{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取环境变量\n",
    "from dotenv import load_dotenv\n",
    "load_dotenv()  # 加载 .env 文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langsmith import traceable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用通义千问\n",
    "from langchain_community.llms import Tongyi\n",
    "\n",
    "import os\n",
    "\n",
    "# 初始化通义模型（以qwen-max为例）\n",
    "llm_tongyi = Tongyi(\n",
    "    model_name=\"qwen-turbo\",\n",
    "    dashscope_api_key=os.getenv(\"DASHSCOPE_API_KEY\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from typing import Callable, List, Dict, Any\n",
    "import inspect\n",
    "\n",
    "@traceable\n",
    "def build_tool_prompt(tools: List[Callable], user_input: str) -> str:\n",
    "    \"\"\"\n",
    "    构造多工具调用提示，用于引导模型调用正确工具。\n",
    "    \"\"\"\n",
    "    tool_descriptions = []\n",
    "    for tool in tools:\n",
    "        sig = inspect.signature(tool)\n",
    "        params = \", \".join(f\"{name}: {param.annotation.__name__}\"\n",
    "                           for name, param in sig.parameters.items())\n",
    "        doc = inspect.getdoc(tool) or \"无描述\"\n",
    "        tool_descriptions.append(f\"\"\"工具名：{tool.__name__}\n",
    "描述：{doc}\n",
    "参数：{params}\n",
    "\"\"\")\n",
    "    \n",
    "    tool_block = \"\\n\\n\".join(tool_descriptions)\n",
    "    prompt = f\"\"\"\n",
    "你是一个助手，有以下工具可以调用：\n",
    "\n",
    "{tool_block}\n",
    "\n",
    "请根据用户请求，选择最合适的工具，并以如下格式返回调用指令（请使用英文括号）：\n",
    "调用：<工具名>(参数名1=值1, 参数名2=值2)\n",
    "\n",
    "如果不需要调用任何工具，请回复：无需调用工具\n",
    "\n",
    "用户请求：{user_input}\n",
    "\"\"\"\n",
    "    return prompt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 示例工具\n",
    "@traceable\n",
    "def multiply(a: int, b: int) -> int:\n",
    "    \"\"\"两个整数相乘\"\"\"\n",
    "    return a * b\n",
    "\n",
    "@traceable\n",
    "def add(a: int, b: int) -> int:\n",
    "    \"\"\"两个整数相加\"\"\"\n",
    "    return a + b\n",
    "\n",
    "TOOLS = [multiply, add]\n",
    "TOOL_MAP = {fn.__name__: fn for fn in TOOLS}\n",
    "\n",
    "# 用户输入\n",
    "user_input = \"23和34的和是多少\"\n",
    "\n",
    "# 构造提示并调用模型\n",
    "prompt = build_tool_prompt(TOOLS, user_input)\n",
    "response = llm_tongyi.invoke(prompt)\n",
    "\n",
    "print(\"🔍 模型响应：\", response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "@traceable\n",
    "def extract_tool_call(response: str) -> Dict[str, Any]:\n",
    "    \"\"\"\n",
    "    从模型响应中提取工具调用命令。\n",
    "    返回格式：{ \"tool_name\": str, \"args\": dict }\n",
    "    \"\"\"\n",
    "    pattern = r\"调用：(\\w+)\\((.*?)\\)\"\n",
    "    match = re.search(pattern, response)\n",
    "    if not match:\n",
    "        return {}\n",
    "    \n",
    "    tool_name, args_str = match.groups()\n",
    "    args = {}\n",
    "    for part in args_str.split(\",\"):\n",
    "        if \"=\" in part:\n",
    "            key, value = part.split(\"=\")\n",
    "            key = key.strip()\n",
    "            value = value.strip()\n",
    "            try:\n",
    "                value = eval(value)  # 小心执行不可信输入\n",
    "            except:\n",
    "                pass\n",
    "            args[key] = value\n",
    "    return {\"tool_name\": tool_name, \"args\": args}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 解析调用\n",
    "tool_call = extract_tool_call(response)\n",
    "if tool_call:\n",
    "    tool_fn = TOOL_MAP.get(tool_call[\"tool_name\"])\n",
    "    if tool_fn:\n",
    "        result = tool_fn(**tool_call[\"args\"])\n",
    "        print(\"✅ 工具执行结果：\", result)\n",
    "    else:\n",
    "        print(\"⚠️ 未知工具：\", tool_call[\"tool_name\"])\n",
    "else:\n",
    "    print(\"ℹ️ 模型未调用任何工具\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(tool_call)"
   ]
  }
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