class_docstr: SimpleQA: Question-Answering on a list of texts
class_docstr_tok: ["SimpleQA",":","Question-Answering","on","a","list","of","texts"]
docstr: ```
  search index for query
  Args:
    query(str): search query
    limit(int):  number of top search results to return
  Returns:
    list of dicts with keys: reference, rawtext
  ```
docstr_tok: ["``","`","search","index","for","query","Args",":","query","(","str",")",":","search","query","limit","(","int",")",":","number","of","top","search","results","to","return","Returns",":","list","of","dicts","with","keys",":","reference",",","rawtext","``","`"]
code: def search(self, query, limit=10):
      """
      ```
      search index for query
      Args:
        query(str): search query
        limit(int):  number of top search results to return
      Returns:
        list of dicts with keys: reference, rawtext
      ```
      """
      ix = self._open_ix()
      with ix.searcher() as searcher:
          query_obj = QueryParser(
              "content", ix.schema, group=qparser.OrGroup
          ).parse(query)
          results = searcher.search(query_obj, limit=limit)
          docs = []
          output = [dict(r) for r in results]
          return output
  
imports: from transformers import AutoModelForQuestionAnswering, AutoTokenizer, TFAutoModelForQuestionAnswering
  from whoosh import index, qparser
  from whoosh.fields import *
  from whoosh.qparser import QueryParser
  from ...None import utils
  from ...imports import *
  from ...torch_base import TorchBase
  from ..None import preprocessor
  from ..None import textutils
  from itertools import chain, zip_longest
label_desc: Use image node_id 6 for calling the SimpleQA obj's underlying member method code with example usage: obj.search(query, limit) and returns: output