Update app.py

app.py

@@ -19,15 +19,20 @@ from transformers import pipeline
 nsfw_detector = pipeline("text-classification", model="michellejieli/NSFW_text_classifier")
 
 def synthesize_speech(text):
-    # Function to synthesize speech from text.
+    # Check for NSFW content using the classifier
+    nsfw_result = nsfw_detector(text)
+    # Extract the label and score from the result
+    label = nsfw_result[0]['label']
+    score = nsfw_result[0]['score']
 
     # First, check if the input text contains NSFW content.
-    nsfw_result = nsfw_detector(text)
-    if nsfw_result[0]['label'] == 'NSFW':
-        # If NSFW content is detected, load a pre-recorded error message.
+    #nsfw_result = nsfw_detector(text)
+    if label == 'NSFW' and score >= 0.95:
+        # Download and read the error audio file
         error_audio_path = hf_hub_download(repo_id="DLI-SLQ/speaker_01234", filename="error_audio.wav")
         with open(error_audio_path, 'rb') as error_audio_file:
             error_audio = error_audio_file.read()
+        # Return the error audio and a warning message
         return error_audio, "NSFW content detected. Cannot process."
 
     # If the content is safe, proceed with speech synthesis.