### Get Available Digital Human Information

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Requests a list of available digital humans, specifying pagination and custom type. This is typically the first step before composing a video.

```java
import com.mobvoi.openapi.model.video.GetManInfoRequest;

// 1. 获取可用的数字人列表
GetManInfoRequest manInfoRequest = GetManInfoRequest.builder()
    .current(1)                    // 页码
    .size(10)                      // 每页数量
    .customType("sys")             // 类型：sys（系统）/ self（定制）
    .speakerName(null)             // 按名称搜索（可选）
    .build();

String manInfoResult = videoClient.getManInfo(manInfoRequest);
System.out.println("数字人列表: " + manInfoResult);
```

--------------------------------

### Get Available Typeface List

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Fetches a list of available typefaces that can be used in video synthesis. This requires a TypefaceRequest object.

```java
import com.mobvoi.openapi.model.video.TypefaceRequest;

// 4. 获取可用字体列表
TypefaceRequest typefaceRequest = new TypefaceRequest();
String typefaceResult = videoClient.getTypeface(typefaceRequest);
System.out.println("字体列表: " + typefaceResult);
```

--------------------------------

### Initialize VideoClient for Digital Human Video Synthesis

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Creates an instance of VideoClient using application credentials. This client is used to interact with the digital human video synthesis service.

```java
import com.mobvoi.openapi.client.video.VideoClient;

// 创建视频客户端
VideoClient videoClient = new VideoClient("your_app_key", "your_app_secret");
```

--------------------------------

### Client Configuration

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Configure the SDK client with your application's credentials and connection settings.

```APIDOC
## Client Configuration

### Description

`ClientConfig` is used to configure client connection parameters, including authentication, timeouts, and retry policies. It supports the Builder pattern for chained calls.

### Method

```java
import com.mobvoi.openapi.client.ClientConfig;
import com.mobvoi.openapi.signature.Md5Signature;

// Basic configuration
ClientConfig config = ClientConfig.builder()
    .appKey("your_app_key")
    .appSecret("your_app_secret")
    .signature(Md5Signature.getInstance())
    .connectTimeout(10)      // Connection timeout (seconds), default 10 seconds
    .readTimeout(10)         // Read timeout (seconds), default 10 seconds
    .writeTimeout(10)        // Write timeout (seconds), default 10 seconds
    .pingInterval(0)         // WebSocket heartbeat interval (seconds)
    .retryOnConnectionFailure(true)  // Retry on connection failure
    .build();
```
```

--------------------------------

### Configure Client Settings

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Use the ClientConfig builder to set authentication credentials, timeouts, and connection policies.

```java
import com.mobvoi.openapi.client.ClientConfig;
import com.mobvoi.openapi.signature.Md5Signature;

// 基础配置
ClientConfig config = ClientConfig.builder()
    .appKey("your_app_key")
    .appSecret("your_app_secret")
    .signature(Md5Signature.getInstance())
    .connectTimeout(10)      // 连接超时（秒），默认10秒
    .readTimeout(10)         // 读取超时（秒），默认10秒
    .writeTimeout(10)        // 写入超时（秒），默认10秒
    .pingInterval(0)         // WebSocket心跳间隔（秒）
    .retryOnConnectionFailure(true)  // 连接失败是否重试
    .build();
```

--------------------------------

### Implement Real-time ASR with AsrSentenceClient

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Uses WebSocket for real-time audio streaming and recognition. Requires an app key and secret for client initialization.

```java
import com.mobvoi.openapi.client.asr.AsrSentenceClient;
import com.mobvoi.openapi.model.asr.AsrSentenceStartRequest;
import com.mobvoi.openapi.constant.AsrSentenceResultType;
import okhttp3.WebSocket;
import okhttp3.WebSocketListener;
import okhttp3.Response;
import java.io.File;

// 创建实时识别客户端
AsrSentenceClient sentenceClient = new AsrSentenceClient("your_app_key", "your_app_secret");

// 配置识别参数
AsrSentenceStartRequest request = AsrSentenceStartRequest.builder()
    .contentType("audio/x-wav;codec=pcm;bit=16;rate=16000")  // 音频格式配置
    .partial_result("enable")    // 启用中间结果（实时显示）
    .silence_detection("enable") // 启用静音检测
    .build();

// 创建WebSocket监听器
WebSocketListener listener = new WebSocketListener() {
    @Override
    public void onOpen(WebSocket webSocket, Response response) {
        System.out.println("WebSocket连接已建立");
    }

    @Override
    public void onMessage(WebSocket webSocket, String text) {
        System.out.println("收到消息: " + text);
        // 消息类型判断
        // AsrSentenceResultType.READY - 服务器就绪
        // AsrSentenceResultType.PARTIAL - 中间识别结果
        // AsrSentenceResultType.END - 语音结束，最终结果
        // AsrSentenceResultType.SILENCE - 检测到静音
        // AsrSentenceResultType.ERROR - 服务器错误
    }

    @Override
    public void onFailure(WebSocket webSocket, Throwable t, Response response) {
        System.err.println("连接失败: " + t.getMessage());
    }

    @Override
    public void onClosed(WebSocket webSocket, int code, String reason) {
        System.out.println("连接已关闭: " + reason);
    }
};

// 建立WebSocket连接
WebSocket webSocket = sentenceClient.connect(request, listener);

// 发送音频数据（文件方式）
sentenceClient.send(new File("/path/to/audio.pcm"));

// 发送结束信号（主动结束本轮交互，获取剩余结果）
sentenceClient.sendEndSignal();

// 或发送取消信号（取消本轮交互，不返回结果）
// sentenceClient.sendCancelSignal();

// 关闭WebSocket连接
sentenceClient.closeWebsocket();
```

--------------------------------

### Create and Use OneboxClient for Smart Search

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Initializes the OneboxClient with app credentials and constructs a search request for specific domains like restaurants. Ensure correct coordinates and API version are used.

```java
import com.mobvoi.openapi.client.onebox.OneboxClient;
import com.mobvoi.openapi.model.onebox.SearchRequest;

// 创建Onebox客户端
OneboxClient oneboxClient = new OneboxClient("your_app_key", "your_app_secret");

// 构建搜索请求
SearchRequest request = SearchRequest.builder()
    .query("附近有什么好吃的餐厅")                           // 查询语句
    .address("中国,北京市,北京市,海淀区,中关村,1号,39.9,116.3")  // 用户位置（百度坐标系）
    .output("lite")                                          // 输出模式，默认lite
    .version("43000")                                        // API版本
    .task("public.restaurant")                               // 指定domain（可选）
    .user_id("user_123")                                     // 用户ID
    .ignore_context(false)                                   // 是否忽略多轮上下文
    .debug(false)                                            // 是否显示调试信息
    .build();

// 执行搜索
String result = oneboxClient.search(request);
System.out.println("搜索结果: " + result);

// 支持的domain类型：
// - public.weather：天气查询
// - public.restaurant：餐厅搜索
// - public.music：音乐搜索
// - public.movie：电影搜索
// 等等...
```

--------------------------------

### Add Maven Dependency

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Include the SDK in your project by adding this dependency to your pom.xml file.

```xml
<dependency>
    <groupId>com.mobvoi</groupId>
    <artifactId>openapi-sdk-java</artifactId>
    <version>1.0.0</version>
</dependency>
```

--------------------------------

### Maven Dependency

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Add the Mobvoi Open API SDK for Java to your project using Maven.

```APIDOC
## Maven Dependency

### Description

Add the Mobvoi Open API SDK for Java to your project using Maven.

### Code

```xml
<dependency>
    <groupId>com.mobvoi</groupId>
    <artifactId>openapi-sdk-java</artifactId>
    <version>1.0.0</version>
</dependency>
```
```

--------------------------------

### Perform Short Audio Recognition

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Use AsrClient to process audio files up to 512KB in wav, mp3, or pcm formats.

```java
import com.mobvoi.openapi.client.asr.AsrClient;
import com.mobvoi.openapi.model.asr.AsrRequest;
import java.io.File;

// 创建ASR客户端
AsrClient asrClient = new AsrClient("your_app_key", "your_app_secret");

// 构建识别请求
AsrRequest request = AsrRequest.builder()
    .audioFile(new File("/path/to/audio.wav"))  // 音频文件，最大512KB
    .type("audio/x-wav")                         // 音频格式类型
    .user_id("user_123")                         // 用户ID（可选）
    .device_id("device_456")                     // 设备ID（可选）
    .build();

// 执行语音识别
String result = asrClient.asr(request);
System.out.println("识别结果: " + result);

// 返回示例：
// {"status":"OK","result":"今天天气怎么样"}
```

--------------------------------

### Compose Digital Human Video with Text-to-Speech

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Configures and initiates a digital human video synthesis task using text-to-speech. Specify TTS parameters, digital human ID, background, video resolution, and callback URL.

```java
import com.mobvoi.openapi.model.video.ComposeVideoRequest;
import com.mobvoi.openapi.model.video.Style;
import com.alibaba.fastjson2.JSONObject;

JSONObject ttsParam = new JSONObject();
ttsParam.put("text", "大家好，我是数字人主播，今天为大家带来最新资讯。");
ttsParam.put("speaker", "cissy_meet");
ttsParam.put("speed", 1.0);

Style style = new Style();
// 设置数字人位置和大小参数

ComposeVideoRequest composeRequest = ComposeVideoRequest.builder()
    .wetaSpeakerId(12345L)                              // 数字人ID
    .ttsParam(ttsParam)                                  // TTS参数（文本合成）
    // .audioUrl("https://example.com/audio.mp3")       // 或使用音频URL
    .videoName("新闻播报视频")                           // 视频名称
    .backUrl("https://example.com/background.jpg")      // 自定义背景
    .width(1080)                                        // 横向分辨率
    .height(1920)                                       // 纵向分辨率
    .fps(30)                                            // 帧率：15/20/25/30
    .bitRate("5M")                                      // 码率：1M-16M
    .videoFormat("mp4")                                 // 视频格式
    .resultType("video")                                // 合成类型
    .callbackUrl("https://your-domain.com/callback")    // 完成回调地址
    .style(style)                                       // 样式配置
    .build();

String composeResult = videoClient.composeVideo(composeRequest);
System.out.println("合成任务创建结果: " + composeResult);
```

--------------------------------

### Short Audio Recognition (ASR)

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Perform speech recognition on short audio files using the AsrClient.

```APIDOC
## Short Audio Recognition (ASR)

### Description

`AsrClient` is used for recognizing short audio files (max 512KB), supporting wav, mp3, and pcm formats. It is suitable for short command recognition scenarios.

### Method

```java
import com.mobvoi.openapi.client.asr.AsrClient;
import com.mobvoi.openapi.model.asr.AsrRequest;
import java.io.File;

// Create ASR client
AsrClient asrClient = new AsrClient("your_app_key", "your_app_secret");

// Build recognition request
AsrRequest request = AsrRequest.builder()
    .audioFile(new File("/path/to/audio.wav"))  // Audio file, max 512KB
    .type("audio/x-wav")                         // Audio format type
    .user_id("user_123")                         // User ID (optional)
    .device_id("device_456")                     // Device ID (optional)
    .build();

// Execute speech recognition
String result = asrClient.asr(request);
System.out.println("Recognition result: " + result);

// Example response:
// {"status":"OK","result":"今天天气怎么样"}
```
```

--------------------------------

### Analyze Natural Language with NlpClient

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Parses user queries to extract intent and slot information. Returns a JSON-formatted string result.

```java
import com.mobvoi.openapi.client.nlp.NlpClient;
import com.mobvoi.openapi.model.nlp.NlpRequest;

// 创建NLP客户端
NlpClient nlpClient = new NlpClient("your_app_key", "your_app_secret");

// 构建NLP请求
NlpRequest request = NlpRequest.builder()
    .query("明天北京的天气怎么样")    // 查询语句
    .context("public.weather")         // 强制指定意图域（可选）
    .build();

// 执行语义分析
String result = nlpClient.nlp(request);
System.out.println("语义分析结果: " + result);

// 返回示例：
// {
//   "status": "OK",
//   "domain": "public.weather",
//   "intent": "query_weather",
//   "slots": {
//     "location": "北京",
//     "date": "明天"
//   }
// }
```

--------------------------------

### Perform Text-to-Speech with TtsClient

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Converts text to audio and saves the output stream to a file. Supports various audio formats and voice parameters.

```java
import com.mobvoi.openapi.client.tts.TtsClient;
import com.mobvoi.openapi.model.tts.TtsRequest;
import okhttp3.Response;
import java.io.InputStream;
import java.io.FileOutputStream;

// 创建TTS客户端
TtsClient ttsClient = new TtsClient("your_app_key", "your_app_secret");

// 构建合成请求
TtsRequest request = TtsRequest.builder()
    .text("你好，欢迎使用出门问问语音合成服务")  // 要合成的文本，最大1000字符
    .speaker("cissy_meet")                          // 发音人，默认cissy_meet
    .audio_type("mp3")                              // 输出格式：mp3/pcm/speex-wb-10/wav
    .speed(1.0f)                                    // 语速：0.5-2.0
    .volume(1.0f)                                   // 音量：0.1-1.0
    .pitch(0f)                                      // 语调：-10到10
    .rate(16000L)                                   // 采样率：8000/16000/24000
    .gen_srt(false)                                 // 是否生成srt字幕文件
    .merge_symbol(true)                             // 粗粒度合成，更接近真人效果
    .ignore_limit(false)                            // 是否忽略字符数限制
    .build();

// 执行语音合成
Response response = ttsClient.tts(request);

// 获取音频流并保存到文件
if (response.isSuccessful() && response.body() != null) {
    try (InputStream inputStream = response.body().byteStream();
         FileOutputStream fos = new FileOutputStream("output.mp3")) {
        byte[] buffer = new byte[4096];
        int bytesRead;
        while ((bytesRead = inputStream.read(buffer)) != -1) {
            fos.write(buffer, 0, bytesRead);
        }
        System.out.println("音频文件已保存");
    }

    // 如果启用了gen_srt，可从响应头获取字幕文件地址
    String srtUrl = response.header("srt-address");
    if (srtUrl != null) {
        Response srtResponse = ttsClient.srt(srtUrl);
        // 处理字幕内容
    }
}
response.close();
```

--------------------------------

### Transcribe Long Audio Files

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Use AsrFileClient to create asynchronous transcription tasks for long audio files via URL and poll for results.

```java
import com.mobvoi.openapi.client.asr.AsrFileClient;
import com.mobvoi.openapi.model.asr.AsrFileCreateTaskRequest;
import com.mobvoi.openapi.model.asr.AsrFileGetTaskRequest;
import com.mobvoi.openapi.constant.AsrFileTaskStatus;
import java.util.Arrays;

// 创建文件转写客户端
AsrFileClient asrFileClient = new AsrFileClient("your_app_key", "your_app_secret");

// 创建转写任务
AsrFileCreateTaskRequest createRequest = AsrFileCreateTaskRequest.builder()
    .audio_url("https://example.com/audio/meeting.mp3")  // 音频文件URL（需公网可访问）
    .language("zh_cn")                                     // 语言：zh_cn（中文）
    .enable_punctuation(true)                             // 启用标点
    .filler_words(Arrays.asList("嗯", "啊", "呃"))        // 语气词过滤列表
    .callbackUrl("https://your-domain.com/callback")      // 完成后回调地址
    .build();

String taskResult = asrFileClient.createTask(createRequest);
System.out.println("任务创建结果: " + taskResult);
// 返回示例：{"code":200,"taskId":"task_123456"}

// 查询任务结果
AsrFileGetTaskRequest getRequest = new AsrFileGetTaskRequest();
getRequest.setAppkey("your_app_key");
// 设置任务ID等参数

String taskStatus = asrFileClient.getTask(getRequest);
System.out.println("任务状态: " + taskStatus);

// 任务状态枚举
// AsrFileTaskStatus.SUBMIT (1) - 提交中
// AsrFileTaskStatus.SUCCESS (2) - 成功
// AsrFileTaskStatus.FAIL (3) - 失败
```

--------------------------------

### Add Mobvoi OpenAPI Java SDK Dependency

Source: https://github.com/mobvoibackend/openapi-sdk-java/blob/main/README.md

Include this Maven dependency in your project to use the Mobvoi OpenAPI Java SDK. Replace '1.0.0' with the latest stable version.

```xml
<dependency>
    <groupId>com.mobvoi</groupId>
    <artifactId>openapi-sdk-java</artifactId>
    <!--请替换成最新稳定版本-->
    <version>1.0.0</version>
</dependency>
```

--------------------------------

### Long Audio File Transcription (ASR)

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Transcribe long audio files asynchronously using the AsrFileClient.

```APIDOC
## Long Audio File Transcription (ASR)

### Description

`AsrFileClient` is used for asynchronous transcription of long audio files. It works by creating a task and polling for results, supporting callback notifications.

### Method

```java
import com.mobvoi.openapi.client.asr.AsrFileClient;
import com.mobvoi.openapi.model.asr.AsrFileCreateTaskRequest;
import com.mobvoi.openapi.model.asr.AsrFileGetTaskRequest;
import com.mobvoi.openapi.constant.AsrFileTaskStatus;
import java.util.Arrays;

// Create file transcription client
AsrFileClient asrFileClient = new AsrFileClient("your_app_key", "your_app_secret");

// Create transcription task
AsrFileCreateTaskRequest createRequest = AsrFileCreateTaskRequest.builder()
    .audio_url("https://example.com/audio/meeting.mp3")  // Audio file URL (must be publicly accessible)
    .language("zh_cn")                                     // Language: zh_cn (Chinese)
    .enable_punctuation(true)                             // Enable punctuation
    .filler_words(Arrays.asList("嗯", "啊", "呃"))        // Filtered filler words list
    .callbackUrl("https://your-domain.com/callback")      // Callback URL upon completion
    .build();

String taskResult = asrFileClient.createTask(createRequest);
System.out.println("Task creation result: " + taskResult);
// Example response: {"code":200,"taskId":"task_123456"}

// Query task status
AsrFileGetTaskRequest getRequest = new AsrFileGetTaskRequest();
getRequest.setAppkey("your_app_key");
// Set task ID and other parameters

String taskStatus = asrFileClient.getTask(getRequest);
System.out.println("Task status: " + taskStatus);

// Task status enumeration:
// AsrFileTaskStatus.SUBMIT (1) - Submitting
// AsrFileTaskStatus.SUCCESS (2) - Success
// AsrFileTaskStatus.FAIL (3) - Failed
```
```

--------------------------------

### Query Digital Human Video Synthesis Status

Source: https://context7.com/mobvoibackend/openapi-sdk-java/llms.txt

Retrieves the status of a digital human video synthesis task. Requires a ComposeResultRequest object, typically containing the task ID.

```java
import com.mobvoi.openapi.model.video.ComposeResultRequest;

// 3. 查询合成结果
ComposeResultRequest resultRequest = new ComposeResultRequest();
// 设置任务ID等参数

String statusResult = videoClient.getComposeResult(resultRequest);
System.out.println("合成状态: " + statusResult);

// 合成状态枚举
// VideoComposeStatus.ING ("ing") - 处理中
// VideoComposeStatus.SUCCESS ("suc") - 成功
// VideoComposeStatus.FAIL ("fail") - 失败
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.