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面试流程性能优化处理

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wangxiangshun
2025-11-26 20:17:19 +08:00
parent 0e78ecc1f1
commit 22a15188be
11 changed files with 600 additions and 335 deletions
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47
vetti-admin/src/main/java/com/vetti/socket/AudioSender.java
View File

@@ -1,47 +0,0 @@
package com.vetti.socket;
import javax.websocket.Session;
import java.nio.ByteBuffer;
import java.util.Queue;
import java.util.concurrent.ConcurrentLinkedQueue;
import java.util.concurrent.atomic.AtomicBoolean;
/**
* 语音发送
*/
public class AudioSender {
private final Queue<byte[]> queue = new ConcurrentLinkedQueue<>();
private final AtomicBoolean sending = new AtomicBoolean(false);
public void sendAudio(Session session, byte[] data) {
queue.add(data);
trySend(session);
}
private void trySend(Session session) {
if (!sending.compareAndSet(false, true)) {
return; // 已在发送中，退出
}
byte[] chunk = queue.poll();
if (chunk == null) {
sending.set(false);
return;
}
ByteBuffer buffer = ByteBuffer.wrap(chunk);
session.getAsyncRemote().sendBinary(buffer, result -> {
sending.set(false);
if (!result.isOK()) {
result.getException().printStackTrace();
}
// 递归发送下一片
trySend(session);
});
}
}

129
vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketHandler.java
View File

@@ -328,31 +328,58 @@ public class ChatWebSocketHandler {
List<Map<String, String>> list = new LinkedList();
Map<String, String> mapEntity = new HashMap<>();
mapEntity.put("role", "system");
mapEntity.put("content", "You are a senior HR interviewer conducting behavioral interviews. You're a \"listener and guide,\" not an \"examiner.\" Your style is warm, natural, and conversational—like chatting with a colleague.\n" +
mapEntity.put("content", "You're Sarah, a senior HR interviewer in Sydney (15 years experience). You make candidates comfortable while getting insights.\n" +
"\n" +
"Core Rules:\n" +
"1. ALWAYS start with: \"Thank you,\" \"Cheers for that,\" or \"Thanks for sharing that\"\n" +
"2. Use Australian English: \"no worries,\" \"fair enough,\" \"mate,\" \"good on you,\" \"G'day\"\n" +
"3. Keep it casual—avoid jargon\n" +
"4. For detailed STAR answers: acknowledge warmly, then move to a NEW topic (don't over-probe)\n" +
"5. For stuck candidates: ease pressure with \"No rush, mate. Even a small example works\"\n" +
"6. For off-topic answers: acknowledge politely, then redirect gently back to the question\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" +
"Opening Pattern:\n" +
"\"G'day! Cheers for coming in. No need to stress—just a casual chat about your experiences. We'll focus on [competencies]. Sound good?\"\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" +
"Response Patterns:\n" +
"- Brief answer → \"Cheers for that. Could you walk me through a specific time? What was the situation, what did you do, and how did it turn out?\"\n" +
"- Detailed answer → \"Thank you. Good on you for [action]. Fair enough. Now, let's chat about [new topic]\"\n" +
"- Stuck candidate → \"No worries, mate. Take your time. Even a small project works. Want me to rephrase that?\"\n" +
"- Off-topic answer → \"Thanks for sharing that. That's interesting, but let me bring us back to [original question]. Could you tell me about [specific aspect]?\"\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" +
"Guardrails:\n" +
"- No discussion of protected characteristics\n" +
"- Base judgments on stated evidence only\n" +
"- Respond in natural English, NOT JSON\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" +
"- Keep candidates focused on the question asked");
"- 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
@@ -673,37 +700,37 @@ public class ChatWebSocketHandler {
* @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();
}
// 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();
// }
}

422
vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketOpusHandler.java → vetti-admin/src/main/java/com/vetti/socket/ChatWebSocketMultipleHandler.java
View File

@@ -1,17 +1,15 @@
package com.vetti.socket;
import cn.hutool.core.collection.CollectionUtil;
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.ElevenLabsClient;
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 com.vetti.hotake.domain.HotakeProblemBaseInfo;
import com.vetti.hotake.service.IHotakeProblemBaseInfoService;
import com.vetti.socket.util.Pcm16ToOpusRealtime;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.io.FileUtils;
import org.springframework.stereotype.Component;
@@ -22,17 +20,19 @@ import javax.websocket.server.ServerEndpoint;
import java.io.File;
import java.math.BigDecimal;
import java.nio.ByteBuffer;
import java.util.*;
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 web处理器
* 语音面试(多客户端) web处理器
*/
@Slf4j
@ServerEndpoint("/voice-websocket-opus/{clientId}")
@ServerEndpoint("/voice-websocket/multiple/{clientId}")
@Component
public class ChatWebSocketOpusHandler {
public class ChatWebSocketMultipleHandler {
/**
* 缓存客户端流式解析的语音文本数据
@@ -48,7 +48,10 @@ public class ChatWebSocketOpusHandler {
* 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
*/
@@ -59,6 +62,11 @@ public class ChatWebSocketOpusHandler {
*/
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/";
@@ -68,7 +76,7 @@ public class ChatWebSocketOpusHandler {
// 系统语音目录
private static final String VOICE_SYSTEM_DIR = "/system_files/";
public ChatWebSocketOpusHandler() {
public ChatWebSocketMultipleHandler() {
// 初始化存储目录
File dir = new File(RuoYiConfig.getProfile() + VOICE_STORAGE_DIR);
if (!dir.exists()) {
@@ -86,11 +94,18 @@ public class ChatWebSocketOpusHandler {
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
@@ -100,6 +115,8 @@ public class ChatWebSocketOpusHandler {
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);
@@ -137,8 +154,9 @@ public class ChatWebSocketOpusHandler {
}
//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, session);
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 {
@@ -150,59 +168,40 @@ public class ChatWebSocketOpusHandler {
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));
promptJson = JSONUtil.toJsonStr(list);
cacheMsgMapData.put(session.getId(), promptJson);
cacheMsgMapData1.put(session.getId(), JSONUtil.toJsonStr(list));
}
//开始返回衔接语
String openingPathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "good.wav";
sendVoiceBuffer(openingPathUrl, session);
//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);
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);
//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
Boolean isEndFlagFollow = checkInterviewIsEnd(resultMsg,session);
if(isEndFlagFollow){
//获取评分
//验证是否触发对应的规则
Boolean isEndFlag = getInterviewScore(resultMsg, session);
if(isEndFlag){
log.info("面试回答符合条件规则,继续追问啦!!!!!");
int resultNum = (int) (Math.random() * 2);
List<String> questions = JSONUtil.toList(mapResultData.get("follow_up_questions").toString(), String.class);
String questionStr = questions.get(resultNum);
if (StrUtil.isNotEmpty(questionStr)) {
//开始进行语音输出-流式持续输出
sendTTSBuffer(clientId, questionStr, session);
// 实时输出内容
try {
//把文本也给前端返回去
Map<String, String> dataText = new HashMap<>();
dataText.put("type", "question");
dataText.put("content", questionStr);
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);
}
}
}
}
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,"");
@@ -275,13 +274,8 @@ public class ChatWebSocketOpusHandler {
try {
//文件转换成文件流
ByteBuffer outByteBuffer = convertFileToByteBuffer(pathUrl);
byte[] bytes = new byte[outByteBuffer.remaining()];
//从缓冲区中读取数据并存储到指定的字节数组中
outByteBuffer.get(bytes);
Pcm16ToOpusRealtime realtime = new Pcm16ToOpusRealtime(16000);
byte[] bytesOut = realtime.encodeOneFrame(bytes);
//发送文件流数据
session.getBasicRemote().sendBinary(ByteBuffer.wrap(bytesOut));
session.getBasicRemote().sendBinary(outByteBuffer);
// 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) {
@@ -299,11 +293,12 @@ public class ChatWebSocketOpusHandler {
private void sendTTSBuffer(String clientId, String content, Session session) {
String resultFileName = clientId + "_" + System.currentTimeMillis() + ".wav";
String resultPathUrl = RuoYiConfig.getProfile() + VOICE_STORAGE_RESULT_DIR + resultFileName;
ElevenLabsClient elevenLabsClient = SpringUtils.getBean(ElevenLabsClient.class);
elevenLabsClient.handleTextToVoice(content, resultPathUrl);
ElevenLabsStreamClient elevenLabsClient = SpringUtils.getBean(ElevenLabsStreamClient.class);
elevenLabsClient.handleTextToVoice(content, resultPathUrl,session);
//持续返回数据流给客户端
log.info("发送语音流成功啦!!!!!!!");
sendVoiceBuffer(resultPathUrl, session);
// sendVoiceBuffer(resultPathUrl, session);
}
/**
@@ -312,55 +307,97 @@ public class ChatWebSocketOpusHandler {
* @param clientId 用户ID
* @param session 客户端会话
*/
private void initializationQuestion(String clientId, Session session) {
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
String openingPathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "good.wav";
sendVoiceBuffer(openingPathUrl, session);
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 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.");
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);
//获取预设问题-直接TTS转换返回语音结果
IHotakeProblemBaseInfoService problemBaseInfoService = SpringUtils.getBean(IHotakeProblemBaseInfoService.class);
HotakeProblemBaseInfo queryPro = new HotakeProblemBaseInfo();
queryPro.setUserId(Long.valueOf(clientId));
List<HotakeProblemBaseInfo> baseInfoList = problemBaseInfoService.selectHotakeProblemBaseInfoList(queryPro);
log.info("准备进行第一个问题的提问:{}",JSONUtil.toJsonStr(baseInfoList));
if (CollectionUtil.isNotEmpty(baseInfoList)) {
HotakeProblemBaseInfo baseInfo = baseInfoList.get(0);
if (StrUtil.isNotEmpty(baseInfo.getContents())) {
String[] qStrs = baseInfo.getContents().split("#AA#");
int random_index = (int) (Math.random() * qStrs.length);
//获取问题文本
String question = qStrs[random_index];
Map<String, String> mapEntityQ = new HashMap<>();
mapEntityQ.put("role", "user");
mapEntityQ.put("content", "Question：" + question + "\\nCandidate Answer：{}");
list.add(mapEntityQ);
log.info("开始提问啦:{}",JSONUtil.toJsonStr(list));
//直接对该问题进行转换处理返回语音流
log.info("第一个问题为:{}",question);
sendTTSBuffer(clientId, question, session);
//发送问题文本
try {
//把文本也给前端返回去
Map<String, String> dataText = new HashMap<>();
dataText.put("type", "question");
dataText.put("content", question);
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();
}
}
}
//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());
@@ -378,11 +415,10 @@ public class ChatWebSocketOpusHandler {
//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 = cacheMsgMapData.get(session.getId());
String msgMapData = cacheMsgMapData1.get(session.getId());
String promptJson = "";
if (StrUtil.isNotEmpty(msgMapData)) {
List<Map> list = JSONUtil.toList(msgMapData, Map.class);
@@ -399,14 +435,23 @@ public class ChatWebSocketOpusHandler {
}
}
}
//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
cacheMsgMapData.put(session.getId(), "");
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, "QA");
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
@@ -523,13 +568,23 @@ public class ChatWebSocketOpusHandler {
*/
private void recordQuestion(String questionResult,Session session) {
if (StrUtil.isNotEmpty(questionResult)) {
//获取缓存记录
//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", "user");
mapEntity.put("content", "Question：" + questionResult + "\\nCandidate Answer：{}");
mapEntity.put("role", "assistant");
mapEntity.put("content", questionResult);
list.add(mapEntity);
cacheMsgMapData.put(session.getId(), JSONUtil.toJsonStr(list));
}
@@ -569,28 +624,147 @@ public class ChatWebSocketOpusHandler {
return flag;
}
/**
* 发送小块语音流
* 验证面试是否结束
* @param session
* @param buffer
* @param chunkSize
* @return
*/
public void sendInChunks(Session session, ByteBuffer buffer, int chunkSize) {
int offset = 0;
ByteBuffer duplicate = buffer.slice();
byte[] audioData = new byte[duplicate.remaining()];
duplicate.get(audioData);
while (offset < audioData.length) {
int end = Math.min(offset + chunkSize, audioData.length);
byte[] chunk = Arrays.copyOfRange(audioData, offset, end);
synchronized(session) {
session.getAsyncRemote().sendBinary(ByteBuffer.wrap(chunk));
}
offset = end;
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);
// 实时输出内容
try{
//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();
}
sendTTSBuffer(clientId,content,session);
}
}
@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();
// }
}
}

53
vetti-admin/src/main/java/com/vetti/socket/util/AudioHub.java Normal file
View File

@@ -0,0 +1,53 @@
package com.vetti.socket.util;
import javax.websocket.Session;
import java.nio.ByteBuffer;
import java.util.Map;
import java.util.concurrent.*;
/**
* 音频自动发送
*/
public class AudioHub {
private static final Map<String, ConcurrentLinkedQueue<ByteBuffer>> userQueues = new ConcurrentHashMap<>();
static {
// 20ms 调度推流线程
new Thread(() -> {
while (true) {
for (Map.Entry<String, ConcurrentLinkedQueue<ByteBuffer>> entry : userQueues.entrySet()) {
String sessionId = entry.getKey();
ConcurrentLinkedQueue<ByteBuffer> queue = entry.getValue();
ByteBuffer frame = queue.poll();
if (frame != null) {
Session s = SessionManager.get(sessionId);
if (s != null && s.isOpen()) {
s.getAsyncRemote().sendBinary(frame);
}
}
}
try { Thread.sleep(20); } catch (Exception ignore) {}
}
}).start();
}
public static void addClient(Session session) {
userQueues.put(session.getId(), new ConcurrentLinkedQueue<>());
SessionManager.add(session);
}
public static void removeClient(Session session) {
userQueues.remove(session.getId());
SessionManager.remove(session.getId());
}
public static void pushToClient(String sessionId, ByteBuffer frame) {
if (userQueues.containsKey(sessionId)) {
userQueues.get(sessionId).add(frame);
}
}
}

94
vetti-admin/src/main/java/com/vetti/socket/util/Pcm16ToOpusRealtime.java
View File

@@ -1,94 +0,0 @@
package com.vetti.socket.util;
import io.github.jaredmdobson.concentus.OpusApplication;
import io.github.jaredmdobson.concentus.OpusDecoder;
import io.github.jaredmdobson.concentus.OpusEncoder;
import io.github.jaredmdobson.concentus.OpusException;
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
import java.util.ArrayList;
import java.util.List;
public class Pcm16ToOpusRealtime {
private static final int FRAME_MS = 20;
private final int frameSize;
private final int frameByte; // 960
private final OpusEncoder enc;
private final OpusDecoder dec;
/* -------------- 编码侧 -------------- */
private final byte[] encBuf; // 缓存
private int encPos = 0; // 当前缓存字节数
public Pcm16ToOpusRealtime(int sampleRate) throws OpusException {
this.enc = new OpusEncoder(sampleRate, 1, OpusApplication.OPUS_APPLICATION_AUDIO);
this.dec = new OpusDecoder(sampleRate, 1);
this.frameSize = sampleRate * FRAME_MS / 1000;
this.frameByte = frameSize * 2;
this.encBuf = new byte[frameByte];
}
/**
* 把任意长度的 24kHz-16bit-单声道 PCM 喂进来，
* 返回当前已经能编出的完整 Opus 帧（可能 0~n 个）
*/
public List<byte[]> encodeStream(byte[] pcmIn) throws OpusException {
List<byte[]> outFrames = new ArrayList<>();
int off = 0;
while (off < pcmIn.length) {
int canCopy = Math.min(pcmIn.length - off, frameByte - encPos);
System.arraycopy(pcmIn, off, encBuf, encPos, canCopy);
encPos += canCopy;
off += canCopy;
if (encPos == frameByte) { // 凑够一帧
outFrames.add(encodeOneFrame(encBuf));
encPos = 0; // 清空缓存
}
}
return outFrames;
}
/** 强制把尾巴编码掉（用 0 补齐） */
public byte[] flush() throws OpusException {
if (encPos == 0) return null; // 没有尾巴
// 补 0
for (int i = encPos; i < frameByte; i++) encBuf[i] = 0;
byte[] last = encodeOneFrame(encBuf);
encPos = 0;
return last;
}
public byte[] encodeOneFrame(byte[] encBuf) throws OpusException {
short[] pcm = byteArrToShortArr(encBuf);
byte[] opus= new byte[400];
int len = enc.encode(pcm, 0, frameSize, opus, 0, opus.length);
byte[] trim= new byte[len];
System.arraycopy(opus, 0, trim, 0, len);
return trim;
}
/* -------------- 解码侧（一次一帧） -------------- */
public byte[] decodeOneFrame(byte[] opusFrame) throws OpusException {
short[] pcm = new short[frameSize];
int samples = dec.decode(opusFrame, 0, opusFrame.length,
pcm, 0, frameSize, false);
return shortArrToByteArr(pcm, samples);
}
/* ====================================================================== */
private static short[] byteArrToShortArr(byte[] b) {
short[] s = new short[b.length / 2];
ByteBuffer.wrap(b).order(ByteOrder.LITTLE_ENDIAN).asShortBuffer().get(s);
return s;
}
private static byte[] shortArrToByteArr(short[] s, int len) {
byte[] b = new byte[len * 2];
ByteBuffer.wrap(b).order(ByteOrder.LITTLE_ENDIAN).asShortBuffer().put(s, 0, len);
return b;
}
}

25
vetti-admin/src/main/java/com/vetti/socket/util/SessionManager.java Normal file
View File

@@ -0,0 +1,25 @@
package com.vetti.socket.util;
import javax.websocket.Session;
import java.util.concurrent.ConcurrentHashMap;
/**
* 客户端对话管理
*/
public class SessionManager {
private static final ConcurrentHashMap<String, Session> clients = new ConcurrentHashMap<>();
public static void add(Session s) {
clients.put(s.getId(), s);
}
public static void remove(String id) {
clients.remove(id);
}
public static Session get(String id) {
return clients.get(id);
}
}

15
vetti-admin/src/main/java/com/vetti/web/controller/ai/AiCommonController.java
View File

@@ -54,14 +54,17 @@ public class AiCommonController extends BaseController
//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("We had a very pleasant chat today. We will get back to you as soon as possible. Also, you are welcome to keep your phone accessible.","/Users/wangxiangshun/Desktop/临时文件/end.wav");
// elevenLabsClient.handleTextToVoice("I usually get started and will stop only if a hazard becomes a problem.","/Users/wangxiangshun/Desktop/临时文件/Low-1.wav");
//
// elevenLabsClient.handleTextToVoice("Got it, yeah ","/Users/wangxiangshun/Desktop/临时文件/gotit.wav");
// elevenLabsClient.handleTextToVoice("I use whatever is available and make do if something is missing.","/Users/wangxiangshun/Desktop/临时文件/Low-2.wav");
//
// elevenLabsClient.handleTextToVoice("Gotcha ","/Users/wangxiangshun/Desktop/临时文件/gotcha.wav");
// elevenLabsClient.handleTextToVoice("If the supervisor sees an issue, I'll fix it then.","/Users/wangxiangshun/Desktop/临时文件/Low-3.wav");
//
// elevenLabsClient.handleTextToVoice("Right , got it ","/Users/wangxiangshun/Desktop/临时文件/rightgot.wav");
// elevenLabsClient.handleTextToVoice("I keep to myself unless there's a major problem.","/Users/wangxiangshun/Desktop/临时文件/Low-4.wav");
//
// elevenLabsClient.handleTextToVoice("I start with what's available and figure out the rest as I go.","/Users/wangxiangshun/Desktop/临时文件/Low-5.wav");
//
// elevenLabsClient.handleTextToVoice("I ignore it unless it directly stops my work.","/Users/wangxiangshun/Desktop/临时文件/Low-6.wav");
return success();
}
@@ -72,7 +75,7 @@ public class AiCommonController extends BaseController
@GetMapping("/handleAiChat")
public AjaxResult handleAiChat(@RequestParam String text)
{
String resultMsg = chatGPTClient.handleAiChat(text,"QA");
String resultMsg = chatGPTClient.handleAiChat(text,"YT");
return AjaxResult.success(resultMsg);
}

1
vetti-common/src/main/java/com/vetti/common/ai/elevenLabs/ElevenLabsClient.java
View File

@@ -101,6 +101,7 @@ public class ElevenLabsClient {
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, outputFile,httpClient);
} catch (IOException e) {

123
vetti-common/src/main/java/com/vetti/common/ai/elevenLabs/ElevenLabsStreamClient.java Normal file
View File

@@ -0,0 +1,123 @@
package com.vetti.common.ai.elevenLabs;
import com.google.gson.Gson;
import com.vetti.common.ai.elevenLabs.vo.VoiceSettings;
import com.vetti.common.ai.elevenLabs.vo.VoicesResponse;
import lombok.extern.slf4j.Slf4j;
import org.apache.http.HttpEntity;
import org.apache.http.client.methods.CloseableHttpResponse;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.methods.HttpPost;
import org.apache.http.entity.ContentType;
import org.apache.http.entity.StringEntity;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Component;
import javax.websocket.Session;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.nio.ByteBuffer;
import java.util.HashMap;
import java.util.Map;
/**
* 文本转换为语音
*/
@Slf4j
@Component
public class ElevenLabsStreamClient {
@Value("${elevenLabs.baseUrl}")
private String BASE_URL;
@Value("${elevenLabs.apiKey}")
private String apiKey;
@Value("${elevenLabs.modelId}")
private String modelId;
/**
* 将文本转换为语音并保存到文件
*
* @param text 要转换的文本
* @param voiceId 语音ID (可从ElevenLabs网站获取)
* @param outputFilePath 输出文件路径
* @throws IOException 网络请求或文件操作异常
*/
private void textToSpeech(String text, String voiceId, String outputFilePath, CloseableHttpClient httpClient, Session session) throws IOException {
HttpPost httpPost = new HttpPost(BASE_URL + "/text-to-speech/" + voiceId+"/stream?output_format=pcm_16000&optimize_streaming_latency=1");
httpPost.setHeader("xi-api-key", apiKey);
httpPost.setHeader("Content-Type", "application/json");
Map<String, Object> payload = new HashMap<>();
payload.put("text", text);
payload.put("model_id", modelId);
payload.put("voice_settings", new VoiceSettings(0.85, 0.5,0.1,0,0.9,1));
Gson gson = new Gson();
StringEntity entity = new StringEntity(gson.toJson(payload), ContentType.APPLICATION_JSON);
httpPost.setEntity(entity);
try (CloseableHttpResponse response = httpClient.execute(httpPost)) {
HttpEntity responseEntity = response.getEntity();
if (responseEntity != null) {
try (InputStream inputStream = responseEntity.getContent();) {
byte[] buffer = new byte[4096];
int bytesRead;
while ((bytesRead = inputStream.read(buffer)) != -1) {
ByteBuffer byteBuffer = ByteBuffer.wrap(buffer, 0, bytesRead);
session.getAsyncRemote().sendBinary(byteBuffer);
log.info("正常语音发送出去语音流啦!!!");
}
}
}
}
}
/**
* 获取可用的语音列表
*
* @return 语音列表响应
* @throws IOException 网络请求异常
*/
private VoicesResponse getVoices(CloseableHttpClient httpClient){
HttpGet httpGet = new HttpGet(BASE_URL + "/voices");
httpGet.setHeader("xi-api-key", apiKey);
Gson gson = new Gson();
try (CloseableHttpResponse response = httpClient.execute(httpGet)) {
HttpEntity responseEntity = response.getEntity();
String responseBody = EntityUtils.toString(responseEntity);
return gson.fromJson(responseBody, VoicesResponse.class);
}catch (Exception e){
throw new RuntimeException("获取可用的语音列表异常");
}
}
/**
* 处理文本转换成语音文件
* @param inputText
* @param outputFile
* @return
*/
public String handleTextToVoice(String inputText, String outputFile, Session session){
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, outputFile,httpClient,session);
} catch (IOException e) {
e.printStackTrace();
} finally {
try {
httpClient.close();
} catch (IOException e) {
e.printStackTrace();
}
}
return outputFile;
}
}

8
vetti-common/src/main/java/com/vetti/common/ai/gpt/OpenAiStreamClient.java
View File

@@ -29,6 +29,9 @@ public class OpenAiStreamClient {
@Value("${chatGpt.model}")
private String model;
@Value("${chatGpt.modelQuestion}")
private String modelQuestion;
@Value("${chatGpt.role}")
private String role;
@@ -52,7 +55,7 @@ public class OpenAiStreamClient {
// 构建请求参数
Map<String, Object> requestBody = new HashMap<>();
requestBody.put("model", model);
requestBody.put("model", modelQuestion);
requestBody.put("stream", true);
// 构建消息
if(StrUtil.isNotEmpty(promptJson)) {
@@ -64,8 +67,6 @@ public class OpenAiStreamClient {
//获取到的提示
requestBody.put("messages", objects);
}
//开始给AI发送请求数据
// System.out.println("请求AI数据参数为:"+JSONUtil.toJsonStr(requestBody));
// 创建请求
Request request = new Request.Builder()
.url(apiUrl)
@@ -75,7 +76,6 @@ public class OpenAiStreamClient {
MediaType.parse("application/json; charset=utf-8")
))
.build();
// 发送异步请求
client.newCall(request).enqueue(new Callback() {
@Override

2
vetti-framework/src/main/java/com/vetti/framework/config/SecurityConfig.java
View File

@@ -112,7 +112,7 @@ public class SecurityConfig
.authorizeHttpRequests((requests) -> {
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/**",
requests.antMatchers("/login", "/register", "/captchaImage","/aiCommon/**","/voice-websocket/multiple/**",
"/voice-websocket/**","/voice-websocket-opus/**","/verification/email/send","/verification/email/verify","/verification/phone/send",
"/forgotPassword").permitAll()
// 静态资源，可匿名访问