cosine similarity

## helps to retrieve similar question based of input vectors/embeddings for test query
def retrieveSimilarFAQ(train_question_vectors, test_question_vectors, train_QA_df, train_column_name, test_QA_df, test_column_name):
  similar_question_index = []
  for test_index, test_vector in enumerate(test_question_vectors):
    sim, sim_Q_index = -1, -1
    for train_index, train_vector in enumerate(train_question_vectors):
      sim_score = cosine_similarity(train_vector, test_vector)[0][0]
     
      if sim < sim_score:
        sim = sim_score
        sim_Q_index = train_index
    
    print("######")
    print(f"Query Question: \t {test_QA_df[test_column_name].iloc[test_index]}")    
    print(f"Retrieved Question: \t {train_QA_df[train_column_name].iloc[sim_Q_index]}")
    print("######")