feat:添加676实验

ad-engine-service/src/main/java/com/tzld/piaoquan/ad/engine/service/predict/impl/PredictModelServiceImpl.java

@@ -6,6 +6,7 @@ import com.alibaba.fastjson.TypeReference;
 import com.tzld.piaoquan.ad.engine.commons.enums.AppTypeEnum;
 import com.tzld.piaoquan.ad.engine.commons.redis.AlgorithmRedisHelper;
 import com.tzld.piaoquan.ad.engine.commons.util.DateUtils;
+import com.tzld.piaoquan.ad.engine.commons.util.JSONUtils;
 import com.tzld.piaoquan.ad.engine.service.predict.config.NewExpUserGroupConfig;
 import com.tzld.piaoquan.ad.engine.service.predict.config.RoiModelConfig;
 import com.tzld.piaoquan.ad.engine.service.predict.constant.RuleRedisKeyConst;
@@ -230,6 +231,7 @@ public class PredictModelServiceImpl implements PredictModelService {
                 result = ThresholdModelContainer.getThresholdPredictModel("random676").predict(modelParam);
                 // 如果676实验返回结果，表示未命中规则即对应的用户来源和所属层存在配置，使用676实验的结果，否则继续走599实验
                 if (Objects.nonNull(result)) {
+                    log.info("广告跳出选择 -- 676实验结果: {}", JSONUtils.toJson(result));
                     return result;
                 }
             }
@@ -242,6 +244,7 @@ public class PredictModelServiceImpl implements PredictModelService {
                 result = ThresholdModelContainer.
                         getThresholdPredictModel("random")
                         .predict(modelParam);
+                log.info("广告跳出选择 -- 599实验结果: {}", JSONUtils.toJson(result));
             } else if (expCodes.contains("667") ||
                     (expCodes.contains(NewExpInfoHelper.flagId) && NewExpInfoHelper.checkInNewExpGroupAndSetParamIfIn(
                             requestParam.getAppType().toString(), requestParam.getNewExpGroup(), "667", modelParam))) {

ad-engine-service/src/main/java/com/tzld/piaoquan/ad/engine/service/predict/model/threshold/RandomPredict676Model.java

@@ -61,7 +61,7 @@ public class RandomPredict676Model extends ThresholdPredictModel {
         result.put("ad_predict", score < threshold ? 2 : 1);
         result.put("score", score);
         result.put("threshold", threshold);
-        result.put("model", "random");
+        result.put("model", this.initName());
 
         return result;
     }