2_ChatGPT的Prompt技巧公式.ipynb

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   "source": [
    "# ChatGPT的prompt技巧公式\n",
    "\n",
    "# 如何用ChatGPT绘制一个五角星？\n",
    "\n",
    "\n",
    "prompt = (角色) + 任务 + 要求 + 提示【步骤拆解、范例说明，技巧点拨等】\n",
    "\n",
    "\n",
    "\n"
   ]
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.10/site-packages/scipy/__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.5\n",
      "  warnings.warn(f\"A NumPy version >={np_minversion} and <{np_maxversion}\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello! How can I assist you today?\n",
      "register magic %%chatgpt sucessed ...\n"
     ]
    }
   ],
   "source": [
    "from torchkeras.chatgpt import ChatGPT \n",
    "api_key = None#'sk-xx'\n",
    "chatgpt = ChatGPT(api_key=api_key,\n",
    "                  max_chat_rounds=3, #支持3轮上下文连续对话\n",
    "                  temperature=0\n",
    "                 )\n"
   ]
  },
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   "cell_type": "code",
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  一，任务"
   ]
  },
  {
   "cell_type": "code",
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     "text": [
      "以下是绘制五角星的Python代码：\n",
      "\n",
      "```python\n",
      "import turtle\n",
      "\n",
      "# 创建一个画布\n",
      "canvas = turtle.Screen()\n",
      "\n",
      "# 创建一个海龟对象\n",
      "pen = turtle.Turtle()\n",
      "\n",
      "# 设置画笔颜色和填充颜色\n",
      "pen.color(\"red\", \"yellow\")\n",
      "\n",
      "# 开始填充\n",
      "pen.begin_fill()\n",
      "\n",
      "# 绘制五角星\n",
      "for i in range(5):\n",
      "    pen.forward(200)\n",
      "    pen.right(144)\n",
      "\n",
      "# 结束填充\n",
      "pen.end_fill()\n",
      "\n",
      "# 隐藏海龟\n",
      "pen.hideturtle()\n",
      "\n",
      "# 点击关闭窗口\n",
      "canvas.exitonclick()\n",
      "```\n",
      "\n",
      "运行代码后，会弹出一个窗口，里面绘制了一个红色边框、黄色填充的五角星。\n"
     ]
    }
   ],
   "source": [
    "%%chatgpt \n",
    "任务：请用Python代码绘制一个五角星。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "cell_type": "code",
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 二，任务+要求"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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     "text": [
      "以下是使用matplotlib库绘制五角星的Python代码：\n",
      "\n",
      "```python\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np\n",
      "\n",
      "# 创建一个画布\n",
      "fig, ax = plt.subplots()\n",
      "\n",
      "# 设置画布大小\n",
      "fig.set_size_inches(5, 5)\n",
      "\n",
      "# 设置线条颜色\n",
      "line_color = 'red'\n",
      "\n",
      "# 计算五角星的顶点坐标\n",
      "theta = np.linspace(0, 2*np.pi, 6)\n",
      "x = np.sin(theta)\n",
      "y = np.cos(theta)\n",
      "\n",
      "# 绘制五角星\n",
      "ax.plot(x, y, color=line_color)\n",
      "\n",
      "# 设置坐标轴范围\n",
      "ax.set_xlim(-1.2, 1.2)\n",
      "ax.set_ylim(-1.2, 1.2)\n",
      "\n",
      "# 隐藏坐标轴\n",
      "ax.axis('off')\n",
      "\n",
      "# 显示绘制结果\n",
      "plt.show()\n",
      "```\n",
      "\n",
      "运行代码后，会弹出一个窗口，里面绘制了一个红色线条的五角星。\n"
     ]
    }
   ],
   "source": [
    "%%chatgpt \n",
    "任务：请用Python代码绘制一个五角星。\n",
    "要求：请使用matplotlib这个库，线条使用红色。\n"
   ]
  },
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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# 创建一个画布\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# 设置画布大小\n",
    "fig.set_size_inches(5, 5)\n",
    "\n",
    "# 设置线条颜色\n",
    "line_color = 'red'\n",
    "\n",
    "# 计算五角星的顶点坐标\n",
    "theta = np.linspace(0, 2*np.pi, 6)\n",
    "x = np.sin(theta)\n",
    "y = np.cos(theta)\n",
    "\n",
    "# 绘制五角星\n",
    "ax.plot(x, y, color=line_color)\n",
    "\n",
    "# 设置坐标轴范围\n",
    "ax.set_xlim(-1.2, 1.2)\n",
    "ax.set_ylim(-1.2, 1.2)\n",
    "\n",
    "# 隐藏坐标轴\n",
    "ax.axis('off')\n",
    "\n",
    "# 显示绘制结果\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 三，(角色)+任务+要求"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-14T15:35:12.313834Z",
     "iopub.status.busy": "2023-05-14T15:35:12.313362Z",
     "iopub.status.idle": "2023-05-14T15:35:18.194385Z",
     "shell.execute_reply": "2023-05-14T15:35:18.192966Z",
     "shell.execute_reply.started": "2023-05-14T15:35:12.313799Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "以下是使用matplotlib库绘制五角星的Python代码：\n",
      "\n",
      "```python\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np\n",
      "\n",
      "# 创建一个画布\n",
      "fig, ax = plt.subplots()\n",
      "\n",
      "# 设置画布大小\n",
      "fig.set_size_inches(5, 5)\n",
      "\n",
      "# 设置线条颜色\n",
      "line_color = 'red'\n",
      "\n",
      "# 计算五角星的顶点坐标\n",
      "theta = np.linspace(0, 2*np.pi, 6)\n",
      "x = np.sin(theta)\n",
      "y = np.cos(theta)\n",
      "\n",
      "# 绘制五角星\n",
      "ax.plot(x, y, color=line_color)\n",
      "\n",
      "# 设置坐标轴范围\n",
      "ax.set_xlim(-1.2, 1.2)\n",
      "ax.set_ylim(-1.2, 1.2)\n",
      "\n",
      "# 隐藏坐标轴\n",
      "ax.axis('off')\n",
      "\n",
      "# 显示绘制结果\n",
      "plt.show()\n",
      "```\n",
      "\n",
      "运行代码后，会弹出一个窗口，里面绘制了一个红色线条的五角星。\n"
     ]
    }
   ],
   "source": [
    "%%chatgpt \n",
    "角色：假设你是一个擅长绘图的Python程序员。\n",
    "任务：请用Python代码绘制一个五角星。\n",
    "要求：请使用matplotlib这个库，线条使用红色。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-14T15:35:35.188482Z",
     "iopub.status.busy": "2023-05-14T15:35:35.187446Z",
     "iopub.status.idle": "2023-05-14T15:35:35.269207Z",
     "shell.execute_reply": "2023-05-14T15:35:35.267567Z",
     "shell.execute_reply.started": "2023-05-14T15:35:35.188420Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# 创建一个画布\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# 设置画布大小\n",
    "fig.set_size_inches(5, 5)\n",
    "\n",
    "# 设置线条颜色\n",
    "line_color = 'red'\n",
    "\n",
    "# 计算五角星的顶点坐标\n",
    "theta = np.linspace(0, 2*np.pi, 6)\n",
    "x = np.sin(theta)\n",
    "y = np.cos(theta)\n",
    "\n",
    "# 绘制五角星\n",
    "ax.plot(x, y, color=line_color)\n",
    "\n",
    "# 设置坐标轴范围\n",
    "ax.set_xlim(-1.2, 1.2)\n",
    "ax.set_ylim(-1.2, 1.2)\n",
    "\n",
    "# 隐藏坐标轴\n",
    "ax.axis('off')\n",
    "\n",
    "# 显示绘制结果\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 四，角色+任务+要求+提示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-14T15:36:15.563027Z",
     "iopub.status.busy": "2023-05-14T15:36:15.562616Z",
     "iopub.status.idle": "2023-05-14T15:36:22.871606Z",
     "shell.execute_reply": "2023-05-14T15:36:22.870201Z",
     "shell.execute_reply.started": "2023-05-14T15:36:15.562997Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "以下是使用matplotlib库绘制五角星的Python代码：\n",
      "\n",
      "```python\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np\n",
      "\n",
      "# 创建一个画布\n",
      "fig, ax = plt.subplots()\n",
      "\n",
      "# 设置画布大小\n",
      "fig.set_size_inches(5, 5)\n",
      "\n",
      "# 设置线条颜色\n",
      "line_color = 'red'\n",
      "\n",
      "# 计算五角星的顶点坐标\n",
      "theta = np.linspace(0, 2*np.pi, 6)\n",
      "x = np.sin(theta)\n",
      "y = np.cos(theta)\n",
      "\n",
      "# 计算五角星的线段坐标\n",
      "lines_x = [x[0], x[2], x[4], x[1], x[3], x[0]]\n",
      "lines_y = [y[0], y[2], y[4], y[1], y[3], y[0]]\n",
      "\n",
      "# 绘制五角星\n",
      "ax.plot(lines_x, lines_y, color=line_color)\n",
      "\n",
      "# 设置坐标轴范围\n",
      "ax.set_xlim(-1.2, 1.2)\n",
      "ax.set_ylim(-1.2, 1.2)\n",
      "\n",
      "# 隐藏坐标轴\n",
      "ax.axis('off')\n",
      "\n",
      "# 显示绘制结果\n",
      "plt.show()\n",
      "```\n",
      "\n",
      "运行代码后，会弹出一个窗口，里面绘制了一个红色线条的五角星。\n"
     ]
    }
   ],
   "source": [
    "%%chatgpt \n",
    "角色：假设你是一个有着丰富经验的Python程序员。\n",
    "任务：请用Python代码绘制一个五角星。\n",
    "要求：请使用matplotlib这个库，线条使用红色。\n",
    "提示：五角星需要先计算五个顶点，然后在每间隔一个顶点的两个顶点之间两两进行连线。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-14T15:36:32.560405Z",
     "iopub.status.busy": "2023-05-14T15:36:32.559586Z",
     "iopub.status.idle": "2023-05-14T15:36:32.647627Z",
     "shell.execute_reply": "2023-05-14T15:36:32.645853Z",
     "shell.execute_reply.started": "2023-05-14T15:36:32.560361Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# 创建一个画布\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# 设置画布大小\n",
    "fig.set_size_inches(5, 5)\n",
    "\n",
    "# 设置线条颜色\n",
    "line_color = 'red'\n",
    "\n",
    "# 计算五角星的顶点坐标\n",
    "theta = np.linspace(0, 2*np.pi, 6)\n",
    "x = np.sin(theta)\n",
    "y = np.cos(theta)\n",
    "\n",
    "# 计算五角星的线段坐标\n",
    "lines_x = [x[0], x[2], x[4], x[1], x[3], x[0]]\n",
    "lines_y = [y[0], y[2], y[4], y[1], y[3], y[0]]\n",
    "\n",
    "# 绘制五角星\n",
    "ax.plot(lines_x, lines_y, color=line_color)\n",
    "\n",
    "# 设置坐标轴范围\n",
    "ax.set_xlim(-1.2, 1.2)\n",
    "ax.set_ylim(-1.2, 1.2)\n",
    "\n",
    "# 隐藏坐标轴\n",
    "ax.axis('off')\n",
    "\n",
    "# 显示绘制结果\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%chatgpt \n",
    "角色：假设你是一个有着丰富经验的Python程序员。\n",
    "任务：请用Python代码绘制一个正五角星。\n",
    "要求：请使用matplotlib这个库。线条使用红色。\n",
    "提示1：五角星需要先绘制五个顶点，然后在每间隔一个顶点的两个顶点之间两两进行连线。\n",
    "提示2：请注意使用%取余计算确保不要超出顶点列表索引范围。"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}