api for answer item2vec

word_vector/api.py

@@ -12,6 +12,7 @@ from utils.es import es_scan
 from utils.files import DATA_PATH, MODEL_PATH
 from utils.message import (send_msg_to_dingtalk, send_performance_msg_to_dingtalk)
 
+from word_vector.answer import ANSWER_CLICK_IDS, ANSWER_CLICK_IDS_MODEL
 from word_vector.tractate import TRACTATE_CLICK_IDS, TRACTATE_CLICK_IDS_MODEL
 
 model_output_name = "w2v_model"
@@ -157,6 +158,36 @@ def clicked_tractate_ids_item2vec_model_by_ids(ids, n=5):
         return []
 
 
+@bind("strategy_embedding/word_vector/answer_item2vec")
+def clicked_answer_ids_item2vec_model(id, n=5):
+    try:
+        time_begin = time.time()
+        res = ANSWER_CLICK_IDS_MODEL.wv.most_similar(id, topn=n)
+        time_end = time.time() - time_begin
+        if time_end > 0.04:
+            timer_dict = {
+                "method": "clicked_answer_ids_item2vec_model",
+                "api": "strategy_embedding/word_vector/answer_item2vec",
+                "id": id,
+                "n": n,
+                "total_time": "{:.3f}ms".format(time_end * 1000)
+            }
+            msg_res = ""
+            for (k, v) in timer_dict.items():
+                msg_res += str(k)
+                msg_res += ": "
+                msg_res += str(v)
+                msg_res += "\n"
+            send_performance_msg_to_dingtalk(msg_res)
+        return res
+    except KeyError as e:
+        # send_msg_to_dingtalk("answer_item2vec: " + str(e))
+        return []
+    except Exception as e:
+        send_msg_to_dingtalk(str(traceback.format_exc()))
+        return []
+
+
 # if __name__ == "__main__":
 
 # w2v_train("dispose_problem.txt", model_output_name)