4.Spring Ai Alibaba

第一章 ChatModel

Spring AI Alibaba官网: https://java2ai.com/docs/versions

第一节父工程

整体项目目录结构

STEP1: 创建普通的Maven项目

注意:不要用SpringInintilizer去创建

STEP2: 修改pom.xml

位置: ~/pom.xml 【共计8处修改】

<?xml version="1.0" encoding="UTF-8"?>
<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>

    <groupId>com.mts</groupId>
    <artifactId>untitled21</artifactId>
    <version>1.0-SNAPSHOT</version>
    <packaging>pom</packaging>                 <!--1-->

    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <!--版本要对应 SpringBoot/SpringAI/SpringAIAlibaba-->
        <java.version>21</java.version>                                  <!--2-->
        <spring-boot.version>3.5.5</spring-boot.version>                 <!--3-->
        <spring-ai.version>1.0.0</spring-ai.version>                     <!--4-->
        <SpringAIAlibaba.version>1.0.0.2</SpringAIAlibaba.version>       <!--5-->
    </properties>

    <!--6.三个依赖-->
    <dependencyManagement>
        <dependencies>
            <!-- Spring Boot -->
            <dependency>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-dependencies</artifactId>
                <version>${spring-boot.version}</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
            <!-- Spring AI -->
            <dependency>
                <groupId>org.springframework.ai</groupId>
                <artifactId>spring-ai-bom</artifactId>
                <version>${spring-ai.version}</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
            <!-- Spring AI Alibaba -->
            <dependency>
                <groupId>com.alibaba.cloud.ai</groupId>
                <artifactId>spring-ai-alibaba-bom</artifactId>
                <version>${SpringAIAlibaba.version}</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>

        </dependencies>
    </dependencyManagement>
    <!--7.build插件-->
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
                <version>${spring-boot.version}</version>
            </plugin>
        </plugins>
    </build>
    <!--8.用Alibaba的仓库,原来的镜像没有SpringAIAlibaba-->
    <repositories>
        <repository>
            <id>spring-milestones</id>
            <name>Spring Milestones</name>
            <url>https://repo.spring.io/milestone</url>
            <snapshots>
                <enabled>false</enabled>
            </snapshots>
        </repository>
    </repositories>


</project>

第二节子工程

STEP1: 创建子model

STEP2: 修改子pom.xml

<?xml version="1.0" encoding="UTF-8"?>
<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>com.mts</groupId>
        <artifactId>untitled21</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>

    <artifactId>SAA01_HelloWorld</artifactId>

    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>


    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!-- 引入 springai alibaba DashScope 模型适配的 Starter -->
        <dependency>
            <groupId>com.alibaba.cloud.ai</groupId>
            <artifactId>spring-ai-alibaba-starter-dashscope</artifactId>
        </dependency>
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--hutool-->
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.8.22</version>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.11.0</version>
                <configuration>
                    <compilerArgs>
                        <arg>-parameters</arg>
                    </compilerArgs>
                    <source>21</source>
                    <target>21</target>
                </configuration>
            </plugin>
        </plugins>
    </build>

    <repositories>
        <repository>
            <id>spring-milestones</id>
            <name>Spring Milestones</name>
            <url>https://repo.spring.io/milestone</url>
            <snapshots>
                <enabled>false</enabled>
            </snapshots>
        </repository>
    </repositories>

</project>

STEP3: application.properties

阿里百炼: https://bailian.console.aliyun.com/cn-beijing?apiKey=1&tab=api#/api

①Key获取	②Model获取		③URL获取

位置: resources/application.properties

server.port=8080

#大模型对话中文乱码UTF8编码处理
server.servlet.encoding.enabled=true
server.servlet.encoding.force=true
server.servlet.encoding.charset=UTF-8

spring.application.name=SAA01_HelloWorld

# ====SpringAIAlibaba Config=============
spring.ai.dashscope.api-key=sk-6bb83948db224d3abcbd03f24be05228
spring.ai.dashscope.base-url=https://dashscope.aliyuncs.com/compatible-mode/v1
spring.ai.dashscope.chat.options.model=qwen-plus

STEP4: SpringBoot的启动类

位置: java/com/mts/SAA01HelloWorldApplication.java

package com.mts;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

@SpringBootApplication
public class SAA01HelloWorldApplication {
    public static void main(String[] args) {
        SpringApplication.run(SAA01HelloWorldApplication.class, args);
    }
}

STEP5: 配置类注入ChatModel

位置: java/com/mts/config/SaaLLMConfig.java
注意: 注意包! 注意包! 注意包! 看清楚是SpringAi的还是DasScope的

package com.mts.config;

import com.alibaba.cloud.ai.dashscope.api.DashScopeApi;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

@Configuration
public class SaaLLMConfig {

    @Value("${spring.ai.dashscope.api-key}")
    private String apiKey;

    @Bean
    public DashScopeApi dashScopeApi() {
        return DashScopeApi.builder().apiKey(apiKey).build();
    }
}

STEP6: 编写Controller进行测试

说明: 我这里前后端传递做了封装, 简单测试就返回String即可
位置: java/com/mts/Controller/ChatHelloController.java

package com.mts.Controller;

import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatModel;
import com.mts.common.response.ResponseResult;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import reactor.core.publisher.Flux;

@RestController
@RequestMapping("/hello")
public class ChatHelloController {

    @Autowired
    private DashScopeChatModel dashScopeChatModel; // ChatModel的实现类

    /**
     * call: 非流式返回
     *
     * @param msg
     * @return
     */
    @GetMapping("/dochat")
    public ResponseResult<String> doChat(@RequestParam(value = "message", defaultValue = "你是谁") String msg) {
        String resContent = dashScopeChatModel.call(msg);
        return ResponseResult.ok(resContent);
    }

    /** stream: 流式返回
     *
     * @param msg
     * @return
     */
    @GetMapping("/streamchat")
    public Flux<String> streamChat(@RequestParam(value = "message", defaultValue = "你是谁") String msg) {
        Flux<String> resStream = dashScopeChatModel.stream(msg);
        return resStream;
    }
}

第二章调用本地模型Ollama

第一节 Ollama本地大模型部署

STPE1: 下载Ollama软件

官网: https://ollama.com/download/windows

STEP2: 配置环境变量

STEP3: 下载deepseek

直接cmd, 输入会自动下载

ollama pull deepseek-r1:1.5b

第二节 Ollama常用命令

指令	作用
`ollama pull xxx`	拉取模型
`ollama ps`	后台正在运行的实例
`ollama list`	查看下载的本地模型
`ollama run xxx`	运行xxx模型在后台
`ollama stop xxx`	停止xxx模型在运行

第三节对接本地大模型

STEP1: 创建子model

STEP2: 修改子pom.xml

位置:~/pom.xml 【共计修改1处】

<?xml version="1.0" encoding="UTF-8"?>
<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>com.mts</groupId>
        <artifactId>untitled21</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>

    <artifactId>SAA02_Ollama</artifactId>

    <properties>
        <maven.compiler.source>21</maven.compiler.source>
        <maven.compiler.target>21</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <!-- 引入 springai alibaba DashScope 模型适配的 Starter -->
        <dependency>
            <groupId>com.alibaba.cloud.ai</groupId>
            <artifactId>spring-ai-alibaba-starter-dashscope</artifactId>
        </dependency>

        <!--!!!!!!!!修改1处: ollama-->                                                    
        <dependency>
            <groupId>org.springframework.ai</groupId>
            <artifactId>spring-ai-starter-model-ollama</artifactId>
            <version>1.0.0</version>
        </dependency>
        
        
        
        <!--lombok-->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        <!--hutool-->
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.8.22</version>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.11.0</version>
                <configuration>
                    <compilerArgs>
                        <arg>-parameters</arg>
                    </compilerArgs>
                    <source>21</source>
                    <target>21</target>
                </configuration>
            </plugin>
        </plugins>
    </build>

    <repositories>
        <repository>
            <id>spring-milestones</id>
            <name>Spring Milestones</name>
            <url>https://repo.spring.io/milestone</url>
            <snapshots>
                <enabled>false</enabled>
            </snapshots>
        </repository>
    </repositories>

</project>

STEP3: application.properties

Ollama端口: 11434
model的名称: 自己去ollama list 查看

server.port=8080

#中文UTF-8
server.servlet.encoding.enabled=true
server.servlet.encoding.force=true
server.servlet.encoding.charset=UTF-8

spring.application.name=SAA01_Ollama

# ====ollama Config =============
spring.ai.dashscope.api-key=sk-6bb83948db224d3abcbd03f24be05228
spring.ai.ollama.base-url=http://localhost:11434
spring.ai.ollama.chat.model=deepseek-r1:1.5b

STEP4: SpringBoot的启动类

STEP5: 编写Controller进行测试

位置: java/com/mts/Controller/ChatHelloController.java
注意: SpringAIAlibaba有dashscopeChatModel和ollamaChatModel两个ChatModel(接口)实现, 分别对应远程调用和本地调用, so要用Qualifier去指定

package com.mts.controller;

import com.mts.common.response.ResponseResult;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import reactor.core.publisher.Flux;

@RestController
@RequestMapping("/ollama")
public class OllamaController {

    // SpringAIAlibaba有dashscopeChatModel和ollamaChatModel两个ChatModel(接口)实现
    // 分别对应 远程调用 和 本地调用 // so要用Qualifier去指定
    @Autowired
    @Qualifier("ollamaChatModel")
    private ChatModel chatModel;

    @GetMapping("/ollama/chat")
    public ResponseResult<String> chat(@RequestParam(name = "message") String msg) {
        String result = chatModel.call(msg);
        return ResponseResult.ok(result);
    }

    @GetMapping("/ollama/streamchat")
    public Flux<String> streamchat(@RequestParam(name = "message", defaultValue = "你是谁") String msg) {
        return chatModel.stream(msg);
    }

}

STEP6: cmd运行Ollama模型

注意: 要cmd运行了对应的模型, 才能有回复

ollama run deepseek-r1:1.5b

第三章 ChatClient

第一节 ChatClient 🆚 ChatModel

	ChatModel	ChatClient
注入形式	自动注入	手动注入且依赖ChatModel，使用自动配置的 ChatClient.Builder
调用方式	直接调用call()或者stream()方法	链式调用，支持同步和反应式（Reactive）编程模型，自动封装提示词和解析响应
结构化输出	需手动解析响应文本	支持自动映射为java对象
适用场景	实现简单功能和场景	快速开发复杂功能的场景，如企业级智能XXX问答系统
功能扩展	偏弱	强，支持聊天记忆(Chat Memory)/工具Tool/函数调用（Function Calling）/RAG等等

第二节如何获取ChatClient

有两个默认实现(①远程模型 ②本地模型)	这个Default其实是null来的

@Autowired
private DashScopeChatModel dashScopeChatModel; // ChatModel的实现类

private ChatClient chatClient; // 报错!!!! 如图3

第三节通过构造方法Builder注入

分析: 可以看到ChatClient不是@Autowired注入的, 而是构造方法中build出来的!

package com.mts.Controller;

import com.mts.common.response.ResponseResult;
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.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import reactor.core.publisher.Flux;

@RestController
@RequestMapping("/chatclient")
public class ChatClientController {


    private ChatClient chatClient;

    // !!!! 构造方法注入; 
    public ChatClientController(ChatModel chatModel) {
        this.chatClient = ChatClient.builder(chatModel).build();
    }
	
	// 非流输出
    @GetMapping("/dochat")
    public ResponseResult<String> doChat(@RequestParam(value = "message", defaultValue = "你是谁") String msg) {
        String resContent = chatClient.prompt().user(msg).call().content();
        return ResponseResult.ok(resContent);
    }
	
	// 流输出
    @GetMapping("/streamchat")
    public Flux<String> streamChat(@RequestParam(value = "message", defaultValue = "你是谁") String msg) {
        Flux<String> resContent = chatClient.prompt().user(msg).stream().content();
        return resContent;
    }

}

第四节通过配置类注入ChatClient

易混: 你第一章/第一节/STEP5不也写的”配置类注入ChatModel”吗? 那不一样? ChatChatModel也需要注入?
回答: 不不不! 那里至少注入apikey, 让DashScopChatModel拿个apikey; 而这里是用配置类build一个ChatClient然后注入Bean

配置类
Controller中使用

位置: java/com/mts/config/SaaLLMConfig.java 【共计4处修改】

package com.mts.config;

import com.alibaba.cloud.ai.dashscope.api.DashScopeApi;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

@Configuration
public class SaaLLMConfig {

    @Value("${spring.ai.dashscope.api-key}")
    private String apiKey;

    @Bean
    public DashScopeApi dashScopeApi() {
        return DashScopeApi.builder().apiKey(apiKey).build();
    }

    @Bean                                                   // 1
    public ChatClient chatClient(ChatModel chatModel) {     // 2
        return ChatClient.builder(chatModel).build();       // 3
    }                                                       // 4
}

位置: 任意Controller中;
如何用: 直接@Autowired即可

@Autowired
private ChatClient dashScopechatClientv2;

第四章多模型共存

第一节 ChatModel配置多模型共存

STEP1: 创建子Model

STEP2: 修改子pom.xml 【同第一章】

STEP3: applicant.properties

位置: resourcesapplicant/properties 【删除两行】
分析: 因为是多个模型, 所以不在配置文件指定

server.port=8080

#?????????UTF8????
server.servlet.encoding.enabled=true
server.servlet.encoding.force=true
server.servlet.encoding.charset=UTF-8

spring.application.name=SAA01_HelloWorld

# ====SpringAIAlibaba Config=============
spring.ai.dashscope.api-key=sk-6bb83948db224d3abcbd03f24be05228
# spring.ai.dashscope.base-url=https://dashscope.aliyuncs.com/compatible-mode/v1  
# spring.ai.dashscope.chat.options.model=qwen-plus

STEP4: SpringBoot启动类

STEP5: 配置类注入多个ChatModel

位置: java/com/mts/config/SaaLLMConfig.java

package com.mts.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.model.ChatModel;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

@Configuration
public class SaaLLMConfig {
    @Value("${spring.ai.dashscope.api-key}")
    private String apiKey;
    // 模型名称
    private final String DEEPSEEKV3_2 = "deepseek-v3.2";
    private final String DEEPSEEKVR1 = "deepseek-r1";

    @Bean
    public ChatModel deepSeekV3_2() {
        return DashScopeChatModel.builder()
                .dashScopeApi(DashScopeApi.builder().apiKey(apiKey).build())
                .defaultOptions(DashScopeChatOptions.builder().withModel(DEEPSEEKV3_2).build())
                .build();
    }

    @Bean
    public ChatModel deepSeekR1() {
        return DashScopeChatModel.builder()
                .dashScopeApi(DashScopeApi.builder().apiKey(apiKey).build())
                .defaultOptions(DashScopeChatOptions.builder().withModel(DEEPSEEKVR1).build())
                .build();
    }

}

STEP6: 编写Controller进行测试

位置: java/src/main/java/com/mts/controller/MulChatModelController.java

package com.mts.controller;

import org.springframework.ai.chat.model.ChatModel;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import reactor.core.publisher.Flux;

@RestController
@RequestMapping("/mulchatmodel")
public class MulChatModelController {

    @Autowired
    @Qualifier("deepSeekV3_2")
    private ChatModel deepSeekV3_2;

    @Autowired
    @Qualifier("deepSeekR1")
    private ChatModel deepSeekR1;

    @GetMapping("/v3stream")
    public Flux<String> v3modelChat(@RequestParam(value = "message") String msg) {return deepSeekV3_2.stream(msg);}

    @GetMapping("/r1stream")
    public Flux<String> r1modelChat(@RequestParam(value = "message") String msg) {return deepSeekR1.stream(msg);}
}

第二节 ChatClient配置多模型共存

STEP5: 配置类注入多个ChatChatClient

位置: 同上【共11行修改】
注意: 要现有ChatModel再有ChatClient

package com.mts.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;

@Configuration
public class SaaLLMConfig {
    @Value("${spring.ai.dashscope.api-key}")
    private String apiKey;
    // 模型名称
    private final String DEEPSEEKV3_2 = "deepseek-v3.2";
    private final String DEEPSEEKVR1 = "deepseek-r1";

    @Bean
    public ChatModel deepSeekV3_2() {
        return DashScopeChatModel.builder()
                .dashScopeApi(DashScopeApi.builder().apiKey(apiKey).build())
                .defaultOptions(DashScopeChatOptions.builder().withModel(DEEPSEEKV3_2).build())
                .build();
    }

    @Bean
    public ChatModel deepSeekR1() {
        return DashScopeChatModel.builder()
                .dashScopeApi(DashScopeApi.builder().apiKey(apiKey).build())
                .defaultOptions(DashScopeChatOptions.builder().withModel(DEEPSEEKVR1).build())
                .build();
    }

    @Bean                                                                                                  // 1
    public ChatClient deepSeekV3_2ChatModel(@Qualifier("deepSeekV3_2") ChatModel deepSeekV3_2ChatModel) {  // 2
        return ChatClient.builder(deepSeekV3_2ChatModel)                                                   // 3
                .defaultOptions(ChatOptions.builder().model(DEEPSEEKV3_2).build())                         // 4
                .build();                                                                                  // 5
    }                                                                                                      // 6

    @Bean
    public ChatClient deepSeekR1ChatModel(@Qualifier("deepSeekR1") ChatModel deepSeekR1ChatModel) {         // 7
        return ChatClient.builder(deepSeekR1ChatModel)                                                      // 8
                .defaultOptions(ChatOptions.builder().model(DEEPSEEKVR1).build())                           // 9
                .build();                                                                                   // 10
    }                                                                                                       // 11

}

STEP6: 编写Controller进行测试

package com.mts.controller;

import org.springframework.ai.chat.client.ChatClient;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import reactor.core.publisher.Flux;

@RestController
@RequestMapping("/mulchatclient")
public class MulChatClientController {

    @Autowired
    @Qualifier("deepSeekV3_2ChatModel")
    private ChatClient deepSeekV3_2ChatModel;

    @Autowired
    @Qualifier("deepSeekR1ChatModel")
    private ChatClient deepSeekR1ChatModel;

    @GetMapping("/v3stream")
    public Flux<String> v3modelChat(@RequestParam(value = "message") String msg) {
        return deepSeekV3_2ChatModel.prompt().user(msg).stream().content();
    }

    @GetMapping("/r1stream")
    public Flux<String> r1modelChat(@RequestParam(value = "message") String msg) {
        return deepSeekR1ChatModel.prompt().user(msg).stream().content();
    }
}

居然能找到这来, 真是厉害~

4.Spring Ai Alibaba

第一章 ChatModel

第一节 父工程

STEP1: 创建普通的Maven项目

STEP2: 修改pom.xml

第二节 子工程

STEP1: 创建子model

STEP2: 修改子pom.xml

STEP3: application.properties

STEP4: SpringBoot的启动类

STEP5: 配置类注入ChatModel

STEP6: 编写Controller进行测试

第二章 调用本地模型Ollama

第一节 Ollama本地大模型部署

STPE1: 下载Ollama软件

STEP2: 配置环境变量

STEP3: 下载deepseek

第二节 Ollama常用命令

第三节 对接本地大模型

STEP1: 创建子model

STEP2: 修改子pom.xml

STEP3: application.properties

STEP4: SpringBoot的启动类

STEP5: 编写Controller进行测试

STEP6: cmd运行Ollama模型

第三章 ChatClient

第一节 ChatClient 🆚 ChatModel

第二节 如何获取ChatClient

第三节 通过构造方法Builder注入

第四节 通过配置类注入ChatClient

第四章 多模型共存

第一节 ChatModel配置多模型共存

STEP1: 创建子Model

STEP2: 修改子pom.xml 【同第一章】

STEP3: applicant.properties

STEP4: SpringBoot启动类

STEP5: 配置类注入多个ChatModel

STEP6: 编写Controller进行测试

第二节 ChatClient配置多模型共存

STEP5: 配置类注入多个ChatChatClient

STEP6: 编写Controller进行测试

第

第一节父工程

第二节子工程

第二章调用本地模型Ollama

第三节对接本地大模型

第二节如何获取ChatClient

第三节通过构造方法Builder注入

第四节通过配置类注入ChatClient

第四章多模型共存