语音模式修改
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@@ -102,7 +102,7 @@ public class ChatWebSocketHandler {
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log.info("WebSocket session 链接已建立:{}", session.getId());
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cacheClientTts.put(clientId, new String());
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//初始化STT流式语音转换文本的socket链接
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createWhisperRealtimeSocket(session.getId());
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// createWhisperRealtimeSocket(session.getId());
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//是初次自我介绍后的问答环节
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cacheReplyFlag.put(session.getId(),"YES");
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//初始化面试回答数据记录
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@@ -129,22 +129,27 @@ public class ChatWebSocketHandler {
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public void onTextMessage(Session session, String message, @PathParam("clientId") String clientId) {
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System.out.println("接收到文本消息: " + message);
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try {
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// {
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// "type": "start | done | end",
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// "content": "内容"
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// }
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//处理文本结果
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if (StrUtil.isNotEmpty(message)) {
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Map<String, String> mapResult = JSONUtil.toBean(JSONUtil.parseObj(message), Map.class);
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String resultFlag = mapResult.get("msg");
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String resultFlag = mapResult.get("type");
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if ("done".equals(resultFlag)) {
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//开始合并语音流
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//发送消息
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WebSocket webSocket = cacheWebSocket.get(session.getId());
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if (webSocket != null) {
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webSocket.send("{\"type\": \"input_audio_buffer.commit\"}");
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webSocket.send("{\"type\": \"response.create\"}");
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}
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// WebSocket webSocket = cacheWebSocket.get(session.getId());
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// if (webSocket != null) {
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// webSocket.send("{\"type\": \"input_audio_buffer.commit\"}");
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// webSocket.send("{\"type\": \"response.create\"}");
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// }
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String startFlag = cacheReplyFlag.get(session.getId());
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//语音结束,开始进行回答解析
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log.info("开始文本处理,客户端ID为:{}",clientId);
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String cacheResultText = cacheClientTts.get(session.getId());
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// String cacheResultText = cacheClientTts.get(session.getId());
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String cacheResultText = mapResult.get("content");
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log.info("开始文本处理,面试者回答信息为:{}", cacheResultText);
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if (StrUtil.isEmpty(cacheResultText)) {
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cacheResultText = "I first check the forklift's logbook for recent issues, inspect tires and brakes, verify the load capacity matches today's task, and confirm my licence is current—all per SWMS requirements.";
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@@ -314,43 +319,43 @@ public class ChatWebSocketHandler {
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// 接收二进制消息(流数据)
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@OnMessage
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public void onBinaryMessage(Session session, @PathParam("clientId") String clientId, ByteBuffer byteBuffer) {
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log.info("客户端ID为:{}", clientId);
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// 处理二进制流数据
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byte[] bytes = new byte[byteBuffer.remaining()];
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//从缓冲区中读取数据并存储到指定的字节数组中
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byteBuffer.get(bytes);
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// 生成唯一文件名
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String fileName = clientId + "_" + System.currentTimeMillis() + ".wav";
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String pathUrl = RuoYiConfig.getProfile() + VOICE_STORAGE_DIR + fileName;
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log.info("文件路径为:{}", pathUrl);
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try {
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saveAsWebM(bytes, pathUrl);
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//接收到数据流后直接就进行SST处理
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//语音格式转换
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String fileOutName = clientId + "_" + System.currentTimeMillis() + ".pcm";
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String pathOutUrl = RuoYiConfig.getProfile() + VOICE_STORAGE_DIR + fileOutName;
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handleAudioToPCM(pathUrl, pathOutUrl);
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//发送消息
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WebSocket webSocket = cacheWebSocket.get(session.getId());
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log.info("获取的socket对象为:{}", webSocket);
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if (webSocket != null) {
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// 1. 启动音频缓冲
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// webSocket.send("{\"type\": \"input_audio_buffer.start\"}");
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File outputFile = new File(pathOutUrl); // 输出PCM格式文件
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ByteBuffer buffer = ByteBuffer.wrap(FileUtils.readFileToByteArray(outputFile));
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byte[] outBytes = new byte[buffer.remaining()];
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//从缓冲区中读取数据并存储到指定的字节数组中
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buffer.get(outBytes);
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String base64Audio = Base64.getEncoder().encodeToString(outBytes);
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String message = "{ \"type\": \"input_audio_buffer.append\", \"audio\": \"" + base64Audio + "\" }";
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webSocket.send(message);
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// 3. 提交音频并请求转录
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// webSocket.send("{\"type\": \"input_audio_buffer.commit\"}");
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// webSocket.send("{\"type\": \"response.create\"}");
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}
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} catch (Exception e) {
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e.printStackTrace();
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}
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// log.info("客户端ID为:{}", clientId);
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// // 处理二进制流数据
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// byte[] bytes = new byte[byteBuffer.remaining()];
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// //从缓冲区中读取数据并存储到指定的字节数组中
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// byteBuffer.get(bytes);
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// // 生成唯一文件名
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// String fileName = clientId + "_" + System.currentTimeMillis() + ".wav";
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// String pathUrl = RuoYiConfig.getProfile() + VOICE_STORAGE_DIR + fileName;
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// log.info("文件路径为:{}", pathUrl);
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// try {
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// saveAsWebM(bytes, pathUrl);
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// //接收到数据流后直接就进行SST处理
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// //语音格式转换
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// String fileOutName = clientId + "_" + System.currentTimeMillis() + ".pcm";
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// String pathOutUrl = RuoYiConfig.getProfile() + VOICE_STORAGE_DIR + fileOutName;
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// handleAudioToPCM(pathUrl, pathOutUrl);
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// //发送消息
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// WebSocket webSocket = cacheWebSocket.get(session.getId());
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// log.info("获取的socket对象为:{}", webSocket);
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// if (webSocket != null) {
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//// 1. 启动音频缓冲
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//// webSocket.send("{\"type\": \"input_audio_buffer.start\"}");
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// File outputFile = new File(pathOutUrl); // 输出PCM格式文件
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// ByteBuffer buffer = ByteBuffer.wrap(FileUtils.readFileToByteArray(outputFile));
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// byte[] outBytes = new byte[buffer.remaining()];
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// //从缓冲区中读取数据并存储到指定的字节数组中
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// buffer.get(outBytes);
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// String base64Audio = Base64.getEncoder().encodeToString(outBytes);
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// String message = "{ \"type\": \"input_audio_buffer.append\", \"audio\": \"" + base64Audio + "\" }";
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// webSocket.send(message);
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// // 3. 提交音频并请求转录
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//// webSocket.send("{\"type\": \"input_audio_buffer.commit\"}");
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//// webSocket.send("{\"type\": \"response.create\"}");
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// }
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// } catch (Exception e) {
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// e.printStackTrace();
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// }
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}
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@@ -167,7 +167,7 @@ whisper:
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chatGpt:
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apiKey: 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
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apiUrl: https://api.openai.com/v1/chat/completions
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model: ft:gpt-3.5-turbo-0125:vetti:construction-labourer-test:CTIvLD5n
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model: ft:gpt-3.5-turbo-0125:vetti:construction-labourer-test:CWKBNvE2
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role: system
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