code: def tfidf_search(text, corpus=tfidf_dense, corpus_text=corpus):
      
      tokens = tokenize(text, vocabulary=corpus.columns)
      tfidf_vector_query = np.array(tfidfer.transform([' '.join(tokens)]).todense())[0]
      query_series = pd.Series(tfidf_vector_query, index=corpus.columns)
  
      return corpus_text[query_series.dot(corpus.T).values.argmax()]
docs: search for the most relevant document