code: def get_candidates(
      prompt: str,
      stop: List[str],
      temperature: float,
      priming_prefix: str,
      engine: str,
      n: int = 5,
  ) -> List[str]:
      """
      Generate N candidate completions based on the prompt, generated with a specific temperature.
  
      :param prompt: The prompt to start the conversation with.
      :param stop: A list of tokens that indicate the end of the generation.
      :param temperature: The temperature of the generation.
      :param priming_prefix: The prefix to use for the priming.
      :param engine: The engine to use for the generation.
      :param n: The number of completions to generate.
      :return: A list of completions.
      """
      response = openai.Completion.create(
          engine=engine,
          prompt=prompt,
          temperature=temperature,
          max_tokens=150,
          top_p=1,
          frequency_penalty=0,
          presence_penalty=0,
          stop=stop,
          n=n,
      )
      responses = [
          priming_prefix + choice.text for choice in response.choices
      ]
      return responses
  
file_path: openai-cookbook/examples/Backtranslation_of_SQL_queries.py
imports: from typing import List, Union
  from smokey import Smokey
  import openai
label_desc: Use image node_id 1 for calling a global function with example usage: get_candidates(prompt, stop, temperature, priming_prefix, engine, n) and returns: responses