def configure_worker(options={}, **kwargs):
    if 'queues' not in options:
        return
    if CORRESPONDING_QUEUE not in options['queues'].split(','):
        return
    print('### STARTING UP A NEAREST NEIGHBOR CONTEXT RECOMMENDER WORKER ###')

    global recommender

    # Setting logging low
    from rdkit import RDLogger
    lg = RDLogger.logger()
    lg.setLevel(RDLogger.CRITICAL)
    try:
        recommender = NNContextRecommender()
        recommender.load_nn_model(model_path=gc.CONTEXT_REC[
                                  'model_path'], info_path=gc.CONTEXT_REC['info_path'])
    except Exception as e:
        print(e)
    print('Loaded context recommendation model')

    print('### NEAREST NEIGHBOR CONTEXT RECOMMENDER STARTED UP ###') 

def configure_worker(options={}, **kwargs):
    if 'queues' not in options:
        return
    if CORRESPONDING_QUEUE not in options['queues'].split(','):
        return
    print('### STARTING UP A NEURAL NETWORK CONTEXT RECOMMENDER WORKER ###')

    global recommender

    # Setting logging low
    from rdkit import RDLogger
    lg = RDLogger.logger()
    lg.setLevel(RDLogger.CRITICAL)
    try:
        recommender = NeuralNetContextRecommender()
        recommender.load()
    except Exception as e:
        print(e)
    print('Loaded context recommendation model')

    print('### NEURAL NETWORK CONTEXT RECOMMENDER STARTED UP ###')