fixed code

ai-moderation/app/services/image_moderation_service.py

@@ -1,12 +1,11 @@
 from PIL import Image
 
+from app.config.image_policy import FORBIDDEN_IMAGE_LABELS
+from app.config.settings import settings
+from app.ml.image.clip_classifier import ClipClassifier
 from app.ml.image.image_classifier import ImageClassifier
 from app.ml.image.image_prediction_result import ImagePredictionResult
-from app.ml.image.clip_classifier import ClipClassifier
 from app.moderation.image.validator import ImageValidator
-from app.config.settings import settings
-from app.config.image_policy import FORBIDDEN_IMAGE_LABELS
-
 
 class ImageModerationService:
 
@@ -21,29 +20,23 @@ class ImageModerationService:
     self.clip_classifier = clip_classifier
     self.validator = validator
 
-
-
   def moderate(
       self,
       image: Image.Image
   ) -> ImagePredictionResult:
 
-
     self.validator.validate(image)
 
-
     # =========================
     # 1. NSFW MODEL
     # =========================
 
     nsfw_prediction = self.classifier.predict(image)
 
-
     if (
         nsfw_prediction.label.lower() == "nsfw"
         and nsfw_prediction.score >= settings.NSFW_THRESHOLD
     ):
-
       nsfw_prediction.approved = False
 
       nsfw_prediction.reason = "NSFW"
@@ -54,8 +47,6 @@ class ImageModerationService:
 
       return nsfw_prediction
 
-
-
     # =========================
     # 2. CLIP MODEL
     # =========================
@@ -64,7 +55,6 @@ class ImageModerationService:
       self.clip_classifier.predict(image)
     )
 
-
     detected_forbidden = [
 
       label
@@ -76,10 +66,7 @@ class ImageModerationService:
 
     ]
 
-
     if detected_forbidden:
-
-
       return ImagePredictionResult(
 
           label=clip_prediction.label,
@@ -94,8 +81,6 @@ class ImageModerationService:
 
       )
 
-
-
     # =========================
     # 3. NORMAL IMAGE
     # =========================
@@ -112,4 +97,4 @@ class ImageModerationService:
 
         detected_labels=[]
 
-    )
+    )

ai-moderation/app/services/text_moderation_service.py

@@ -16,28 +16,21 @@ class TextModerationService:
     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",
@@ -54,23 +47,17 @@ class TextModerationService:
 
       )
 
-
-
     prediction = self.classifier.predict(text)
 
-
-
     prediction.approved = (
         prediction.score <
         settings.TEXT_TOXIC_THRESHOLD
     )
 
-
     prediction.reason = (
       "OK"
       if prediction.approved
       else "TOXIC"
     )
 
-
-    return prediction
+    return prediction