class_docstr: Interact with Weaviate database to store vectors. This hook uses the 'conn_id'.
  
  :param conn_id: The connection id to use when connecting to Weaviate. <howto/connection:weaviate>
class_docstr_tok: ["Interact","with","Weaviate","database","to","store","vectors",".","This","hook","uses","the","'conn_id","'",".",":","param","conn_id",":","The","connection","id","to","use","when","connecting","to","Weaviate",".","<","howto\/connection",":","weaviate",">"]
docstr: Query using near text.
  
  This method uses a vector search using a Get query. we are using a nearText operator to provide
  weaviate with a query search_text. Weaviate then converts this into a vector through the inference
  API (OpenAI in this particular example) and uses that vector as the basis for a vector search.
code: def query_without_vector(
      self,
      search_text: str,
      class_name: str,
      *properties: list[str],
      limit: int = 1,
  ) -> dict[str, dict[Any, Any]]:
      """
      Query using near text.
  
      This method uses a vector search using a Get query. we are using a nearText operator to provide
      weaviate with a query search_text. Weaviate then converts this into a vector through the inference
      API (OpenAI in this particular example) and uses that vector as the basis for a vector search.
      """
      client = self.conn
      results: dict[str, dict[Any, Any]] = (
          client.query.get(class_name, properties[0])
          .with_near_text({"concepts": [search_text]})
          .with_limit(limit)
          .do()
      )
      return results
  
imports: from __future__ import annotations
  import contextlib
  import json
  import warnings
  from functools import cached_property
  from typing import TYPE_CHECKING, Any, Dict, List, Sequence, cast
  import requests
  import weaviate.exceptions
  from tenacity import Retrying, retry, retry_if_exception, retry_if_exception_type, stop_after_attempt
  from weaviate import Client
  from weaviate.auth import AuthApiKey, AuthBearerToken, AuthClientCredentials, AuthClientPassword
  from weaviate.data.replication import ConsistencyLevel
  from weaviate.exceptions import ObjectAlreadyExistsException
  from weaviate.util import generate_uuid5
  from airflow.exceptions import AirflowProviderDeprecationWarning
  from airflow.hooks.base import BaseHook
label_desc: Use image node_id 21 for calling the WeaviateHook obj's underlying member method code with example usage: obj.query_without_vector(search_text, class_name) and returns: results