import os
import sys
sys.path.append(os.getcwd())
import tensorflow as tf
from libreco.algorithms import PinSage
from libreco.data import DataInfo
import collections
from datetime import datetime
from config import subject_pinsage_model_path
from config import logger,test_user_id

def load_mmodel(model_path,model_name):

    tf.compat.v1.reset_default_graph()
    # load data_info
    data_info = DataInfo.load(path=model_path, model_name=model_name)
    model = PinSage.load(
        path=model_path, model_name=model_name,  data_info=data_info,manual=True
    )
    return model

def pinsage_recall(user_id, topk=20):
    """
    通过pinsage推荐指定用户topk物品
    """
    #加载预训练模型pinsage
    pinsage = load_mmodel(model_path=subject_pinsage_model_path,model_name="pinsage_model")
    start_time = datetime.now()
    logger.info(f"本次需要进行pinsage召回的用户ID: {user_id}")
    user_recall_items_dict = collections.defaultdict(dict)
    
    item_list = list(pinsage.recommend_user(user=user_id, n_rec=topk).values())[0].tolist()
    score = []
    for i in item_list:
        score.append(pinsage.predict(user=user_id, item=i)[0])
    user_recall_items_dict[user_id] = list(zip(item_list,tuple(score)))
   # 计算耗时毫秒
    end_time = datetime.utcnow()
    cost_time_millisecond = round(float((end_time - start_time).microseconds / 1000.0), 3)    

    logger.info(f"本次推荐总耗时: {cost_time_millisecond} 毫秒")
    return user_recall_items_dict[user_id]  

if __name__ == '__main__':
    recall_results = pinsage_recall(user_id=test_user_id, topk=20)
    print(recall_results)