code: def find_nearest_training(question, n_results=10):
      q_rep = embed_questions_for_retrieval(
          [question], qar_tokenizer, qar_model
      )
      D, I = eli5_train_q_index.search(q_rep, n_results)
      nn_examples = [eli5_train[int(i)] for i in I[0]]
      return nn_examples
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/longform-qa/eli5_app.py
imports: import datasets
  import numpy
  import streamlit
  import torch
  from elasticsearch import Elasticsearch
  import faiss
  import transformers
  from eli5_utils import embed_questions_for_retrieval, make_qa_s2s_model, qa_s2s_generate, query_es_index, query_qa_dense_index
  from transformers import AutoModel, AutoModelForSeq2SeqLM, AutoTokenizer
label_desc: Use image node_id 4 for calling a global function with example usage: find_nearest_training(question, n_results) and returns: nn_examples