text: import os
  from milvus import *
  
  
  
  # MILVUS_HOST = '192.168.1.85'
  # MILVUS_PORT = 19560
  
  MILVUS_HOST = os.getenv("MILVUS_HOST", "127.0.0.1")
  MILVUS_PORT = os.getenv("MILVUS_PORT", 19530)
  
  
  # BERT_HOST = os.getenv("BERT_HOST", "127.0.0.1")
  # BERT_PORT = os.getenv("BERT_PORT", 5555)
  
  
  MYSQL_HOST = os.getenv("MYSQL_HOST", "127.0.0.1")
  MYSQL_PORT = os.getenv("MYSQL_PORT", 3306)
  MYSQL_USER = os.getenv("MYSQL_USER", 'root')
  MYSQL_PASSWORD = os.getenv("MYSQL_PASSWORD", '123456')
  MYSQL_DATABASE = os.getenv("MYSQL_DATABASE", 'mysql')
  
  
  TABLE_NAME = os.getenv("DEFAULT_TABLE", "recipe4")
  
  
  data_path = '/data1/workspace/lym/im2recipe-Pytorch/data/test_lmdb'
  
  im_path = '/data1/workspace/lym/im2recipe-Pytorch/milvus_im2recipe/ima_test/'
  
  # midel
  model_path = '/data1/workspace/lym/im2recipe-Pytorch/model/model_e500_v-8.950.pth.tar'
  
  
  file_keys_pkl = '/data1/workspace/lym/im2recipe-Pytorch/data/test_keys.pkl'
  
  ingrW2V = '/data1/workspace/lym/im2recipe-Pytorch/data/vocab.bin'
  
  recipe_json_fname = '/data1/workspace/lym/im2recipe-Pytorch/data/recipe1M/layer1.json'
  
  
  # batch_size = 10000
  temp_file_path = 'temp.csv'
  
  
  
  
  
  collection_param = {
      'collection_name': TABLE_NAME,
      'dimension': 1024,
      'index_file_size':2048,
      'metric_type':  MetricType.IP
  }
  
  search_param = {'nprobe': 16}
  
  top_k = 3
  
  