AI 提问追问环境demo 添加

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

@@ -8,6 +8,7 @@ import com.vetti.common.ai.gpt.OpenAiStreamClient;
 import com.vetti.common.ai.gpt.service.OpenAiStreamListenerService;
 import com.vetti.common.ai.whisper.WhisperClient;
 import com.vetti.common.config.RuoYiConfig;
+import com.vetti.common.core.redis.RedisCache;
 import com.vetti.common.utils.spring.SpringUtils;
 import lombok.extern.slf4j.Slf4j;
 import okhttp3.*;
@@ -24,6 +25,7 @@ import java.io.*;
 import java.nio.ByteBuffer;
 import java.util.*;
 import java.util.concurrent.ConcurrentHashMap;
+import java.util.concurrent.CopyOnWriteArrayList;
 
 /**
  * 语音面试 web处理器
@@ -60,6 +62,16 @@ public class ChatWebSocketHandler {
      */
     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,AI提问的问题结果信息
+     */
+    private final Map<String,String> cacheQuestionResult = new ConcurrentHashMap<>();
+
     // 语音文件保存目录
     private static final String VOICE_STORAGE_DIR = "/voice_files/";
 
@@ -92,6 +104,10 @@ public class ChatWebSocketHandler {
         createWhisperRealtimeSocket(session.getId());
         //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(),"");
+        //初始化面试问题
+        cacheQuestionResult.put(session.getId(),"");
         //发送初始化面试官语音流
         String openingPathUrl = RuoYiConfig.getProfile() + VOICE_SYSTEM_DIR + "opening.wav";
         try {
@@ -128,10 +144,11 @@ public class ChatWebSocketHandler {
                     String startFlag = cacheReplyFlag.get(session.getId());
                     //语音结束,开始进行回答解析
                     String cacheResultText = cacheClientTts.get(clientId);
-                    log.info("返回的结果为:{}", cacheResultText);
+                    log.info("面试者回答信息为:{}", cacheResultText);
                     if (StrUtil.isEmpty(cacheResultText)) {
                         cacheResultText = "Hi.";
                     }
+                    String promptJson = "";
                     if("YES".equals(startFlag)) {
                         //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
@@ -146,7 +163,37 @@ public class ChatWebSocketHandler {
                         } catch (IOException e) {
                             e.printStackTrace();
                         }
-                        cacheResultText = "你是面试官，根据Construction Labourer候选人回答生成追问。只要一个问题";
+                        Map<String,String> mapEntity = new HashMap<>();
+                        mapEntity.put("role","system");
+                        mapEntity.put("content","你是面试官，根据Construction Labourer候选人回答生成追问。只要一个问题,问题不要重复");
+                        List<Map<String,String>> list = new LinkedList();
+                        list.add(mapEntity);
+                        promptJson = JSONUtil.toJsonStr(list);
+                        //记录缓存中
+                        cacheMsgMapData.put(session.getId(),promptJson);
+                    }else{
+                        //开始根据面试者回答的问题,进行追问回答
+//                        {
+//                            role: "system",
+//                                    content: "你是面试官，根据Construction Labourer候选人回答生成追问。"
+//                        },
+//                        {
+//                            role: "user",
+//                                    content: `问题：${question}\n候选人回答：${answer}`
+//                        }
+                        //获取面试者回答信息
+                        //获取缓存记录
+                        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 = 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);
+                        }
                     }
                     //获取完问答数据,直接清空缓存数据
                     cacheClientTts.put(clientId,"");
@@ -154,10 +201,18 @@ public class ChatWebSocketHandler {
                     log.info("1、开始进行AI回答时间:{}", System.currentTimeMillis() / 1000);
                     //把提问的文字发送给CPT(流式处理)
                     OpenAiStreamClient aiStreamClient = SpringUtils.getBean(OpenAiStreamClient.class);
-                    aiStreamClient.streamChat(cacheResultText, new OpenAiStreamListenerService() {
+                    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);
+                            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
                             //开始进行语音输出-流式持续输出
                             log.info("2、开始进行AI回答时间:{}", System.currentTimeMillis() / 1000);
@@ -185,6 +240,21 @@ public class ChatWebSocketHandler {
                         @Override
                         public void onComplete() {
                             try {
+                                //开始往缓存中记录提问的问题
+                                String questionResult = cacheQuestionResult.get(session.getId());
+                                //获取缓存记录
+                                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","system");
+                                    mapEntity.put("content","问题："+questionResult+"\\n候选人回答：{}");
+                                    list.add(mapEntity);
+                                    cacheMsgMapData.put(session.getId(),JSONUtil.toJsonStr(list));
+                                }
+                                //清空问题
+                                cacheQuestionResult.put(session.getId(),"");
+
                                 Map<String, String> resultEntity = new HashMap<>();
                                 resultEntity.put("msg", "done");
                                 //发送通知告诉客户端已经回答结束了
@@ -454,6 +524,5 @@ public class ChatWebSocketHandler {
         }
     }
 
-
 }
 

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

@@ -10,6 +10,7 @@ import org.springframework.stereotype.Component;
 
 import java.io.IOException;
 import java.util.HashMap;
+import java.util.List;
 import java.util.Map;
 import java.util.concurrent.TimeUnit;
 
@@ -37,10 +38,10 @@ public class OpenAiStreamClient {
     /**
      * 发送流式请求
      *
-     * @param prompt   提示词
+     * @param promptJson   提示词json数据集合
      * @param listener 流式响应监听器
      */
-    public void streamChat(String prompt, OpenAiStreamListenerService listener) {
+    public void streamChat(String promptJson, OpenAiStreamListenerService listener) {
         OkHttpClient client = new OkHttpClient.Builder()
                 .connectTimeout(30, TimeUnit.SECONDS)
                 .readTimeout(60, TimeUnit.SECONDS)
@@ -53,13 +54,18 @@ public class OpenAiStreamClient {
         Map<String, Object> requestBody = new HashMap<>();
         requestBody.put("model", model);
         requestBody.put("stream", true);
-
         // 构建消息
-        Map<String, String> message = new HashMap<>();
+        if(StrUtil.isNotEmpty(promptJson)) {
-        message.put("role", role);
+            List<Map> promptList = JSONUtil.toList(promptJson, Map.class);
-        message.put("content", prompt);
+            Object[] objects = new Object[promptList.size()];
-        requestBody.put("messages", new Object[]{message});
+            for (int i = 0; i < promptList.size(); i++) {
-
+                objects[i] = promptList.get(i);
+            }
+            //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)