new_contents: from nlp import cluster_prep
  import pandas as pd
  import psycopg2
  from sklearn.feature_extraction.text import TfidfVectorizer
  from sklearn.cluster import KMeans
  from sklearn.externals import joblib
  
  def predict_cluster(article_string):
          '''
          Takes in a string which is the article body to be processed and cluster value predicted
          article_string - string 
          returns the integer label for the cluster the text fits in
          '''
          z = cluster_prep(article_string)
          # reformat the result for tfidf
          z = ' '.join(z)
          km = joblib.load('model/kmeans_model.pkl')
          vectorizer = joblib.load('model/tf_vectorizer_obj.pkl')
          x_test = vectorizer.transform([z])
          res = km.predict(x_test)
          return res[0]	
  
subject: create prediction function