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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# @Time : 2025/3/16 09:46
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# @Author : old-tom
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# @File : llm_agent
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# @Project : llmFunctionCallDemo
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# @Desc : llm代理，负责初始化模型
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from langchain_openai import ChatOpenAI
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from langchain_core.prompts import ChatPromptTemplate
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from langchain_core.output_parsers import StrOutputParser
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# 默认系统提示词
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DEFAULT_SYS_PROMPT = ''
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parser = StrOutputParser()
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# 模型初始化，注意替换成自己的模型和api_key
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llm = ChatOpenAI(
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model='deepseek-r1-250120', api_key='4eefc827-187f-4756-9637-7e0153c93d81',
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base_url='https://ark.cn-beijing.volces.com/api/v3/', max_tokens=4096, temperature=0.5, streaming=True
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)
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# 工具函数定义,deepseek 官方定义的格式（最多支持 128 个 function），参考 https://api-docs.deepseek.com/zh-cn/guides/function_calling
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TOOLS = [
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{
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"type": "function",
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"function": {
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"name": "get_current_weather",
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"description": "Get weather of an location, the user shoud supply a location first",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA",
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}
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},
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"required": ["location"]
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},
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}
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},
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{
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"type": "function",
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"function": {
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"name": "play_video",
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"description": "播放、查看、打开实时视频",
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"parameters": {
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"type": "object",
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"properties": {
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"camera_name": {
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"type": "string",
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"description": "相机名称,例如：南卡口1号相机",
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}
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},
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"required": ["camera_name"]
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},
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}
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},
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{
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"type": "function",
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"function": {
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"name": "split_screen",
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"description": "切换分屏",
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"parameters": {
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"type": "object",
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"properties": {
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"split_n": {
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"type": "int",
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"description": "要切换的分屏数量,整数并且大于0，例如：1分屏、2分屏",
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}
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},
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"required": ["split_n"]
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},
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}
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},
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{
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"type": "function",
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"function": {
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"name": "play_video_record",
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"description": "播放、打开录像",
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"parameters": {
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"type": "object",
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"properties": {
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"camera_name": {
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"type": "string",
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"description": "相机名称，例如：南卡口1号相机",
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},
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"start_time": {
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"type": "string",
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"description": "录像开始时间,格式为yyyy-MM-dd hh:mm:ss，例 2025-03-16 01:00:00",
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},
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"end_time": {
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"type": "string",
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"description": "录像结束时间,格式为yyyy-MM-dd hh:mm:ss，例 2025-03-16 02:09:31",
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}
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},
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"required": ["camera_name", "start_time", "end_time"]
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},
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}
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},
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{
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"type": "function",
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"function": {
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"name": "switch_page",
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"description": "打开、跳转页面",
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"parameters": {
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"type": "object",
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"properties": {
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"page_name": {
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"type": "string",
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"description": "页面中文名称或者缩写，例：人员核查、系统日志、设备管理、首页",
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}
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},
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"required": ["page_name"]
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},
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}
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},
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{
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"type": "function",
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"function": {
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"name": "zoom_in",
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"description": "放大电子地图",
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"parameters": {
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"type": "object",
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"properties": {
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"level_n": {
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"type": "int",
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"description": "放大等级,整数并且大于0小于5，例如：放大1级、放大2级",
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}
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},
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"required": ["level_n"]
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},
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}
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},
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{
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"type": "function",
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"function": {
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"name": "view_flight_details",
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"description": "查询指定机场指定航班及时间的出入境人员明细",
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"parameters": {
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"type": "object",
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"properties": {
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"airport_name": {
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"type": "string",
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"description": "机场名称，简体中文，可以是缩写，例如：成都天府机场、天府机场、长水机场、上海浦东机场",
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},
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"flight_code": {
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"type": "string",
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"description": "航班编号,由字母+数字组成的完整编号,若编号包含多余字符（如标点符号），需过滤后保留有效部分",
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},
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"flight_date": {
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"type": "string",
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"description": "提取完整日期（年月日），自动补零至标准格式 yyyy-MM-dd, 例：2025-03-16",
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},
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"ie_type": {
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"type": "string",
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"description": "出入境类型，仅识别'入境'或'出境'两种类型",
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}
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},
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"required": ["airport_name", "flight_code", "flight_date"]
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},
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}
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}
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]
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class DeepSeekR1Agent(object):
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def __init__(self, system_prompt: str = DEFAULT_SYS_PROMPT):
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"""
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:param system_prompt: 系统提示词
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"""
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self.prompt = ChatPromptTemplate(
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[
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("system", system_prompt),
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("human", "{user_input}")
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]
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)
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def invoke(self, user_input: str):
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"""
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请求模型并一次性返回
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:param user_input: 用户输入
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:return:
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"""
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chain = self.prompt | llm
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return chain.invoke({
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'user_input': user_input
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}).content
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def invoke_by_stream(self, user_input: str):
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"""
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请求模型并流式返回（同步流）
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:param user_input: 用户输入
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:return:
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"""
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chain = self.prompt | llm | parser
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response = chain.stream({'user_input': user_input})
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for chunk in response:
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print(chunk, flush=True, end='')
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@staticmethod
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def invoke_with_tool(user_input: str):
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"""
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工具链调用,function calling时system prompt不会生效
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:param user_input:
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:return: 这里返回的是LLM推理出的tool信息，格式如下：
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[{'name': 'get_current_weather', 'args': {'location': 'Beijing, China'}, 'id': 'call_xeeq4q52fw9x61lkrqwy9cr6', 'type': 'tool_call'}]
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"""
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llm_with_tools = llm.bind_tools(TOOLS)
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return llm_with_tools.invoke(user_input).tool_calls
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