{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ba07da4b-ec08-42e8-a733-6d52624c7ba3",
   "metadata": {},
   "source": [
    "# DeepSeek API 对话类\n",
    "\n",
    "> 指导文章：[DeepSeek API 统一模型对话逻辑与流式输出](https://github.com/Hoper-J/AI-Guide-and-Demos-zh_CN/blob/master/Guide/DeepSeek%20API%20统一模型对话逻辑与流式输出.md)\n",
    "\n",
    "\n",
    "在线链接：[Kaggle](https://www.kaggle.com/code/aidemos/deepseek-api-guide-5) | [Colab](https://colab.research.google.com/drive/1N-twn0YVMhvEQ_6hmDWI1giP6ipkzeQs?usp=sharing)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b25ba7e5-a9b6-4303-a9b3-90c0721ade7f",
   "metadata": {},
   "source": [
    "## 导入库\n",
    "\n",
    "你需要先运行当前模块才能正确执行后续的代码。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bcdf4746-d7d5-47e3-bcc3-15a5c189e114",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-07-06T02:50:17.793332Z",
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     "shell.execute_reply": "2026-07-06T02:50:18.717186Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import ipywidgets as widgets\n",
    "from IPython.display import display, HTML\n",
    "from typing import Dict, Optional\n",
    "\n",
    "from openai import OpenAI"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74158d62-9fd2-44b5-8bda-d2c91f63f356",
   "metadata": {},
   "source": [
    "## 配置设置\n",
    "\n",
    "> 这里是一个快捷配置类，可以不用关注这个它的代码细节。\n",
    "\n",
    "在接下来的学习中，都将用 `APIConfigManager` 进行配置，使用 `Shift + 回车` 运行后，填写对应平台的 `API Key` 后点击 `保存配置` 按钮，就可以顺利运行之后的代码。\n",
    "\n",
    "后续切换平台或者模型后，也需要点击 `保存配置` 按钮。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "42ab5e7a-c6bd-41d7-a1b7-fa4afe90b23c",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2026-07-06T02:50:18.746855Z"
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   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d7c3bbfd876e4c8098fdf731556914ee",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Dropdown(description='选择平台:', layout=Layout(width='300px'), options=('DeepSeek', '硅基流动', '阿里云百炼…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class APIConfigManager:\n",
    "    \"\"\"API 配置管理器，用于处理环境变量和配置信息\"\"\"\n",
    "    \n",
    "    # 状态颜色映射\n",
    "    STATUS_COLORS = {\n",
    "        'success': 'green',\n",
    "        'warning': 'orange',\n",
    "        'error': 'red'\n",
    "    }\n",
    "    \n",
    "    # 平台配置信息，新平台或配置可以在此处修改\n",
    "    PLATFORM_CONFIG = {\n",
    "        'DeepSeek': {\n",
    "            'api_key_name': 'DEEPSEEK_API_KEY',\n",
    "            'base_url': 'https://api.deepseek.com',\n",
    "            'chat_model_id': 'deepseek-v4-flash',\n",
    "            'reasoner_model_id': 'deepseek-v4-flash'\n",
    "        },\n",
    "        '硅基流动': {\n",
    "            'api_key_name': 'SILICONFLOW_API_KEY',\n",
    "            'base_url': 'https://api.siliconflow.cn/v1',\n",
    "            'chat_model_id': 'deepseek-ai/DeepSeek-V4-Flash',\n",
    "            'reasoner_model_id': 'deepseek-ai/DeepSeek-V4-Flash'\n",
    "        },\n",
    "        '阿里云百炼': {\n",
    "            'api_key_name': 'DASHSCOPE_API_KEY',\n",
    "            'base_url': 'https://dashscope.aliyuncs.com/compatible-mode/v1',\n",
    "            'chat_model_id': 'deepseek-v4-flash',\n",
    "            'reasoner_model_id': 'deepseek-v4-flash'\n",
    "        },\n",
    "        '百度智能云': {\n",
    "            'api_key_name': 'BAIDU_API_KEY',\n",
    "            'base_url': 'https://qianfan.baidubce.com/v2',\n",
    "            'chat_model_id': 'deepseek-v4-flash',\n",
    "            'reasoner_model_id': 'deepseek-v4-flash'\n",
    "        },\n",
    "        '字节火山引擎': {\n",
    "            'api_key_name': 'ARK_API_KEY',\n",
    "            'base_url': 'https://ark.cn-beijing.volces.com/api/v3',\n",
    "            'chat_model_id': 'deepseek-v4-flash-260425',\n",
    "            'reasoner_model_id': 'deepseek-v4-flash-260425'\n",
    "        }\n",
    "    }\n",
    "    \n",
    "    def __init__(self):\n",
    "        \"\"\"初始化配置管理器\"\"\"\n",
    "        self.current_config: Dict[str, str] = {}\n",
    "        self._setup_widgets()\n",
    "        \n",
    "    def _setup_widgets(self):\n",
    "        \"\"\"设置 ipywidgets 界面组件\"\"\"\n",
    "        self.platform_dropdown = widgets.Dropdown(\n",
    "            options=list(self.PLATFORM_CONFIG.keys()),\n",
    "            description='选择平台:',\n",
    "            layout={'width': '300px'}\n",
    "        )\n",
    "        \n",
    "        self.model_type_dropdown = widgets.Dropdown(\n",
    "            options=[('聊天模型', 'chat'), ('推理模型', 'reasoner')],\n",
    "            description='模型类型:',\n",
    "            layout={'width': '300px'}\n",
    "        )\n",
    "\n",
    "        # 默认允许编辑模型ID\n",
    "        self.model_id_input = widgets.Text(\n",
    "            description='模型 ID:',\n",
    "            layout={'width': '500px'},\n",
    "            disabled=False\n",
    "        )\n",
    "        \n",
    "        self.api_key_input = widgets.Password(\n",
    "            description='API Key:',\n",
    "            layout={'width': '500px'}\n",
    "        )\n",
    "        \n",
    "        self.status_label = widgets.HTML(\n",
    "            value='',\n",
    "            layout={'width': '400px'}\n",
    "        )\n",
    "        \n",
    "        self.save_button = widgets.Button(\n",
    "            description='保存配置',\n",
    "            button_style='primary',  # 默认灰色，设置为蓝色\n",
    "            layout={'width': '150px'}\n",
    "        )\n",
    "        \n",
    "        # 绑定事件处理函数\n",
    "        self.platform_dropdown.observe(self._on_platform_change, names='value')\n",
    "        self.model_type_dropdown.observe(self._on_model_type_change, names='value')\n",
    "        self.save_button.on_click(self._on_save_click)\n",
    "        \n",
    "        # 创建布局\n",
    "        self.widget = widgets.VBox([\n",
    "            self.platform_dropdown,\n",
    "            self.model_type_dropdown,\n",
    "            self.model_id_input,\n",
    "            self.api_key_input,\n",
    "            self.status_label,\n",
    "            self.save_button\n",
    "        ])\n",
    "    \n",
    "    def _on_platform_change(self, change):\n",
    "        \"\"\"处理平台选择变化事件\"\"\"\n",
    "        if not change.new:\n",
    "            return\n",
    "            \n",
    "        platform = change.new\n",
    "        model_type = self.model_type_dropdown.value\n",
    "        platform_config = self.PLATFORM_CONFIG[platform]\n",
    "        \n",
    "        # 更新 API Key 输入框描述和值\n",
    "        self.api_key_input.description = f'API Key ({platform_config[\"api_key_name\"]}):'\n",
    "        api_key = os.getenv(platform_config['api_key_name'])\n",
    "        self.api_key_input.value = api_key if api_key else ''\n",
    "        \n",
    "        # 获取当前模型 ID\n",
    "        current_model_id = platform_config[f'{model_type}_model_id']\n",
    "        \n",
    "        # 设置模型ID输入框的描述信息\n",
    "        self.model_id_input.description = '模型 ID:'\n",
    "        \n",
    "        # 尝试从环境变量获取模型ID（优先级高于平台配置）\n",
    "        env_var_name = f\"{platform_config['api_key_name'].replace('_API_KEY', '')}_{model_type.upper()}_MODEL_ID\"\n",
    "        env_model_id = os.getenv(env_var_name, '')\n",
    "        \n",
    "        # 如果环境变量中有值，使用环境变量的值，否则使用平台配置（PLATFORM_CONFIG）中的默认值\n",
    "        self.model_id_input.value = env_model_id if env_model_id else current_model_id\n",
    "        \n",
    "        if api_key:\n",
    "            self._update_status('检测到所需配置，点击\"保存配置\"按钮完成设置', 'success')\n",
    "        else:\n",
    "            self._update_status(f'请输入 {platform_config[\"api_key_name\"]}，填写完成后点击\"保存配置\"按钮', 'warning')\n",
    "    \n",
    "    \n",
    "    def _on_model_type_change(self, change):\n",
    "        \"\"\"处理模型类型变化事件\"\"\"\n",
    "        if change.new and self.platform_dropdown.value:\n",
    "            # 重用平台变更的逻辑\n",
    "            self._on_platform_change(type('Change', (), {'new': self.platform_dropdown.value})())\n",
    "    \n",
    "    def _on_save_click(self, b):\n",
    "        \"\"\"处理保存按钮点击事件\"\"\"\n",
    "        try:\n",
    "            platform = self.platform_dropdown.value\n",
    "            platform_config = self.PLATFORM_CONFIG[platform]\n",
    "            model_type = self.model_type_dropdown.value\n",
    "            \n",
    "            if not platform or not self.api_key_input.value:\n",
    "                raise ValueError('请填写所有必填项')\n",
    "            \n",
    "            if not self.model_id_input.value:\n",
    "                raise ValueError('请填写模型 ID')\n",
    "            \n",
    "            # 设置API Key环境变量\n",
    "            os.environ[platform_config['api_key_name']] = self.api_key_input.value\n",
    "            \n",
    "            # 使用用户输入的模型ID\n",
    "            self.current_config = {\n",
    "                'api_key': self.api_key_input.value,\n",
    "                'base_url': platform_config['base_url'],\n",
    "                'model': self.model_id_input.value\n",
    "            }\n",
    "            \n",
    "            self._update_status('配置已保存', 'success')\n",
    "        except Exception as e:\n",
    "            self._update_status(str(e), 'error')\n",
    "    \n",
    "    def _update_status(self, message: str, status_type: str):\n",
    "        \"\"\"更新状态显示\"\"\"\n",
    "        self.status_label.value = f'<span style=\"color: {self.STATUS_COLORS[status_type]};\">{message}</span>'\n",
    "    \n",
    "    def get_config(self) -> Optional[Dict[str, str]]:\n",
    "        \"\"\"获取当前配置\"\"\"\n",
    "        return self.current_config or None\n",
    "    \n",
    "    def display(self):\n",
    "        \"\"\"显示配置界面\"\"\"\n",
    "        display(self.widget)\n",
    "        # 触发平台变更事件来初始化界面状态\n",
    "        self._on_platform_change(type('Change', (), {'new': self.platform_dropdown.value})())\n",
    "\n",
    "def setup_chat_session():\n",
    "    \"\"\"创建并显示配置管理器，返回配置实例\"\"\"\n",
    "    config_manager = APIConfigManager()\n",
    "    config_manager.display()\n",
    "    return config_manager\n",
    "\n",
    "config_manager = setup_chat_session()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20d3a090-8981-4f15-adc8-303d18fa7388",
   "metadata": {},
   "source": [
    "## 开始对话\n",
    "\n",
    "> `ChatSession` 是一个非常基础的对话类。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8416a5ac-e888-442c-acaa-eed1e457b263",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-07-06T02:50:18.763310Z",
     "iopub.status.busy": "2026-07-06T02:50:18.763162Z",
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     "shell.execute_reply": "2026-07-06T02:50:18.768457Z"
    }
   },
   "outputs": [],
   "source": [
    "class ChatSession:\n",
    "    def __init__(self, api_key=None, base_url=\"https://api.deepseek.com\", model=\"deepseek-v4-flash\", system_message=\"You are a helpful assistant.\", thinking=None):\n",
    "        \"\"\"\n",
    "        参数:\n",
    "            api_key (str): 平台的 API Key，默认从环境变量 `DEEPSEEK_API_KEY` 读取\n",
    "            base_url (str): API 请求地址，默认为 DeepSeek 官方平台\n",
    "            model (str): 模型名称，默认为 'deepseek-v4-flash'（更强的 'deepseek-v4-pro' 用法相同）\n",
    "            system_message (str): 系统消息，用于设定对话背景，默认为 'You are a helpful assistant.'\n",
    "        \"\"\"\n",
    "        # 处理 API Key 优先级：显式传入 > 环境变量\n",
    "        self.api_key = api_key or os.getenv(\"DEEPSEEK_API_KEY\")\n",
    "        if not self.api_key:\n",
    "            raise ValueError(\"API Key 未提供，请通过参数传入或设置环境变量 DEEPSEEK_API_KEY\")\n",
    "        self.base_url = base_url\n",
    "        \n",
    "        # 初始化 OpenAI 客户端\n",
    "        self.client = OpenAI(\n",
    "            api_key=self.api_key,\n",
    "            base_url=self.base_url,\n",
    "        )\n",
    "        \n",
    "        self.model = model\n",
    "        self.thinking = thinking  # None=平台默认；True/False=显式开/关思考（V4 生效）\n",
    "        self.messages = [{'role': 'system', 'content': system_message}]\n",
    "\n",
    "    def append_message(self, role, content):\n",
    "        \"\"\"\n",
    "        添加一条对话消息\n",
    "\n",
    "        参数:\n",
    "            role (str): 消息角色，为 'user' 或 'assistant'\n",
    "            content (str): 消息内容\n",
    "        \"\"\"\n",
    "        self.messages.append({'role': role, 'content': content})\n",
    "\n",
    "    def get_response(self, user_input, stream=False):\n",
    "        \"\"\"\n",
    "        添加用户消息，调用 API 获取回复，并返回推理过程和回复内容\n",
    "\n",
    "        参数:\n",
    "            user_input (str): 用户输入的消息\n",
    "            stream (bool): 是否启用流式输出，默认为 False\n",
    "\n",
    "        返回:\n",
    "            当 stream=False 时:\n",
    "                tuple: (reasoning_content, content)\n",
    "                reasoning_content (str|None): 推理过程，仅思考模式返回，非思考模式为 None\n",
    "                content (str): 模型的回复内容\n",
    "\n",
    "            当 stream=True 时:\n",
    "                generator: 生成一系列 (reasoning_content, content) 元组\n",
    "                其中:\n",
    "                    推理过程: (reasoning_content, None)\n",
    "                    回复内容: (None, content)\n",
    "                两者必定有一个为 None，另一个包含当前数据块的实际内容\n",
    "        \"\"\"\n",
    "        # 记录用户输入\n",
    "        self.append_message('user', user_input)\n",
    "        \n",
    "        # 调用 API\n",
    "        completion = self.client.chat.completions.create(\n",
    "            model=self.model,\n",
    "            **({\"extra_body\": {\"thinking\": {\"type\": \"enabled\" if self.thinking else \"disabled\"}}} if self.thinking is not None else {}),\n",
    "            messages=self.messages,\n",
    "            stream=stream\n",
    "        )\n",
    "        \n",
    "        if not stream:\n",
    "            # 非流式输出\n",
    "            content = completion.choices[0].message.content\n",
    "            reasoning_content = getattr(completion.choices[0].message, 'reasoning_content', None)\n",
    "            \n",
    "            # 记录模型回复\n",
    "            self.append_message('assistant', content)\n",
    "            \n",
    "            return reasoning_content, content\n",
    "        else:\n",
    "            # 流式输出，返回生成器\n",
    "            return self._process_stream(completion)\n",
    "    \n",
    "    def _process_stream(self, completion):\n",
    "        \"\"\"\n",
    "        处理流式输出的数据块\n",
    "\n",
    "        参数:\n",
    "            completion: API 返回的流式输出对象\n",
    "\n",
    "        返回:\n",
    "            generator: 生成器对象，每次返回 (reasoning_content, content) 元组\n",
    "            其中:\n",
    "                推理过程: yield (reasoning_content, None)\n",
    "                回复内容: yield (None, content)\n",
    "        \"\"\"\n",
    "        content = \"\"  # 用于存储完整回复\n",
    "        \n",
    "        for chunk in completion:\n",
    "            delta = chunk.choices[0].delta\n",
    "            # 处理推理过程（仅思考模式有）\n",
    "            if getattr(delta, 'reasoning_content', None):\n",
    "                yield delta.reasoning_content, None\n",
    "            # 处理回复内容\n",
    "            elif delta.content:\n",
    "                content += delta.content  # 需要记录 content 维护对话历史\n",
    "                yield None, delta.content\n",
    "                \n",
    "            # 如果是最后一个数据块（finish_reason 不为 None）\n",
    "            if chunk.choices[0].finish_reason is not None:\n",
    "                # 记录完整的模型回复 content\n",
    "                self.append_message('assistant', content)\n",
    "                break"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcfe30e6-87d7-4541-be44-d06792f8c0e1",
   "metadata": {},
   "source": [
    "> 一个更熟悉的写法（直接将输出逻辑放在类中）：\n",
    "> \n",
    "> ```python\n",
    "> def _process_stream(self, completion):\n",
    ">     content = \"\"\n",
    ">     \n",
    ">     for chunk in completion:\n",
    ">         delta = chunk.choices[0].delta\n",
    ">         if getattr(delta, 'reasoning_content', None):\n",
    ">             print(delta.reasoning_content, end='')\n",
    ">         elif delta.content:\n",
    ">             content += delta.content\n",
    ">             print(delta.content, end='')\n",
    ">                 \n",
    ">     ...\n",
    "> ```\n",
    ">\n",
    "> 此时会自动打印输出。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65f141a2-78c8-4971-ad34-1c65fd6d4741",
   "metadata": {},
   "source": [
    "### 非流式输出"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8962d1a0-f2d3-4889-905e-45876548f925",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-07-06T02:50:18.774546Z",
     "iopub.status.busy": "2026-07-06T02:50:18.774217Z",
     "iopub.status.idle": "2026-07-06T02:50:22.319024Z",
     "shell.execute_reply": "2026-07-06T02:50:22.318207Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===== 推理过程 =====\n",
      "Hmm, the user simply said \"Hello\" — a very common greeting. This doesn't seem to require any complex analysis or deep reasoning. The user might just be initiating a conversation or testing if I'm responsive. \n",
      "\n",
      "Since the response should be friendly and open-ended to encourage further interaction, I'll reply with a warm greeting and an offer to help. A simple \"Hello\" back, followed by an invitation to ask questions, feels appropriate. \n",
      "\n",
      "I'll keep it natural and approachable, without overcomplicating it. The tone should match the user's casual opening.\n",
      "\n",
      "===== 模型回复 =====\n",
      "AI: Hello! How can I assist you today?\n",
      "\n"
     ]
    }
   ],
   "source": [
    "user_input = \"Hello\"\n",
    "stream = False  # 非流式输出\n",
    "\n",
    "# 更新配置\n",
    "config = config_manager.get_config()\n",
    "# print(config)\n",
    "session = ChatSession(**config)\n",
    "\n",
    "# 获取回复\n",
    "reasoning, reply = session.get_response(user_input, stream=stream)\n",
    "if reasoning:\n",
    "    print(f\"===== 推理过程 =====\\n{reasoning}\\n\")\n",
    "print(f\"===== 模型回复 =====\\nAI: {reply}\\n\")"
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    "### 流式输出"
   ]
  },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hmm, the user just said \"Hello.\" This is a simple greeting."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " I should respond in a friendly and welcoming manner. \n",
      "\n",
      "Since there's no specific question"
     ]
    },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      " or request, I can offer a cheerful greeting back"
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      " and leave the conversation open for the user to ask anything they need. \n",
      "\n",
      "A short, warm"
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    },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      " response like \"Hello! How can I help you today?\" feels appropriate."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " It acknowledges the greeting and invites further interaction.Hello! How"
     ]
    },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      " can I help you today?"
     ]
    }
   ],
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    "user_input = \"Hello\"\n",
    "stream = True  # 流式输出\n",
    "\n",
    "# 更新配置\n",
    "config = config_manager.get_config()\n",
    "# print(config)\n",
    "session = ChatSession(**config)\n",
    "\n",
    "# 实时打印模型回复的增量内容，print() 设置 end=''实现不换行输出\n",
    "for reasoning, reply in session.get_response(user_input, stream=stream):\n",
    "    if reasoning:\n",
    "        print(reasoning, end='')  \n",
    "    else:\n",
    "        print(reply, end='')"
   ]
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