add business_tags

personas_vector/match_api.py

@@ -23,24 +23,24 @@ def match_tractate_by_device(device_id, n=10):
         if device_id not in ["0", "unknown", "87654"]:
             time_begin = time.time()
             business_tags = get_user_portrait_tag3_from_redis(device_id, tags_num=3).get("business_tags", [])
-            # business_tags = ["假体下巴", "你好", "假体隆胸"]
             res = []
-            vectors = []
-            for tag in business_tags:
-                lst = json.loads(TAG_EMBEDDING_DICT.get(bytes(tag, "utf-8"), b"[]"))
-                if lst:
-                    vectors.append(np.array(lst).astype("float32"))
-            if vectors:
-                D, I = FAISS_TAGS_INDEX.search(np.array([np.average(vectors, axis=0)]).astype("float32"), n)
-                distances = D.tolist()[0]
-                ids = I.tolist()[0]
-                for (index, i) in enumerate(distances):
-                    if i <= 5.0:
-                        res.append(ids[index])
-            time_end = time.time() - time_begin
-            if time_end > 0.04:
-                send_performance_msg_to_dingtalk("match_tractate_by_device {} n={} cost {:.3f}ms".format(
-                    device_id, n, time_end * 1000))
+            if business_tags:
+                vectors = []
+                for tag in business_tags:
+                    lst = json.loads(TAG_EMBEDDING_DICT.get(bytes(tag, "utf-8"), b"[]"))
+                    if lst:
+                        vectors.append(np.array(lst).astype("float32"))
+                if vectors:
+                    D, I = FAISS_TAGS_INDEX.search(np.array([np.average(vectors, axis=0)]).astype("float32"), n)
+                    distances = D.tolist()[0]
+                    ids = I.tolist()[0]
+                    for (index, i) in enumerate(distances):
+                        if i <= 5.0:
+                            res.append(ids[index])
+                time_end = time.time() - time_begin
+                if time_end > 0.04:
+                    send_performance_msg_to_dingtalk("match_tractate_by_device {} n={} cost {:.3f}ms".format(
+                        device_id, n, time_end * 1000))
             return res
         return []
     except Exception as e: