diff --git a/vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketMultipleHandler.java b/vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketMultipleHandler.java
index 94d6f3d..8a18f48 100644
--- a/vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketMultipleHandler.java
+++ b/vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketMultipleHandler.java
@@ -194,7 +194,6 @@ public class ChatWebSocketMultipleHandler {
                             sendConnectionVoice(session);
                             //开始使用模型进行追问
                             //把提问的文字发送给GPT
-                            ChatGPTClient chatGPTClient = SpringUtils.getBean(ChatGPTClient.class);
                             log.info("AI提示词为:{}", promptJson);
                             log.info("开始请求AI:{}",System.currentTimeMillis()/1000);
                             chatGptStream(promptJson,session,clientId);
@@ -302,7 +301,7 @@ public class ChatWebSocketMultipleHandler {
 //        String resultFileName = clientId + "_" + System.currentTimeMillis() + ".wav";
 //        String resultPathUrl = RuoYiConfig.getProfile() + VOICE_STORAGE_RESULT_DIR + resultFileName;
         ElevenLabsStreamClient elevenLabsClient = SpringUtils.getBean(ElevenLabsStreamClient.class);
-        elevenLabsClient.handleTextToVoice(content,session);
+        elevenLabsClient.handleTextToVoice(content,session,"mp3_44100_128");
         //持续返回数据流给客户端
         log.info("发送语音流成功啦!!!!!!!");
 //        sendVoiceBuffer(resultPathUrl, session);
@@ -685,12 +684,12 @@ public class ChatWebSocketMultipleHandler {
     private void chatGptStream(String  promptJson,Session session,String clientId){
         //把提问的文字发送给CPT(流式处理)
         OpenAiStreamClient aiStreamClient = SpringUtils.getBean(OpenAiStreamClient.class);
-        log.info("AI提示词为:{}",promptJson);
+//        log.info("AI提示词为:{}",promptJson);
         aiStreamClient.streamChat(promptJson, new OpenAiStreamListenerService() {
             @Override
             public void onMessage(String content) {
                 log.info("返回AI结果：{}", content);
-                if(StrUtil.isNotEmpty(content)){
+                if(isValidString(content)){
                     String questionResult = cacheQuestionResult.get(session.getId());
                     if(StrUtil.isEmpty(questionResult)){
                         questionResult = content;
@@ -698,13 +697,9 @@ public class ChatWebSocketMultipleHandler {
                         questionResult = questionResult + content;
                     }
                     cacheQuestionResult.put(session.getId(),questionResult);
-                    sendTTSBuffer(clientId,content,session);
-                    //上面语音发送完成了,开始发送问题文本啦
+                    //先发送问题文本啦
                     // 实时输出内容
                     try{
-                        try {
-                            Thread.sleep(300);
-                        }catch (Exception e){}
                         //把文本也给前端返回去
                         Map<String,String> dataText = new HashMap<>();
                         dataText.put("type","question");
@@ -713,6 +708,8 @@ public class ChatWebSocketMultipleHandler {
                     }catch (Exception e){
                         e.printStackTrace();
                     }
+                    //开发发送语音啦
+                    sendTTSBuffer(clientId,content,session);
 
                 }
             }
@@ -738,6 +735,21 @@ public class ChatWebSocketMultipleHandler {
     }
 
 
+    /**
+     * 验证字符串：不能为空且必须包含英文字符
+     * @param input 待验证的字符串
+     * @return 如果满足条件返回true，否则返回false
+     */
+    public static boolean isValidString(String input) {
+        // 1. 检查字符串是否为空（包括null和空字符串）
+        if (StrUtil.isEmpty(input)) {
+            return false;
+        }
+        // 2. 检查是否包含至少一个英文字母（a-z, A-Z）
+        return input.matches(".*[a-zA-Z]+.*");
+    }
+
+
 
     /**
      * 发送语音流给前端
diff --git a/vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketMultiplePcmHandler.java b/vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketMultiplePcmHandler.java
new file mode 100644
index 0000000..d604ec1
--- /dev/null
+++ b/vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketMultiplePcmHandler.java
@@ -0,0 +1,782 @@
+package com.vetti.socket;
+
+import cn.hutool.core.date.DateUtil;
+import cn.hutool.core.util.ObjectUtil;
+import cn.hutool.core.util.StrUtil;
+import cn.hutool.json.JSONUtil;
+import com.vetti.common.ai.elevenLabs.ElevenLabsStreamClient;
+import com.vetti.common.ai.gpt.ChatGPTClient;
+import com.vetti.common.ai.gpt.OpenAiStreamClient;
+import com.vetti.common.ai.gpt.service.OpenAiStreamListenerService;
+import com.vetti.common.config.RuoYiConfig;
+import com.vetti.common.utils.spring.SpringUtils;
+import lombok.extern.slf4j.Slf4j;
+import org.apache.commons.io.FileUtils;
+import org.springframework.stereotype.Component;
+
+import javax.websocket.*;
+import javax.websocket.server.PathParam;
+import javax.websocket.server.ServerEndpoint;
+import java.io.File;
+import java.math.BigDecimal;
+import java.nio.ByteBuffer;
+import java.util.HashMap;
+import java.util.LinkedList;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.ConcurrentHashMap;
+
+/**
+ * 语音面试(多客户端) web处理器
+ */
+@Slf4j
+@ServerEndpoint("/voice-websocket/multiplePcm/{clientId}")
+@Component
+public class ChatWebSocketMultiplePcmHandler {
+
+    /**
+     * 缓存客户端流式解析的语音文本数据
+     */
+    private final Map<String, String> cacheClientTts = new ConcurrentHashMap<>();
+
+    /**
+     * 缓存客户端,标记是否是自我介绍后的初次问答
+     */
+    private final Map<String, String> cacheReplyFlag = new ConcurrentHashMap<>();
+
+    /**
+     * 缓存客户端,面试回答信息
+     */
+    private final Map<String, String> cacheMsgMapData = new ConcurrentHashMap<>();
+    /**
+     * 缓存客户端,面试回答信息
+     */
+    private final Map<String, String> cacheMsgMapData1 = new ConcurrentHashMap<>();
+    /**
+     * 缓存客户端,AI提问的问题结果信息
+     */
+    private final Map<String, String> cacheQuestionResult = new ConcurrentHashMap<>();
+
+    /**
+     * 缓存客户端,得分结果记录
+     */
+    private final Map<String, Map<String, Integer>> cacheScoreResult = new ConcurrentHashMap<>();
+
+    /**
+     * 缓存客户端,回答问题次数-回答5轮就自动停止当前问答,返回对应的评分
+     */
+    private final Map<String,Long> cacheQuestionNum = new ConcurrentHashMap<>();
+
+    // 语音文件保存目录
+    private static final String VOICE_STORAGE_DIR = "/voice_files/";
+
+    // 语音结果文件保存目录
+    private static final String VOICE_STORAGE_RESULT_DIR = "/voice_result_files/";
+
+    // 系统语音目录
+    private static final String VOICE_SYSTEM_DIR = "/system_files/";
+
+    public ChatWebSocketMultiplePcmHandler() {
+        // 初始化存储目录
+        File dir = new File(RuoYiConfig.getProfile() + VOICE_STORAGE_DIR);
+        if (!dir.exists()) {
+            dir.mkdirs();
+        }
+
+        File resultDir = new File(RuoYiConfig.getProfile() + VOICE_STORAGE_RESULT_DIR);
+        if (!resultDir.exists()) {
+            resultDir.mkdirs();
+        }
+    }
+
+    // 连接建立时调用
+    @OnOpen
+    public void onOpen(Session session, @PathParam("clientId") String clientId) {
+        log.info("WebSocket 链接已建立:{}", clientId);
+        log.info("WebSocket session 链接已建立:{}", session.getId());
+
+        //启动客户端,自动发送语音流
+//        AudioHub.addClient(session);
+//        System.out.println("Client connected: " + session.getId());
+
+        cacheClientTts.put(clientId, new String());
+        //是初次自我介绍后的问答环节
+        cacheReplyFlag.put(session.getId(), "YES");
+        //初始化面试回答数据记录
+        cacheMsgMapData.put(session.getId(), "");
+        //初始化面试回答数据记录
+        cacheMsgMapData1.put(session.getId(), "");
+        //初始化面试问题
+        cacheQuestionResult.put(session.getId(), "");
+        //初始化得分结果记录
+        Map<String, Integer> scoreResultData = new HashMap<>();
+        scoreResultData.put("0-1", 0);
+        scoreResultData.put("4-5", 0);
+        scoreResultData.put("2-3", 0);
+        scoreResultData.put("2-5", 0);
+        cacheScoreResult.put(session.getId(), scoreResultData);
+        //初始化问答次数
+        cacheQuestionNum.put(session.getId(), 0L);
+        //发送初始化面试官语音流
+        String openingPathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "opening.wav";
+        sendVoiceBuffer(openingPathUrl, session);
+    }
+
+    /**
+     * 接收文本消息
+     *
+     * @param session  客户端会话
+     * @param message  消息
+     *                 如:
+     *                 {
+     *                 "type": "start | done | end",
+     *                 "content": "内容"
+     *                 }
+     * @param clientId 用户ID
+     */
+    @OnMessage
+    public void onTextMessage(Session session, String message, @PathParam("clientId") String clientId) {
+        log.info("我是接收文本消息:{}", message);
+        try {
+            //处理文本结果
+            if (StrUtil.isNotEmpty(message)) {
+                Map<String, String> mapResult = JSONUtil.toBean(JSONUtil.parseObj(message), Map.class);
+                String resultFlag = mapResult.get("type");
+                if ("done".equals(resultFlag)) {
+                    //开始合并语音流
+                    String startFlag = cacheReplyFlag.get(session.getId());
+                    //语音结束,开始进行回答解析
+                    log.info("开始文本处理,客户端ID为:{}", clientId);
+                    String cacheResultText = mapResult.get("content");
+                    log.info("开始文本处理,面试者回答信息为:{}", cacheResultText);
+                    if (StrUtil.isEmpty(cacheResultText)) {
+                        cacheResultText = "";
+                    }
+                    //这是初次处理的逻辑
+                    if ("YES".equals(startFlag)) {
+                        //自我介绍
+                        //初始化-不走大模型-直接对候选人进行提问
+                        initializationQuestion(clientId,cacheResultText ,session);
+                        //发送完第一次消息后,直接删除标记,开始进行正常的面试问答流程
+                        cacheReplyFlag.put(session.getId(), "");
+                    } else {
+                        //开始根据面试者回答的问题,进行追问回答
+                        //获取面试者回答信息
+                        //获取缓存记录
+                        String promptJson = "";
+                        String msgMapData = cacheMsgMapData.get(session.getId());
+                        if (StrUtil.isNotEmpty(msgMapData)) {
+                            List<Map> list = JSONUtil.toList(msgMapData, Map.class);
+                            //获取最后一条数据记录
+                            Map<String, String> mapEntity = new HashMap<>();
+                            mapEntity.put("role", "user");
+                            mapEntity.put("content", cacheResultText);
+                            list.add(mapEntity);
+                            promptJson = JSONUtil.toJsonStr(list);
+                            cacheMsgMapData.put(session.getId(), promptJson);
+                        }
+                        //记录新的数据
+                        String msgMapData1 = cacheMsgMapData1.get(session.getId());
+                        if (StrUtil.isNotEmpty(msgMapData1)) {
+                            List<Map> list = JSONUtil.toList(msgMapData1, Map.class);
+                            //获取最后一条数据记录
+                            Map<String, String> mapEntity = list.get(list.size() - 1);
+                            //更新问题记录
+                            String content = mapEntity.get("content");
+                            mapEntity.put("content", StrUtil.format(content, cacheResultText));
+                            cacheMsgMapData1.put(session.getId(), JSONUtil.toJsonStr(list));
+                        }
+
+                        //验证是否结速
+                        Boolean isEndFlag = checkIsEnd(session);
+                        if(isEndFlag){
+                            //开始返回衔接语
+                            sendConnectionVoice(session);
+                            //开始使用模型进行追问
+                            //把提问的文字发送给GPT
+                            ChatGPTClient chatGPTClient = SpringUtils.getBean(ChatGPTClient.class);
+                            log.info("AI提示词为:{}", promptJson);
+                            log.info("开始请求AI:{}",System.currentTimeMillis()/1000);
+                            chatGptStream(promptJson,session,clientId);
+                            log.info("结束请求AI:{}",System.currentTimeMillis()/1000);
+                        }
+
+                    }
+                } else if ("end".equals(resultFlag)) {
+                    log.info("面试结束啦!!!!!");
+                    handleInterviewEnd(clientId,session,"");
+                }
+            }
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+    // 接收二进制消息（流数据）
+    @OnMessage
+    public void onBinaryMessage(Session session, @PathParam("clientId") String clientId, ByteBuffer byteBuffer) {
+        log.info("我是接受二进制流的-客户端ID为:{}", clientId);
+    }
+
+    // 连接关闭时调用
+    @OnClose
+    public void onClose(Session session, CloseReason reason) {
+        System.out.println("WebSocket连接已关闭: " + session.getId() + ", 原因: " + reason.getReasonPhrase());
+        //链接关闭,清空内存
+        //是初次自我介绍后的问答环节
+        cacheReplyFlag.put(session.getId(), "");
+        //初始化面试回答数据记录
+        cacheMsgMapData.put(session.getId(), "");
+        //初始化面试问题
+        cacheQuestionResult.put(session.getId(), "");
+
+        cacheScoreResult.put(session.getId(), null);
+    }
+
+    // 发生错误时调用
+    @OnError
+    public void onError(Session session, Throwable throwable) {
+        System.err.println("WebSocket发生错误: 页面关闭,链接断开了");
+        if(session != null) {
+            //是初次自我介绍后的问答环节
+            cacheReplyFlag.put(session.getId(), "");
+            //初始化面试回答数据记录
+            cacheMsgMapData.put(session.getId(), "");
+            //初始化面试问题
+            cacheQuestionResult.put(session.getId(), "");
+            cacheScoreResult.put(session.getId(), null);
+        }
+    }
+
+    /**
+     * File 转换成 ByteBuffer
+     *
+     * @param fileUrl 文件路径
+     * @return
+     */
+    private ByteBuffer convertFileToByteBuffer(String fileUrl) {
+        File file = new File(fileUrl);
+        try {
+            return ByteBuffer.wrap(FileUtils.readFileToByteArray(file));
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+        return null;
+    }
+
+    /**
+     * 发送语音流给前端
+     *
+     * @param pathUrl 语音文件地址
+     * @param session 客户端会话
+     */
+    private void sendVoiceBuffer(String pathUrl, Session session) {
+        try {
+            //文件转换成文件流
+            ByteBuffer outByteBuffer = convertFileToByteBuffer(pathUrl);
+            //发送文件流数据
+            session.getBasicRemote().sendBinary(outByteBuffer);
+            try {
+                Thread.sleep(200);
+            }catch (Exception e){}
+            //提示已经结束
+            Map<String,String> dataText = new HashMap<>();
+            dataText.put("type","voiceEnd");
+            dataText.put("content","");
+            session.getBasicRemote().sendText(JSONUtil.toJsonStr(dataText));
+            // 发送响应确认
+            log.info("已经成功发送了语音流给前端:{}", DateUtil.now());
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+    /**
+     * 发送文本转语音,发送语音流给前端
+     *
+     * @param clientId 用户ID
+     * @param content  文本内容
+     * @param session  客户端会话ID
+     */
+    private void sendTTSBuffer(String clientId, String content, Session session) {
+//        String resultFileName = clientId + "_" + System.currentTimeMillis() + ".wav";
+//        String resultPathUrl = RuoYiConfig.getProfile() + VOICE_STORAGE_RESULT_DIR + resultFileName;
+        ElevenLabsStreamClient elevenLabsClient = SpringUtils.getBean(ElevenLabsStreamClient.class);
+        elevenLabsClient.handleTextToVoice(content,session,"pcm_24000");
+        //持续返回数据流给客户端
+        log.info("发送语音流成功啦!!!!!!!");
+//        sendVoiceBuffer(resultPathUrl, session);
+    }
+
+    /**
+     * 对候选者初次进行提问业务逻辑处理(初始化系统随机获取第一个问题)
+     *
+     * @param clientId 用户ID
+     * @param session  客户端会话
+     */
+    private void initializationQuestion(String clientId,String cacheResultText,Session session) {
+        try {
+            log.info("开始获取到clientid :{}",clientId);
+            //自我介绍结束后马上返回一个Good
+            //发送初始化面试官语音流
+            sendConnectionVoice(session);
+            //初始化面试流程的提问
+            //先记录这个问题
+            List<Map<String, String>> list = new LinkedList();
+            Map<String, String> mapEntity = new HashMap<>();
+            mapEntity.put("role", "system");
+            mapEntity.put("content", "You're Sarah, a senior HR interviewer in Sydney (15 years experience). You make candidates comfortable while getting insights.\n" +
+                    "\n" +
+                    "Style: Chat like having coffee with a mate—warm, genuine, curious. React naturally: \"Oh nice one!\" \"Good on you, mate.\" When they're stuck, ease pressure like a friend would.\n" +
+                    "\n" +
+                    "Australian English:\n" +
+                    "Start: \"Cheers for that,\" \"Thanks mate,\" \"Righto\"\n" +
+                    "Encourage: \"Good on you,\" \"Nice one\"\n" +
+                    "Casual: \"No worries,\" \"All good\"\n" +
+                    "Transition: \"Right, so...\" \"Okay, cool...\"\n" +
+                    "\n" +
+                    "Opening:\n" +
+                    "\"G'day! Thanks for coming in. Look, no need to be nervous—this is just a casual chat, yeah? I want to hear about your real experiences. We'll talk about [safety, technical skills, problem-solving]. Sound good? Let's get into it.\"\n" +
+                    "\n" +
+                    "Brief Answer → Need Story:\n" +
+                    "Think: \"They gave me the headline, now I need the story.\"\n" +
+                    "Say: \"Cheers for that. So tell me more—walk me through a specific time. What was going on, what did you actually do, how'd it turn out?\"\n" +
+                    "\n" +
+                    "Detailed STAR Answer → Acknowledge & Move On:\n" +
+                    "Think: \"Perfect! They've given me everything. Don't over-probe.\"\n" +
+                    "Say: \"Thanks mate, appreciate that. Good on you for [action]. Right, so let's chat about [new topic].\"\n" +
+                    "\n" +
+                    "Stuck/Nervous → Ease Pressure:\n" +
+                    "Think: \"They're feeling the pressure. Take it down a notch.\"\n" +
+                    "Say: \"No worries, mate. Take your time, yeah? Even a small example works—doesn't have to be anything massive. Want me to ask it differently?\"\n" +
+                    "\n" +
+                    "Off-Topic → Gentle Redirect:\n" +
+                    "Think: \"They're talking about something else. Gently bring them back.\"\n" +
+                    "Say: \"Yeah, thanks for sharing that. That's interesting. But let me bring us back to [question]—could you tell me about [specific thing]?\"\n" +
+                    "\n" +
+                    "Assess:\n" +
+                    "- Specific examples? (not \"I always do X\")\n" +
+                    "- STAR? (Situation, Task, Action, Result)\n" +
+                    "- Good judgment? (especially safety)\n" +
+                    "- Clear communication?\n" +
+                    "\n" +
+                    "Flow:\n" +
+                    "- Cover 5-7 areas: safety, technical, problem-solving, communication, teamwork\n" +
+                    "- 1-2 questions per area\n" +
+                    "- Keep moving, don't over-probe\n" +
+                    "- 15-20 minutes\n" +
+                    "\n" +
+                    "Closing:\n" +
+                    "\"Righto, thanks for sharing all that. That gives me a good sense of your experience. Any questions for me?\"\n" +
+                    "\n" +
+                    "Rules:\n" +
+                    "- No protected characteristics (age, gender, race, religion)\n" +
+                    "- Base on what they say\n" +
+                    "- Talk like a real person, not a robot\n" +
+                    "- One question at a time\n" +
+                    "- If they give gold, acknowledge and move on\n" +
+                    "\n" +
+                    "Remember: Conversation, not interrogation. Be genuinely interested, react naturally, help them show their best self.");
+            list.add(mapEntity);
+
+            //记录另外一个评分的提示词
+            List<Map<String, String>> list1 = new LinkedList();
+            Map<String, String> mapEntity1 = new HashMap<>();
+            mapEntity1.put("role", "system");
+            mapEntity1.put("content", "You are a construction industry interview expert. Evaluate candidate responses and provide scores (1-5) and follow-up questions when needed. Always respond in JSON format.");
+            list1.add(mapEntity1);
+
+            //不用预设问题了,直接通过大模型返回问题
+            //1、先推送一个自我介绍
+            Map<String, String> mapEntityJs = new HashMap<>();
+            mapEntityJs.put("role", "user");
+            mapEntityJs.put("content", cacheResultText);
+            list.add(mapEntityJs);
+
+            //初始化记录提示词数据到-缓存中
+            cacheMsgMapData.put(session.getId(), JSONUtil.toJsonStr(list));
+            cacheMsgMapData1.put(session.getId(), JSONUtil.toJsonStr(list1));
+
+            //2、推送大模型
+            String promptJson = JSONUtil.toJsonStr(list);
+            log.info("AI提示词为:{}", promptJson);
+            log.info("开始请求AI:{}",System.currentTimeMillis()/1000);
+            //大模型问答流式输出
+            //把提问的文字发送给CPT(流式处理)
+            chatGptStream(promptJson,session,clientId);
+            log.info("结束请求AI:{}",System.currentTimeMillis()/1000);
+        } catch (Exception e) {
+            e.printStackTrace();
+            log.error("面试流程初始化失败:{}", e.getMessage());
+        }
+    }
+
+    /**
+     * 处理面试结束业务逻辑
+     *
+     * @param session 客户端会话
+     * @param position 职位
+     */
+    private void handleInterviewEnd(String clientId,Session session,String position) {
+        //暂时的业务逻辑
+        //发送面试官结束语音流
+        String openingPathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "end.wav";
+        sendVoiceBuffer(openingPathUrl, session);
+        //返回文本评分
+        //处理模型提问逻辑
+        //获取缓存记录
+        String msgMapData = cacheMsgMapData1.get(session.getId());
+        String promptJson = "";
+        if (StrUtil.isNotEmpty(msgMapData)) {
+            List<Map> list = JSONUtil.toList(msgMapData, Map.class);
+            //获取第一条数据记录
+            Map<String, String> mapEntity = list.get(0);
+            //更新问题记录
+            mapEntity.put("role", "system");
+            mapEntity.put("content", "You are a construction industry interview expert. Evaluate candidate responses and provide scores (1-5) and follow-up questions when needed. Always respond in JSON format.");
+            //每个回答的内容前面要加上候选人的职位
+            if (StrUtil.isNotEmpty(position)) {
+                for (Map map : list) {
+                    if ("user".equals(map.get("role").toString())) {
+                        map.put("content", "Position: " + position + "\\n" + map.get("content"));
+                    }
+                }
+            }
+            //未回答的时候,答案初始化
+            for(Map entity : list){
+                Object content = entity.get("content");
+                if(ObjectUtil.isNotEmpty(content)){
+                    if(content.toString().contains("Candidate Answer：{}")){
+                        entity.put("content", StrUtil.format(content.toString(), "unanswered"));
+                    }
+                }
+            }
+            promptJson = JSONUtil.toJsonStr(list);
+            //结束回答要清空问答数据
+            cacheMsgMapData1.put(session.getId(), "");
+        }
+        log.info("结束AI提示词为:{}", promptJson);
+        ChatGPTClient gptClient = SpringUtils.getBean(ChatGPTClient.class);
+        String resultMsg = gptClient.handleAiChat(promptJson, "PF");
+        log.info("返回的结果为:{}",resultMsg);
+        //开始解析返回结果
+        Map mapResultData = JSONUtil.toBean(resultMsg,Map.class);
+        //获取评分
+        Object scoreStr = mapResultData.get("score");
+        Object assessment = mapResultData.get("assessment");
+
+        Map<String, String> resultEntity = new HashMap<>();
+        resultEntity.put("content", scoreStr +"\n"+assessment);
+        resultEntity.put("type", "score");
+        try{
+            //返回最终的评分结构
+            log.info("返回最终的评分结构:{}",JSONUtil.toJsonStr(resultEntity));
+            session.getBasicRemote().sendText(JSONUtil.toJsonStr(resultEntity));
+        }catch (Exception e){
+            e.printStackTrace();
+        }
+    }
+
+    /**
+     * 处理评分记录
+     * 触发规则:
+     * 1、获得 0-1 分 大于1次  立即结束面试
+     * 2、获取 4-5 分 大于3次  立即结束面试
+     * 3、获取 2-3 分 大于3次  立即结束面试
+     * 4、获取 2-5 分 大于4次  立即结束面试
+     *
+     * @param content
+     * @param session return false 立即结束面试
+     */
+    private Boolean handleScoreRecord(Object content, Session session) {
+        Map<String, Integer> scoreRecordMap = cacheScoreResult.get(session.getId());
+        log.info("获取评分结果:{}",content);
+        //对评分进行处理
+        if (ObjectUtil.isNotEmpty(content)) {
+            String[] strs = content.toString().split("/");
+            //取第一个数就是对应的评分
+            log.info("获取的数据为:{}",strs[0]);
+            BigDecimal score = new BigDecimal(strs[0].trim());
+            //记录Key为1
+            if (BigDecimal.ZERO.compareTo(score) <= 0 && BigDecimal.ONE.compareTo(score) >= 0) {
+                Integer n1 = scoreRecordMap.get("0-1") + 1;
+                scoreRecordMap.put("0-1", n1);
+                if (n1 > 1) {
+                    return false;
+                }
+            }
+            //记录Key为2
+            if (new BigDecimal(4).compareTo(score) <= 0 && new BigDecimal(5).compareTo(score) >= 0) {
+                Integer n1 = scoreRecordMap.get("4-5") + 1;
+                scoreRecordMap.put("4-5", n1);
+                if (n1 > 3) {
+                    return false;
+                }
+            }
+            //记录Key为3
+            if (new BigDecimal(2).compareTo(score) <= 0 && new BigDecimal(3).compareTo(score) >= 0) {
+                Integer n1 = scoreRecordMap.get("2-3") + 1;
+                scoreRecordMap.put("2-3", n1);
+                if (n1 > 3) {
+                    return false;
+                }
+            }
+            //记录Key为4
+            if (new BigDecimal(2).compareTo(score) <= 0 && new BigDecimal(5).compareTo(score) >= 0) {
+                Integer n1 = scoreRecordMap.get("2-5") + 1;
+                scoreRecordMap.put("2-5", n1);
+                if (n1 > 4) {
+                    return false;
+                }
+            }
+        }
+        return true;
+    }
+
+    /**
+     * 校验是否结束面试,结束后直接返回评分
+     *
+     * @param resultMsg 问答AI返回的结果数据
+     * @param session    客户端会话
+     */
+    private Boolean getInterviewScore(String resultMsg, Session session) {
+        //返回文本评分
+        //开始解析返回结果
+        Map mapResultData = JSONUtil.toBean(resultMsg,Map.class);
+        //获取评分
+        Object scoreStr = mapResultData.get("score");
+        Object assessment = mapResultData.get("assessment");
+        //校验面试是否结束
+        Boolean flag = handleScoreRecord(scoreStr, session);
+        try {
+            if (!flag) {
+                //发送面试官结束语音流
+                String openingPathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "end.wav";
+                sendVoiceBuffer(openingPathUrl, session);
+
+                Map<String, String> resultEntity = new HashMap<>();
+                resultEntity.put("content", scoreStr +"\n"+assessment);
+                resultEntity.put("type", "score");
+                //返回评分结果
+                log.info("返回最终的评分结果:{}",JSONUtil.toJsonStr(resultEntity));
+                session.getBasicRemote().sendText(JSONUtil.toJsonStr(resultEntity));
+
+            }
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+        return flag;
+    }
+
+    /**
+     * 记录问题
+     * @param questionResult
+     * @param session
+     */
+    private void recordQuestion(String questionResult,Session session) {
+        if (StrUtil.isNotEmpty(questionResult)) {
+            //评分获取缓存记录
+            String msgMapData1 = cacheMsgMapData1.get(session.getId());
+            if (StrUtil.isNotEmpty(msgMapData1)) {
+                List<Map> list = JSONUtil.toList(msgMapData1, Map.class);
+                Map<String, String> mapEntity = new HashMap<>();
+                mapEntity.put("role", "user");
+                mapEntity.put("content", "Question：" + questionResult + "\\nCandidate Answer：{}");
+                list.add(mapEntity);
+                cacheMsgMapData1.put(session.getId(), JSONUtil.toJsonStr(list));
+            }
+           //正常问题记录
+            String msgMapData = cacheMsgMapData.get(session.getId());
+            if (StrUtil.isNotEmpty(msgMapData)) {
+                List<Map> list = JSONUtil.toList(msgMapData, Map.class);
+                Map<String, String> mapEntity = new HashMap<>();
+                mapEntity.put("role", "assistant");
+                mapEntity.put("content", questionResult);
+                list.add(mapEntity);
+                cacheMsgMapData.put(session.getId(), JSONUtil.toJsonStr(list));
+            }
+        }
+    }
+
+    /**
+     * 验证面试是否结束,不继续追问了
+     * @param resultMsg
+     * @param session
+     * @return
+     */
+    private Boolean checkInterviewIsEnd(String resultMsg, Session session){
+        Map mapResultData = JSONUtil.toBean(resultMsg,Map.class);
+        //获取评分
+        Object scoreStr = mapResultData.get("score");
+        Object assessment = mapResultData.get("assessment");
+        Object followUpNeeded = mapResultData.get("follow_up_needed");
+        Boolean flag = Boolean.valueOf(followUpNeeded.toString());
+        try {
+            //不继续追问了
+            if (ObjectUtil.isNotEmpty(followUpNeeded) && !flag) {
+                //发送面试官结束语音流
+                String openingPathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "end.wav";
+                sendVoiceBuffer(openingPathUrl, session);
+
+                Map<String, String> resultEntity = new HashMap<>();
+                resultEntity.put("content", scoreStr +"\n"+assessment);
+                resultEntity.put("type", "score");
+                //返回评分结果
+                log.info("返回最终的评分结果:{}",JSONUtil.toJsonStr(resultEntity));
+                session.getBasicRemote().sendText(JSONUtil.toJsonStr(resultEntity));
+            }
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+        return flag;
+    }
+
+
+    /**
+     * 验证面试是否结束
+     * @param session
+     * @return
+     */
+    private Boolean checkIsEnd(Session session){
+        Long replyNums = cacheQuestionNum.get(session.getId());
+        //回答次数大于等于5就直接结束面试
+        Boolean flag  = true;
+        if(replyNums >= 5){
+            //获取问答评分记录
+            String promptJson = cacheMsgMapData1.get(session.getId());
+            //根据模型获取评分
+            ChatGPTClient chatGPTClient = SpringUtils.getBean(ChatGPTClient.class);
+            String resultMsg = chatGPTClient.handleAiChat(promptJson,"PF");
+            if(StrUtil.isNotEmpty(resultMsg)) {
+                //直接返回问题了
+                //开始解析返回结果
+                Map mapResultData = JSONUtil.toBean(resultMsg, Map.class);
+                //获取评分
+                Object scoreStr = mapResultData.get("score");
+                Object assessment = mapResultData.get("assessment");
+                //发送面试官结束语音流
+                String openingPathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "end.wav";
+                sendVoiceBuffer(openingPathUrl, session);
+
+                Map<String, String> resultEntity = new HashMap<>();
+                resultEntity.put("content", scoreStr +"\n"+assessment);
+                resultEntity.put("type", "score");
+                //返回评分结果
+                try {
+                    log.info("返回最终的评分结果:{}",JSONUtil.toJsonStr(resultEntity));
+                    session.getBasicRemote().sendText(JSONUtil.toJsonStr(resultEntity));
+                }catch (Exception e) {
+                    e.printStackTrace();
+                }
+            }
+            flag = false;
+        }else{
+            cacheQuestionNum.put(session.getId(), replyNums+1);
+        }
+        return flag;
+    }
+
+    /**
+     * 大模型流式追问
+     * @param promptJson
+     * @param session
+     * @param clientId
+     */
+    private void chatGptStream(String  promptJson,Session session,String clientId){
+        //把提问的文字发送给CPT(流式处理)
+        OpenAiStreamClient aiStreamClient = SpringUtils.getBean(OpenAiStreamClient.class);
+        log.info("AI提示词为:{}",promptJson);
+        aiStreamClient.streamChat(promptJson, new OpenAiStreamListenerService() {
+            @Override
+            public void onMessage(String content) {
+                log.info("返回AI结果：{}", content);
+                if(StrUtil.isNotEmpty(content)){
+                    String questionResult = cacheQuestionResult.get(session.getId());
+                    if(StrUtil.isEmpty(questionResult)){
+                        questionResult = content;
+                    }else{
+                        questionResult = questionResult + content;
+                    }
+                    cacheQuestionResult.put(session.getId(),questionResult);
+                    sendTTSBuffer(clientId,content,session);
+                    //上面语音发送完成了,开始发送问题文本啦
+                    // 实时输出内容
+                    try{
+                        try {
+                            Thread.sleep(300);
+                        }catch (Exception e){}
+                        //把文本也给前端返回去
+                        Map<String,String> dataText = new HashMap<>();
+                        dataText.put("type","question");
+                        dataText.put("content",content);
+                        session.getBasicRemote().sendText(JSONUtil.toJsonStr(dataText));
+                    }catch (Exception e){
+                        e.printStackTrace();
+                    }
+
+                }
+            }
+
+            @Override
+            public void onComplete() {
+                try {
+                    //开始往缓存中记录提问的问题
+                    String questionResult = cacheQuestionResult.get(session.getId());
+                    //开始对问题进行缓存
+                    recordQuestion(questionResult,session);
+                    //清空问题
+                    cacheQuestionResult.put(session.getId(),"");
+                } catch (Exception e) {
+                    throw new RuntimeException(e);
+                }
+            }
+            @Override
+            public void onError(Throwable throwable) {
+                throwable.printStackTrace();
+            }
+        });
+    }
+
+
+
+    /**
+     * 发送语音流给前端
+     *
+     * @param session 客户端会话
+     */
+    private void sendConnectionVoice(Session session) {
+//        try {
+//            int resultNum = (int) (Math.random() * 5);
+//            String pathUrl = "";
+//            String resultText = "";
+//            if(resultNum == 0){
+//                pathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "rightgot.wav";
+//                resultText = "Right , got it";
+//            }else if(resultNum == 1){
+//                pathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "yeah.wav";
+//                resultText = "Yeah , Good";
+//            }else if(resultNum == 2){
+//                pathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "gotit.wav";
+//                resultText = "Got it, yeah";
+//            }else if(resultNum == 3){
+//                pathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "right.wav";
+//                resultText = "Right , understood";
+//            }else{
+//                pathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "ok.wav";
+//                resultText = "Yeah… ok…";
+//            }
+//            sendVoiceBuffer(pathUrl,session);
+//            //发送衔接语文本
+//            Map<String, String> dataText = new HashMap<>();
+//            dataText.put("type", "question");
+//            dataText.put("content", resultText);
+//            session.getBasicRemote().sendText(JSONUtil.toJsonStr(dataText));
+//            // 发送响应确认
+//            log.info("已经成功发送了语音流给前端:{}", DateUtil.now());
+//        } catch (Exception e) {
+//            e.printStackTrace();
+//        }
+    }
+
+
+}
diff --git a/vetti-common/src/main/java/com/vetti/common/ai/elevenLabs/ElevenLabsStreamClient.java b/vetti-common/src/main/java/com/vetti/common/ai/elevenLabs/ElevenLabsStreamClient.java
index 1ba4790..a4c13b4 100644
--- a/vetti-common/src/main/java/com/vetti/common/ai/elevenLabs/ElevenLabsStreamClient.java
+++ b/vetti-common/src/main/java/com/vetti/common/ai/elevenLabs/ElevenLabsStreamClient.java
@@ -19,10 +19,7 @@ import org.springframework.beans.factory.annotation.Value;
 import org.springframework.stereotype.Component;
 
 import javax.websocket.Session;
-import java.io.ByteArrayInputStream;
-import java.io.FileOutputStream;
-import java.io.IOException;
-import java.io.InputStream;
+import java.io.*;
 import java.nio.ByteBuffer;
 import java.util.HashMap;
 import java.util.Map;
@@ -51,8 +48,8 @@ public class ElevenLabsStreamClient {
      * @param voiceId        语音ID (可从ElevenLabs网站获取)
      * @throws IOException 网络请求或文件操作异常
      */
-    private void textToSpeech(String text, String voiceId, CloseableHttpClient httpClient, Session session) throws IOException {
-        HttpPost httpPost = new HttpPost(BASE_URL + "/text-to-speech/" + voiceId+"/stream?output_format=mp3_24000_48&optimize_streaming_latency=2");
+    private void textToSpeech(String text, String voiceId, CloseableHttpClient httpClient, Session session,String outputFormat) throws IOException {
+        HttpPost httpPost = new HttpPost(BASE_URL + "/text-to-speech/" + voiceId+"/stream?output_format="+outputFormat);
         httpPost.setHeader("xi-api-key", apiKey);
         httpPost.setHeader("Content-Type", "application/json");
 
@@ -67,25 +64,48 @@ public class ElevenLabsStreamClient {
             HttpEntity responseEntity = response.getEntity();
             if (responseEntity != null) {
                 try (InputStream inputStream = responseEntity.getContent();) {
-//                    byte[] allData = inputStream.readAllBytes();
-//                    InputStream stableStream = new ByteArrayInputStream(allData);
-//                    sendAudioStream(session,stableStream);
+                    //用来合并零散的碎片
+                    ByteArrayOutputStream smallChunkBuffer = new ByteArrayOutputStream();  //
                     byte[] buffer = new byte[4096];
                     int bytesRead;
+                    int n = 0;
                     while ((bytesRead = inputStream.read(buffer)) != -1) {
-                        ByteBuffer byteBuffer = ByteBuffer.wrap(buffer, 0, bytesRead);
-//                        log.info("字符流的长度大小:{}", bytesRead);
-                        if(bytesRead != 1 && bytesRead != 2){
-                            session.getAsyncRemote().sendBinary(byteBuffer);
+                        //语音流合并到2KB左右进行发送
+                        if(smallChunkBuffer.size() >= 3072){
+                            log.info("语音流大于"+smallChunkBuffer.size()+"啦,发送完成!!!");
+                            byte[] merged = smallChunkBuffer.toByteArray();
+                            smallChunkBuffer.reset();
+                            session.getAsyncRemote().sendBinary(ByteBuffer.wrap(merged));
                             try {
-                                Thread.sleep(20);
+                                Thread.sleep(50);
                             }catch (Exception e){}
-//                            log.info("正常语音发送出去语音流啦!!!");
                         }
+                        //发送三次告诉前端要合成一次语音
+//                        if(n == 2){
+//                            Map<String,String> dataText = new HashMap<>();
+//                            dataText.put("type","voiceMiddleEnd");
+//                            dataText.put("content","");
+//                            session.getBasicRemote().sendText(JSONUtil.toJsonStr(dataText));
+//                            //重置一下
+//                            n = 0;
+//                        }
+                        // 零散的碎片 → 加入缓冲区，不立即发送
+                        smallChunkBuffer.write(buffer, 0, bytesRead);
+                        n++;
+                    }
+                    //都加完缓冲区,最最后一次发送
+                    if(smallChunkBuffer.size() > 2){
+                        log.info("最后一次发送,语音流大于"+smallChunkBuffer.size()+"啦,发送完成!!!");
+                        byte[] merged = smallChunkBuffer.toByteArray();
+                        smallChunkBuffer.reset();
+                        session.getAsyncRemote().sendBinary(ByteBuffer.wrap(merged));
+                        try {
+                            Thread.sleep(50);
+                        }catch (Exception e){}
                     }
                     //返回结束点
                     try {
-                        Thread.sleep(100);
+                        Thread.sleep(50);
                     }catch (Exception e){}
                     Map<String,String> dataText = new HashMap<>();
                     dataText.put("type","voiceEnd");
@@ -120,13 +140,13 @@ public class ElevenLabsStreamClient {
      * @param inputText
      * @return
      */
-    public void handleTextToVoice(String inputText,Session session){
+    public void handleTextToVoice(String inputText,Session session,String outputFormat){
         CloseableHttpClient httpClient = HttpClients.createDefault();
         try {
             // 使用第一个可用语音进行文本转语音(澳洲本地女声)
 //            String firstVoiceId = "56bWURjYFHyYyVf490Dp";
             String firstVoiceId = "56bWURjYFHyYyVf490Dp";
-            textToSpeech(inputText, firstVoiceId,httpClient,session);
+            textToSpeech(inputText, firstVoiceId,httpClient,session,outputFormat);
         } catch (IOException e) {
             e.printStackTrace();
         } finally {
diff --git a/vetti-framework/src/main/java/com/vetti/framework/config/SecurityConfig.java b/vetti-framework/src/main/java/com/vetti/framework/config/SecurityConfig.java
index 1dfae5c..0686670 100644
--- a/vetti-framework/src/main/java/com/vetti/framework/config/SecurityConfig.java
+++ b/vetti-framework/src/main/java/com/vetti/framework/config/SecurityConfig.java
@@ -113,7 +113,7 @@ public class SecurityConfig
                 permitAllUrl.getUrls().forEach(url -> requests.antMatchers(url).permitAll());
                 // 对于登录login 注册register 验证码captchaImage 允许匿名访问
                 requests.antMatchers("/login", "/register", "/captchaImage","/aiCommon/**","/voice-websocket/multiple/**",
-                                "/voice-websocket/**","/voice-websocket-opus/**","/verification/email/send","/verification/email/verify","/verification/phone/send",
+                                "/voice-websocket/**","/voice-websocket/multiplePcm/**","/verification/email/send","/verification/email/verify","/verification/phone/send",
                                 "/forgotPassword").permitAll()
                     // 静态资源，可匿名访问
                     .antMatchers(HttpMethod.GET, "/", "/*.html", "/**/*.html", "/**/*.css", "/**/*.js", "/profile/**").permitAll()