DashScope4j：灵积 Java SDK

DashScope4j是一个开源的灵积非官方 Java SDK，基于 JDK17 构建。它旨在提供一个功能丰富、易于集成和使用灵积API（通义千问模型）的Java库，以便开发者能够通灵积API轻松实现多模态对话、向量嵌入和图像处理等功能。

请注意：在使用 DashScope4j 时，你需要遵守灵积API的使用条款和条件。

重要更新

• 1.4.0： 支持无感临时空间、请求和应答拦截器
• 1.3.0： 支持多模态向量计算
• 1.2.0： 支持多函数级联调用
• 1.1.1： 第一个稳定版本

支持请求和应答拦截器

• RequestInterceptor： 可以拦截和修改请求
• ResponseInterceptor： 可以拦截和修改应答

通过DashScopeClient.Builder设置，示例代码

DashScopeClient client = DashScopeClient.newBuilder()
    .ak(AK)
    .executor(executor)
    .requestInterceptors(new RequestInterceptor() {
        
        @Override
        public CompletableFuture<ApiRequest<?>> preHandle(InvocationContext ctx, ApiRequest<?> req) {
            return CompletableFuture.completedFuture(req);
        }
        
    })
    .build();

支持无感使用临时空间

在对话、多模态向量计算和文档分析插件等请求中如果需要解析图片、音频、文档等内容，不再需要提前上传到OSS转换为外网可访问的URL连接。这样极不方便也不安全。

通过灵积平台提供的临时空间可以很好的解决这个问题，但操作起来需要调用额外的api且需要对url进行拼接和替换，略为繁琐。

dashscope4j帮你封装了这个繁琐的操作，你只需要设置内容的时候将本地文件、BufferedImage甚至byte[]直接传入Content，框架会自动识别并帮你完成临时空间上传和转换连接操作。并自带一个缓存避免重复上传。

final var request = ChatRequest.newBuilder()
        .model(ChatModel.QWEN_VL_MAX)
        .option(ChatOptions.ENABLE_INCREMENTAL_OUTPUT, true)
        .user(
                Content.ofImage(new File("C:\\Users\\vlinux\\图片\\image-002.jpeg").toURI()),
                Content.ofText("图片中一共多少辆自行车?")
        )
        .build();

依赖使用

<dependency>
    <groupId>io.github.oldmanpushcart</groupId>
    <artifactId>dashscope4j</artifactId>
    <version>1.4.1</version>
</dependency>

一、主要功能

DashScope4j支持以下API功能：

• 对话（Chat）

  • 提供用户与灵积进行多模态(图、文)对话
  • 提供用户与灵积进行多模态(图、音)对话
  • 提供用户与灵积进行函数对话
  • 支持灵积提供的临时空间

• 向量（Embeddings）

  • 将文本转换为向量表示，用于文本相似度比较、聚类等任务
  • 将图音文本转换为向量表示，用于图音文相似度比较、聚类等任务
  • 支持灵积提供的临时空间

• 图像（Images）

  • 文生图： 将文本描述转换为相应的图像

• 插件应用（Plugin）

  • OCR插件： 图像理解识别，并对图像内容进行总结概述，输出用户可理解的句子或段落
  • PDF解析插件： 对PDF文件进行解析，提取、理解文本内容
  • 计算器插件： 对用户输入的数学表达式进行计算
  • 文生图插件： 将文本描述转换为相应的图像

二、系统要求

1. JDK17或更高版本

三、跑通测试

1. 到阿里云的模型服务-灵积中开通服务，获取AK
2. 到API-KEY管理中创建一个API-KEY，获取其AK
3. 声明环境变量export DASHSCOPE_AK=<YOUR APP-KEY>
4. 运行测试用例：mvn test

四、使用示例

创建客户端

// 线程池
final var executor = Executors.newFixedThreadPool(10);

// 创建客户端
final var client = DashScopeClient.newBuilder()
    .ak("<YOUR APP-KEY>")
    .executor(executor)
    .build();

对话示例（异步）

// 创建请求
final var request = ChatRequest.newBuilder()
    .model(ChatModel.QWEN_VL_MAX)
    .user(
        Content.ofImage(URI.create("https://ompc-images.oss-cn-hangzhou.aliyuncs.com/image-002.jpeg")),
        Content.ofText("图片中一共多少辆自行车?")
    )
    .build();

// 异步应答
final var response = client.chat(request)
    .async()
    .join();

// 输出结果（异步）
System.out.println(response.output().best().message().text());

输出日志

2024-02-29 00:49:56 DEBUG dashscope://chat/qwen-vl-max => {"model":"qwen-vl-max","input":{"messages":[{"role":"user","content":[{"image":"https://ompc-images.oss-cn-hangzhou.aliyuncs.com/image-002.jpeg"},{"text":"图片中一共多少辆自行车?"}]}]},"parameters":{}}
2024-02-29 00:49:59 DEBUG dashscope://chat/qwen-vl-max <= {"output":{"choices":[{"finish_reason":"stop","message":{"role":"assistant","content":[{"text":"图片中有两辆自行车。"}]}}]},"usage":{"output_tokens":7,"input_tokens":1264,"image_tokens":1230},"request_id":"f11e20f0-6774-9649-a0c9-6095e6287cdc"}
图片中有两辆自行车。

对话示例（流式）

// 创建请求
final var request = ChatRequest.newBuilder()
    .model(ChatModel.QWEN_VL_MAX)
    .option(ChatOptions.ENABLE_INCREMENTAL_OUTPUT, true)
    .user(
            Content.ofImage(URI.create("https://ompc-images.oss-cn-hangzhou.aliyuncs.com/image-002.jpeg")),
            Content.ofText("图片中一共多少辆自行车?")
    )
    .build();

// 流式应答
final var publisher = client.chat(request)
    .flow()
    .join();

// 应答输出（流式）
final var latch = new CountDownLatch(1);
final var stringSB = new StringBuilder();
publisher.subscribe(new Flow.Subscriber<>(){

    @Override
    public void onSubscribe(Flow.Subscription subscription) {
        subscription.request(Long.MAX_VALUE);
    }
    
    @Override
    public void onNext(ChatResponse response) {
        stringSB.append(response.output().best().message().text());
    }
    
    @Override
    public void onError(Throwable ex) {
        ex.printStackTrace(System.err);
    }
    
    @Override
    public void onComplete() {
        latch.countDown();
    }

});

// 等待处理完成
latch.await();
System.out.println(stringSB);

输出日志

2024-02-29 01:21:42 DEBUG dashscope://chat/qwen-vl-max => {"model":"qwen-vl-max","input":{"messages":[{"role":"user","content":[{"image":"https://ompc-images.oss-cn-hangzhou.aliyuncs.com/image-002.jpeg"},{"text":"图片中一共多少辆自行车?"}]}]},"parameters":{"incremental_output":true}}
2024-02-29 01:21:44 DEBUG dashscope://chat/qwen-vl-max <= {"output":{"choices":[{"message":{"content":[{"text":"图片"}],"role":"assistant"},"finish_reason":"null"}]},"usage":{"input_tokens":1264,"output_tokens":1,"image_tokens":1230},"request_id":"9713405c-31b3-97a5-8e99-ac2c685798a0"}
2024-02-29 01:21:44 DEBUG dashscope://chat/qwen-vl-max <= {"output":{"choices":[{"message":{"content":[{"text":"中有"}],"role":"assistant"},"finish_reason":"null"}]},"usage":{"input_tokens":1264,"output_tokens":2,"image_tokens":1230},"request_id":"9713405c-31b3-97a5-8e99-ac2c685798a0"}
2024-02-29 01:21:45 DEBUG dashscope://chat/qwen-vl-max <= {"output":{"choices":[{"message":{"content":[{"text":"两"}],"role":"assistant"},"finish_reason":"null"}]},"usage":{"input_tokens":1264,"output_tokens":3,"image_tokens":1230},"request_id":"9713405c-31b3-97a5-8e99-ac2c685798a0"}
2024-02-29 01:21:45 DEBUG dashscope://chat/qwen-vl-max <= {"output":{"choices":[{"message":{"content":[{"text":"辆自行车。"}],"role":"assistant"},"finish_reason":"stop"}]},"usage":{"input_tokens":1264,"output_tokens":7,"image_tokens":1230},"request_id":"9713405c-31b3-97a5-8e99-ac2c685798a0"}
图片中有两辆自行车。

函数调用示例

灵积在 2024-03-12 放出了函数调用的功能，当前支持的模型是大语言模型：qwen-turbo、qwen-plus、qwen-max、qwen-max-longcontext，下面是一个函数调用的示例：

单个函数调用示例：回显

假设我们有一个回显函数:echo

@ChatFn(name = "echo", description = "当用户输入echo:，回显后边的文字")
public class EchoFunction implements ChatFunction<EchoFunction.Echo, EchoFunction.Echo> {

    @Override
    public CompletableFuture<Echo> call(Echo echo) {
        return CompletableFuture.completedFuture(new Echo(echo.words()));
    }

    public record Echo(
            @JsonPropertyDescription("需要回显的文字")
            String words
    ) {

    }

}

我们可以通过以下代码来调用这个函数：

final var request = ChatRequest.newBuilder()
    .model(ChatModel.QWEN_MAX)
    .functions(new EchoFunction())
    .user("echo: HELLO!")
    .build();
final var response = client.chat(request)
    .async()
    .join();

输出日志

2024-03-19 21:28:38 DEBUG dashscope://chat/qwen-max => {"model":"qwen-max","input":{"messages":[{"role":"user","content":"echo: HELLO!"}]},"parameters":{"result_format":"message","tools":[{"function":{"name":"echo","description":"当用户输入echo:，回显后边的文字","parameters":{"type":"object","properties":{"words":{"type":"string","description":"需要回显的文字"}}}},"type":"function"}]}}
2024-03-19 21:28:40 DEBUG dashscope://chat/qwen-max <= {"output":{"choices":[{"finish_reason":"tool_calls","message":{"role":"assistant","tool_calls":[{"function":{"name":"echo","arguments":"{\"words\": \"HELLO!\"}"},"id":"","type":"function"}],"content":""}}]},"usage":{"total_tokens":28,"output_tokens":23,"input_tokens":5},"request_id":"8af40d7a-d43d-9d7f-9f12-8d52accfe8ac"}
2024-03-19 21:28:40 DEBUG dashscope://chat/function/echo <= {"words":"HELLO!"}
2024-03-19 21:28:40 DEBUG dashscope://chat/function/echo => {"words":"HELLO!"}
2024-03-19 21:28:40 DEBUG dashscope://chat/qwen-max => {"model":"qwen-max","input":{"messages":[{"role":"user","content":"echo: HELLO!"},{"role":"assistant","tool_calls":[{"function":{"name":"echo","arguments":"{\"words\": \"HELLO!\"}"},"type":"function"}],"content":""},{"role":"tool","name":"echo","content":"{\"words\":\"HELLO!\"}"}]},"parameters":{"result_format":"message","tools":[{"function":{"name":"echo","description":"当用户输入echo:，回显后边的文字","parameters":{"type":"object","properties":{"words":{"type":"string","description":"需要回显的文字"}}}},"type":"function"}]}}
2024-03-19 21:28:42 DEBUG dashscope://chat/qwen-max <= {"output":{"choices":[{"finish_reason":"stop","message":{"role":"assistant","content":"HELLO!"}}]},"usage":{"total_tokens":8,"output_tokens":3,"input_tokens":5},"request_id":"37ff7303-c1b2-9d7c-966d-82a7446fc52e"}
HELLO!

级联函数调用示例：成绩查询

我们有两个函数

• 查询成绩函数：query_score
• 计算平均分函数：compute_avg_score

现在需要查询某个同学的所有成绩，并计算其平均分。LLM需要先调用 query_score 函数查询成绩，然后再调用 compute_avg_score 函数计算平均分。

final var request = ChatRequest.newBuilder()
    .model(ChatModel.QWEN_PLUS)
    .functions(new QueryScoreFunction(), new ComputeAvgScoreFunction())
    .user("张三的所有成绩，并计算平均分")
    .build();
final var response = client.chat(request)
    .async()
    .join();

输出日志

2024-03-20 23:50:17 DEBUG dashscope://chat/qwen-plus => {"model":"qwen-plus","input":{"messages":[{"role":"user","content":"张三的所有成绩，并计算平均分"}]},"parameters":{"result_format":"message","tools":[{"function":{"name":"query_score","description":"query student's scores","parameters":{"type":"object","properties":{"name":{"type":"string","description":"the student name to query"},"subjects":{"type":"array","description":"the subjects to query","items":{"type":"string","enum":["CHINESE","MATH","ENGLISH"]}}},"required":["name","subjects"]}},"type":"function"},{"function":{"name":"compute_avg_score","description":"计算平均成绩","parameters":{"type":"object","properties":{"scores":{"type":"array","description":"分数集合","items":{"type":"number"}}}}},"type":"function"}]}}
2024-03-20 23:50:20 DEBUG dashscope://chat/qwen-plus <= {"output":{"choices":[{"finish_reason":"tool_calls","message":{"role":"assistant","tool_calls":[{"function":{"name":"query_score","arguments":"{\"name\": \"张三\", \"subjects\": [\"CHINESE\", \"MATH\", \"ENGLISH\"]}"},"id":"","type":"function"}],"content":""}}]},"usage":{"total_tokens":47,"output_tokens":39,"input_tokens":8},"request_id":"4703f631-a245-967e-ba86-8f01327a82bf"}
2024-03-20 23:50:20 DEBUG dashscope://chat/function/query_score <= {"name":"张三","subjects":["CHINESE","MATH","ENGLISH"]}
2024-03-20 23:50:20 DEBUG dashscope://chat/function/query_score => {"message":"查询成功","data":[{"name":"张三","subject":"CHINESE","value":90.0},{"name":"张三","subject":"MATH","value":80.0},{"name":"张三","subject":"ENGLISH","value":70.0}],"success":true}
2024-03-20 23:50:20 DEBUG dashscope://chat/qwen-plus => {"model":"qwen-plus","input":{"messages":[{"role":"user","content":"张三的所有成绩，并计算平均分"},{"role":"assistant","tool_calls":[{"function":{"arguments":"{\"name\": \"张三\", \"subjects\": [\"CHINESE\", \"MATH\", \"ENGLISH\"]}","name":"query_score"},"type":"function"}],"content":""},{"role":"tool","name":"query_score","content":"{\"message\":\"查询成功\",\"data\":[{\"name\":\"张三\",\"subject\":\"CHINESE\",\"value\":90.0},{\"name\":\"张三\",\"subject\":\"MATH\",\"value\":80.0},{\"name\":\"张三\",\"subject\":\"ENGLISH\",\"value\":70.0}],\"success\":true}"}]},"parameters":{"result_format":"message","tools":[{"function":{"name":"query_score","description":"query student's scores","parameters":{"type":"object","properties":{"name":{"type":"string","description":"the student name to query"},"subjects":{"type":"array","description":"the subjects to query","items":{"type":"string","enum":["CHINESE","MATH","ENGLISH"]}}},"required":["name","subjects"]}},"type":"function"},{"function":{"name":"compute_avg_score","description":"计算平均成绩","parameters":{"type":"object","properties":{"scores":{"type":"array","description":"分数集合","items":{"type":"number"}}}}},"type":"function"}]}}
2024-03-20 23:50:24 DEBUG dashscope://chat/qwen-plus <= {"output":{"choices":[{"finish_reason":"tool_calls","message":{"role":"assistant","tool_calls":[{"function":{"name":"compute_avg_score","arguments":"{\"scores\": [90.0, 80.0, 70.0]}"},"id":"","type":"function"}],"content":"张三的成绩如下：\n\n- 中文: 90.0分\n- 数学: 80.0分\n- 英语: 70.0分\n\n现在我们来计算他的平均分。"}}]},"usage":{"total_tokens":93,"output_tokens":85,"input_tokens":8},"request_id":"0f662c8b-ca5d-9512-9f92-597045977eca"}
2024-03-20 23:50:24 DEBUG dashscope://chat/function/compute_avg_score <= {"scores":[90.0,80.0,70.0]}
2024-03-20 23:50:24 DEBUG dashscope://chat/function/compute_avg_score => {"avg_score":80.0}
2024-03-20 23:50:24 DEBUG dashscope://chat/qwen-plus => {"model":"qwen-plus","input":{"messages":[{"role":"user","content":"张三的所有成绩，并计算平均分"},{"role":"assistant","tool_calls":[{"function":{"arguments":"{\"name\": \"张三\", \"subjects\": [\"CHINESE\", \"MATH\", \"ENGLISH\"]}","name":"query_score"},"type":"function"}],"content":""},{"role":"tool","name":"query_score","content":"{\"message\":\"查询成功\",\"data\":[{\"name\":\"张三\",\"subject\":\"CHINESE\",\"value\":90.0},{\"name\":\"张三\",\"subject\":\"MATH\",\"value\":80.0},{\"name\":\"张三\",\"subject\":\"ENGLISH\",\"value\":70.0}],\"success\":true}"},{"role":"assistant","tool_calls":[{"function":{"arguments":"{\"scores\": [90.0, 80.0, 70.0]}","name":"compute_avg_score"},"type":"function"}],"content":"张三的成绩如下：\n\n- 中文: 90.0分\n- 数学: 80.0分\n- 英语: 70.0分\n\n现在我们来计算他的平均分。"},{"role":"tool","name":"compute_avg_score","content":"{\"avg_score\":80.0}"}]},"parameters":{"result_format":"message","tools":[{"function":{"name":"query_score","description":"query student's scores","parameters":{"type":"object","properties":{"name":{"type":"string","description":"the student name to query"},"subjects":{"type":"array","description":"the subjects to query","items":{"type":"string","enum":["CHINESE","MATH","ENGLISH"]}}},"required":["name","subjects"]}},"type":"function"},{"function":{"name":"compute_avg_score","description":"计算平均成绩","parameters":{"type":"object","properties":{"scores":{"type":"array","description":"分数集合","items":{"type":"number"}}}}},"type":"function"}]}}
2024-03-20 23:50:25 DEBUG dashscope://chat/qwen-plus <= {"output":{"choices":[{"finish_reason":"stop","message":{"role":"assistant","content":"张三的平均分是 80.0 分。"}}]},"usage":{"total_tokens":68,"output_tokens":13,"input_tokens":55},"request_id":"c01da60a-21d7-9e2f-ae5d-17a9b622ed41"}
张三的平均分是 80.0 分。

文生图示例

// 创建请求
final var request = GenImageRequest.newBuilder()
    .model(GenImageModel.WANX_V1)
    .option(GenImageOptions.NUMBER, 1)
    .option(GenImageOptions.STYLE, GenImageRequest.Style.ANIME)
    .prompt("画古风美少女，黑发，面容白皙精致，发饰精美")
    .build();

// 任务应答
final var response = client.genImage(request)
    .task(Task.WaitStrategies.perpetual(Duration.ofSeconds(1L)))
    .join();

输出日志

2024-02-29 01:27:01 DEBUG dashscope://image/generation/wanx-v1 => {"model":"wanx-v1","input":{"prompt":"画古风美少女，黑发，面容白皙精致，发饰精美","negative_prompt":null},"parameters":{"style":"<anime>","n":1}}
2024-02-29 01:27:02 DEBUG dashscope://task/get => dd693d99-0b5e-4261-8b08-7c633919d2fc
2024-02-29 01:27:02 DEBUG dashscope://task/get <= {"request_id":"becb655f-2e7c-9a82-8d0a-c0e48f925221","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"RUNNING","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","task_metrics":{"TOTAL":1,"SUCCEEDED":0,"FAILED":0}}}
2024-02-29 01:27:03 DEBUG dashscope://task/get => dd693d99-0b5e-4261-8b08-7c633919d2fc
2024-02-29 01:27:03 DEBUG dashscope://task/get <= {"request_id":"f329109b-8d7f-9e7f-9049-faced6937cc8","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"RUNNING","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","task_metrics":{"TOTAL":1,"SUCCEEDED":0,"FAILED":0}}}
2024-02-29 01:27:04 DEBUG dashscope://task/get => dd693d99-0b5e-4261-8b08-7c633919d2fc
2024-02-29 01:27:04 DEBUG dashscope://task/get <= {"request_id":"ec190c02-33b4-91ca-8fa2-2abb0dfd979e","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"RUNNING","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","task_metrics":{"TOTAL":1,"SUCCEEDED":0,"FAILED":0}}}
2024-02-29 01:27:05 DEBUG dashscope://task/get => dd693d99-0b5e-4261-8b08-7c633919d2fc
2024-02-29 01:27:05 DEBUG dashscope://task/get <= {"request_id":"f7e2dbe9-11e8-9681-9a07-1e5076369d62","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"RUNNING","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","task_metrics":{"TOTAL":1,"SUCCEEDED":0,"FAILED":0}}}
...
2024-02-29 01:27:26 DEBUG dashscope://task/get => dd693d99-0b5e-4261-8b08-7c633919d2fc
2024-02-29 01:27:26 DEBUG dashscope://task/get <= {"request_id":"5e50bc5e-9215-9737-9ecb-dc3fd8c586d1","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"RUNNING","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","task_metrics":{"TOTAL":1,"SUCCEEDED":0,"FAILED":0}}}
2024-02-29 01:27:27 DEBUG dashscope://task/get => dd693d99-0b5e-4261-8b08-7c633919d2fc
2024-02-29 01:27:27 DEBUG dashscope://task/get <= {"request_id":"408498bc-26c9-9792-b47d-d8b4950a116c","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"RUNNING","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","task_metrics":{"TOTAL":1,"SUCCEEDED":0,"FAILED":0}}}
2024-02-29 01:27:28 DEBUG dashscope://task/get => dd693d99-0b5e-4261-8b08-7c633919d2fc
2024-02-29 01:27:29 DEBUG dashscope://task/get <= {"request_id":"cd3bcc40-3ad6-9f7c-acad-f29653f53c2d","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"RUNNING","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","task_metrics":{"TOTAL":1,"SUCCEEDED":0,"FAILED":0}}}
2024-02-29 01:27:30 DEBUG dashscope://task/get => dd693d99-0b5e-4261-8b08-7c633919d2fc
2024-02-29 01:27:30 DEBUG dashscope://task/get <= {"request_id":"34b79abd-aa21-988c-87b5-f00261a40ad9","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"RUNNING","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","task_metrics":{"TOTAL":1,"SUCCEEDED":0,"FAILED":0}}}
2024-02-29 01:27:31 DEBUG dashscope://task/get => dd693d99-0b5e-4261-8b08-7c633919d2fc
2024-02-29 01:27:31 DEBUG dashscope://task/get <= {"request_id":"682cec73-19d1-9fbd-a50c-465908c64106","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"RUNNING","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","task_metrics":{"TOTAL":1,"SUCCEEDED":0,"FAILED":0}}}
2024-02-29 01:27:32 DEBUG dashscope://task/get => dd693d99-0b5e-4261-8b08-7c633919d2fc
2024-02-29 01:27:32 DEBUG dashscope://task/get <= {"request_id":"7414bd26-8b51-9e04-abad-c223985ee809","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"SUCCEEDED","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","end_time":"2024-02-29 01:27:32.081","results":[{"url":"https://dashscope-result-bj.oss-cn-beijing.aliyuncs.com/1d/a8/20240229/c34adf05/3464efa2-8874-4aa9-86a4-8aba14b9707d-1.png?Expires=1709227651&OSSAccessKeyId=LTAI5tQZd8AEcZX6KZV4G8qL&Signature=yZ04L3oCKULBD%2By3PGSdmh0jg6M%3D"}],"task_metrics":{"TOTAL":1,"SUCCEEDED":1,"FAILED":0}},"usage":{"image_count":1}}
2024-02-29 01:27:32 DEBUG dashscope://image/generation/wanx-v1 <= {"request_id":"7414bd26-8b51-9e04-abad-c223985ee809","output":{"task_id":"dd693d99-0b5e-4261-8b08-7c633919d2fc","task_status":"SUCCEEDED","submit_time":"2024-02-29 01:27:02.856","scheduled_time":"2024-02-29 01:27:02.911","end_time":"2024-02-29 01:27:32.081","results":[{"url":"https://dashscope-result-bj.oss-cn-beijing.aliyuncs.com/1d/a8/20240229/c34adf05/3464efa2-8874-4aa9-86a4-8aba14b9707d-1.png?Expires=1709227651&OSSAccessKeyId=LTAI5tQZd8AEcZX6KZV4G8qL&Signature=yZ04L3oCKULBD%2By3PGSdmh0jg6M%3D"}],"task_metrics":{"TOTAL":1,"SUCCEEDED":1,"FAILED":0}},"usage":{"image_count":1}}

然后你就可以通过response.output().results().get(0)拿到生成的图片地址。

插件调用示例

PDF提取插件

我从网上下载了一份《十四五规划》的PDF文件，然后通过PDF提取插件来提取PDF文件的内容。

final var request = ChatRequest.newBuilder()
    .model(ChatModel.QWEN_PLUS)
    .plugins(ChatPlugin.PDF_EXTRACTER)
    .user(
        Content.ofText("请总结这篇文档"),
        Content.ofFile(URI.create("https://ompc.oss-cn-hangzhou.aliyuncs.com/share/P020210313315693279320.pdf"))
    )
    .build();
final var response = client.chat(request)
    .async()
    .join();

输出日志

2024-03-20 00:24:22 DEBUG dashscope://chat/qwen-plus => {"model":"qwen-plus","input":{"messages":[{"role":"user","content":[{"text":"请总结这篇文档"},{"file":"https://ompc.oss-cn-hangzhou.aliyuncs.com/share/P020210313315693279320.pdf"}]}]},"parameters":{"result_format":"message"}}
2024-03-20 00:24:47 DEBUG dashscope://chat/qwen-plus <= {"output":{"choices":[{"finish_reason":"stop","message":{"role":"assistant","content":"这篇文档是中国国民经济和社会发展第十四个五年规划和2035年远景目标纲要，它阐述了中国在新发展阶段的主要任务和战略目标。规划涵盖了多个领域，包括创新驱动发展、产业升级、市场体系建设、数字化发展、深化改革、乡村振兴、城镇化、区域协调发展、文化建设、绿色发展、对外开放、教育与健康、民生福祉、国家安全、国防和军队现代化、民主法治以及监督制度的完善。\n\n在创新驱动方面，强调了强化国家战略科技力量，提升企业创新能力，激发人才创新活力，并完善科技创新机制。在产业发展上，致力于制造业升级，发展战略性新兴产业，促进服务业繁荣，同时建设现代化基础设施体系。\n\n为了构建新发展格局，规划提出畅通国内大循环，促进国内外双循环，加快培育完整内需体系。数字化发展被放在重要位置，旨在打造数字经济新优势，加速数字社会建设，提升数字政府水平，并营造健康的数字环境。\n\n在深化改革方面，将激发各类市场主体活力，建设高标准市场体系，改革财税金融体制，提升政府经济治理能力。农业、农村发展和乡村振兴是关注焦点，包括提高农业质量和效益，实施乡村建设行动，以及城乡融合发展。\n\n此外，规划还强调优化区域经济布局，促进区域协调发展，发展社会主义先进文化，推动绿色发展，实行高水平对外开放，提升国民素质，增进民生福祉，加强国家安全和国防建设，以及加强民主法治和监督制度。\n\n最后，规划提出了一系列实施保障措施，包括加强党的领导，健全规划体系，完善实施机制，确保党中央重大决策的贯彻落实，激发全社会参与规划实施的积极性，并通过监测评估、政策保障和考核监督机制，确保规划目标的实现。整个规划为全面建设社会主义现代化国家描绘了蓝图，是全国各族人民共同遵循的行动纲领。"}}]},"usage":{"total_tokens":365,"output_tokens":361,"input_tokens":4},"request_id":"d1eb2274-35cc-97fb-b60a-570fab96ab0b"}

计算器插件

final var request = ChatRequest.newBuilder()
    .model(ChatModel.QWEN_PLUS)
    .plugins(ChatPlugin.CALCULATOR)
    .user("1+2*3-4/5=?")
    .build();
final var response = client.chat(request)
    .async()
    .join();

输出日志

2024-03-20 00:29:11 DEBUG dashscope://chat/qwen-plus => {"model":"qwen-plus","input":{"messages":[{"role":"user","content":"1+2*3-4/5=?"}]},"parameters":{"result_format":"message"}}
2024-03-20 00:29:15 DEBUG dashscope://chat/qwen-plus <= {"output":{"choices":[{"finish_reason":"stop","messages":[{"role":"assistant","plugin_call":{"name":"calculator","arguments":"{\"payload__input__text\": \"1+2*3-4/5\"}"},"content":""},{"role":"plugin","name":"calculator","content":"{\"equations\": [\"1 + 2 * 3 - 4 / 5\"], \"results\": [6.2]}","status":{"code":200,"name":"Success","message":"success"}},{"role":"assistant","content":"The result of the expression \\(1 + 2 \\times 3 - \\frac{4}{5}\\) is approximately 6.2."}]}]},"usage":{"total_tokens":103,"output_tokens":93,"input_tokens":10},"request_id":"3659340f-7dad-9815-bd11-ce6c6eb4d1c2"}

向量计算示例

文本向量计算

// 请求
final var request = EmbeddingRequest.newBuilder()
    .model(EmbeddingModel.TEXT_EMBEDDING_V2)
    .documents("我爱北京天安门", "天安门上太阳升")
    .build();

// 应答
final var response = client.embedding(request)
    .async()
    .join();

输出日志

2024-03-29 00:06:04 DEBUG dashscope://embedding/text-embedding-v2 => {"model":"text-embedding-v2","input":{"texts":["我爱北京天安门","天安门上太阳升"]},"parameters":{}}
2024-03-29 00:06:05 DEBUG dashscope://embedding/text-embedding-v2 <= 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多模态向量计算

// 请求
final var request = MmEmbeddingRequest.newBuilder()
    .model(MmEmbeddingModel.MM_EMBEDDING_ONE_PEACE_V1)
    .option(MmEmbeddingOptions.AUTO_TRUNCATION, true)
    .contents(
        FactorContent.ofAudio(URI.create("https://dashscope.oss-cn-beijing.aliyuncs.com/audios/2channel_16K.wav")),
        FactorContent.ofImage(URI.create("https://ompc-images.oss-cn-hangzhou.aliyuncs.com/image-002.jpeg")),
        FactorContent.ofText("一个帅哥在骑自行车念经"),
        FactorContent.ofText("有两个自行车")
    )
    .build();

// 应答
final var response = client.mmEmbedding(request)
    .async()
    .join();

输出日志

2024-03-29 00:07:26 DEBUG dashscope://embeddingx/multimodal-embedding-one-peace-v1 => {"model":"multimodal-embedding-one-peace-v1","input":{"contents":[{"factor":1.0,"audio":"https://dashscope.oss-cn-beijing.aliyuncs.com/audios/2channel_16K.wav"},{"image":"https://ompc-images.oss-cn-hangzhou.aliyuncs.com/image-002.jpeg","factor":1.0},{"factor":1.0,"text":"一个帅哥在骑自行车念经"},{"factor":1.0,"text":"有两个自行车"}]},"parameters":{"auto_truncation":true}}
2024-03-29 00:07:27 DEBUG dashscope://embeddingx/multimodal-embedding-one-peace-v1 <= 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五、参与贡献

如果你对DashScope4j感兴趣并希望为其做出贡献，请遵循以下步骤：

1. Fork本项目到你的GitHub账户。
2. 克隆项目到你的本地环境。
3. 创建一个新的分支用于你的修改。
4. 提交你的更改并通过Pull Request请求合并到主分支。

在提交Pull Request之前，请确保你的代码符合项目的编码规范和最佳实践，并且已经通过了相关的测试。

六、关于软件

版本号声明

软件版本号采用：大版本.小版本.漏洞修复的格式

• 大版本： 程序的架构设计进行重大升级或重大改造

• 小版本：

  1. 增加新的API功能
  2. 在现有架构下完成局部架构的微调

• 漏洞修复： 在不改变现有架构和API情况下，对漏洞修复和增强

写在最后

灵积是有官方的Java客户端的，我之所以还需要开发这个DashScope4j主要是基于以下几点考虑

1. 官方的SDK并不开源，你无法查看其源码，也无法自行修改和定制
2. 个人练手习惯，反正也不花我多少时间，嗯嗯

七、相关链接

• 模型服务-灵积
• 帮助文档-灵积