召回模型获取用户画像改为从DMP

conf/default.conf

@@ -5,3 +5,6 @@ host = am-bp1w063w3g4908x1890650o.ads.aliyuncs.com
 port = 3306
 user = 
 password = 
+
+[DMP]
+url = 

src/core/profile.py

@@ -114,7 +114,11 @@ class UserPreferenceCateProfile(BaseProfile):
 
     def convert(self, value):
         ret = [0.] * 8
-        if pd.isnull(value):
+
+        if isinstance(value, list):
+            if not value:
+                return ret
+        elif pd.isnull(value):
             return ret
 
         if isinstance(value, str):

src/core/recommender.py

@@ -2,9 +2,11 @@
 
 import os
 import json
-from typing import List, Dict
+import configparser
+from typing import List
 
 import faiss
+import requests
 import numpy as np
 
 from ydl_ai_recommender.src.core.indexer import (
@@ -15,7 +17,6 @@ from ydl_ai_recommender.src.core.indexer import (
     CounselorCounselorCFIndexer,
 )
 from ydl_ai_recommender.src.core.profile import encode_user_profile
-from ydl_ai_recommender.src.data.mysql_client import MySQLClientPool
 from ydl_ai_recommender.src.utils import get_conf_path, get_data_path
 from ydl_ai_recommender.src.utils.log import create_logger
 
@@ -40,33 +41,33 @@ class Recommender():
 
 class UserCFRecommender(Recommender):
 
-    def __init__(self, top_n=5, k=20, is_use_db=True, u2c='combination', c2c=None) -> None:
+    def __init__(self, top_n=5, k=20, u2c='combination', c2c=None) -> None:
         """
         params:
             top_n: 每个召回的用户获取的相关咨询师个数
             k: 召回的相似用户数
-            is_use_db: 是否使用数据库
             u2c: [用户->咨询师] 索引方法
             c2c: [咨询师->咨询师] 索引方法，None 表示不使用咨询师拓展
         """
         super().__init__()
-        self.select_items_str = ', '.join([
+        select_items = [
             'uid', 'country_code', 'channel_id_type', 'ffrom_login', 'user_preference_cate', 'consult_pay_money',
             'listen_pay_money', 'test_items_pay_money', 'course_pay_money', 'consult_order_num',
             'listen_order_num', 'test_items_order_num', 'course_order_num', 'aidi_cst_bias_city',
             'aidi_cst_bias_sex', 'aidi_cst_bias_price', 'aidi_cst_bias_server_type', 'user_login_city',
             'd30_inquire_order_num', 'd30_session_num',
-        ])
+        ]
+        self.select_fields = {k: True for k in select_items}
         # 召回 top_n 个相似用户
         self.top_n = top_n
         # 每个召回的用户取 k 个相关咨询师
         self.k = k
 
         self.logger = create_logger(__name__, 'recommender.log')
-        if is_use_db:
-            self.client = MySQLClientPool.create_from_config_file(get_conf_path())
-        else:
-            self.logger.warn('未连接数据库')
+        
+        config = configparser.RawConfigParser()
+        config.read(get_conf_path())
+        self.dmp_url = config.get('DMP', 'url')
 
         if u2c == 'chat':
             self.indexer = UserCounselorChatIndexer(self.logger)
@@ -107,18 +108,32 @@ class UserCFRecommender(Recommender):
         if user_id == '0':
             return []
             
-        sql = 'SELECT {} FROM ads.ads_register_user_profiles'.format(self.select_items_str)
-        sql += ' WHERE uid={}'.format(user_id)
+        headers = {
+            'X-App-Id': 'plough_cloud',            
+            'Content-Type': 'application/json'
+        }
+
+        payload = {
+            "filter": {
+                "uid": user_id,
+            },
+            "fields": self.select_fields,
+            "limit": 10
+        }
+
         try:
-            _, all_data = self.client.query(sql)
-            if len(all_data) == 0:
-                return []
-            return all_data[0]
+            response = requests.request('POST', self.dmp_url, headers=headers, json=payload)
+            resp = response.json()
+            return resp['data']['objects'][0]
         except Exception as e:
-            self.logger.error('获取用户画像数据失败', exc_info=True)
-            
+            self.logger.error('获取用户画像数据失败: %s', e, exc_info=True)
+            try:
+                self.logger.exception('response json data %s', resp)
+            except:
+                pass
             return []
 
+
     def _recommend(self, user_embedding):
         D, I = self.index.search(np.array([user_embedding]), self.k)
         counselors = []
@@ -227,5 +242,5 @@ class ItemCFRecommender(Recommender):
 
 
 if __name__ == '__main__':
-    recommender = ItemCFRecommender()
-    print(recommender.recommend('10957910'))
+    recommender = UserCFRecommender()
+    print(recommender.recommend('12047'))
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