yinruoxi

新增：
  1.讯飞大模型升级为3.0版本
  2.更新3.0对话模版

xueyi-modules/xueyi-nlt/src/main/java/com/xueyi/nlt/netty/client/WebSocketClient.java

@@ -45,9 +45,10 @@ public class WebSocketClient extends WebSocketListener {
 
     @Value("${secret.spark.apiKey}")
     private String apiKey;
-
+    @Value("${secret.spark.hostUrl}")
+    public static String hostUrl;
     public final static Object LOCK = new Object();
-    public static String hostUrl = "https://spark-api.xf-yun.com/v2.1/chat";
+
 //    public static String APPID = "3d9282da";//从开放平台控制台中获取
 //    public static String APIKEY = "7c217b3a313f4b66fcc14a8e97f85103";//从开放平台控制台中获取
 //    public static String APISecret = "ZTRiNDQwMTRlOTlmZDQwMDUwYTdjMDM0";//从开放平台控制台中获取
@@ -206,7 +207,7 @@ public class WebSocketClient extends WebSocketListener {
             header.addProperty("uid","123456789");
             //填充parameter
 //            chat.addProperty("domain","general");     //1.0版本
-            chat.addProperty("domain","generalv2");   // 2.0版本
+            chat.addProperty("domain","generalv3");   // 3.0版本
             chat.addProperty("random_threshold",0.5);
             chat.addProperty("max_tokens",1024);
             chat.addProperty("auditing","default");

xueyi-modules/xueyi-nlt/src/main/java/com/xueyi/nlt/nlt/template/FreeChatTemplate.java

@@ -36,44 +36,42 @@ public class FreeChatTemplate implements BaseTemplate{
         Long operatorId = TerminalSecurityContextHolder.getOperatorId();
         String redisKey = "group:nlp:" + SecurityContextHolder.getLocalMap().get("enterprise_id") + ":" + operatorId;
         // 根据content内容调用模版并返回结果
-        synchronized (WebSocketClient.LOCK) {
-            // 通过redis获取数字人上下文信息
-            Long size = redisTemplate.opsForList().size(redisKey);
-            if (size > 8) {
-                redisTemplate.opsForList().leftPop(redisKey,2);
-            }
-            size = redisTemplate.opsForList().size(redisKey);
-            List<String> context = new ArrayList<>();
-            context.add("你是一位公司前台事务的专家。");
-            context.addAll(redisTemplate.opsForList().range(redisKey,size-6,size));
+        // 通过redis获取数字人上下文信息
+        Long size = redisTemplate.opsForList().size(redisKey);
+        if (size > 8) {
+            redisTemplate.opsForList().leftPop(redisKey,2);
+        }
+        size = redisTemplate.opsForList().size(redisKey);
+        List<String> context = new ArrayList<>();
+        context.add("你是一位企业前台。你来自于缔智元公司。你的名字叫小智，你是一位数字员工。");
+        context.addAll(redisTemplate.opsForList().range(redisKey,size-6,size));
 
-            context.add(content);
+        context.add(content);
 
-            //webSocketClient.sendMsg(context);
+        //webSocketClient.sendMsg(context);
 
-            LlmContext llmContext = LlmContext.parse(context,true);
-            LlmParam param = new LlmParam();
-            LlmResponse response = sysLlmService.chat(llmContext,param);
-            String result = response.getContent();
+        LlmContext llmContext = LlmContext.parse(context,true);
+        LlmParam param = new LlmParam();
+        LlmResponse response = sysLlmService.chat(llmContext,param);
+        String result = response.getContent();
+
+        // 处理数据
+        if (result.contains("我是科大讯飞")) {
+            result = "我是缔智元公司的数字人员工，我采用的是科大讯飞的星火大模型。";
+        }
 
-            // 处理数据
-            if (result.contains("我是科大讯飞")) {
-                result = result.replaceAll("科大讯飞", "缔智元");
-            }
-            result = result.replaceAll("认知模型", "数字员工");
-            result = result.replaceAll("认知智能模型", "数字员工");
-            if (result.equals("-1")) {
-                result = "这个问题超出了我无法回答，您可以提出更多关于公司相关问题。";
-            }
 
-            if(!StringUtils.isEmpty(result)){
+        if(!StringUtils.isEmpty(result)){
+            if (result.equals("-1")) {
+                result = "这个问题超出了我的能力，您可以提出更多关于公司相关问题。";
+            } else {
                 redisTemplate.opsForList().rightPush(redisKey,content);
                 redisTemplate.opsForList().rightPush(redisKey,result);
             }
-            JSONObject resultJson = new JSONObject();
-            resultJson.put("msg",result);
-            return resultJson;
         }
+        JSONObject resultJson = new JSONObject();
+        resultJson.put("msg",result);
+        return resultJson;
     }
 
     public JSONObject handle(String dev, String content, boolean stream) {

xueyi-modules/xueyi-nlt/src/main/java/com/xueyi/nlt/nlt/template/MovieChatTemplate.java

@@ -37,40 +37,42 @@ public class MovieChatTemplate implements BaseTemplate{
         // 判断content如果小于5五个字，返回msg：对不起，能否再描述清除一些。
         if(content.length() < 5){
             JSONObject resultJson = new JSONObject();
-            resultJson.put("msg","对不起，能否再描述清除一些。");
+            resultJson.put("msg","对不起，能否再描述清楚一些。");
             return resultJson;
         }
         Long operatorId = TerminalSecurityContextHolder.getOperatorId();
         String redisKey = "group:nlp:" + SecurityContextHolder.getLocalMap().get("enterprise_id") + ":" + operatorId;
         // 根据content内容调用模版并返回结果
-            // 通过redis获取数字人上下文信息
-            Long size = redisTemplate.opsForList().size(redisKey);
-            if (size > 8) {
-                redisTemplate.opsForList().leftPop(redisKey,2);
-            }
-            size = redisTemplate.opsForList().size(redisKey);
-            List<String> context = new ArrayList<>();
-            context.add("你现在扮演一位电影专家，你的话十分严谨。");
-            context.addAll(redisTemplate.opsForList().range(redisKey,size-6,size));
+        // 通过redis获取数字人上下文信息
+        Long size = redisTemplate.opsForList().size(redisKey);
+        if (size > 8) {
+            redisTemplate.opsForList().leftPop(redisKey,2);
+        }
+        size = redisTemplate.opsForList().size(redisKey);
+        List<String> context = new ArrayList<>();
+        context.add("你是一位电影领域的专家。你来自于缔智元公司。你的名字叫小智");
+        context.addAll(redisTemplate.opsForList().range(redisKey,size-6,size));
 
-            context.add(content);
-            LlmContext llmContext = LlmContext.parse(context,true);
-            LlmParam param = new LlmParam();
-            LlmResponse response = sysLlmService.chat(llmContext,param);
+        context.add(content);
+        LlmContext llmContext = LlmContext.parse(context,true);
+        LlmParam param = new LlmParam();
+        LlmResponse response = sysLlmService.chat(llmContext,param);
 
-            String result = response.getContent();
+        String result = response.getContent();
 
-            String[] blockedWord = {"科大讯飞", "认知模型", "抱歉","认知智能模型"};
-            for(String a :blockedWord){
-                if(result != null && result.contains(a)){
-                    result = "";
-                    break;
-                }
-            }
-            if(!StringUtils.isEmpty(result)){
+        // 处理数据
+        if (result.contains("我是科大讯飞")) {
+            result = "我是缔智元公司的数字人员工，我采用的是科大讯飞的星火大模型。";
+        }
+
+        if(!StringUtils.isEmpty(result)){
+            if (result.equals("-1")) {
+                result = "这个问题超出了我的能力，您可以提出更多关于公司相关问题。";
+            } else {
                 redisTemplate.opsForList().rightPush(redisKey,content);
                 redisTemplate.opsForList().rightPush(redisKey,result);
             }
+        }
 
             JSONObject resultJson = new JSONObject();
             resultJson.put("msg",result);