init

pom.xml

@@ -0,0 +1,67 @@
+<?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>org.springframework.boot</groupId>
+        <artifactId>spring-boot-starter-parent</artifactId>
+        <version>3.5.8</version>
+        <relativePath/>
+    </parent>
+
+    <groupId>com.baoshi</groupId>
+    <artifactId>spring-ai-alibaba-demo</artifactId>
+    <version>1.0-SNAPSHOT</version>
+
+    <properties>
+        <maven.compiler.source>17</maven.compiler.source>
+        <maven.compiler.target>17</maven.compiler.target>
+        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+    </properties>
+
+    <dependencies>
+        <!-- 显式指定 jackson-annotations 版本，解决 mcp-core 引入的 2.17.0 与 jackson-databind 2.19.4 不兼容导致的 NoSuchMethodError: JsonProperty.isRequired() -->
+        <dependency>
+            <groupId>com.fasterxml.jackson.core</groupId>
+            <artifactId>jackson-annotations</artifactId>
+            <version>2.19.4</version>
+        </dependency>
+
+        <!-- Spring AI Alibaba Agent Framework -->
+        <dependency>
+            <groupId>com.alibaba.cloud.ai</groupId>
+            <artifactId>spring-ai-alibaba-agent-framework</artifactId>
+            <version>1.1.2.2</version>
+        </dependency>
+
+        <!-- Spring AI Ollama - 本地运行大模型（需与 spring-ai-alibaba 1.1.2 同版本） -->
+        <dependency>
+            <groupId>org.springframework.ai</groupId>
+            <artifactId>spring-ai-starter-model-ollama</artifactId>
+            <version>1.1.2</version>
+        </dependency>
+
+        <!-- DashScope ChatModel 支持（如果使用其他模型，请跳转 Spring AI 文档选择对应的 starter） -->
+        <dependency>
+            <groupId>com.alibaba.cloud.ai</groupId>
+            <artifactId>spring-ai-alibaba-starter-dashscope</artifactId>
+            <version>1.1.2.2</version>
+        </dependency>
+
+        <!-- WebFlux：Spring AI 依赖引入 spring-webflux 后，Spring Boot 会以响应式模式启动，需显式添加此 starter 提供 ReactiveWebServerFactory -->
+        <dependency>
+            <groupId>org.springframework.boot</groupId>
+            <artifactId>spring-boot-starter-webflux</artifactId>
+        </dependency>
+
+        <!-- 测试依赖（含 JUnit 5，支持方法参数 @Autowired 注入） -->
+        <dependency>
+            <groupId>org.springframework.boot</groupId>
+            <artifactId>spring-boot-starter-test</artifactId>
+            <scope>test</scope>
+        </dependency>
+    </dependencies>
+
+</project>

src/main/java/com/baoshi/ApiListTool.java

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+package com.baoshi;
+
+import org.springframework.ai.chat.model.ToolContext;
+
+import java.util.List;
+import java.util.Map;
+import java.util.function.BiFunction;
+
+/**
+ * 业务
+ */
+public class ApiListTool implements BiFunction<ApiListTool.DomainRequest, ToolContext, String> {
+
+    //Map<String, List<String>>.of("仓库",)
+    private final Map<String, List<String>> map = Map.of(
+            "出库", List.of("/api/outbound"),
+            "存储", List.of("/api/Inventory")
+    );
+
+    @Override
+    public String apply(DomainRequest request, ToolContext toolContext) {
+        return String.join(",", map.get(request.domain()));
+    }
+
+    /** 与 LLM tool call 返回的 JSON 结构对应 */
+    public record DomainRequest(String domain) {
+    }
+}

src/main/java/com/baoshi/BusinessRouteTool.java

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+package com.baoshi;
+
+import org.springframework.ai.chat.model.ToolContext;
+
+import java.util.function.BiFunction;
+
+/**
+ * 业务
+ */
+public class BusinessRouteTool implements BiFunction<BusinessRouteTool.RouteRequest, ToolContext, String> {
+
+    @Override
+    public String apply(RouteRequest request, ToolContext toolContext) {
+
+        return """
+               订单相关业务域:出库,
+               移库、盘点、上架相关业务域:存储
+               """;
+    }
+
+    /** 与 LLM tool call 返回的 JSON 结构对应 */
+    public record RouteRequest() {
+    }
+}

src/main/java/com/baoshi/Main.java

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+package com.baoshi;
+
+import org.springframework.boot.SpringApplication;
+import org.springframework.boot.autoconfigure.SpringBootApplication;
+
+/**
+ * @author Wen
+ * @date 2026/3/12 18:38
+ */
+//TIP To <b>Run</b> code, press <shortcut actionId="Run"/> or
+// click the <icon src="AllIcons.Actions.Execute"/> icon in the gutter.
+@SpringBootApplication
+public class Main {
+    public static void main(String[] args) {
+        SpringApplication.run(Main.class, args);
+    }
+}

src/main/java/com/baoshi/conf/AiConfig.java

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+package com.baoshi.conf;
+
+import com.alibaba.cloud.ai.autoconfigure.dashscope.DashScopeChatProperties;
+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.model.ollama.autoconfigure.OllamaChatProperties;
+import org.springframework.ai.ollama.OllamaChatModel;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+
+@Configuration
+public class AiConfig {
+
+    @Bean
+    public ChatClient dashScope(@Autowired DashScopeChatModel dashScopeChatModel,
+                                @Autowired DashScopeChatProperties properties) {
+        return ChatClient.builder(dashScopeChatModel)
+                //.defaultOptions(DashScopeChatOptions.builder().build())
+                .build();
+    }
+
+    @Bean
+    public ChatClient ollama(@Autowired OllamaChatModel ollamaChatModel,
+                             @Autowired OllamaChatProperties properties) {
+        return ChatClient.builder(ollamaChatModel).defaultOptions(properties.getOptions()).build();
+    }
+
+}

src/main/java/com/baoshi/controller/MultiModelsController.java

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+package com.baoshi.controller;
+
+import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.http.MediaType;
+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;
+import reactor.core.publisher.Mono;
+import reactor.core.scheduler.Schedulers;
+
+import java.util.Map;
+
+@RestController
+public class MultiModelsController {
+
+    @Autowired
+    private Map<String, ChatClient> chatClientMap;
+
+    @GetMapping("/chat")
+    Mono<String> generation(@RequestParam String message,
+                            @RequestParam String model) {
+        ChatClient chatClient = chatClientMap.get(model);
+        if (chatClient == null) {
+            return Mono.just("Unknown model: " + model);
+        }
+        return Mono.fromCallable(() -> chatClient.prompt().user(message).call().content())
+                .subscribeOn(Schedulers.boundedElastic());
+    }
+
+    @GetMapping(value = "/chatStream", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
+    Flux<String> chatStream(@RequestParam String message,
+                            @RequestParam String model) {
+        ChatClient chatClient = chatClientMap.get(model);
+        if (chatClient == null) {
+            return Flux.just("Unknown model: " + model);
+        }
+        return chatClient.prompt().user(message).stream().content();
+    }
+}

src/main/resources/application.yml

@@ -0,0 +1,13 @@
+# 解决 Spring AI 1.0.0-M6 与 1.1.x 并存时的 chatClientBuilderConfigurer bean 冲突
+spring:
+  ai:
+    ollama:
+      base-url: http://100.121.13.117:11434
+      chat:
+        model: qwen2.5:7b
+    dashscope:
+      api-key: sk-36a57382b9ae4db696ecd07eb7150a88
+      chat:
+        api-key: sk-36a57382b9ae4db696ecd07eb7150a88
+server:
+  port: 8080

src/test/java/com/baoshi/ChatModelTest.java

@@ -0,0 +1,13 @@
+package com.baoshi;
+
+import org.springframework.boot.test.context.SpringBootTest;
+
+/**
+ * @author Wen
+ * @date 2026/3/20 18:26
+ */
+@SpringBootTest(classes = Main.class)
+public class ChatModelTest {
+
+    
+}

src/test/java/com/baoshi/DemoTest.java

@@ -0,0 +1,203 @@
+package com.baoshi;
+
+import com.alibaba.cloud.ai.dashscope.audio.tts.DashScopeAudioSpeechModel;
+import com.alibaba.cloud.ai.dashscope.audio.tts.DashScopeAudioSpeechOptions;
+import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatModel;
+import com.alibaba.cloud.ai.dashscope.chat.DashScopeChatOptions;
+import com.alibaba.cloud.ai.dashscope.chat.MessageFormat;
+import com.alibaba.cloud.ai.dashscope.common.DashScopeApiConstants;
+import com.alibaba.cloud.ai.dashscope.image.DashScopeImageModel;
+import com.alibaba.cloud.ai.dashscope.image.DashScopeImageOptions;
+import com.alibaba.cloud.ai.dashscope.spec.DashScopeModel;
+import com.alibaba.cloud.ai.dashscope.video.DashScopeVideoModel;
+import com.alibaba.cloud.ai.dashscope.video.DashScopeVideoOptions;
+import com.alibaba.cloud.ai.dashscope.video.VideoMessage;
+import com.alibaba.cloud.ai.dashscope.video.VideoPrompt;
+import com.alibaba.cloud.ai.dashscope.video.VideoResponse;
+import com.alibaba.cloud.ai.graph.agent.ReactAgent;
+import com.alibaba.cloud.ai.graph.checkpoint.savers.MemorySaver;
+import com.alibaba.cloud.ai.graph.exception.GraphRunnerException;
+import com.baoshi.BusinessRouteTool.RouteRequest;
+import org.junit.jupiter.api.Test;
+import org.springframework.ai.audio.tts.Speech;
+import org.springframework.ai.audio.tts.TextToSpeechPrompt;
+import org.springframework.ai.audio.tts.TextToSpeechResponse;
+import org.springframework.ai.chat.messages.AssistantMessage;
+import org.springframework.ai.chat.messages.UserMessage;
+import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.ai.chat.model.ChatResponse;
+import org.springframework.ai.chat.prompt.Prompt;
+import org.springframework.ai.content.Media;
+import org.springframework.ai.image.ImagePrompt;
+import org.springframework.ai.image.ImageResponse;
+import org.springframework.ai.tool.ToolCallback;
+import org.springframework.ai.tool.function.FunctionToolCallback;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.beans.factory.annotation.Qualifier;
+import org.springframework.boot.test.context.SpringBootTest;
+import org.springframework.core.io.FileSystemResource;
+import org.springframework.util.MimeTypeUtils;
+import reactor.core.publisher.Flux;
+
+import java.io.ByteArrayOutputStream;
+import java.io.File;
+import java.io.FileOutputStream;
+import java.io.IOException;
+import java.net.MalformedURLException;
+import java.util.Collections;
+
+/**
+ * @author Wen
+ * @date 2026/3/12 21:45
+ */
+@SpringBootTest(classes = Main.class)
+class DemoTest {
+    @Autowired
+    @Qualifier("ollamaChatModel")
+    // @Qualifier("dashScopeChatModel")
+    private ChatModel chatModel;
+
+    @Test
+    void contextLoads() throws GraphRunnerException {
+        ToolCallback businessTool = FunctionToolCallback
+                .builder("business_route", new BusinessRouteTool())
+                .description("根据用户描述确定业务域")
+                .inputType(RouteRequest.class)
+                .build();
+
+        ToolCallback apiListTool = FunctionToolCallback
+                .builder("api_list", new ApiListTool())
+                .description("根据业务域名获取对应接口")
+                .inputType(ApiListTool.DomainRequest.class)
+                .build();
+
+        // 创建 agent
+        ReactAgent agent = ReactAgent.builder()
+                .name("warehouse_agent")
+                .model(chatModel)
+                .tools(apiListTool, businessTool)
+                .systemPrompt("你是一个业务知识助手,可以根据用户描述提供相关业务领域知识,在对话期间最先应该获取到当前用户想要讨论的业务域,再进行其他工具的调用.")
+                .saver(new MemorySaver())
+                .build();
+
+        // 运行 agent
+        AssistantMessage response = agent.call("请告诉我订单相关接口");
+        System.out.println(response);
+    }
+
+    /**
+     * 文生图示例
+     * 模型：wanx2.1-t2i-turbo(快速)、wan2.2-t2i-plus(增强)、qwen-image 等
+     * 可选：style(photography/anime/watercolor...)、size、n(数量)、negativePrompt
+     */
+    @Test
+    void text2Img(@Autowired DashScopeImageModel imageModel) {
+        DashScopeImageOptions options = DashScopeImageOptions.builder()
+                .model("wanx2.1-t2i-turbo")
+                // .style("anime")           // 风格：photography/portrait/3d cartoon/anime/oil painting/watercolor/sketch/chinese painting/flat illustration/auto
+                // .n(1)                    // 生成数量 1-4
+                // .size("1024*1024")       // 尺寸：1024*1024、720*1280、1280*720
+                // .negativePrompt("模糊")  // 负面提示词
+                .build();
+
+        ImageResponse response = imageModel.call(new ImagePrompt("程序员徐庶", options));
+        String imageUrl = response.getResult().getOutput().getUrl();
+
+        System.out.println("文生图 URL: " + imageUrl);
+        // 或获取 base64: response.getResult().getOutput().getB64Json();
+    }
+
+    /**
+     * 文生视频示例（异步，通常需 1-5 分钟）
+     * 模型：wanx2.1-t2v-turbo(快速)、wanx2.1-t2v-plus(增强)、wanx2.5-t2v-preview 等
+     * 可选：size(1280*720)、duration、imageUrl(图生视频)、negativePrompt
+     *
+     * 已知问题：spring-ai-alibaba 1.1.2.0 存在 DashScopeVideoOptions Jackson 反序列化 bug，
+     * 调用会抛出 InvalidDefinitionException，待上游修复。可关注：
+     * https://github.com/alibaba/spring-ai-alibaba/issues
+     */
+    @Test
+    void text2Video(@Autowired DashScopeVideoModel videoModel) {
+        DashScopeVideoOptions options = DashScopeVideoOptions.builder()
+                .model(DashScopeModel.VideoModel.WANX21_T2V_TURBO.getName())  // 文生视频用 T2V，I2V 需提供 imageUrl
+                .input(DashScopeVideoOptions.InputOptions.builder()
+                        .prompt("一只阳光下奔跑的猫")
+                        .build())
+                .build();
+
+
+        VideoPrompt prompt = new VideoPrompt(Collections.singletonList(new VideoMessage("一只阳光下奔跑的猫")), options);
+        VideoResponse response = videoModel.call(prompt);
+
+        String videoUrl = response.getResult().getOutput().videoUrl();
+        String taskStatus = response.getResult().getOutput().taskStatus();
+
+        System.out.println("文生视频 状态: " + taskStatus + ", URL: " + videoUrl);
+    }
+
+    /**
+     * 文生语音
+     * 
+     * @param audioSpeechModel
+     * @throws IOException
+     */
+    @Test
+    void testText2Audio(@Autowired DashScopeAudioSpeechModel audioSpeechModel) throws IOException {
+        DashScopeAudioSpeechOptions options = DashScopeAudioSpeechOptions.builder()
+                .model(DashScopeModel.AudioModel.COSYVOICE_V1.getValue())
+                .voice("longlaotie")
+                .format("mp3")
+                .build();
+
+        TextToSpeechPrompt prompt = new TextToSpeechPrompt("大家好，我是人帅活好的徐庶。", options);
+
+        // 使用 stream() 收集所有音频块，call() 内部聚合可能有问题
+        ByteArrayOutputStream baos = new ByteArrayOutputStream();
+        Flux<TextToSpeechResponse> stream = audioSpeechModel.stream(prompt);
+        stream.doOnNext(r -> {
+            for (Speech speech : r.getResults()) {
+                byte[] bytes = speech.getOutput();
+                if (bytes.length > 0) {
+                    try {
+                        baos.write(bytes);
+                    } catch (IOException e) {
+                        throw new RuntimeException(e);
+                    }
+                }
+            }
+        }).blockLast();
+
+        byte[] audioBytes = baos.toByteArray();
+        if (audioBytes.length == 0) {
+            throw new IllegalStateException("未收到任何音频数据");
+        }
+
+        File file = new File("./output.mp3");
+        try (FileOutputStream fos = new FileOutputStream(file)) {
+            fos.write(audioBytes);
+        }
+    }
+
+    /**
+     * 多模态
+     */
+    @Test
+    public void testMultimodal(@Autowired DashScopeChatModel dashScopeChatModel) throws MalformedURLException {
+        // flac、mp3、mp4、mpeg、mpga、m4a、ogg、wav 或 webm。需先运行 testText2Audio 生成 output.mp3
+        var audioFile = new FileSystemResource("output.mp3");
+
+        Media media = new Media(MimeTypeUtils.parseMimeType("audio/mpeg"), audioFile);
+        UserMessage userMessage = UserMessage.builder().media(media).text("识别音频内容").build();
+        userMessage.getMetadata().put(DashScopeApiConstants.MESSAGE_FORMAT, MessageFormat.AUDIO);
+
+        DashScopeChatOptions options = DashScopeChatOptions.builder()
+                .multiModel(true)
+                .model("qwen-audio-turbo-latest")  // 音频识别用 qwen-audio，qwen-vl 仅支持图片
+                .build();
+
+        Prompt prompt = Prompt.builder().chatOptions(options).messages(userMessage).build();
+        ChatResponse response = dashScopeChatModel.call(prompt);
+
+        System.out.println(response.getResult().getOutput().getText());
+    }
+}