Get warning level of text from GPT-3

get_gpt3_warning_level.py

def get_warning_level(content_to_classify):
  content_filter_results = openai.Completion.create(
        engine="content-filter-alpha-c4",
        prompt = "<|endoftext|>"+content_to_classify+"\n--\nLabel:",
        temperature=0,
        max_tokens=1,
        top_p=1,
        frequency_penalty=0,
        presence_penalty=0,
        logprobs=10)
  output_label = content_filter_results["choices"][0]["text"]
  # This is the probability at which we evaluate that a "2" is likely real
  # vs. should be discarded as a false positive
  toxic_threshold = -0.355
  if output_label == "2":
    # If the model returns "2", return its confidence in 2 or other output-labels
    logprobs = content_filter_results["choices"][0]["logprobs"]["top_logprobs"][0]
    # If the model is not sufficiently confident in "2",
    # choose the most probable of "0" or "1"
    # Guaranteed to have a confidence for 2 since this was the selected token.
    if logprobs["2"] < toxic_threshold:
      logprob_0 = logprobs.get("0", None)
      logprob_1 = logprobs.get("1", None)
      # If both "0" and "1" have probabilities, set the output label
      # to whichever is most probable
      if logprob_0 is not None and logprob_1 is not None:
        if logprob_0 >= logprob_1:
          output_label = "0"
        else:
          output_label = "1"
      # If only one of them is found, set output label to that one
      elif logprob_0 is not None:
        output_label = "0"
      elif logprob_1 is not None:
        output_label = "1"
      # If neither "0" or "1" are available, stick with "2"
      # by leaving output_label unchanged.
  # if the most probable token is none of "0", "1", or "2"
  # this should be set as unsafe
  if output_label not in ["0", "1", "2"]:
    output_label = "2"
  return output_label