from app.exceptions.invalid_text_exception import InvalidTextException
from app.moderation.profanity.detector import ProfanityDetector
from app.ml.text_classifier import TextClassifier
from app.ml.prediction_result import PredictionResult
from app.config.settings import settings


class TextModerationService:

  def __init__(
      self,
      classifier: TextClassifier,
      profanity_detector: ProfanityDetector
  ):

    self.classifier = classifier
    self.profanity_detector = profanity_detector

  def moderate(
      self,
      text: str
  ) -> PredictionResult:

    if text is None or not text.strip():
      raise InvalidTextException(
          "Text is empty"
      )

    detected_words = (
      self.profanity_detector.detect(text)
    )

    if detected_words:
      return PredictionResult(

          label="PROFANITY",

          score=1.0,

          approved=False,

          raw_scores=[],

          reason="PROFANITY",

          detected_words=detected_words

      )

    prediction = self.classifier.predict(text)

    prediction.approved = (
        prediction.score <
        settings.TEXT_TOXIC_THRESHOLD
    )

    prediction.reason = (
      "OK"
      if prediction.approved
      else "TOXIC"
    )

    return prediction