文章介绍
本文章将介绍：
- 什么是Langchain4j
- 快速入门Langchain4j实现基本对话功能
- 实现其进阶用法（聊天记忆，隔离对话，FunctionCalling）
- 从0到1落地一个医疗智能体项目，实现特定角色的医疗咨询服务以及挂号，取消挂号服务
什么是langchain4j？
LangChain4j 是一个 Java 版本的 LangChain 框架。
简单来说，你可以把它理解为：
- "为 Java 开发者量身打造的 AI 应用开发工具箱"。
快速入门
下面以以接入阿里云的通义千问为例：
引依赖（Maven）
XML
<dependency>
<groupId>dev.langchain4j</groupId>
<artifactId>langchain4j-spring-boot-starter</artifactId>
<version>1.0.0-beta3</version>
</dependency>
<dependency>
<groupId>dev.langchain4j</groupId>
<artifactId>langchain4j-community-dashscope-spring-boot-starter</artifactId>
</dependency>配参数（API）
XML
langchain4j.community.dashscope.chat-model.api-key=${DASH_SCOPE_API_KEY}
langchain4j.community.dashscope.chat-model.model-name=qwen-flash
DASH_SCOPE_API_KEY为API-key，需要配置环境变量
测试
java
/**
*通义千问大模型
*/
@Autowired
private QwenChatModel qwenChatModel;
@Test
public void testDashScopeQwen(){
//向模型提问
Stringanswer=qwenChatModel.chat("你好");
//输出结果
System.out.println(answer);
}进阶
使用AIService
AIService使用面向接口和动态代理的方式完成程序的编写，更灵活的实现高级功能。
java
@AiService
public interface Assistant {
String chat(String userMessage);
}
java
@SpringBootTest
public classAIServiceTest{
@Autowired
privateQwenChatModelqwenChatModel;
@Test
public void testChat(){
//创建AIService
Assistant assistant=AiServices.create(Assistant.class,qwenChatModel);
//调用service的接口
String answer=assistant.chat("Hello");
System.out.println(answer);
}
}实现聊天记忆
测试对话是否记忆（默认没有记忆）
java
@SpringBootTest
public class ChatMemoryTest {
@Autowired
private Assistant assistant;
@Test
public void testChatMemory() {
String answer1 = assistant.chat("我是张三");
System.out.println(answer1);
String answer2 = assistant.chat("我是谁");
System.out.println(answer2);
}
}使用AIService实现聊天记忆
java
@AiService(
wiringMode = EXPLICIT,
chatModel = "qwenChatModel",
chatMemory = "chatMemory"
)
public interface MemoryChatAssistant {
String chat(String message);
}
java
@Configuration
public class MemoryChatAssistantConfig {
@Bean
public ChatMemory chatMemory() {
//设置聊天记录的message数量
return MessageWindowChatMemory.withMaxMessages(10);
}
}测试
java
@Autowired
private MemoryChatAssistant memoryChatAssistant;
@Test
public void testChatMemory4() {
String answer1 = memoryChatAssistant.chat("我是张三");
System.out.println(answer1);
String answer2 = memoryChatAssistant.chat("我是谁");
System.out.println(answer2);
}实现聊天记忆隔离
创建记忆隔离对话智能体
java
@AiService(
wiringMode = EXPLICIT,
chatMemory = "chatMemory",
chatMemoryProvider = "chatMemoryProvider"
)
public interface SeparateChatAssistant {
/**
* 分离聊天记录
* @param memoryId 聊天id
* @param userMessage 用户消息
* @return
*/
String chat(@MemoryId int memoryId, @UserMessage String userMessage);
}配置ChatMemoryProvider
java
@Configuration
public class SeparateChatAssistantConfig {
@Bean
public ChatMemoryProvider chatMemoryProvider() {
return memoryId -> MessageWindowChatMemory.builder()
.id(memoryId)
.maxMessages(10)
.build();
}
}测试
java
@Autowired
private SeparateChatAssistant separateChatAssistant;
@Test
public void testChatMemory5() {
String answer1 = separateChatAssistant.chat(1, "我是张三");
System.out.println(answer1);
String answer2 = separateChatAssistant.chat(1, "我是谁");
System.out.println(answer2);
String answer3 = separateChatAssistant.chat(2, "我是谁");
System.out.println(answer3);
}实现聊天记忆持久化（mongoDB）
mongoDB使用见我下面文章，这里不再赘述
java
@Component
public class MongoChatMemoryStore implements ChatMemoryStore {
@Autowired
private MongoTemplate mongoTemplate;
@Override
public List<ChatMessage> getMessages(Object memoryId) {
Criteria criteria=Criteria.where("memoryId").is(memoryId);
Query query=new Query(criteria);
ChatMessages chatMessages=mongoTemplate.findOne(query, ChatMessages.class);
if (chatMessages==null)return new LinkedList<>();
String contentJson = chatMessages.getContent();
return ChatMessageDeserializer.messagesFromJson(contentJson);
}
@Override
public void updateMessages(Object memoryId, List<ChatMessage> list) {
Criteria criteria=Criteria.where("memoryId").is(memoryId);
Query query=new Query(criteria);
Update update=new Update();
update.set("content", ChatMessageSerializer.messagesToJson( list));
mongoTemplate.upsert(query, update, ChatMessages.class);
}
@Override
public void deleteMessages(Object memoryId) {
Criteria criteria=Criteria.where("memoryId").is(memoryId);
Query query=new Query(criteria);
mongoTemplate.remove(query, ChatMessages.class);
}
}在配置类中注入持久化对象
java
@Configuration
public class SeparateChatAssistantConfig {
//注入持久化对象
@Autowired
private MongoChatMemoryStore mongoChatMemoryStore;
@Bean
public ChatMemoryProvider chatMemoryProvider() {
return memoryId -> MessageWindowChatMemory.builder()
.id(memoryId)
.maxMessages(10)
.chatMemoryStore(mongoChatMemoryStore)//配置持久化对象
.build();
}
}测试
java
@Test
public void testSeparateChatMemory() {
String result = separateChatAssistant.chat(1,"告诉你我叫张三，记住了");
System.out.println(result);
String result2 = separateChatAssistant.chat(1,"我是谁");
System.out.println(result2);
String result3 = separateChatAssistant.chat(2,"告诉你我叫李四，记住了");
System.out.println(result3);
String result4 = separateChatAssistant.chat(2,"我是谁");
System.out.println(result4);
}提示词Prompt
直接加载
java
@SystemMessage("你是我的好朋友，请用东北话回答问题。今天是{{current_date}}")//系统消息提示词
String chat(@MemoryId int memoryId, @UserMessage String userMessage);从txt文件中加载
java
@SystemMessage(fromResource="system.txt")
Stringchat(@MemoryIdintmemoryId,@UserMessageStringuserMessage);
Function calling函数调用
例如，大语言模型本身并不擅长数学运算。如果应用场景中偶尔会涉及到数学计算，我们可以为他提供一个"数学工具"。当我们提出问题时，大语言模型会判断是否使用某个工具。
RAG知识库
待更
java
@Component
public class CalculatorTools {
@Tool
public double sum(double a, double b) {
System.out.println("调用加法运算");
return a + b;
}
@Tool
public double squareRoot(double x) {
System.out.println("调用平方根运算");
return Math.sqrt(x);
}
}添加tools
java
@AiService(
wiringMode = EXPLICIT,
chatModel = "qwenChatModel",
chatMemoryProvider = "chatMemoryProvider",
tools = "calculatorTools" // 配置tools
)测试
java
@SpringBootTest
public class ToolsTest {
@Autowired
private SeparateChatAssistant separateChatAssistant;
@Test
public void testCalculatorTools() {
String answer = separateChatAssistant.chat(1, "1+2等于几，475695037565的平方根是多少？");
//答案: 3, 689706.4865
System.out.println(answer);
}
}项目实战（小智医疗）
创建AIService和配置类
java
@AiService(
wiringMode = EXPLICIT,
chatModel = "qwenChatModel",
chatMemoryProvider = "chatMemoryProviderXiaozhi"
)
public interface XiaozhiAgent {
@SystemMessage(fromResource = "xiaozhi-prompt-template.txt")
String chat(@MemoryId Long memoryId, @UserMessage String userMessage );
}
bash
你的名字是"硅谷小智"，你是一家名为"北京协和医院"的智能客服。
你是一个训练有素的医疗顾问和医疗伴诊助手。
你态度友好、礼貌且言辞简洁。
1、请仅在用户发起第一次会话时，和用户打个招呼，并介绍你是谁。
2、作为一个训练有素的医疗顾问，
请基于当前临床实践和研究，针对患者提出的特定健康问题，提供详细、准确且实用的医疗建议。请同时考虑可能的病因、诊断流程、治疗方案以及预防措施，并给出在不同情境下的应对策略。对于药物治疗，请特别指明适用的药品名称、剂量和疗程。如果需要进一步的检查或就医，也请明确指示。
3、作为医疗伴诊助手，你可以回答用户就医流程中的相关问题，主要包含以下功能：
AI分导诊：根据患者的病情和就医需求，智能推荐最合适的科室。
AI挂号助手：实现智能查询是否有挂号号源服务；实现智能预约挂号服务；实现智能取消挂号服务。
4、你必须遵守的规则如下：
在获取挂号预约详情或取消挂号预约之前，你必须确保自己知晓用户的姓名（必选）、身份证号（必选）、预约科室（必选）、预约日期（必选，格式举例：2025-04-14）、预约时间（必选，格式：上午 或 下午）、预约医生（可选）。
当被问到其他领域的咨询时，要表示歉意并说明你无法在这方面提供帮助。
5、请在回答的结果中适当包含一些轻松可爱的图标和表情。
6、今天是{{current_date}}。
java
@Configuration
public class AIConfig {
@Autowired
private MongoChatMemoryStore mongoChatMemoryStore;
@Bean
public ChatMemory chatMemory() {
return MessageWindowChatMemory.withMaxMessages(10);
}
@Bean
public ChatMemoryProvider chatMemoryProviderXiaozhi() {
return memoryId -> MessageWindowChatMemory
.builder()
.id(memoryId)
.maxMessages(50)
.chatMemoryStore(mongoChatMemoryStore)
.build();
}
}配置controller
java
@Tag(name = "小智医疗")
@RestController
@RequestMapping("/xiaozhi")
public class XiaozhiController {
@Autowired
private XiaozhiAgent xiaozhiAgent;
@Operation(summary = "对话")
@PostMapping("/chat")
public String chat(@RequestBody ChatForm chatForm){
return xiaozhiAgent.chat(chatForm.getMemoryId(),chatForm.getMessage());
}
}建表语句（实体类）
sql
CREATE DATABASE `guiguxiaozhi`;
USE `guiguxiaozhi`;
CREATE TABLE `appointment` (
`id` BIGINT NOT NULL AUTO_INCREMENT,
`username` VARCHAR(50) NOT NULL,
`id_card` VARCHAR(18) NOT NULL,
`department` VARCHAR(50) NOT NULL,
`date` VARCHAR(10) NOT NULL,
`time` VARCHAR(10) NOT NULL,
`doctor_name` VARCHAR(50) DEFAULT NULL,
PRIMARY KEY (`id`)
);
java
@Data
@AllArgsConstructor
@NoArgsConstructor
public class Appointment {
@TableId(type = IdType.AUTO)
private Long id;
private String username;
private String idCard;
private String department;
private String date;
private String time;
private String doctorName;
}
java
@Data
@AllArgsConstructor
@NoArgsConstructor
@Getter
@Setter
public class Department {
private String name;
private String doctorName;
private LocalDate startTime;
private LocalDate endTime;
}Mapper与Service
XML
<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE mapper
PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
"http://mybatis.org/dtd/mybatis-3-mapper.dtd">
<mapper namespace="com.eden.mapper.AppointmentMapper">
</mapper>
java
package com.eden.mapper;
import com.baomidou.mybatisplus.core.mapper.BaseMapper;
import com.eden.dao.po.Appointment;
import org.apache.ibatis.annotations.Mapper;
/**
* @author 25094
* @create 2026/2/2 下午5:45
* @description
*/
@Mapper
public interface AppointmentMapper extends BaseMapper<Appointment> {
}
java
package com.eden.service;
import com.baomidou.mybatisplus.extension.service.IService;
import com.eden.dao.po.Appointment;
/**
* @author 25094
* @create 2026/2/3 下午2:05
* @description
*/
public interface AppointmentService extends IService<Appointment> {
Appointment getOne(Appointment appointment);
}
java
@Service
public class AppointmentServiceImpl extends ServiceImpl<AppointmentMapper, Appointment> implements AppointmentService {
/**
* 查询订单是否存在
* @param appointment
* @return
*/
@Override
public Appointment getOne(Appointment appointment) {
LambdaQueryWrapper<Appointment> queryWrapper = new LambdaQueryWrapper<>();
queryWrapper.eq(Appointment::getUsername, appointment.getUsername());
queryWrapper.eq(Appointment::getIdCard, appointment.getIdCard());
queryWrapper.eq(Appointment::getDepartment, appointment.getDepartment());
queryWrapper.eq(Appointment::getDate, appointment.getDate());
queryWrapper.eq(Appointment::getTime, appointment.getTime());
return baseMapper.selectOne(queryWrapper);
}
}创建Tools(简单实现)
java
@Component
public class AppointmentTools {
@Autowired
private AppointmentService appointmentService;
@Tool(name="预约挂号",value = "根据参数，先执行工具方法queryDepartment查询告诉用户是否可预约，" +
"并让用户确认所有预约信息，用户确认后再进行预约")
public String bookAppointment(Appointment appointment){
Appointment appointmentDB=appointmentService.getOne( appointment);
if (appointmentDB==null){
appointment.setId( null);//防止大模型幻觉设置了id
if (appointmentService.save( appointment)){
return "预约成功";
}else{
return "预约失败";
}
}
return "该用户已预约挂号";
}
@Tool(name="查询是有号源",value = "根据科室名称，日期，时间和医生查询是否有号源，并返回给用户")
public String queryDepartment(
@P(value = "科室名称") String name,
@P(value = "日期") String date,
@P(value = "时间,可选值：上午、下午") String time,
@P(value = "医生名称",required = false) String doctor
){
System.out.println("查询是否有号源");
System.out.println("科室名称："+ name);
System.out.println("日期："+ date);
System.out.println("时间："+ time);
System.out.println("医生名称："+ doctor);
Department department=new Department();
department.setName("小儿科");
department.setDoctorName("王医生");
LocalDate startTime=LocalDate.of(2026,1,1);
department.setStartTime(startTime);
department.setEndTime(startTime.plusDays(180));
if (department.getName().equals( name)){
if (department.getDoctorName().equals( doctor)||doctor==null){
if (department.getStartTime().isBefore( LocalDate.parse(date))&&department.getEndTime().isAfter( LocalDate.parse(date))){
return "该医生有号源，请确认预约信息：科室名称："+ name+"，日期："+ date+"，时间："+ time;
}else {
return "您所预定的日期对应的医生排期不在排班时间内，该医生的排班时间为"+
department.getStartTime()+"至"+department.getEndTime();
}
}else {
return "没有该医生";
}
}else{
return "没有该科室";
}
}
@Tool(name="取消预约",value = "根据参数，取消预约挂号")
public String cancelAppointment(Appointment appointment){
Appointment appointmentDB=appointmentService.getOne( appointment);
if (appointmentDB!= null) {
//删除预约记录
if (appointmentService.removeById(appointmentDB.getId())){
return "取消成功";
}else {
return "取消失败";
}
}
return "您没有预约记录，请核对预约科室和时间";
}
}把tool配置在智能体中
java
@AiService(
wiringMode = EXPLICIT,
chatModel = "qwenChatModel",
chatMemoryProvider = "chatMemoryProviderXiaozhi",
tools = "appointmentTools"
)
public interface XiaozhiAgent {
@SystemMessage(fromResource = "xiaozhi-prompt-template.txt")
String chat(@MemoryId Long memoryId, @UserMessage String userMessage );
}测试
