#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2025/3/16 09:46 # @Author : old-tom # @File : llm_agent # @Project : llmFunctionCallDemo # @Desc : llm代理,负责初始化模型 from langchain_openai import ChatOpenAI from langchain_core.prompts import ChatPromptTemplate from langchain_core.output_parsers import StrOutputParser # 默认系统提示词 DEFAULT_SYS_PROMPT = '' parser = StrOutputParser() # 模型初始化,注意替换成自己的模型和api_key llm = ChatOpenAI( model='deepseek-r1-250120', api_key='4eefc827-187f-4756-9637-7e0153c93d81', base_url='https://ark.cn-beijing.volces.com/api/v3/', max_tokens=4096, temperature=0.5, streaming=True ) # 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 TOOLS = [ { "type": "function", "function": { "name": "get_current_weather", "description": "Get weather of an location, the user shoud supply a location first", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "The city and state, e.g. San Francisco, CA", } }, "required": ["location"] }, } }, { "type": "function", "function": { "name": "play_video", "description": "播放、查看、打开实时视频", "parameters": { "type": "object", "properties": { "camera_name": { "type": "string", "description": "相机名称,例如:南卡口1号相机", } }, "required": ["camera_name"] }, } }, { "type": "function", "function": { "name": "split_screen", "description": "切换分屏", "parameters": { "type": "object", "properties": { "split_n": { "type": "int", "description": "要切换的分屏数量,整数并且大于0,例如:1分屏、2分屏", } }, "required": ["split_n"] }, } }, { "type": "function", "function": { "name": "play_video_record", "description": "播放、打开录像", "parameters": { "type": "object", "properties": { "camera_name": { "type": "string", "description": "相机名称,例如:南卡口1号相机", }, "start_time": { "type": "string", "description": "录像开始时间,格式为yyyy-MM-dd hh:mm:ss,例 2025-03-16 01:00:00", }, "end_time": { "type": "string", "description": "录像结束时间,格式为yyyy-MM-dd hh:mm:ss,例 2025-03-16 02:09:31", } }, "required": ["camera_name", "start_time", "end_time"] }, } }, { "type": "function", "function": { "name": "switch_page", "description": "打开、跳转页面", "parameters": { "type": "object", "properties": { "page_name": { "type": "string", "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", } }, "required": ["page_name"] }, } }, { "type": "function", "function": { "name": "zoom_in", "description": "放大电子地图", "parameters": { "type": "object", "properties": { "level_n": { "type": "int", "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", } }, "required": ["level_n"] }, } }, { "type": "function", "function": { "name": "view_flight_details", "description": "查询指定机场指定航班及时间的出入境人员明细", "parameters": { "type": "object", "properties": { "airport_name": { "type": "string", "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", }, "flight_code": { "type": "string", "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", }, "flight_date": { "type": "string", "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", }, "ie_type": { "type": "string", "description": "出入境类型,仅识别'入境'或'出境'两种类型", } }, "required": ["airport_name", "flight_code", "flight_date"] }, } } ] class DeepSeekR1Agent(object): def __init__(self, system_prompt: str = DEFAULT_SYS_PROMPT): """ :param system_prompt: 系统提示词 """ self.prompt = ChatPromptTemplate( [ ("system", system_prompt), ("human", "{user_input}") ] ) def invoke(self, user_input: str): """ 请求模型并一次性返回 :param user_input: 用户输入 :return: """ chain = self.prompt | llm return chain.invoke({ 'user_input': user_input }).content def invoke_by_stream(self, user_input: str): """ 请求模型并流式返回(同步流) :param user_input: 用户输入 :return: """ chain = self.prompt | llm | parser response = chain.stream({'user_input': user_input}) for chunk in response: print(chunk, flush=True, end='') @staticmethod def invoke_with_tool(user_input: str): """ 工具链调用,function calling时system prompt不会生效 :param user_input: :return: 这里返回的是LLM推理出的tool信息,格式如下: [{'name': 'get_current_weather', 'args': {'location': 'Beijing, China'}, 'id': 'call_xeeq4q52fw9x61lkrqwy9cr6', 'type': 'tool_call'}] """ llm_with_tools = llm.bind_tools(TOOLS) return llm_with_tools.invoke(user_input).tool_calls