4.7学习笔记

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/.gitignore

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+HELP.md
+target/
+.mvn/wrapper/maven-wrapper.jar
+!**/src/main/**/target/
+!**/src/test/**/target/
+
+### STS ###
+.apt_generated
+.classpath
+.factorypath
+.project
+.settings
+.springBeans
+.sts4-cache
+
+### IntelliJ IDEA ###
+.idea
+*.iws
+*.iml
+*.ipr
+
+### NetBeans ###
+/nbproject/private/
+/nbbuild/
+/dist/
+/nbdist/
+/.nb-gradle/
+build/
+!**/src/main/**/build/
+!**/src/test/**/build/
+
+### VS Code ###
+.vscode/

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/.mvn/wrapper/maven-wrapper.properties

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+wrapperVersion=3.3.4
+distributionType=only-script
+distributionUrl=https://repo.maven.apache.org/maven2/org/apache/maven/apache-maven/3.9.14/apache-maven-3.9.14-bin.zip

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/pom.xml

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+<?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 https://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>3.5.13</version>
+        <relativePath/> <!-- lookup parent from repository -->
+    </parent>
+    <groupId>com.example</groupId>
+    <artifactId>SpringAIEmbedding</artifactId>
+    <version>0.0.1-SNAPSHOT</version>
+    <name>SpringAIEmbedding</name>
+    <description>SpringAIEmbedding</description>
+    <url/>
+    <licenses>
+        <license/>
+    </licenses>
+    <developers>
+        <developer/>
+    </developers>
+    <scm>
+        <connection/>
+        <developerConnection/>
+        <tag/>
+        <url/>
+    </scm>
+    <properties>
+        <java.version>17</java.version>
+        <spring-ai.version>1.1.3</spring-ai.version>
+    </properties>
+
+    <dependencyManagement>
+        <dependencies>
+            <dependency>
+                <groupId>org.springframework.ai</groupId>
+                <artifactId>spring-ai-bom</artifactId>
+                <version>1.0.0-SNAPSHOT</version>
+                <type>pom</type>
+                <scope>import</scope>
+            </dependency>
+        </dependencies>
+    </dependencyManagement>
+
+    <dependencies>
+        <dependency>
+            <groupId>org.springframework.boot</groupId>
+            <artifactId>spring-boot-starter-web</artifactId>
+        </dependency>
+        <!-- Spring AI Zhipuai 模型依赖 -->
+        <dependency>
+            <groupId>org.springframework.ai</groupId>
+            <artifactId>spring-ai-starter-model-zhipuai</artifactId>
+        </dependency>
+
+        <!-- Spring AI Chat 客户端依赖 中包括TokenTextSplitter、TextReader、Document 等工具类 -->
+        <dependency>
+            <groupId>org.springframework.ai</groupId>
+            <artifactId>spring-ai-client-chat</artifactId>
+            <version>1.0.0</version>
+        </dependency>
+    </dependencies>
+
+
+    <!-- 声明仓库，用于获取 Spring AI 以及相关预发布版本 -->
+    <repositories>
+        <!-- Spring Milestones 仓库 -->
+        <repository>
+            <id>spring-milestones</id>
+            <name>Spring Milestones</name>
+            <url>https://repo.spring.io/milestone</url>
+            <snapshots>
+                <enabled>false</enabled>
+            </snapshots>
+        </repository>
+        <!-- Spring Snapshots 仓库 -->
+        <repository>
+            <id>spring-snapshots</id>
+            <name>Spring Snapshots</name>
+            <url>https://repo.spring.io/snapshot</url>
+            <releases>
+                <enabled>false</enabled>
+            </releases>
+            <snapshots>
+                <enabled>true</enabled>
+            </snapshots>
+        </repository>
+    </repositories>
+
+    <build>
+        <plugins>
+            <plugin>
+                <groupId>org.springframework.boot</groupId>
+                <artifactId>spring-boot-maven-plugin</artifactId>
+            </plugin>
+        </plugins>
+    </build>
+
+</project>

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/src/main/java/com/example/springaiembedding/SpringAiEmbeddingApplication.java

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+package com.example.springaiembedding;
+
+import org.springframework.boot.SpringApplication;
+import org.springframework.boot.autoconfigure.SpringBootApplication;
+
+@SpringBootApplication
+public class SpringAiEmbeddingApplication {
+
+    public static void main(String[] args) {
+        SpringApplication.run(SpringAiEmbeddingApplication.class, args);
+    }
+
+}

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/src/main/java/com/example/springaiembedding/controller/EmbeddingController.java

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+package com.example.springaiembedding.controller;
+
+import com.example.springaiembedding.service.TextSimilarityService;
+import jakarta.annotation.Resource;
+import jakarta.servlet.http.HttpServlet;
+import jakarta.servlet.http.HttpServletResponse;
+import org.springframework.ai.embedding.EmbeddingModel;
+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 java.util.Arrays;
+import java.util.Map;
+
+@RestController
+@RequestMapping("/ai")
+public class EmbeddingController {
+
+    @Autowired
+    private EmbeddingModel embeddingModel;
+
+    //对用户传入的文本进行向量化处理，测试embedding模型
+
+    @RequestMapping("/embedding")
+    public Map<String,Object> embedding(
+            @RequestParam(value = "message",defaultValue = "给我讲个笑话") String message
+    ){
+
+        // 对用户传入的文本进行向量化处理
+        float[] embedding = embeddingModel.embed(message);
+
+        return Map.of("message",message,
+                      "vector",embedding);
+    }
+
+
+    @Resource
+    private TextSimilarityService textSimilarityService;
+
+    /**
+     * 查找相似文本接口
+     * @param message 查询文本
+     * @return 相似文本+相似度
+     */
+    @GetMapping("/similarity")
+    public Map<String, Double> findSimilarText(@RequestParam String message) {
+        // 查询Top3相似文本
+        return textSimilarityService.findSimilarTexts(message, 3);
+    }
+
+
+}

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/src/main/java/com/example/springaiembedding/controller/RagController.java

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+package com.example.springaiembedding.controller;
+
+import com.example.springaiembedding.service.RagService;
+import jakarta.annotation.Resource;
+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;
+
+
+@RestController
+@RequestMapping("/ai/rag")
+public class RagController {
+    @Resource
+    private RagService ragService;
+
+    // 问答接口
+    @GetMapping("/query")
+    public String query(@RequestParam String question) {
+        return ragService.generateAnswer(question);
+    }
+}

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/src/main/java/com/example/springaiembedding/service/RagService.java

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+package com.example.springaiembedding.service;
+
+import com.example.springaiembedding.tool.DocumentLoader;
+import jakarta.annotation.PostConstruct;
+import jakarta.annotation.Resource;
+import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.EmbeddingResponse;
+import org.springframework.stereotype.Service;
+
+import java.io.IOException;
+import java.util.*;
+import java.util.stream.Collectors;
+
+@Service
+public class RagService {
+    @Resource
+    private EmbeddingModel embeddingModel;
+    @Resource
+    private ChatModel chatModel;
+
+    // 内存存储：知识库片段 → 对应向量
+    private Map<String, float[]> knowledgeVectors = new HashMap<>();
+
+    // 项目启动时自动加载并向量化知识库
+    @PostConstruct
+    public void initKnowledgeBase() throws IOException {
+        // 1. 加载并拆分文档
+        List<String> chunks = DocumentLoader.loadAndSplit("knowledge.txt");
+        // 2. 批量向量化（一次请求生成所有片段向量）
+        EmbeddingResponse embeddingResponse = embeddingModel.embedForResponse(chunks);
+        // 3. 存储片段与向量的映射
+        for (int i = 0; i < chunks.size(); i++) {
+            knowledgeVectors.put(chunks.get(i), embeddingResponse.getResults().get(i).getOutput());
+        }
+    }
+
+    // 检索与用户问题最相似的 Top N 片段
+    private List<String> retrieveSimilarChunks(String query, int topN) {
+        // 1. 用户问题向量化
+        float[] queryVector = embeddingModel.embed(query);
+        // 2. 计算与所有知识库片段的相似度
+        Map<String, Double> similarityMap = new HashMap<>();
+        //Entry是什么？Map.Entry<String, float[]> entry 是一个 Map.Entry 对象，用于遍历 Map 中的键值对。
+        for (Map.Entry<String, float[]> entry : knowledgeVectors.entrySet()) {
+            similarityMap.put(entry.getKey(), CosineSimilarityCalculator.calculate(queryVector, entry.getValue()));
+        }
+        // 3. 按相似度降序排序，取 Top N
+        return similarityMap.entrySet().stream()
+                .sorted(Collections.reverseOrder(Map.Entry.comparingByValue()))
+                .limit(topN)
+                .map(Map.Entry::getKey)
+                .collect(Collectors.toList());
+    }
+
+    // 生成最终回答
+    public String generateAnswer(String query) {
+        // 1. 检索相似片段（取 Top 2）
+        List<String> similarChunks = retrieveSimilarChunks(query, 2);
+        // 2. 拼接 Prompt（约束模型基于知识库回答）
+        StringBuilder prompt = new StringBuilder();
+        prompt.append("请基于以下知识库内容回答用户问题，禁止编造信息：\n");
+        for (String chunk : similarChunks) {
+            prompt.append("- ").append(chunk).append("\n");
+        }
+        prompt.append("\n用户问题：").append(query);
+        // 3. 调用 Chat 模型生成回答
+        ChatClient chatClient = ChatClient.builder(chatModel).build();
+        return chatClient.prompt().user(prompt.toString()).call().content();
+    }
+
+    public class CosineSimilarityCalculator {
+        // 计算两个 float[] 向量的余弦相似度
+        public static double calculate(float[] vectorA, float[] vectorB) {
+            double dotProduct = 0.0;
+            double normA = 0.0;
+            double normB = 0.0;
+            for (int i = 0; i < vectorA.length; i++) {
+                dotProduct += vectorA[i] * vectorB[i];
+                normA += Math.pow(vectorA[i], 2);
+                normB += Math.pow(vectorB[i], 2);
+            }
+            return dotProduct / (Math.sqrt(normA) * Math.sqrt(normB));
+        }
+    }
+}

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/src/main/java/com/example/springaiembedding/service/TextSimilarityService.java

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+package com.example.springaiembedding.service;
+
+import org.springframework.ai.embedding.EmbeddingModel;
+import org.springframework.ai.embedding.EmbeddingResponse;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.stereotype.Service;
+
+import java.util.*;
+import java.util.stream.Collectors;
+
+@Service
+public class TextSimilarityService {
+
+    @Autowired
+    private EmbeddingModel embeddingModel;
+
+    // 模拟本地文本库（可替换为数据库/向量库）
+    private final List<String> TEXT_LIBRARY = Arrays.asList(
+            "我爱Java编程",
+            "SpringBoot是最流行的后端框架",
+            "人工智能改变世界",
+            "大模型应用开发",
+            "我喜欢学习编程",
+            "向量数据库用于存储Embedding",
+            "SpringAI简化大模型开发"
+    );
+
+    /**
+     * 查找最相似的文本
+     * @param queryText 查询文本
+     * @param topN 返回前N条结果
+     * @return 相似文本+相似度
+     */
+
+    public Map<String, Double> findSimilarTexts(String queryText, int topN) {
+        // 1. 将查询文本转为向量
+        //float[] queryVector = embeddingModel.embed(queryText);
+        EmbeddingResponse queryEmbedding = embeddingModel.embedForResponse(List.of(queryText));
+        float[] queryVector = queryEmbedding.getResults().get(0).getOutput();
+
+        // 2. 将文本库所有文本转为向量
+        // 2. 将文本库所有文本转为向量
+        Map<String, float[]> textVectorMap = new HashMap<>();
+        for (String text : TEXT_LIBRARY) {
+            float[] textVector = embeddingModel.embed(text);
+            //put是将文本和向量存储到Map中
+            textVectorMap.put(text, textVector);
+        }
+
+        // 3. 计算相似度并排序
+        Map<String, Double> similarityMap = new HashMap<>();
+        for (Map.Entry<String, float[]> entry : textVectorMap.entrySet()) {
+            double similarity = CosineSimilarityCalculator.calculate(queryVector, entry.getValue());
+            similarityMap.put(entry.getKey(), similarity);
+        }
+
+        // 4. 按相似度降序排序，取TopN
+        return similarityMap.entrySet().stream()
+                .sorted(Collections.reverseOrder(Map.Entry.comparingByValue()))
+                .limit(topN)
+                .collect(Collectors.toMap(
+                        Map.Entry::getKey,
+                        Map.Entry::getValue,
+                        (oldValue, newValue) -> oldValue,
+                        LinkedHashMap::new
+                ));
+    }
+
+    /**
+     * 余弦相似度工具类（计算文本向量相似度）
+     */
+    public class CosineSimilarityCalculator {
+
+        /**
+         * 计算两个向量的余弦相似度
+         * @param vectorA 向量A
+         * @param vectorB 向量B
+         * @return 相似度 0~1，值越大越相似
+         */
+        public static double calculate(float[] vectorA, float[] vectorB) {
+            double dotProduct = 0.0;
+            double normA = 0.0;
+            double normB = 0.0;
+
+            for (int i = 0; i < vectorA.length; i++) {
+                dotProduct += vectorA[i] * vectorB[i];
+                normA += Math.pow(vectorA[i], 2);
+                normB += Math.pow(vectorB[i], 2);
+            }
+            return dotProduct / (Math.sqrt(normA) * Math.sqrt(normB));
+        }
+}
+}

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/src/main/java/com/example/springaiembedding/tool/DocumentLoader.java

@@ -0,0 +1,28 @@
+package com.example.springaiembedding.tool;
+
+import org.springframework.core.io.ClassPathResource;
+import java.io.BufferedReader;
+import java.io.IOException;
+import java.io.InputStreamReader;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.stream.Collectors;
+
+
+// 文档加载工具类
+public class DocumentLoader {
+    // 加载并拆分知识库文档
+    public static List<String> loadAndSplit(String resourcePath) throws IOException {
+        ClassPathResource resource = new ClassPathResource(resourcePath); // 从类路径加载资源
+        BufferedReader reader = new BufferedReader(new InputStreamReader(resource.getInputStream())); // 按行读取
+        String content = reader.lines().collect(Collectors.joining("\n"));   // 读取文件内容，将所有行连接起来一个字符串
+
+        // 按 "---" 拆分片段，过滤空内容
+        List<String> chunks = new ArrayList<>();
+        for (String chunk : content.split("---")) {
+            String trimmed = chunk.trim();
+            if (!trimmed.isEmpty()) chunks.add(trimmed);
+        }
+        return chunks;
+    }
+}

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/src/main/resources/application.properties

@@ -0,0 +1,21 @@
+spring.application.name=SpringAIEmbedding
+
+server.port=8080
+
+## ????AI ????
+# Embedding ??
+spring.ai.zhipuai.api-key=c721340a438942d0942148b48a22e50e.5VCKagzmQdyHpwyc
+spring.ai.zhipuai.base-url=https://open.bigmodel.cn/api/paas
+
+# Embedding ??
+spring.ai.zhipuai.embedding-model=embedding-2
+# Chat ??
+spring.ai.zhipuai.chat.options.model=GLM-4.7-Flash
+
+# ??????
+logging.pattern.console=%-5level %logger - %msg%n
+
+
+
+
+

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/src/main/resources/knowledge.txt

@@ -0,0 +1,8 @@
+---
+Spring AI 是一个用于简化大模型应用开发的框架，支持智谱AI、OpenAI 等多种大模型厂商。
+---
+智谱AI Embedding 模型可将文本转换为向量，用于语义检索、相似匹配等场景。
+---
+RAG（检索增强生成）通过检索本地知识库内容，辅助大模型生成更准确的回答，避免幻觉。
+---
+Spring AI 提供 EmbeddingModel 和 ChatModel 接口，让开发者快速接入大模型能力。

黄永兴学习笔记/StudySpringAI/SpringAIEmbedding/src/test/java/com/example/springaiembedding/SpringAiEmbeddingApplicationTests.java

@@ -0,0 +1,13 @@
+package com.example.springaiembedding;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.boot.test.context.SpringBootTest;
+
+@SpringBootTest
+class SpringAiEmbeddingApplicationTests {
+
+    @Test
+    void contextLoads() {
+    }
+
+}

黄永兴学习笔记/StudySpringAI/SpringAIQuickStart/.gitignore

@@ -0,0 +1,33 @@
+HELP.md
+target/
+.mvn/wrapper/maven-wrapper.jar
+!**/src/main/**/target/
+!**/src/test/**/target/
+
+### STS ###
+.apt_generated
+.classpath
+.factorypath
+.project
+.settings
+.springBeans
+.sts4-cache
+
+### IntelliJ IDEA ###
+.idea
+*.iws
+*.iml
+*.ipr
+
+### NetBeans ###
+/nbproject/private/
+/nbbuild/
+/dist/
+/nbdist/
+/.nb-gradle/
+build/
+!**/src/main/**/build/
+!**/src/test/**/build/
+
+### VS Code ###
+.vscode/

黄永兴学习笔记/StudySpringAI/SpringAIQuickStart/.mvn/wrapper/maven-wrapper.properties

@@ -0,0 +1,3 @@
+wrapperVersion=3.3.4
+distributionType=only-script
+distributionUrl=https://repo.maven.apache.org/maven2/org/apache/maven/apache-maven/3.9.14/apache-maven-3.9.14-bin.zip

黄永兴学习笔记/StudySpringAI/SpringAIQuickStart/pom.xml

@@ -0,0 +1,104 @@
+<?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 https://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>3.5.13</version>
+        <relativePath/> <!-- lookup parent from repository -->
+    </parent>
+    <groupId>com.example</groupId>
+    <artifactId>SpringAIQuickStart</artifactId>
+    <version>0.0.1-SNAPSHOT</version>
+    <name>SpringAIQuickStart</name>
+    <description>SpringAIQuickStart</description>
+    <url/>
+    <licenses>
+        <license/>
+    </licenses>
+    <developers>
+        <developer/>
+    </developers>
+    <scm>
+        <connection/>
+        <developerConnection/>
+        <tag/>
+        <url/>
+    </scm>
+    <properties>
+        <java.version>17</java.version>
+    </properties>
+
+    <dependencyManagement>
+        <dependencies>
+            <dependency>
+                <groupId>org.springframework.ai</groupId>
+                <artifactId>spring-ai-bom</artifactId>
+                <version>1.0.0-SNAPSHOT</version>
+                <type>pom</type>
+                <scope>import</scope>
+            </dependency>
+        </dependencies>
+    </dependencyManagement>
+
+    <dependencies>
+        <dependency>
+            <groupId>org.springframework.boot</groupId>
+            <artifactId>spring-boot-starter</artifactId>
+        </dependency>
+
+        <dependency>
+            <groupId>org.springframework.boot</groupId>
+            <artifactId>spring-boot-starter-web</artifactId>
+        </dependency>
+
+        <!-- Spring AI Deepseek 模型依赖 -->
+        <dependency>
+            <groupId>org.springframework.ai</groupId>
+            <artifactId>spring-ai-starter-model-deepseek</artifactId>
+        </dependency>
+
+
+        <dependency>
+            <groupId>org.springframework.boot</groupId>
+            <artifactId>spring-boot-starter-test</artifactId>
+            <scope>test</scope>
+        </dependency>
+    </dependencies>
+
+    <!-- 声明仓库，用于获取 Spring AI 以及相关预发布版本 -->
+    <repositories>
+        <!-- Spring Milestones 仓库 -->
+        <repository>
+            <id>spring-milestones</id>
+            <name>Spring Milestones</name>
+            <url>https://repo.spring.io/milestone</url>
+            <snapshots>
+                <enabled>false</enabled>
+            </snapshots>
+        </repository>
+        <!-- Spring Snapshots 仓库 -->
+        <repository>
+            <id>spring-snapshots</id>
+            <name>Spring Snapshots</name>
+            <url>https://repo.spring.io/snapshot</url>
+            <releases>
+                <enabled>false</enabled>
+            </releases>
+            <snapshots>
+                <enabled>true</enabled>
+            </snapshots>
+        </repository>
+    </repositories>
+
+    <build>
+        <plugins>
+            <plugin>
+                <groupId>org.springframework.boot</groupId>
+                <artifactId>spring-boot-maven-plugin</artifactId>
+            </plugin>
+        </plugins>
+    </build>
+
+</project>

黄永兴学习笔记/StudySpringAI/SpringAIQuickStart/src/main/java/com/example/springaiquickstart/SpringAiQuickStartApplication.java

@@ -0,0 +1,13 @@
+package com.example.springaiquickstart;
+
+import org.springframework.boot.SpringApplication;
+import org.springframework.boot.autoconfigure.SpringBootApplication;
+
+@SpringBootApplication
+public class SpringAiQuickStartApplication {
+
+    public static void main(String[] args) {
+        SpringApplication.run(SpringAiQuickStartApplication.class, args);
+    }
+
+}

黄永兴学习笔记/StudySpringAI/SpringAIQuickStart/src/main/java/com/example/springaiquickstart/controller/ChatController.java

@@ -0,0 +1,127 @@
+package com.example.springaiquickstart.controller;
+
+
+import jakarta.servlet.http.HttpServlet;
+import jakarta.servlet.http.HttpServletResponse;
+import org.springframework.ai.chat.messages.AssistantMessage;
+import org.springframework.ai.chat.messages.Message;
+import org.springframework.ai.chat.messages.SystemMessage;
+import org.springframework.ai.chat.messages.UserMessage;
+import org.springframework.ai.chat.model.ChatResponse;
+import org.springframework.ai.chat.model.Generation;
+import org.springframework.ai.chat.prompt.ChatOptions;
+import org.springframework.ai.chat.prompt.Prompt;
+import org.springframework.ai.deepseek.DeepSeekChatModel;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.http.HttpRequest;
+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;
+
+import java.util.Arrays;
+import java.util.List;
+
+@RestController
+@RequestMapping("/ai")
+public class ChatController {
+
+    @Autowired
+    private DeepSeekChatModel chatModel;
+
+    // 与模型直接对话，返回字符串响应
+    @GetMapping("/generate")
+    public String generate(@RequestParam(value = "message",defaultValue = "你好,你是谁？") String message) {
+        System.out.println("message: " + message);
+
+        // 与模型直接对话，调用chatModel的call方法生成响应
+        String response = chatModel.call(message);
+
+        System.out.println("response: " + response);
+
+        return response;
+    }
+
+    // 与模型对话，流式返回内容
+    @GetMapping("/generateStream1")
+    public Flux<ChatResponse> generateStream1(@RequestParam(value = "message",defaultValue = "你好,你是谁？") String message) {
+        System.out.println("message: " + message);
+
+        // 与模型对话，流式返回内容
+        Prompt prompt = new Prompt(message);
+        Flux<ChatResponse> stream = chatModel.stream(prompt);
+
+        System.out.println("stream: " + stream);
+
+        return stream;
+    }
+
+    // 与模型对话，流式返回内容，转换为字符串流
+    // 解决中文乱码问题
+    // 用lambda表达式简化
+    @GetMapping("/generateStream2")
+    public Flux<String> generateStream2(
+            @RequestParam(value = "message",defaultValue = "你好,你是谁？") String message,
+            HttpServletResponse response
+    ) {
+        //设置字符编码为UTF-8,解决中文乱码问题
+        response.setCharacterEncoding("UTF-8");
+        System.out.println("message: " + message);
+
+        // 与模型对话，流式返回内容
+        Prompt prompt = new Prompt(message);
+        Flux<ChatResponse> stream = chatModel.stream(prompt);
+
+        // 转换为字符串流，用lambda表达式简化
+        Flux<String> result = stream.map(ChatResponse ->
+            ChatResponse.getResult().getOutput().getText()
+        );
+        // 转换为字符串流，用方法引用简化
+//        Flux<String> result = stream.map(ChatResponse::getResult)
+//                .map(Generation::getOutput)
+//                .map(AssistantMessage::getText);
+
+
+        System.out.println("result: " + result);
+
+        return result;
+    }
+
+    //运行时设置模型参数
+    @GetMapping("/runtimeOptions")
+    public Flux<String> runtimeOptions(
+            @RequestParam(value = "message",defaultValue = "你好,你是谁？") String message,
+            @RequestParam(value = "temperature",required = false) Double temp,
+            HttpServletResponse response
+    ) {
+        //设置字符编码为UTF-8,解决中文乱码问题
+        response.setCharacterEncoding("UTF-8");
+        // 构建系统提示
+        SystemMessage systemMessage = new SystemMessage("你是一个资深Java开发工程师，回答要简洁专业");
+        // 构建用户消息
+        UserMessage userMessage = new UserMessage(message);
+        // 构建历史消息（多轮对话时加入）
+        List<Message> messages = Arrays.asList(systemMessage, userMessage);
+
+        // 封装成 Prompt，还可以设置模型参数
+        Prompt prompt = new Prompt(messages,
+                ChatOptions.builder()
+                        .temperature(temp)
+                        .maxTokens(1000)
+                        .build()
+        );
+
+        // 流式调用
+        Flux<ChatResponse> stream = chatModel.stream(prompt);
+        // 转换为字符串流，用lambda表达式简化
+        Flux<String> result = stream.map(ChatResponse ->
+            ChatResponse.getResult().getOutput().getText()
+        );
+
+        System.out.println("result: " + result);
+        return result;
+    }
+
+
+}

黄永兴学习笔记/StudySpringAI/SpringAIQuickStart/src/main/resources/application.properties

@@ -0,0 +1,13 @@
+spring.application.name=SpringAIQuickStart
+
+server.port=8080
+
+#?? Deepseek ???????url?????????
+spring.ai.deepseek.base-url=https://api.deepseek.com
+spring.ai.deepseek.api-key=sk-ccbfe09f433148129cd98df6150653e8
+spring.ai.deepseek.chat.options.model=deepseek-chat
+
+#??0-2???0????????2???????
+spring.ai.deepseek.chat.options.temperature=0.8
+
+

黄永兴学习笔记/StudySpringAI/SpringAIQuickStart/src/main/resources/static/index.html

@@ -0,0 +1,224 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Spring AI 聊天助手</title>
+    <script src="https://cdn.tailwindcss.com"></script>
+    <link href="https://cdn.jsdelivr.net/npm/font-awesome@4.7.0/css/font-awesome.min.css" rel="stylesheet">
+    <script>
+        tailwind.config = {
+            theme: {
+                extend: {
+                    colors: {
+                        primary: '#3b82f6',
+                        secondary: '#64748b',
+                        neutral: '#f8fafc',
+                        dark: '#1e293b'
+                    },
+                    fontFamily: {
+                        sans: ['Inter', 'system-ui', 'sans-serif']
+                    }
+                }
+            }
+        }
+    </script>
+    <style type="text/tailwindcss">
+        @layer utilities {
+            .content-auto {
+                content-visibility: auto;
+            }
+            .chat-message {
+                @apply p-4 rounded-lg mb-4 max-w-[80%];
+            }
+            .user-message {
+                @apply bg-primary text-white self-end;
+            }
+            .ai-message {
+                @apply bg-neutral border border-gray-200 text-dark self-start;
+            }
+        }
+    </style>
+</head>
+<body class="bg-gray-50 min-h-screen flex flex-col">
+    <!-- 顶部导航栏 -->
+    <header class="bg-white shadow-sm">
+        <div class="container mx-auto px-4 py-4 flex justify-between items-center">
+            <div class="flex items-center space-x-2">
+                <i class="fa fa-robot text-primary text-2xl"></i>
+                <h1 class="text-xl font-bold text-dark">Spring AI 聊天助手</h1>
+            </div>
+            <div class="text-sm text-secondary">
+                <span id="status" class="flex items-center">
+                    <span class="w-2 h-2 bg-green-500 rounded-full mr-2"></span>
+                    在线
+                </span>
+            </div>
+        </div>
+    </header>
+
+    <!-- 主内容区 -->
+    <main class="flex-1 container mx-auto px-4 py-8 max-w-4xl">
+        <!-- 聊天区域 -->
+        <div class="bg-white rounded-xl shadow-md overflow-hidden">
+            <!-- 聊天头部 -->
+            <div class="bg-primary text-white p-4">
+                <h2 class="text-lg font-semibold">AI 助手</h2>
+                <p class="text-sm opacity-80">基于 DeepSeek 模型</p>
+            </div>
+            
+            <!-- 聊天消息区 -->
+            <div id="chat-messages" class="p-4 h-[500px] overflow-y-auto flex flex-col space-y-4">
+                <!-- 欢迎消息 -->
+                <div class="chat-message ai-message">
+                    <div class="flex items-start">
+                        <div class="w-8 h-8 rounded-full bg-primary text-white flex items-center justify-center mr-3 flex-shrink-0">
+                            <i class="fa fa-robot"></i>
+                        </div>
+                        <div>
+                            <p class="font-semibold mb-1">AI 助手</p>
+                            <p>你好！我是基于 DeepSeek 模型的 AI 助手，有什么可以帮助你的吗？</p>
+                        </div>
+                    </div>
+                </div>
+            </div>
+            
+            <!-- 输入区域 -->
+            <div class="p-4 border-t">
+                <form id="chat-form" class="flex space-x-2">
+                    <input 
+                        type="text" 
+                        id="message-input" 
+                        placeholder="输入消息..." 
+                        class="flex-1 border border-gray-300 rounded-lg px-4 py-2 focus:outline-none focus:ring-2 focus:ring-primary focus:border-transparent"
+                    >
+                    <button 
+                        type="submit" 
+                        id="send-button" 
+                        class="bg-primary text-white rounded-lg px-6 py-2 hover:bg-primary/90 transition-colors flex items-center space-x-2"
+                    >
+                        <span>发送</span>
+                        <i class="fa fa-paper-plane"></i>
+                    </button>
+                </form>
+            </div>
+        </div>
+        
+        <!-- 功能说明 -->
+        <div class="mt-8 bg-white rounded-xl shadow-md p-6">
+            <h3 class="text-lg font-semibold mb-4">功能说明</h3>
+            <ul class="space-y-2 text-secondary">
+                <li class="flex items-center">
+                    <i class="fa fa-check-circle text-green-500 mr-2"></i>
+                    支持自然语言对话
+                </li>
+                <li class="flex items-center">
+                    <i class="fa fa-check-circle text-green-500 mr-2"></i>
+                    基于 DeepSeek 大语言模型
+                </li>
+                <li class="flex items-center">
+                    <i class="fa fa-check-circle text-green-500 mr-2"></i>
+                    实时响应生成
+                </li>
+                <li class="flex items-center">
+                    <i class="fa fa-check-circle text-green-500 mr-2"></i>
+                    简洁美观的用户界面
+                </li>
+            </ul>
+        </div>
+    </main>
+
+    <!-- 页脚 -->
+    <footer class="bg-white shadow-sm mt-8">
+        <div class="container mx-auto px-4 py-4 text-center text-secondary text-sm">
+            <p>© 2026 Spring AI 聊天助手 | 基于 DeepSeek 模型</p>
+        </div>
+    </footer>
+
+    <script>
+        document.addEventListener('DOMContentLoaded', function() {
+            const chatForm = document.getElementById('chat-form');
+            const messageInput = document.getElementById('message-input');
+            const chatMessages = document.getElementById('chat-messages');
+            const sendButton = document.getElementById('send-button');
+            const status = document.getElementById('status');
+
+            // 发送消息
+            chatForm.addEventListener('submit', function(e) {
+                e.preventDefault();
+                const message = messageInput.value.trim();
+                if (message) {
+                    // 添加用户消息到聊天区
+                    addMessage('user', message);
+                    messageInput.value = '';
+                    
+                    // 禁用发送按钮
+                    sendButton.disabled = true;
+                    sendButton.classList.add('opacity-50');
+                    status.innerHTML = '<span class="w-2 h-2 bg-yellow-500 rounded-full mr-2"></span>处理中...';
+                    
+                    // 调用后端 API
+                    fetch(`/ai/generate?message=${encodeURIComponent(message)}`)
+                        .then(response => response.text())
+                        .then(data => {
+                            // 添加 AI 响应到聊天区
+                            addMessage('ai', data);
+                        })
+                        .catch(error => {
+                            console.error('Error:', error);
+                            addMessage('ai', '抱歉，处理请求时出错，请稍后再试。');
+                        })
+                        .finally(() => {
+                            // 恢复发送按钮状态
+                            sendButton.disabled = false;
+                            sendButton.classList.remove('opacity-50');
+                            status.innerHTML = '<span class="w-2 h-2 bg-green-500 rounded-full mr-2"></span>在线';
+                        });
+                }
+            });
+
+            // 添加消息到聊天区
+            function addMessage(type, content) {
+                const messageDiv = document.createElement('div');
+                messageDiv.className = `chat-message ${type === 'user' ? 'user-message' : 'ai-message'} self-${type === 'user' ? 'end' : 'start'}`;
+                
+                if (type === 'user') {
+                    messageDiv.innerHTML = `
+                        <div class="flex items-start justify-end">
+                            <div>
+                                <p class="font-semibold mb-1 text-right">你</p>
+                                <p>${content}</p>
+                            </div>
+                            <div class="w-8 h-8 rounded-full bg-gray-300 text-dark flex items-center justify-center ml-3 flex-shrink-0">
+                                <i class="fa fa-user"></i>
+                            </div>
+                        </div>
+                    `;
+                } else {
+                    messageDiv.innerHTML = `
+                        <div class="flex items-start">
+                            <div class="w-8 h-8 rounded-full bg-primary text-white flex items-center justify-center mr-3 flex-shrink-0">
+                                <i class="fa fa-robot"></i>
+                            </div>
+                            <div>
+                                <p class="font-semibold mb-1">AI 助手</p>
+                                <p>${content}</p>
+                            </div>
+                        </div>
+                    `;
+                }
+                
+                chatMessages.appendChild(messageDiv);
+                chatMessages.scrollTop = chatMessages.scrollHeight;
+            }
+
+            // 回车键发送消息
+            messageInput.addEventListener('keypress', function(e) {
+                if (e.key === 'Enter') {
+                    chatForm.dispatchEvent(new Event('submit'));
+                }
+            });
+        });
+    </script>
+</body>
+</html>

黄永兴学习笔记/StudySpringAI/SpringAIQuickStart/src/test/java/com/example/springaiquickstart/SpringAiQuickStartApplicationTests.java

@@ -0,0 +1,13 @@
+package com.example.springaiquickstart;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.boot.test.context.SpringBootTest;
+
+@SpringBootTest
+class SpringAiQuickStartApplicationTests {
+
+    @Test
+    void contextLoads() {
+    }
+
+}

黄永兴学习笔记/StudySpringAI/StudySpringAI.iml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="GENERAL_MODULE" version="4">
+  <component name="NewModuleRootManager" inherit-compiler-output="true">
+    <exclude-output />
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/.mvn/wrapper/maven-wrapper.properties

@@ -0,0 +1,3 @@
+wrapperVersion=3.3.4
+distributionType=only-script
+distributionUrl=https://repo.maven.apache.org/maven2/org/apache/maven/apache-maven/3.9.14/apache-maven-3.9.14-bin.zip

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/SpringAIAlibaba.iml

@@ -0,0 +1,10 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module version="4">
+  <component name="AdditionalModuleElements">
+    <content url="file://$MODULE_DIR$" dumb="true">
+      <sourceFolder url="file://$MODULE_DIR$/src/main/java" isTestSource="false" />
+      <sourceFolder url="file://$MODULE_DIR$/src/main/resources" type="java-resource" />
+      <sourceFolder url="file://$MODULE_DIR$/src/test/java" isTestSource="true" />
+    </content>
+  </component>
+</module>

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/pom.xml

@@ -0,0 +1,133 @@
+<?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 https://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>3.5.13</version>
+        <relativePath/> <!-- lookup parent from repository -->
+    </parent>
+    <groupId>com.example</groupId>
+    <artifactId>SpringAIAlibaba</artifactId>
+    <version>1.1.2.0</version>
+    <name>SpringAIAlibaba</name>
+    <description>SpringAIAlibaba</description>
+
+    <properties>
+        <java.version>17</java.version>
+        <!-- 阿里云DashScope SDK版本（官方要求>=2.15.0） -->
+        <dashscope.version>2.22.13</dashscope.version>
+        <!-- RxJava版本（适配DashScope SDK） -->
+        <rxjava.version>2.2.21</rxjava.version>
+    </properties>
+
+    <url/>
+    <licenses>
+        <license/>
+    </licenses>
+    <developers>
+        <developer/>
+    </developers>
+    <scm>
+        <connection/>
+        <developerConnection/>
+        <tag/>
+        <url/>
+    </scm>
+
+    <dependencyManagement>
+        <dependencies>
+            <dependency>
+                <groupId>com.alibaba.cloud.ai</groupId>
+                <artifactId>spring-ai-alibaba-bom</artifactId>
+                <version>1.1.2.0</version>
+                <type>pom</type>
+                <scope>import</scope>
+            </dependency>
+            <dependency>
+                <groupId>org.springframework.ai</groupId>
+                <artifactId>spring-ai-bom</artifactId>
+                <version>1.1.2</version>
+                <type>pom</type>
+                <scope>import</scope>
+            </dependency>
+            <dependency>
+                <groupId>com.alibaba.cloud.ai</groupId>
+                <artifactId>spring-ai-alibaba-extensions-bom</artifactId>
+                <version>1.1.2.1</version>
+                <type>pom</type>
+                <scope>import</scope>
+            </dependency>
+        </dependencies>
+    </dependencyManagement>
+
+    <dependencies>
+
+
+        <!-- Spring AI Alibaba Agent Framework -->
+        <dependency>
+            <groupId>com.alibaba.cloud.ai</groupId>
+            <artifactId>spring-ai-alibaba-agent-framework</artifactId>
+            <version>1.1.2.0</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>1.1.2.0</version>
+        </dependency>
+
+        <dependency>
+            <groupId>org.springframework.boot</groupId>
+            <artifactId>spring-boot-starter-web</artifactId>
+        </dependency>
+
+        <!-- Spring WebFlux 流式核心 -->
+        <dependency>
+            <groupId>org.springframework.boot</groupId>
+            <artifactId>spring-boot-starter-webflux</artifactId>
+        </dependency>
+
+        <dependency>
+            <groupId>io.projectreactor.addons</groupId>
+            <artifactId>reactor-adapter</artifactId>
+        </dependency>
+
+        <dependency>
+            <groupId>org.projectlombok</groupId>
+            <artifactId>lombok</artifactId>
+            <optional>true</optional>
+        </dependency>
+
+        <!-- 1. 阿里云DashScope官方SDK（解决所有dashscope包报红） -->
+        <dependency>
+            <groupId>com.alibaba</groupId>
+            <artifactId>dashscope-sdk-java</artifactId>
+            <version>${dashscope.version}</version>
+        </dependency>
+
+        <!-- 2. RxJava 2.x（解决io.reactivex.Flowable报红） -->
+        <dependency>
+            <groupId>io.reactivex.rxjava2</groupId>
+            <artifactId>rxjava</artifactId>
+            <version>${rxjava.version}</version>
+        </dependency>
+
+
+
+
+
+    </dependencies>
+
+    <build>
+        <plugins>
+            <plugin>
+                <groupId>org.springframework.boot</groupId>
+                <artifactId>spring-boot-maven-plugin</artifactId>
+            </plugin>
+        </plugins>
+    </build>
+
+</project>

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/src/main/java/com/example/springaialibaba/SpringAiAlibabaApplication.java

@@ -0,0 +1,13 @@
+package com.example.springaialibaba;
+
+import org.springframework.boot.SpringApplication;
+import org.springframework.boot.autoconfigure.SpringBootApplication;
+
+@SpringBootApplication
+public class SpringAiAlibabaApplication {
+
+    public static void main(String[] args) {
+        SpringApplication.run(SpringAiAlibabaApplication.class, args);
+    }
+
+}

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/src/main/java/com/example/springaialibaba/controller/CustomerServiceController.java

@@ -0,0 +1,230 @@
+package com.example.springaialibaba.controller;
+
+
+import com.alibaba.cloud.ai.dashscope.agent.DashScopeAgent;
+import com.alibaba.dashscope.app.*;
+import com.example.springaialibaba.pojo.StreamResponse;
+import com.example.springaialibaba.service.SpeechSynthesisService;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import io.reactivex.Flowable;
+import jakarta.servlet.http.HttpServletResponse;
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+
+import java.nio.ByteBuffer;
+import java.util.Base64;
+import java.util.UUID;
+import java.util.concurrent.CountDownLatch;
+import java.util.concurrent.atomic.AtomicInteger;
+
+import org.springframework.http.MediaType;
+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 org.springframework.web.servlet.mvc.method.annotation.StreamingResponseBody;
+import reactor.adapter.rxjava.RxJava2Adapter;
+import reactor.adapter.rxjava.RxJava3Adapter;
+import reactor.core.publisher.Flux;
+import reactor.core.publisher.Mono;
+
+@Slf4j
+@RestController
+@RequiredArgsConstructor    //使用RequiredArgsConstructor注解，自动注入final类型的字段
+@RequestMapping("/customer")
+public class CustomerServiceController {
+
+    //注入Spring AI Alibaba Agent
+    //@Autowired
+    private final DashScopeAgent dashScopeAgent;
+    private final SpeechSynthesisService speechSynthesisService;
+
+    /**
+     * 智能客服接口（非流式，同步获取结果）
+     * @param question 用户问题
+     * @return 知识库标准答案
+     */
+    @GetMapping("/service")
+    public String customerServiceController(@RequestParam("question") String question) {
+
+        try {
+            /*
+                DashScopeAgentOptions 是工作流 / 智能体的调用参数，它只负责「触发工作流」，不负责「修改大模型的推理参数」。
+                因为 Spring AI Alibaba 的自动配置在工作流（Agent）模式下不生效！
+            */
+
+            //
+           /* ChatResponse response = dashScopeAgent.call(
+                    new Prompt(question,  DashScopeAgentOptions.builder()
+                            .appId("df04e1abf24a416c8702260e88863ac4")
+                            .build()
+                            )
+            );
+
+            return response.getResult().getOutput().getText();*/
+
+            ApplicationParam param = ApplicationParam.builder()
+                    // 若没有配置环境变量，可用百炼API Key将下行替换为：.apiKey("sk-xxx")。但不建议在生产环境中直接将API Key硬编码到代码中，以减少API Key泄露风险。
+                    .apiKey(System.getenv("sk-f7d2253302b547c7a2fe257673cb854b"))
+                    .appId("df04e1abf24a416c8702260e88863ac4")
+                    .prompt(question)
+                    .build();
+
+            Application application = new Application();
+            ApplicationResult result = application.call(param);
+            return result.getOutput().getText();
+
+        } catch (Exception e) {
+            log.error("客服调用失败", e);
+            return "抱歉，智能客服暂时无法响应，请联系人工客服。";
+        }
+    }
+
+    // 官方原生流式调用（1:1对照文档）
+    @GetMapping(value = "/service2", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
+    public Flux<String> customerService2Controller(
+            @RequestParam("question") String question,
+            HttpServletResponse response
+    ) {
+        //设置字符编码为UTF-8,解决中文乱码问题
+        response.setCharacterEncoding("UTF-8");
+
+        ObjectMapper objectMapper = new ObjectMapper();
+        AtomicInteger counter = new AtomicInteger(0);
+
+        try {
+            // 【官方原版写法】
+            ApplicationParam param = ApplicationParam.builder()
+                    .apiKey("sk-f7d2253302b547c7a2fe257673cb854b")
+                    .appId("df04e1abf24a416c8702260e88863ac4")
+                    .prompt(question)
+                    .flowStreamMode(FlowStreamMode.MESSAGE_FORMAT)
+                    .build();
+
+            Application application = new Application();
+
+            // 官方流式调用
+            Flowable<ApplicationResult> resultFlowable = application.streamCall(param);
+
+            // RxJava适配器 flowable 转换为 flux Mono是单元素的Flux
+            return RxJava2Adapter.flowableToFlux(resultFlowable)
+                    .flatMap(res -> {
+                        String content = extractContent(res);
+                        if (content != null && !content.trim().isEmpty()) {
+                            try {
+                                String id = UUID.randomUUID().toString().substring(0, 8);
+                                int seq = counter.incrementAndGet();
+                                String jsonData = objectMapper.writeValueAsString(new StreamResponse(id, seq, content));
+                                return Mono.just(jsonData);
+                            } catch (Exception e) {
+                                log.error("JSON序列化失败", e);
+                                return Mono.empty();
+                            }
+                        }
+                        return Mono.empty();
+                    });
+
+        } catch (Exception e) {
+            log.error("客服调用失败", e);
+            return Flux.error(e);
+        }
+    }
+
+
+    // 语音合成接口 - 单向流式返回音频流数据
+    @GetMapping(value = "/synthesize", produces = "audio/wav")
+    public StreamingResponseBody synthesizeSpeech(@RequestParam("text") String text) {
+        log.info("开始语音合成，文本: {}", text);
+        
+        return outputStream -> {
+            CountDownLatch latch = new CountDownLatch(1);
+            try {
+                Flux<byte[]> audioFlux = speechSynthesisService.streamSynthesize(text);
+                audioFlux.subscribe(
+                    bytes -> {
+                        try {
+                            log.info("Controller收到音频数据，大小: {} 字节，写入输出流", bytes.length);
+                            outputStream.write(bytes);
+                            outputStream.flush();
+                            log.info("已刷新输出流");
+                        } catch (Exception e) {
+                            log.error("写入音频数据失败", e);
+                        }
+                    },
+                    error -> {
+                        log.error("音频流处理错误", error);
+                        latch.countDown();
+                    },
+                    () -> {
+                        log.info("音频数据传输完成");
+                        latch.countDown();
+                    }
+                );
+                log.info("等待音频流完成...");
+                latch.await();
+                log.info("音频流完成，结束请求");
+            } catch (Exception e) {
+                log.error("语音合成失败", e);
+            }
+        };
+    }
+
+    // SSE推送音频数据接口
+    @GetMapping(value = "/synthesize-sse", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
+    public Flux<String> synthesizeSpeechSSE(@RequestParam("text") String text) {
+        log.info("开始SSE语音合成，文本: {}", text);
+        
+        Flux<byte[]> audioFlux = speechSynthesisService.streamSynthesize(text);
+        AtomicInteger seq = new AtomicInteger(0);
+        
+        return audioFlux
+                .map(bytes -> {
+                    String base64Data = Base64.getEncoder().encodeToString(bytes);
+                    int currentSeq = seq.incrementAndGet();
+                    String jsonData = String.format("{\"seq\":%d,\"data\":\"%s\",\"size\":%d}", 
+                            currentSeq, base64Data, bytes.length);
+                    log.info("SSE推送音频数据块 [{}], 大小: {} 字节", currentSeq, bytes.length);
+                    return "data: " + jsonData + "\n\n";
+                })
+                .doOnComplete(() -> {
+                    log.info("SSE音频推送完成");
+                })
+                .doOnError(error -> {
+                    log.error("SSE音频推送错误", error);
+                });
+    }
+    
+    // 从 ApplicationResult 中提取内容 
+    private String extractContent(ApplicationResult res) {
+        if (res == null || res.getOutput() == null) return null;
+        if (res.getOutput().getWorkflowMessage() != null) {
+            WorkflowMessage workflowMessage = res.getOutput().getWorkflowMessage();
+            if (workflowMessage != null && workflowMessage.getMessage() != null) {
+                String nodeId = workflowMessage.getNodeId();
+                String content = workflowMessage.getMessage().getContent();
+                // 区分不同的nodeId
+                if ("Output_emZG".equals(nodeId)) {
+                    // 流程输出节点，返回内容
+                    return content;
+                } else if ("End_mOtD".equals(nodeId)) {
+                    // 结束节点，不返回内容
+                    log.debug("流式传输结束，收到完整结果，不返回");
+                    return null;
+                } else {
+                    // 其他节点，返回内容
+                    return content;
+                }
+            }
+        }
+        return null;
+    }
+
+    
+
+
+
+
+
+
+
+}

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/src/main/java/com/example/springaialibaba/controller/Main.java

@@ -0,0 +1,97 @@
+package com.example.springaialibaba.controller;
+
+import com.alibaba.dashscope.audio.tts.SpeechSynthesisResult;
+import com.alibaba.dashscope.audio.ttsv2.SpeechSynthesisAudioFormat;
+import com.alibaba.dashscope.audio.ttsv2.SpeechSynthesisParam;
+import com.alibaba.dashscope.audio.ttsv2.SpeechSynthesizer;
+import com.alibaba.dashscope.common.ResultCallback;
+import com.alibaba.dashscope.utils.Constants;
+
+import java.time.LocalDateTime;
+import java.time.format.DateTimeFormatter;
+
+class TimeUtils {
+    private static final DateTimeFormatter formatter =
+            DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss.SSS");
+
+    public static String getTimestamp() {
+        return LocalDateTime.now().format(formatter);
+    }
+}
+
+
+public class Main {
+    private static String[] textArray = {"流式文本语音合成SDK，",
+            "可以将输入的文本", "合成为语音二进制数据，", "相比于非流式语音合成，",
+            "流式合成的优势在于实时性", "更强。用户在输入文本的同时",
+            "可以听到接近同步的语音输出，", "极大地提升了交互体验，",
+            "减少了用户等待时间。", "适用于调用大规模", "语言模型（LLM），以",
+            "流式输入文本的方式", "进行语音合成的场景。"};
+    private static String model = "cosyvoice-v3-flash"; // 模型
+    private static String voice = "longanyang"; // 音色
+
+    public static void streamAudioDataToSpeaker() {
+        // 配置回调函数
+        ResultCallback<SpeechSynthesisResult> callback = new ResultCallback<SpeechSynthesisResult>() {
+            @Override
+            public void onEvent(SpeechSynthesisResult result) {
+                // System.out.println("收到消息: " + result);
+                if (result.getAudioFrame() != null) {
+                    // 此处实现处理音频数据的逻辑
+                    System.out.println(TimeUtils.getTimestamp() + " 收到音频");
+                }
+            }
+
+            @Override
+            public void onComplete() {
+                System.out.println(TimeUtils.getTimestamp() + " 收到Complete，语音合成结束");
+            }
+
+            @Override
+            public void onError(Exception e) {
+                System.out.println("出现异常：" + e.toString());
+            }
+        };
+
+        // 请求参数
+        SpeechSynthesisParam param =
+                SpeechSynthesisParam.builder()
+                        // 新加坡和北京地域的API Key不同。获取API Key：https://help.aliyun.com/zh/model-studio/get-api-key
+                        // 若没有配置环境变量，请用百炼API Key将下行替换为：.apiKey("sk-xxx")
+                        .apiKey("sk-f7d2253302b547c7a2fe257673cb854b")
+                        .model(model)
+                        .voice(voice)
+                        .format(SpeechSynthesisAudioFormat
+                                .PCM_22050HZ_MONO_16BIT) // 流式合成使用PCM或者MP3
+                        .build();
+        SpeechSynthesizer synthesizer = new SpeechSynthesizer(param, callback);
+        // 带Callback的call方法将不会阻塞当前线程
+        try {
+            for (String text : textArray) {
+                // 发送文本片段，在回调接口的onEvent方法中实时获取二进制音频
+                synthesizer.streamingCall(text);
+            }
+            // 等待结束流式语音合成
+            synthesizer.streamingComplete();
+        } catch (Exception e) {
+            throw new RuntimeException(e);
+        } finally {
+            // 任务结束关闭websocket连接
+            synthesizer.getDuplexApi().close(1000, "bye");
+        }
+
+        // 首次发送文本时需建立 WebSocket 连接，因此首包延迟会包含连接建立的耗时
+        System.out.println(
+                "[Metric] requestId为："
+                        + synthesizer.getLastRequestId()
+                        + "，首包延迟（毫秒）为："
+                        + synthesizer.getFirstPackageDelay());
+    }
+
+    public static void main(String[] args) {
+        // 以下为北京地域url，若使用新加坡地域的模型，需将url替换为：wss://dashscope-intl.aliyuncs.com/api-ws/v1/inference
+        Constants.baseWebsocketApiUrl = "wss://dashscope.aliyuncs.com/api-ws/v1/inference";
+        streamAudioDataToSpeaker();
+        System.exit(0);
+    }
+}

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/src/main/java/com/example/springaialibaba/controller/SpeechSynthesisController.java

@@ -0,0 +1,118 @@
+package com.example.springaialibaba.controller;
+
+import com.alibaba.dashscope.audio.tts.SpeechSynthesisParam;
+import com.alibaba.dashscope.audio.tts.SpeechSynthesizer;
+import com.alibaba.dashscope.audio.tts.SpeechSynthesisResult;
+import com.alibaba.dashscope.exception.NoApiKeyException;
+import com.alibaba.dashscope.utils.Constants;
+import io.reactivex.Flowable;
+import jakarta.servlet.http.HttpServletResponse;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.http.MediaType;
+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.adapter.rxjava.RxJava2Adapter;
+import reactor.core.publisher.Flux;
+import reactor.core.publisher.Mono;
+
+import java.io.IOException;
+import java.io.OutputStream;
+import java.util.Base64;
+
+@Slf4j
+@RestController
+@RequestMapping("/speech")
+public class SpeechSynthesisController {
+
+    private static final String MODEL = "cosyvoice-v3-flash";
+    private static final String VOICE = "longanyang";
+
+    static {
+        // 北京地域url，若使用新加坡地域的模型，需将url替换为：wss://dashscope-intl.aliyuncs.com/api-ws/v1/inference
+        Constants.baseWebsocketApiUrl = "wss://dashscope.aliyuncs.com/api-ws/v1/inference";
+    }
+
+    @GetMapping(value = "/synthesize", produces = MediaType.APPLICATION_OCTET_STREAM_VALUE)
+    public void synthesizeAudio(
+            @RequestParam("text") String text,
+            HttpServletResponse response
+    ) throws NoApiKeyException, IOException {
+
+        // 设置响应头
+        response.setContentType("audio/wav");
+        response.setHeader("Content-Disposition", "attachment; filename=output.wav");
+
+        // 请求参数
+        SpeechSynthesisParam param = SpeechSynthesisParam.builder()
+                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
+                .model(MODEL)
+                .voice(VOICE)
+                .build();
+
+        SpeechSynthesizer synthesizer = new SpeechSynthesizer(param, null);
+
+        // 流式获取音频数据
+        Flowable<SpeechSynthesisResult> resultFlowable = synthesizer.callAsFlowable(text);
+
+        // 处理音频数据
+        OutputStream outputStream = response.getOutputStream();
+
+        resultFlowable.blockingForEach(result -> {
+            if (result.getAudioFrame() != null) {
+                try {
+                    // 音频数据是Base64编码的，需要解码
+                    byte[] audioData = Base64.getDecoder().decode(result.getAudioFrame().getAudio());
+                    outputStream.write(audioData);
+                    outputStream.flush();
+                    log.debug("写入音频数据: {} bytes", audioData.length);
+                } catch (IOException e) {
+                    log.error("写入音频数据失败", e);
+                }
+            }
+        });
+
+        // 关闭连接和输出流
+        synthesizer.getDuplexApi().close(1000, "bye");
+        outputStream.close();
+
+        // 打印首包延迟
+        log.info("[Metric] requestId为：{}", synthesizer.getLastRequestId());
+        log.info("首包延迟（毫秒）为：{}", synthesizer.getFirstPackageDelay());
+    }
+
+    @GetMapping(value = "/stream", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
+    public Flux<String> streamAudio(
+            @RequestParam("text") String text
+    ) throws NoApiKeyException {
+
+        // 请求参数
+        SpeechSynthesisParam param = SpeechSynthesisParam.builder()
+                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
+                .model(MODEL)
+                .voice(VOICE)
+                .build();
+
+        SpeechSynthesizer synthesizer = new SpeechSynthesizer(param, null);
+
+        // 流式获取音频数据
+        Flowable<SpeechSynthesisResult> resultFlowable = synthesizer.callAsFlowable(text);
+
+        // 转换为Flux并返回
+        return RxJava2Adapter.flowableToFlux(resultFlowable)
+                .flatMap(result -> {
+                    if (result.getAudioFrame() != null) {
+                        String audioBase64 = result.getAudioFrame().getAudio();
+                        return Mono.just("data: " + audioBase64 + "\n\n");
+                    }
+                    return Mono.empty();
+                })
+                .doOnTerminate(() -> {
+                    // 关闭连接
+                    synthesizer.getDuplexApi().close(1000, "bye");
+                    log.info("[Metric] requestId为：{}", synthesizer.getLastRequestId());
+                    log.info("首包延迟（毫秒）为：{}", synthesizer.getFirstPackageDelay());
+                });
+    }
+}

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/src/main/java/com/example/springaialibaba/pojo/StreamResponse.java

@@ -0,0 +1,14 @@
+package com.example.springaialibaba.pojo;
+
+// 流式响应数据结构
+public class StreamResponse {
+    public String id;
+    public int seq;
+    public String text;
+
+    public StreamResponse(String id, int seq, String text) {
+        this.id = id;
+        this.seq = seq;
+        this.text = text;
+    }
+}

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/src/main/java/com/example/springaialibaba/service/AudioGenerationService.java

@@ -0,0 +1,107 @@
+package com.example.springaialibaba.service;
+
+import com.alibaba.dashscope.audio.tts.SpeechSynthesisResult;
+import com.alibaba.dashscope.audio.ttsv2.SpeechSynthesisParam;
+import com.alibaba.dashscope.audio.ttsv2.SpeechSynthesizer;
+import com.alibaba.dashscope.common.ResultCallback;
+import com.alibaba.dashscope.exception.NoApiKeyException;
+import com.alibaba.dashscope.utils.Constants;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Service;
+import reactor.core.publisher.Flux;
+import reactor.core.publisher.Mono;
+
+import java.nio.ByteBuffer;
+import java.util.ArrayList;
+import java.util.List;
+
+@Slf4j
+@Service
+public class AudioGenerationService {
+
+    private static final String MODEL = "cosyvoice-v3-flash";
+    private static final String VOICE = "longanyang";
+
+    static {
+        // 设置WebSocket API地址（北京地域）
+        Constants.baseWebsocketApiUrl = "wss://dashscope.aliyuncs.com/api-ws/v1/inference";
+    }
+
+    /**
+     * 生成文本的音频数据
+     * @param text 要转换为音频的文本
+     * @return 音频数据的Flux流
+     */
+    public Flux<ByteBuffer> generateAudio(String text) {
+        return Mono.fromCallable(() -> {
+            try {
+                SpeechSynthesisParam param = SpeechSynthesisParam.builder()
+                        .apiKey("sk-f7d2253302b547c7a2fe257673cb854b")
+                        .model(MODEL)
+                        .voice(VOICE)
+                        .build();
+
+                SpeechSynthesizer synthesizer = new SpeechSynthesizer(param, null);
+                
+                List<ByteBuffer> audioChunks = new ArrayList<>();
+                
+                synthesizer.callAsFlowable(text).blockingForEach(result -> {
+                    if (result.getAudioFrame() != null) {
+                        ByteBuffer audioData = ByteBuffer.wrap(result.getAudioFrame());
+                        audioChunks.add(audioData);
+                        log.debug("收到音频数据块，大小: {} bytes", result.getAudioFrame().length);
+                    }
+                });
+                
+                synthesizer.getDuplexApi().close(1000, "bye");
+                
+                log.info("音频生成完成，首包延迟: {} ms", synthesizer.getFirstPackageDelay());
+                
+                return Flux.fromIterable(audioChunks);
+                
+            } catch (NoApiKeyException e) {
+                log.error("API Key错误", e);
+                return Flux.error(e);
+            } catch (Exception e) {
+                log.error("音频生成失败", e);
+                return Flux.error(e);
+            }
+        }).flatMapMany(flux -> flux);
+    }
+
+    /**
+     * 生成单个音频数据块（用于实时流式传输）
+     * @param text 要转换为音频的文本
+     * @return 音频数据的Mono
+     */
+    public Mono<ByteBuffer> generateAudioChunk(String text) {
+        return Mono.fromCallable(() -> {
+            try {
+                SpeechSynthesisParam param = SpeechSynthesisParam.builder()
+                        .apiKey("sk-f7d2253302b547c7a2fe257673cb854b")
+                        .model(MODEL)
+                        .voice(VOICE)
+                        .build();
+
+                SpeechSynthesizer synthesizer = new SpeechSynthesizer(param, null);
+
+                ByteBuffer audioData = null;
+                
+                synthesizer.callAsFlowable(text).blockingForEach(result -> {
+                    if (result.getAudioFrame() != null) {
+                        audioData = ByteBuffer.wrap(result.getAudioFrame());
+                        log.debug("生成音频数据块，大小: {} bytes", result.getAudioFrame().length);
+                    }
+                });
+                
+                synthesizer.getDuplexApi().close(1000, "bye");
+                
+                return audioData;
+                
+            } catch (Exception e) {
+                log.error("音频生成失败", e);
+                throw new RuntimeException("音频生成失败", e);
+            }
+        });
+    }
+}

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/src/main/java/com/example/springaialibaba/service/SpeechSynthesisService.java

@@ -0,0 +1,82 @@
+package com.example.springaialibaba.service;
+
+
+import com.alibaba.dashscope.audio.tts.SpeechSynthesisResult;
+import com.alibaba.dashscope.audio.ttsv2.SpeechSynthesisParam;
+import com.alibaba.dashscope.audio.ttsv2.SpeechSynthesizer;
+import com.alibaba.dashscope.utils.Constants;
+import io.reactivex.Flowable;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Service;
+import reactor.adapter.rxjava.RxJava2Adapter;
+import reactor.core.publisher.Flux;
+
+import java.nio.ByteBuffer;
+
+@Slf4j
+@Service
+public class SpeechSynthesisService {
+
+    private static final String MODEL = "cosyvoice-v3-flash";
+    private static final String VOICE = "longanyang";
+
+    public Flux<byte[]> streamSynthesize(String text) {
+        try {
+            Constants.baseWebsocketApiUrl = "wss://dashscope.aliyuncs.com/api-ws/v1/inference";
+
+            SpeechSynthesisParam param = SpeechSynthesisParam.builder()
+                    .apiKey("sk-f7d2253302b547c7a2fe257673cb854b")
+                    .model(MODEL)
+                    .voice(VOICE)
+                    .build();
+
+            SpeechSynthesizer synthesizer = new SpeechSynthesizer(param, null);
+            Flowable<SpeechSynthesisResult> resultFlowable = synthesizer.callAsFlowable(text);
+
+            Flux<byte[]> audioFlux = RxJava2Adapter.flowableToFlux(resultFlowable)
+                    .doOnNext(result -> {
+                        log.info("收到SpeechSynthesisResult, audioFrame: {}, frameSize: {}", 
+                                result.getAudioFrame() != null,
+                                result.getAudioFrame() != null ? result.getAudioFrame().remaining() : 0);
+                    })
+                    .filter(result -> {
+                        boolean hasAudio = result.getAudioFrame() != null;
+                        if (!hasAudio) {
+                            log.info("跳过无音频帧的结果");
+                        }
+                        return hasAudio;
+                    })
+                    .map(result -> {
+                        ByteBuffer buffer = result.getAudioFrame();
+                        byte[] bytes = new byte[buffer.remaining()];
+                        buffer.get(bytes);
+                        log.info("处理音频数据块，大小: {} 字节", bytes.length);
+                        return bytes;
+                    })
+                    .doOnComplete(() -> {
+                        log.info("语音合成完成，requestId: {}, 首包延迟: {}ms", 
+                                synthesizer.getLastRequestId(), 
+                                synthesizer.getFirstPackageDelay());
+                        try {
+                            synthesizer.getDuplexApi().close(1000, "bye");
+                        } catch (Exception e) {
+                            log.error("关闭连接失败", e);
+                        }
+                    })
+                    .doOnError(error -> {
+                        log.error("语音合成错误", error);
+                        try {
+                            synthesizer.getDuplexApi().close(1000, "bye");
+                        } catch (Exception e) {
+                            log.error("关闭连接失败", e);
+                        }
+                    });
+
+            return audioFlux;
+
+        } catch (Exception e) {
+            log.error("语音合成失败", e);
+            return Flux.error(e);
+        }
+    }
+}

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/src/main/resources/application.yml

@@ -0,0 +1,14 @@
+server:
+  port: 8080
+
+spring:
+  ai:
+    dashscope:
+      # 核心：工作流应用的AppId
+      agent:
+        app-id: df04e1abf24a416c8702260e88863ac4
+      # 核心：你的API-Key
+      api-key: sk-f7d2253302b547c7a2fe257673cb854b
+      # 业务空间ID
+      workspace-id: llm-fuczq7vkh8vyz716
+

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/src/main/resources/static/index.html

@@ -0,0 +1,263 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>智能客服 - 文本 + 语音</title>
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            max-width: 1000px;
+            margin: 30px auto;
+            padding: 20px;
+        }
+        .container {
+            border: 1px solid #ddd;
+            border-radius: 8px;
+            padding: 30px;
+        }
+        h1 {
+            color: #333;
+            margin-bottom: 30px;
+        }
+        .input-group {
+            margin-bottom: 20px;
+        }
+        textarea {
+            width: 100%;
+            height: 100px;
+            padding: 12px;
+            font-size: 16px;
+            border: 1px solid #ccc;
+            border-radius: 4px;
+            resize: vertical;
+            box-sizing: border-box;
+        }
+        button {
+            padding: 12px 30px;
+            font-size: 16px;
+            background-color: #007bff;
+            color: white;
+            border: none;
+            border-radius: 4px;
+            cursor: pointer;
+        }
+        button:hover {
+            background-color: #0056b3;
+        }
+        button:disabled {
+            background-color: #ccc;
+            cursor: not-allowed;
+        }
+        .output-section {
+            margin-top: 30px;
+            border-top: 1px solid #eee;
+            padding-top: 20px;
+        }
+        .output-title {
+            font-size: 18px;
+            font-weight: bold;
+            margin-bottom: 15px;
+            color: #333;
+        }
+        .output-text {
+            padding: 15px;
+            background-color: #f8f9fa;
+            border-radius: 4px;
+            border: 1px solid #e9ecef;
+            min-height: 100px;
+            font-size: 16px;
+            line-height: 1.8;
+            color: #333;
+            white-space: pre-wrap;
+        }
+        .status {
+            margin-top: 20px;
+            padding: 15px;
+            background-color: #d1ecf1;
+            border-radius: 4px;
+            color: #0c5460;
+            font-size: 16px;
+        }
+        audio {
+            margin-top: 20px;
+            width: 100%;
+        }
+        .example-btn {
+            margin-left: 10px;
+            background-color: #28a745;
+        }
+        .example-btn:hover {
+            background-color: #218838;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>🤖 智能客服 - 文本 + 语音</h1>
+        
+        <div class="input-group">
+            <label style="display: block; margin-bottom: 10px; font-size: 16px;">请输入您的问题：</label>
+            <textarea id="questionInput" placeholder="请输入您的问题，例如：什么是半仓？"></textarea>
+        </div>
+        
+        <div class="input-group">
+            <button id="generateBtn" onclick="askQuestion()">提问</button>
+            <button class="example-btn" onclick="fillExample()">示例问题</button>
+        </div>
+        
+        <div class="status" id="status">
+            状态：等待提问
+        </div>
+        
+        <div class="output-section">
+            <div class="output-title">📝 回答内容</div>
+            <div class="output-text" id="outputText">
+                （回答将在这里显示）
+            </div>
+        </div>
+        
+        <audio id="audioPlayer" controls></audio>
+    </div>
+
+    <script>
+        const exampleQuestion = "什么是半仓？";
+
+        function fillExample() {
+            document.getElementById('questionInput').value = exampleQuestion;
+        }
+
+        async function askQuestion() {
+            const question = document.getElementById('questionInput').value.trim();
+            const statusDiv = document.getElementById('status');
+            const outputText = document.getElementById('outputText');
+            const audioPlayer = document.getElementById('audioPlayer');
+            const generateBtn = document.getElementById('generateBtn');
+            
+            if (!question) {
+                alert('请输入您的问题！');
+                return;
+            }
+
+            generateBtn.disabled = true;
+            outputText.textContent = '';
+            statusDiv.textContent = '状态：正在获取回答...';
+            console.log('开始提问:', question);
+
+            let fullText = '';
+            let eventSource = null;
+            
+            try {
+                eventSource = new EventSource(`/customer/service2?question=${encodeURIComponent(question)}`);
+                
+                eventSource.onmessage = (event) => {
+                    console.log('收到原始数据:', event.data);
+                    
+                    const dataStr = event.data;
+                    
+                    if (!dataStr || dataStr.trim() === '') {
+                        console.log('跳过空数据');
+                        return;
+                    }
+                    
+                    try {
+                        const data = JSON.parse(dataStr);
+                        const text = data.text;
+                        if (text) {
+                            fullText += text;
+                            outputText.textContent += text;
+                            outputText.scrollTop = outputText.scrollHeight;
+                            statusDiv.textContent = `状态：正在获取回答... (已收到 ${fullText.length} 字)`;
+                            console.log('解析到文本:', text);
+                        }
+                    } catch (parseError) {
+                        console.error('JSON解析失败:', parseError, '原始数据:', dataStr);
+                    }
+                };
+                
+                eventSource.onerror = (error) => {
+                    console.log('EventSource 连接关闭:', error);
+                    eventSource.close();
+                    
+                    if (fullText.length > 0) {
+                        statusDiv.textContent = '状态：回答获取完成，正在生成语音...';
+                        console.log('完整回答:', fullText);
+                        
+                        generateAndPlayAudio(fullText);
+                    } else {
+                        statusDiv.textContent = '状态：未获取到回答';
+                        generateBtn.disabled = false;
+                    }
+                };
+
+            } catch (error) {
+                console.error('获取回答错误:', error);
+                statusDiv.textContent = `状态：获取回答失败 - ${error.message}`;
+                generateBtn.disabled = false;
+            }
+        }
+
+        async function generateAndPlayAudio(text) {
+            const statusDiv = document.getElementById('status');
+            const audioPlayer = document.getElementById('audioPlayer');
+            const generateBtn = document.getElementById('generateBtn');
+            
+            statusDiv.textContent = '状态：正在生成语音...';
+            console.log('开始语音合成，文本长度:', text.length);
+
+            try {
+                const url = `/customer/synthesize?text=${encodeURIComponent(text)}`;
+                
+                audioPlayer.src = url;
+                
+                audioPlayer.onloadstart = () => {
+                    statusDiv.textContent = '状态：开始接收音频流...';
+                    console.log('开始接收音频流');
+                };
+                
+                audioPlayer.onloadeddata = () => {
+                    statusDiv.textContent = '状态：数据加载中，准备播放...';
+                    console.log('音频数据加载完成，可以开始播放');
+                };
+                
+                audioPlayer.onplaying = () => {
+                    statusDiv.textContent = '状态：正在播放（流式）';
+                    console.log('开始播放音频');
+                };
+                
+                audioPlayer.onwaiting = () => {
+                    statusDiv.textContent = '状态：缓冲中...';
+                };
+                
+                audioPlayer.oncanplay = () => {
+                    statusDiv.textContent = '状态：正在播放（流畅）';
+                };
+                
+                audioPlayer.onended = () => {
+                    statusDiv.textContent = '状态：播放完成';
+                    generateBtn.disabled = false;
+                    console.log('播放完成');
+                };
+                
+                audioPlayer.onerror = (e) => {
+                    console.error('音频播放错误:', e);
+                    statusDiv.textContent = `状态：音频播放失败 - ${audioPlayer.error ? audioPlayer.error.message : '未知错误'}`;
+                    generateBtn.disabled = false;
+                };
+                
+                audioPlayer.play();
+                console.log('已调用 audio.play()');
+                
+            } catch (error) {
+                console.error('语音合成错误:', error);
+                statusDiv.textContent = `状态：出错了 - ${error.message}`;
+                generateBtn.disabled = false;
+            }
+        }
+
+        window.onload = () => {
+            console.log('页面加载完成');
+        };
+    </script>
+</body>
+</html>

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/src/test/java/com/example/springaialibaba/SpringAiAlibabaApplicationTests.java

@@ -0,0 +1,13 @@
+package com.example.springaialibaba;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.boot.test.context.SpringBootTest;
+
+@SpringBootTest
+class SpringAiAlibabaApplicationTests {
+
+    @Test
+    void contextLoads() {
+    }
+
+}

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/target/classes/application.yml

@@ -0,0 +1,14 @@
+server:
+  port: 8080
+
+spring:
+  ai:
+    dashscope:
+      # 核心：工作流应用的AppId
+      agent:
+        app-id: df04e1abf24a416c8702260e88863ac4
+      # 核心：你的API-Key
+      api-key: sk-f7d2253302b547c7a2fe257673cb854b
+      # 业务空间ID
+      workspace-id: llm-fuczq7vkh8vyz716
+

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/target/classes/static/index.html

@@ -0,0 +1,263 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>智能客服 - 文本 + 语音</title>
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            max-width: 1000px;
+            margin: 30px auto;
+            padding: 20px;
+        }
+        .container {
+            border: 1px solid #ddd;
+            border-radius: 8px;
+            padding: 30px;
+        }
+        h1 {
+            color: #333;
+            margin-bottom: 30px;
+        }
+        .input-group {
+            margin-bottom: 20px;
+        }
+        textarea {
+            width: 100%;
+            height: 100px;
+            padding: 12px;
+            font-size: 16px;
+            border: 1px solid #ccc;
+            border-radius: 4px;
+            resize: vertical;
+            box-sizing: border-box;
+        }
+        button {
+            padding: 12px 30px;
+            font-size: 16px;
+            background-color: #007bff;
+            color: white;
+            border: none;
+            border-radius: 4px;
+            cursor: pointer;
+        }
+        button:hover {
+            background-color: #0056b3;
+        }
+        button:disabled {
+            background-color: #ccc;
+            cursor: not-allowed;
+        }
+        .output-section {
+            margin-top: 30px;
+            border-top: 1px solid #eee;
+            padding-top: 20px;
+        }
+        .output-title {
+            font-size: 18px;
+            font-weight: bold;
+            margin-bottom: 15px;
+            color: #333;
+        }
+        .output-text {
+            padding: 15px;
+            background-color: #f8f9fa;
+            border-radius: 4px;
+            border: 1px solid #e9ecef;
+            min-height: 100px;
+            font-size: 16px;
+            line-height: 1.8;
+            color: #333;
+            white-space: pre-wrap;
+        }
+        .status {
+            margin-top: 20px;
+            padding: 15px;
+            background-color: #d1ecf1;
+            border-radius: 4px;
+            color: #0c5460;
+            font-size: 16px;
+        }
+        audio {
+            margin-top: 20px;
+            width: 100%;
+        }
+        .example-btn {
+            margin-left: 10px;
+            background-color: #28a745;
+        }
+        .example-btn:hover {
+            background-color: #218838;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>🤖 智能客服 - 文本 + 语音</h1>
+        
+        <div class="input-group">
+            <label style="display: block; margin-bottom: 10px; font-size: 16px;">请输入您的问题：</label>
+            <textarea id="questionInput" placeholder="请输入您的问题，例如：什么是半仓？"></textarea>
+        </div>
+        
+        <div class="input-group">
+            <button id="generateBtn" onclick="askQuestion()">提问</button>
+            <button class="example-btn" onclick="fillExample()">示例问题</button>
+        </div>
+        
+        <div class="status" id="status">
+            状态：等待提问
+        </div>
+        
+        <div class="output-section">
+            <div class="output-title">📝 回答内容</div>
+            <div class="output-text" id="outputText">
+                （回答将在这里显示）
+            </div>
+        </div>
+        
+        <audio id="audioPlayer" controls></audio>
+    </div>
+
+    <script>
+        const exampleQuestion = "什么是半仓？";
+
+        function fillExample() {
+            document.getElementById('questionInput').value = exampleQuestion;
+        }
+
+        async function askQuestion() {
+            const question = document.getElementById('questionInput').value.trim();
+            const statusDiv = document.getElementById('status');
+            const outputText = document.getElementById('outputText');
+            const audioPlayer = document.getElementById('audioPlayer');
+            const generateBtn = document.getElementById('generateBtn');
+            
+            if (!question) {
+                alert('请输入您的问题！');
+                return;
+            }
+
+            generateBtn.disabled = true;
+            outputText.textContent = '';
+            statusDiv.textContent = '状态：正在获取回答...';
+            console.log('开始提问:', question);
+
+            let fullText = '';
+            let eventSource = null;
+            
+            try {
+                eventSource = new EventSource(`/customer/service2?question=${encodeURIComponent(question)}`);
+                
+                eventSource.onmessage = (event) => {
+                    console.log('收到原始数据:', event.data);
+                    
+                    const dataStr = event.data;
+                    
+                    if (!dataStr || dataStr.trim() === '') {
+                        console.log('跳过空数据');
+                        return;
+                    }
+                    
+                    try {
+                        const data = JSON.parse(dataStr);
+                        const text = data.text;
+                        if (text) {
+                            fullText += text;
+                            outputText.textContent += text;
+                            outputText.scrollTop = outputText.scrollHeight;
+                            statusDiv.textContent = `状态：正在获取回答... (已收到 ${fullText.length} 字)`;
+                            console.log('解析到文本:', text);
+                        }
+                    } catch (parseError) {
+                        console.error('JSON解析失败:', parseError, '原始数据:', dataStr);
+                    }
+                };
+                
+                eventSource.onerror = (error) => {
+                    console.log('EventSource 连接关闭:', error);
+                    eventSource.close();
+                    
+                    if (fullText.length > 0) {
+                        statusDiv.textContent = '状态：回答获取完成，正在生成语音...';
+                        console.log('完整回答:', fullText);
+                        
+                        generateAndPlayAudio(fullText);
+                    } else {
+                        statusDiv.textContent = '状态：未获取到回答';
+                        generateBtn.disabled = false;
+                    }
+                };
+
+            } catch (error) {
+                console.error('获取回答错误:', error);
+                statusDiv.textContent = `状态：获取回答失败 - ${error.message}`;
+                generateBtn.disabled = false;
+            }
+        }
+
+        async function generateAndPlayAudio(text) {
+            const statusDiv = document.getElementById('status');
+            const audioPlayer = document.getElementById('audioPlayer');
+            const generateBtn = document.getElementById('generateBtn');
+            
+            statusDiv.textContent = '状态：正在生成语音...';
+            console.log('开始语音合成，文本长度:', text.length);
+
+            try {
+                const url = `/customer/synthesize?text=${encodeURIComponent(text)}`;
+                
+                audioPlayer.src = url;
+                
+                audioPlayer.onloadstart = () => {
+                    statusDiv.textContent = '状态：开始接收音频流...';
+                    console.log('开始接收音频流');
+                };
+                
+                audioPlayer.onloadeddata = () => {
+                    statusDiv.textContent = '状态：数据加载中，准备播放...';
+                    console.log('音频数据加载完成，可以开始播放');
+                };
+                
+                audioPlayer.onplaying = () => {
+                    statusDiv.textContent = '状态：正在播放（流式）';
+                    console.log('开始播放音频');
+                };
+                
+                audioPlayer.onwaiting = () => {
+                    statusDiv.textContent = '状态：缓冲中...';
+                };
+                
+                audioPlayer.oncanplay = () => {
+                    statusDiv.textContent = '状态：正在播放（流畅）';
+                };
+                
+                audioPlayer.onended = () => {
+                    statusDiv.textContent = '状态：播放完成';
+                    generateBtn.disabled = false;
+                    console.log('播放完成');
+                };
+                
+                audioPlayer.onerror = (e) => {
+                    console.error('音频播放错误:', e);
+                    statusDiv.textContent = `状态：音频播放失败 - ${audioPlayer.error ? audioPlayer.error.message : '未知错误'}`;
+                    generateBtn.disabled = false;
+                };
+                
+                audioPlayer.play();
+                console.log('已调用 audio.play()');
+                
+            } catch (error) {
+                console.error('语音合成错误:', error);
+                statusDiv.textContent = `状态：出错了 - ${error.message}`;
+                generateBtn.disabled = false;
+            }
+        }
+
+        window.onload = () => {
+            console.log('页面加载完成');
+        };
+    </script>
+</body>
+</html>

黄永兴学习笔记/智能客服案例/SpringAIAlibaba/target/maven-status/maven-compiler-plugin/compile/default-compile/inputFiles.lst

@@ -0,0 +1,4 @@
+C:\Users\Mayn\IdeaProjects\StudySpringAI\StudySpringAI\SpringAIAlibaba\src\main\java\com\example\springaialibaba\controller\CustomerServiceController.java
+C:\Users\Mayn\IdeaProjects\StudySpringAI\StudySpringAI\SpringAIAlibaba\src\main\java\com\example\springaialibaba\controller\Main.java
+C:\Users\Mayn\IdeaProjects\StudySpringAI\StudySpringAI\SpringAIAlibaba\src\main\java\com\example\springaialibaba\service\SpeechSynthesisService.java
+C:\Users\Mayn\IdeaProjects\StudySpringAI\StudySpringAI\SpringAIAlibaba\src\main\java\com\example\springaialibaba\SpringAiAlibabaApplication.java