结束评分结果逻辑修改

vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketHandler.java

@@ -7,8 +7,6 @@ import cn.hutool.core.util.StrUtil;
 import cn.hutool.json.JSONUtil;
 import com.vetti.common.ai.elevenLabs.ElevenLabsClient;
 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 com.vetti.hotake.domain.HotakeProblemBaseInfo;
@@ -145,7 +143,6 @@ public class ChatWebSocketHandler {
                     if (StrUtil.isEmpty(cacheResultText)) {
                         cacheResultText = "";
                     }
-
                     //这是初次处理的逻辑
                     if ("YES".equals(startFlag)) {
                         //初始化-不走大模型-直接对候选人进行提问
@@ -176,37 +173,43 @@ public class ChatWebSocketHandler {
                         //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);
                         String resultMsg = chatGPTClient.handleAiChat(promptJson,"QA");
                         if(StrUtil.isNotEmpty(resultMsg)) {
                             //开始解析返回结果
                             Map mapResultData = JSONUtil.toBean(resultMsg,Map.class);
-                            //获取评分
+                            //验证是否有追问问题返回,如果没有问题返回直接返回评分停止面试
-                            //验证是否触发对应的规则
+                            Boolean isEndFlagFollow = checkInterviewIsEnd(resultMsg,session);
-                            Boolean isEndFlag = getInterviewScore(resultMsg, session);
+                            if(isEndFlagFollow){
-                            if(isEndFlag){
+                                //获取评分
-                                log.info("面试回答符合条件规则,继续追问啦!!!!!");
+                                //验证是否触发对应的规则
-                                int resultNum = (int) (Math.random() * 2);
+                                Boolean isEndFlag = getInterviewScore(resultMsg, session);
-                                List<String> questions = JSONUtil.toList(mapResultData.get("follow_up_questions").toString(), String.class);
+                                if(isEndFlag){
-                                String questionStr = questions.get(resultNum);
+                                    log.info("面试回答符合条件规则,继续追问啦!!!!!");
-                                if (StrUtil.isNotEmpty(questionStr)) {
+                                    int resultNum = (int) (Math.random() * 2);
-                                    //开始进行语音输出-流式持续输出
+                                    List<String> questions = JSONUtil.toList(mapResultData.get("follow_up_questions").toString(), String.class);
-                                    sendTTSBuffer(clientId, questionStr, session);
+                                    String questionStr = questions.get(resultNum);
-                                    // 实时输出内容
+                                    if (StrUtil.isNotEmpty(questionStr)) {
-                                    try {
+                                        //开始进行语音输出-流式持续输出
-                                        //把文本也给前端返回去
+                                        sendTTSBuffer(clientId, questionStr, session);
-                                        Map<String, String> dataText = new HashMap<>();
+                                        // 实时输出内容
-                                        dataText.put("type", "question");
+                                        try {
-                                        dataText.put("content", questionStr);
+                                            //把文本也给前端返回去
-                                        log.info("提问的问题文本发送啦:{}",JSONUtil.toJsonStr(dataText));
+                                            Map<String, String> dataText = new HashMap<>();
-                                        session.getBasicRemote().sendText(JSONUtil.toJsonStr(dataText));
+                                            dataText.put("type", "question");
-                                    } catch (Exception e) {
+                                            dataText.put("content", questionStr);
-                                        e.printStackTrace();
+                                            log.info("提问的问题文本发送啦:{}",JSONUtil.toJsonStr(dataText));
+                                            session.getBasicRemote().sendText(JSONUtil.toJsonStr(dataText));
+                                        } catch (Exception e) {
+                                            e.printStackTrace();
+                                        }
+                                        //开始对问题进行缓存
+                                        recordQuestion(questionStr,session);
                                     }
-                                    //开始对问题进行缓存
-                                    recordQuestion(questionStr,session);
                                 }
                             }
                         }
+                        log.info("结束请求AI:{}",System.currentTimeMillis()/1000);
                     }
                 } else if ("end".equals(resultFlag)) {
                     log.info("面试结束啦!!!!!");
@@ -242,8 +245,16 @@ public class ChatWebSocketHandler {
     // 发生错误时调用
     @OnError
     public void onError(Session session, Throwable throwable) {
-        System.err.println("WebSocket错误发生: " + throwable.getMessage());
+        System.err.println("WebSocket发生错误: 页面关闭,链接断开了");
-        throwable.printStackTrace();
+        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);
+        }
     }
 
     /**
@@ -528,5 +539,38 @@ public class ChatWebSocketHandler {
         }
     }
 
+    /**
+     * 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;
+    }
+
 }
 

vetti-admin/src/main/java/com/vetti/web/controller/ai/AiCommonController.java

@@ -53,7 +53,7 @@ public class AiCommonController extends BaseController
         //你好,我是本次的面试官Vetti,请点击开始按钮后,做一段自我介绍.
         //你好,我是本次的面试官Vetti,请在三秒后,开始做一段自我介绍.
         //本轮面试结束,谢谢您的配合,面试结果将稍后通知
-        elevenLabsClient.handleTextToVoice("Ok, I have received your reply.","/Users/wangxiangshun/Desktop/临时文件/good.wav");
+        elevenLabsClient.handleTextToVoice("Yeah","/Users/wangxiangshun/Desktop/临时文件/Yeah.wav");
 
         return success();
     }

vetti-admin/src/main/resources/application-dev.yml

@@ -156,7 +156,7 @@ whisper:
     apiKey: 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
     language: en
     apiClientTokenUrl: https://api.openai.com/v1/realtime/sessions
-    prompt: This is a clear conversation in English. The user is speaking naturally through their device microphone. Please transcribe accurately with proper punctuation and natural speech patterns.
+    prompt: You are a translator. Detect when the user stops speaking. When a full sentence is complete, send recognized text as type:\'transcript\', and send its English translation as type:\'translation\'.
 
 
 # AI 聊天

vetti-admin/src/main/resources/application-druid.yml

@@ -163,7 +163,7 @@ whisper:
     apiKey: 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
     language: en
     apiClientTokenUrl: https://api.openai.com/v1/realtime/sessions
-    prompt: This is a clear conversation in English. The user is speaking naturally through their device microphone. Please transcribe accurately with proper punctuation and natural speech patterns.
+    prompt: You are a translator. Detect when the user stops speaking. When a full sentence is complete, send recognized text as type:\'transcript\', and send its English translation as type:\'translation\'.
 
 # AI 聊天
 chatGpt:

vetti-admin/target/classes/application-druid.yml

@@ -163,7 +163,7 @@ whisper:
     apiKey: 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
     language: en
     apiClientTokenUrl: https://api.openai.com/v1/realtime/sessions
-    prompt: This is a clear conversation in English. The user is speaking naturally through their device microphone. Please transcribe accurately with proper punctuation and natural speech patterns.
+    prompt: You are a translator. Detect when the user stops speaking. When a full sentence is complete, send recognized text as type:\'transcript\', and send its English translation as type:\'translation\'.
 
 # AI 聊天
 chatGpt: