276 lines
12 KiB
Plaintext
276 lines
12 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Openai Function Call \n",
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"https://platform.openai.com/docs/guides/function-calling"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"User>\t How's the weather in Hangzhou?\n",
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"[ChatCompletionMessageToolCall(id='call_zvxBS1zoCa6X9fJzE48BYo2z', function=Function(arguments='{\"location\":\"Hangzhou, China\"}', name='get_weather', parameters=None), type='function')]\n",
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"https://api.weatherapi.com/v1/current.json?key=b7e69154e60b427586983619250502&q=Hangzhou, China\n",
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"Tool call>\t Temperature: 13.0°C, Condition: Partly cloudy\n",
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"Model>\t The current weather in Hangzhou, China is partly cloudy with a temperature of 13.0°C.\n"
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]
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}
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],
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"source": [
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"from openai import OpenAI\n",
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"import json\n",
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"import requests\n",
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"\n",
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"# 定义获取天气的工具\n",
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"def get_weather(location: str):\n",
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" \"\"\"调用天气 API 获取指定地点的天气信息\"\"\"\n",
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" url = f\"https://api.weatherapi.com/v1/current.json?key=b7e69154e60b427586983619250502&q={location}\"\n",
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" print(url)\n",
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" response = requests.get(url)\n",
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" if response.status_code == 200:\n",
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" data = response.json()\n",
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" return f\"Temperature: {data['current']['temp_c']}°C, Condition: {data['current']['condition']['text']}\"\n",
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" return \"Weather data not found\"\n",
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"\n",
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"def send_messages(messages):\n",
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" response = client.chat.completions.create(\n",
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" model=\"gpt-4o\",\n",
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" messages=messages,\n",
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" tools=tools, # 指定可调用的函数\n",
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" )\n",
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" return response.choices[0].message\n",
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"\n",
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"client = OpenAI(\n",
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" api_key=\"sk-lXFW7Bl1ruw2qmHu287e979847354601A07fE2D85a567bD7\", # pass litellm proxy key, if you're using virtual keys\n",
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" base_url=\"https://yunwu.ai/v1/\" # litellm-proxy-base url\n",
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")\n",
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"\n",
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"tools = [{\n",
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" \"type\": \"function\",\n",
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" \"function\": {\n",
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" \"name\": \"get_weather\",\n",
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" \"description\": \"Get current temperature for a given location.\",\n",
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" \"parameters\": {\n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" \"location\": {\n",
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" \"type\": \"string\",\n",
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" \"description\": \"City and country e.g. Bogotá, Colombia\"\n",
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" }\n",
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" },\n",
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" \"required\": [\n",
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" \"location\"\n",
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" ],\n",
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" \"additionalProperties\": False\n",
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" },\n",
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" \"strict\": True\n",
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" }\n",
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"}]\n",
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"# step1\n",
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"messages = [{\"role\": \"user\", \"content\": \"How's the weather in Hangzhou?\"}]\n",
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"message = send_messages(messages)\n",
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"print(f\"User>\\t {messages[0]['content']}\")\n",
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"print(message.tool_calls)\n",
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"\n",
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"# step2\n",
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"tool_call = message.tool_calls[0]\n",
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"\n",
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"#step3 tool call chioce to local function call\n",
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"args = json.loads(tool_call.function.arguments)\n",
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"result = get_weather(args[\"location\"])\n",
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"print(\"Tool call>\\t\", result)\n",
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"\n",
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"# step4\n",
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"messages.append(message) # append model's function call message\n",
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"messages.append({ # append result message\n",
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" \"role\": \"tool\",\n",
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" \"tool_call_id\": tool_call.id,\n",
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" \"content\": result\n",
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"})\n",
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"\n",
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"message = send_messages(messages)\n",
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"\n",
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"# step5\n",
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"print(\"Model>\\t\", message.content)\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Qwen Tool Use Example"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"------------------------------------------------------------\n",
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"\n",
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"第1轮大模型输出信息：{'id': 'chatcmpl-91008e14-9254-98b9-8b14-da6632f6c711', 'choices': [{'finish_reason': 'tool_calls', 'index': 0, 'logprobs': None, 'message': {'content': '', 'refusal': None, 'role': 'assistant', 'audio': None, 'function_call': None, 'tool_calls': [{'id': 'call_5ae24ff6a07e4a1093fff6', 'function': {'arguments': '{}', 'name': 'get_current_time'}, 'type': 'function', 'index': 0}]}}], 'created': 1738762202, 'model': 'qwen-max-2025-01-25', 'object': 'chat.completion', 'service_tier': None, 'system_fingerprint': None, 'usage': {'completion_tokens': 13, 'prompt_tokens': 219, 'total_tokens': 232, 'completion_tokens_details': None, 'prompt_tokens_details': None}}\n",
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"\n",
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"工具输出信息：当前时间：2025-02-05 21:29:58。\n",
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"\n",
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"------------------------------------------------------------\n",
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"第2轮大模型输出信息：{'content': '现在的时间是2025年2月5日，晚上9点29分58秒。', 'refusal': None, 'role': 'assistant', 'audio': None, 'function_call': None, 'tool_calls': None}\n",
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"\n",
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"最终答案：现在的时间是2025年2月5日，晚上9点29分58秒。\n"
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]
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}
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],
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"source": [
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"from openai import OpenAI\n",
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"from datetime import datetime\n",
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"import json\n",
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"import os\n",
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"\n",
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"client = OpenAI(\n",
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" # 若没有配置环境变量，请用百炼API Key将下行替换为：api_key=\"sk-xxx\",\n",
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" api_key=\"sk-487d366becc14df0a58ff4d4559fabf4\",\n",
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" base_url=\"https://dashscope.aliyuncs.com/compatible-mode/v1\", # 填写DashScope SDK的base_url\n",
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")\n",
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"\n",
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"# 定义工具列表，模型在选择使用哪个工具时会参考工具的name和description\n",
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"tools = [\n",
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" # 工具1 获取当前时刻的时间\n",
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" {\n",
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" \"type\": \"function\",\n",
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" \"function\": {\n",
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" \"name\": \"get_current_time\",\n",
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" \"description\": \"当你想知道现在的时间时非常有用。\",\n",
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" # 因为获取当前时间无需输入参数，因此parameters为空字典\n",
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" \"parameters\": {}\n",
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" }\n",
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" }, \n",
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" # 工具2 获取指定城市的天气\n",
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" {\n",
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" \"type\": \"function\",\n",
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" \"function\": {\n",
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" \"name\": \"get_current_weather\",\n",
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" \"description\": \"当你想查询指定城市的天气时非常有用。\",\n",
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" \"parameters\": { \n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" # 查询天气时需要提供位置，因此参数设置为location\n",
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" \"location\": {\n",
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" \"type\": \"string\",\n",
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" \"description\": \"城市或县区，比如北京市、杭州市、余杭区等。\"\n",
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" }\n",
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" }\n",
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" },\n",
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" \"required\": [\n",
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" \"location\"\n",
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" ]\n",
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" }\n",
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" }\n",
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"]\n",
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"\n",
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"# 模拟天气查询工具。返回结果示例：“北京今天是雨天。”\n",
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"def get_current_weather(location):\n",
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" return f\"{location}今天是雨天。 \"\n",
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"\n",
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"# 查询当前时间的工具。返回结果示例：“当前时间：2024-04-15 17:15:18。“\n",
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"def get_current_time():\n",
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" # 获取当前日期和时间\n",
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" current_datetime = datetime.now()\n",
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" # 格式化当前日期和时间\n",
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" formatted_time = current_datetime.strftime('%Y-%m-%d %H:%M:%S')\n",
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" # 返回格式化后的当前时间\n",
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" return f\"当前时间：{formatted_time}。\"\n",
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"\n",
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"# 封装模型响应函数\n",
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"def get_response(messages):\n",
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" completion = client.chat.completions.create(\n",
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" model=\"qwen-max-2025-01-25\",\n",
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" messages=messages,\n",
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" tools=tools\n",
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" )\n",
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" return completion.model_dump()\n",
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"\n",
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"def call_with_messages():\n",
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" print('\\n')\n",
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" messages = [\n",
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" {\n",
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" \"content\": input('现在几点了？'), # 提问示例：\"现在几点了？\" \"一个小时后几点\" \"北京天气如何？\"\n",
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" \"role\": \"user\"\n",
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" }\n",
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" ]\n",
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" print(\"-\"*60)\n",
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" # 模型的第一轮调用\n",
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" i = 1\n",
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" first_response = get_response(messages)\n",
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" assistant_output = first_response['choices'][0]['message']\n",
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" print(f\"\\n第{i}轮大模型输出信息：{first_response}\\n\")\n",
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" if assistant_output['content'] is None:\n",
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" assistant_output['content'] = \"\"\n",
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" messages.append(assistant_output)\n",
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" # 如果不需要调用工具，则直接返回最终答案\n",
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" if assistant_output['tool_calls'] == None: # 如果模型判断无需调用工具，则将assistant的回复直接打印出来，无需进行模型的第二轮调用\n",
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" print(f\"无需调用工具，我可以直接回复：{assistant_output['content']}\")\n",
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" return\n",
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" # 如果需要调用工具，则进行模型的多轮调用，直到模型判断无需调用工具\n",
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" while assistant_output['tool_calls'] != None:\n",
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" # 如果判断需要调用查询天气工具，则运行查询天气工具\n",
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" if assistant_output['tool_calls'][0]['function']['name'] == 'get_current_weather':\n",
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" tool_info = {\"name\": \"get_current_weather\", \"role\":\"tool\"}\n",
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" # 提取位置参数信息\n",
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" location = json.loads(assistant_output['tool_calls'][0]['function']['arguments'])['location']\n",
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" tool_info['content'] = get_current_weather(location)\n",
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" # 如果判断需要调用查询时间工具，则运行查询时间工具\n",
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" elif assistant_output['tool_calls'][0]['function']['name'] == 'get_current_time':\n",
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" tool_info = {\"name\": \"get_current_time\", \"role\":\"tool\"}\n",
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" tool_info['content'] = get_current_time()\n",
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" print(f\"工具输出信息：{tool_info['content']}\\n\")\n",
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" print(\"-\"*60)\n",
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" messages.append(tool_info)\n",
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" assistant_output = get_response(messages)['choices'][0]['message']\n",
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" if assistant_output['content'] is None:\n",
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" assistant_output['content'] = \"\"\n",
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" messages.append(assistant_output)\n",
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" i += 1\n",
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" print(f\"第{i}轮大模型输出信息：{assistant_output}\\n\")\n",
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" print(f\"最终答案：{assistant_output['content']}\")\n",
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"\n",
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"call_with_messages()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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