add ad_predict_with_model

ad_recommend.py

@@ -294,6 +294,41 @@ def predict_mid_video_res_with_add(now_date, mid, video_id, abtest_param, abtest
             'ad_predict': ad_predict}
     return result
 
+def predict_mid_video_res_with_model(now_date, mid, video_id, abtest_param, abtest_id, abtest_config_tag, ab_test_code, care_model_status):
+    # now_dt = datetime.datetime.strftime(now_date, '%Y%m%d')
+    now_dt = '20231129'
+    model_key = abtest_param.get('model_key', 'ad_out_v2_model_v1.day')
+    user_key_name = f"{config_.KEY_NAME_PREFIX_AD_OUT_MODEL_SCORE_USER}{model_key}:{now_dt}"
+    item_key_name = f"{config_.KEY_NAME_PREFIX_AD_OUT_MODEL_SCORE_ITEM}{model_key}:{now_dt}"
+
+    user_score = redis_helper.get_score_with_value(key_name=user_key_name, value=mid)
+    item_score = redis_helper.get_score_with_value(key_name=item_key_name, value=video_id)
+    if user_score is None:
+        user_score = 0.0
+    if item_score is None:
+        item_score = 0.0
+    mid_video_predict_res = user_score + item_score
+
+    # 获取对应的阈值
+    threshold_key_name_prefix = config_.KEY_NAME_PREFIX_AD_THRESHOLD
+    threshold_key_name = f"{threshold_key_name_prefix}{abtest_id}:{abtest_config_tag}:{ab_test_code}:"
+    # threshold = redis_helper.get_data_from_redis(key_name=threshold_key_name)
+    threshold = 0.2
+
+    # 阈值判断
+    if mid_video_predict_res > threshold:
+        # 大于阈值，出广告
+        ad_predict = 2
+    else:
+        # 否则，不出广告
+        ad_predict = 1
+    result = {
+        'user_score': user_score,
+        'item_score': item_score,
+        'threshold': threshold,
+        'ad_predict': ad_predict
+    }
+    return result
 
 def predict_mid_video_res_with_multiply(now_date, mid, video_id, abtest_param, abtest_id, abtest_config_tag, ab_test_code, care_model_status):
     now_dt = datetime.datetime.strftime(now_date, '%Y%m%d')
@@ -449,6 +484,17 @@ def ad_recommend_predict(app_type, mid, video_id, ab_exp_info, ab_test_code, car
                 ab_test_code=ab_test_code,
                 care_model_status=care_model_status
             )
+        elif threshold_mix_func == 'model':
+            result = predict_mid_video_res_with_model(
+                now_date=now_date,
+                mid=mid,
+                video_id=video_id,
+                abtest_param=abtest_param,
+                abtest_id=abtest_id,
+                abtest_config_tag=abtest_config_tag,
+                ab_test_code=ab_test_code,
+                care_model_status=care_model_status
+            )
         else:
             result = predict_mid_video_res(
                 now_date=now_date,

config.py

@@ -1886,6 +1886,10 @@ class BaseConfig(object):
 
     }
 
+    # 有广告时的用户跳出分数预测结果存放 redis key 前缀，完整格式：ad:out:model:score:user:{model_key}:{date}
+    KEY_NAME_PREFIX_AD_OUT_MODEL_SCORE_USER = 'ad:out:model:score:user:'
+    # 有广告时的视频跳出分数预测结果存放 redis key 前缀，完整格式：ad:out:model:score:video:{model_key}:{date}
+    KEY_NAME_PREFIX_AD_OUT_MODEL_SCORE_ITEM = 'ad:out:model:score:item:'
     # 用户组有广告时的分享率预测结果存放 redis key 前缀，完整格式：ad:users:group:predict:share:rate:{user_data_key}:{date}
     KEY_NAME_PREFIX_AD_GROUP = 'ad:users:group:predict:share:rate:'
     # 视频有广告时的分享率预测结果存放 redis key 前缀，完整格式：ad:video:predict:share:rate:{video_data_key}:{date}