  # 为角色配备 CodeWrite 动作\n",
    "\n",
    "    async def _act(self) -> Message:\n",
    "        \"\"\"\n",
    "        定义角色行动逻辑\n",
    "        \"\"\"\n",
    "        logger.info(f\"{self._setting}: ready to {self.rc.todo}\")  # 记录日志\n",
    "        todo = self.rc.todo  # 获取待执行的动作 (CodeWriter)\n",
    "\n",
    "        msg = self.get_memories(k=1)[0]  # 获取最近一条记忆 (用户输入)\n",
    "\n",
    "        code_text = await todo.run(msg.content)  # 执行 CodeWrite 动作，获取生成的代码\n",
    "        msg = Message(content=code_text, role=self.profile, cause_by=type(todo))  # 构造 Message 对象\n",
    "\n",
    "        return msg  # 返回生成的 Message\n",
    "\n",
    "async def main():\n",
    "    msg = \"如何用python获取最新的股票统计数据？\"\n",
    "    role = CodeWriter() # 实例化CodeWrite\n",
    "    logger.info(msg) # 记录日志信息\n",
    "    result = await role.run(msg) # 得到运行结果\n",
    "    logger.info(result) # 记录运行结果\n",
    "\n",
    "asyncio.run(main()) # 异步运行main函数 # 正常python文件使用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构建多动作Agent\n",
    "import re\n",
    "import asyncio\n",
    "import subprocess\n",
    "from metagpt.actions import Action\n",
    "from metagpt.roles import Role\n",
    "from metagpt.schema import Message\n",
    "from metagpt.logs import logger\n",
    "\n",
    "# 代码撰写Action\n",
    "class CodeWrite(Action):\n",
    "    PROMPT_TEMPLATE: str = \"\"\"\n",
    "    根据以下需求，编写一个能够实现{requirements}的Python函数，并提供两个可运行的测试用例。\n",
    "    返回的格式为：```python\\n你的代码\\n```，请不要包含其他的文本。\n",
    "    ```python\n",
    "    # your code here\n",
    "    ```\n",
    "    \"\"\"\n",
    "\n",
    "    name: str = \"CodeWriter\"\n",
    "\n",
    "    async def run(self, requirements: str):\n",
    "        prompt = self.PROMPT_TEMPLATE.format(requirements=requirements)\n",
    "        rsp = await self._aask(prompt)\n",
    "        code_text = CodeWrite.parse_code(rsp)\n",
    "        return code_text\n",
    "\n",
    "    @staticmethod\n",
    "    def parse_code(rsp): # 从模型生成中字符串匹配提取生成的代码\n",
    "        pattern = r'```python(.*?)```'  # 使用非贪婪匹配\n",
    "        match = re.search(pattern, rsp, re.DOTALL)\n",
    "        code_text = match.group(1) if match else rsp\n",
    "        return code_text\n",
    "\n",
    "\n",
    "# 需求优化Action\n",
    "class RequirementsOpt(Action):\n",
    "    PROMPT_TEMPLATE: str = \"\"\"\n",
    "    你要遵守的规范有：\n",
    "    1.简要说明 (Brief Description)\n",
    "　　简要介绍该用例的作用和目的。\n",
    "　　2.事件流 (Flow of Event)\n",
    "　　包括基本流和备选流，事件流应该表示出所有的场景。\n",
    "　　3.用例场景 (Use-Case Scenario)\n",
    "　　包括成功场景和失败场景，场景主要是由基本流和备选流组合而成的。\n",
    "　　4.特殊需求 (Special Requirement)\n",
    "　　描述与该用例相关的非功能性需求（包括性能、可靠性、可用性和可扩展性等）和设计约束（所使用的操作系统、开发工具等）。\n",
    "　　5.前置条件 (Pre-Condition)\n",
    "　　执行用例之前系统必须所处的状态。\n",
    "　　6.后置条件 (Post-Condition)\n",
    "　　用例执行完毕后系统可能处于的一组状态。\n",
    "　　请优化以下需求，使其更加明确和全面：\n",
    "    {requirements}\n",
    "    \"\"\"\n",
    "\n",
    "    name: str = \"RequirementsOpt\"\n",
    "\n",
    "    async def run(self, requirements: str):\n",
    "        prompt = self.PROMPT_TEMPLATE.format(requirements=requirements)\n",
    "        rsp = await self._aask(prompt)\n",
    "        return rsp.strip()  # 返回优化后的需求\n",
    "\n",
    "\n",
    "# 代码运行Action\n",
    "class CodeRun(Action):\n",
    "    name: str = \"CodeRun\"\n",
    "\n",
    "    async def run(self, code_text: str):\n",
    "        try:\n",
    "            result = subprocess.run(\n",
    "                ['python', '-c', code_text],\n",
    "                text=True,\n",
    "                capture_output=True,\n",
    "                check=True\n",
    "            )\n",
    "            return result.stdout\n",
    "        except subprocess.CalledProcessError as e:\n",
    "            return e.stderr\n",
    "\n",
    "\n",
    "# 设计Programmer Agent人设\n",
    "class Programmer(Role):\n",
    "    \"\"\"\n",
    "    Programmer 角色类，继承自 Role 基类\n",
    "    \"\"\"\n",
    "\n",
    "    name: str = \"cheems\"\n",
    "    profile: str = \"Programmer\"\n",
    "\n",
    "    def __init__(self, **kwargs):\n",
    "        \"\"\"\n",
    "        初始化 Programmer 角色\n",
    "        \"\"\"\n",
    "        super().__init__(**kwargs)  # 调用基类构造函数\n",
    "        self.set_actions([RequirementsOpt, CodeWrite, CodeRun])  # 为角色配备三个动作\n",
    "        self._set_react_mode(react_mode=\"by_order\") # 顺序执行\n",
    "\n",
    "    async def _act(self) -> Message:\n",
    "        \"\"\"\n",
    "        定义角色行动逻辑\n",
    "        \"\"\"\n",
    "        logger.info(f\"{self._setting}: 准备 {self.rc.todo}\")  # 记录日志\n",
    "        todo = self.rc.todo  # 按照排列顺序获取待执行的动作\n",
    "\n",
    "        msg = self.get_memories(k=1)[0]  # 获取最相似的一条记忆 (用户输入)\n",
    "\n",
    "        # 优化需求》编写代码》运行代码\n",
    "        result = await todo.run(msg.content)\n",
    "\n",
    "        # 构造 Message 对象\n",
    "        msg = Message(content=result, role=self.profile, cause_by=type(todo))\n",
    "        self.rc.memory.add(msg) # 将运行结果添加到记忆\n",
    "\n",
    "        return msg  # 返回最终的 Message\n",
    "        \n",
    "# 运行我们的Agent\n",
    "async def main():\n",
    "    msg = \"如何用python爬取每日新闻数据？要求不使用API，安装包的代码要直接在python代码中运行，而非手动输入cmd;\"\n",
    "    role = Programmer()  # 实例化 Programmer\n",
    "    logger.info(msg)  # 记录日志信息\n",
    "    result = await role.run(msg)  # 得到运行结果\n",
    "    logger.info(result)  # 记录运行结果\n",
    "\n",
    "asyncio.run(main())  # 异步运行 main 函数"
   ]
  }
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