一、说明
本章节主要实现在同一个项目中，同时使用不同的大模型，比如同时使用deepseek和qwen。
另外本章节代码是基于前面几篇SSA系列文章，所使用的都是同一个父工程的聚合工程。
二、POM依赖
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.example</groupId>
<artifactId>ssa</artifactId>
<version>1.0-SNAPSHOT</version>
</parent>
<artifactId>ssa-streaming</artifactId>
<packaging>jar</packaging>
<name>ssa-streaming</name>
<url>http://maven.apache.org</url>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<maven.compiler.source>17</maven.compiler.source>
<maven.compiler.target>17</maven.compiler.target>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>com.alibaba.cloud.ai</groupId>
<artifactId>spring-ai-alibaba-starter-dashscope</artifactId>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>1.18.34</version>
<optional>true</optional>
</dependency>
<dependency>
<groupId>cn.hutool</groupId>
<artifactId>hutool-all</artifactId>
<version>5.8.16</version>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.8.1</version>
<configuration>
<source>17</source>
<target>17</target>
<encoding>UTF-8</encoding>
</configuration>
</plugin>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
<version>${spring-boot.version}</version>
</plugin>
</plugins>
</build>
</project>
三、配置文件
# 启动端口设置
server.port=8083
# 字符编码设置，防止乱码
server.servlet.encoding.enabled=true
server.servlet.encoding.force=true
server.servlet.encoding.charset=UTF-8
# 项目名称
spring.application.name=ssa-streaming
# AI 配置文件
spring.ai.dashscope.api-key=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxx
spring.ai.dashscope.base-url=https://dashscope.aliyuncs.com/compatible-mode/v1
spring.ai.dashscope.chat.options.model=qwen3-max
四、配置类
package org.example.config;
import com.alibaba.cloud.ai.dashscope.api.DashScopeApi;
import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatModel;
import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatOptions;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.prompt.ChatOptions;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
/**
* @author zhanxuewei
*/
@Configuration
public class SsaLLMConfig {
@Value("${spring.ai.dashscope.api-key}")
private String apiKey;
private static final String MODEL_DEEPSEEK = "deepseek-v3";
private static final String MODEL_QWEN = "qwen-max";
@Bean(name = "deepseek")
public ChatModel deepseek() {
return DashScopeChatModel.builder()
.dashScopeApi(DashScopeApi.builder().apiKey(apiKey).build())
.defaultOptions(DashScopeChatOptions.builder().withModel(MODEL_DEEPSEEK).build())
.build();
}
@Bean(name = "qwen")
public ChatModel qwen() {
return DashScopeChatModel.builder()
.dashScopeApi(DashScopeApi.builder().apiKey(apiKey).build())
.defaultOptions(DashScopeChatOptions.builder().withModel(MODEL_QWEN).build())
.build();
}
@Bean(name = "deepseekChatClient")
public ChatClient deepeekChatClient(@Qualifier("deepseek") ChatModel deepseek) {
return ChatClient.builder(deepseek)
.defaultOptions(ChatOptions.builder().model(MODEL_DEEPSEEK).build())
.build();
}
@Bean(name = "qwenChatClient")
public ChatClient qwenChatClient(@Qualifier("qwen") ChatModel qwen) {
return ChatClient.builder(qwen)
.defaultOptions(ChatOptions.builder().model(MODEL_QWEN).build())
.build();
}
}
五、控制层
package org.example.controller;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import reactor.core.publisher.Flux;
@Slf4j
@RestController
public class StreamingController {
@Resource(name = "deepseek")
private ChatModel deepseekChatModel;
@Resource(name = "qwen")
private ChatModel qwenChatModel;
@Resource(name = "deepseekChatClient")
private ChatClient deepseekChatClient;
@Resource(name = "qwenChatClient")
private ChatClient qwenChatClient;
/**
* 调用模型
*
* @param msg
* @return
*/
@GetMapping("/text/chat")
public String textChat(@RequestParam(name = "msg", defaultValue = "你是谁？") String msg) {
String content = deepseekChatClient
.prompt(msg)
.call()
.content();
log.info("content: {}", content);
return content;
}
@GetMapping("/stream/chat")
public Flux<String> streamChat(@RequestParam(name = "message", defaultValue = "你是谁？") String message) {
log.info("message: {}", message);
Flux<String> result = deepseekChatModel.stream(message);
log.info("result: {}", result);
return result;
}
}
六、测试
