Update app.py

app.py

@@ -11,9 +11,9 @@ st.title("Toxic Tweets Sentiment Analysis")
 def create_dict(prob, text):
   sorted_indices = np.argsort(prob)[-2:]
   info = {"text": text,
-         "toxicity": labels[sorted_indices[1]],
+         "label1": toxic_tweet_cats[sorted_indices[1]],
          "percentage1": str(round(prob[sorted_indices[1]], 3)),
-         "obscenity": labels[sorted_indices[0]],
+         "label2": toxic_tweet_cats[sorted_indices[0]],
          "percentage2": str(round(prob[sorted_indices[0]], 3))}
   return info
 def get_cats(text):
@@ -30,6 +30,8 @@ def get_cats(text):
 words = "Take that, you funking cat-dragon! You smell really bad!"
 text = st.text_area("Insert text for analysis below.", words)
 
+toxic_tweet_cats = ["Toxic", "Severe Toxic", "Obscene", "Threat", "Insult", "Identity Hate", "Not Toxic"]
+
 model_list = ["aim9061/fine-tuned-toxic-tweet-dilbert", "distilbert-base-uncased-finetuned-sst-2-english", "bert-base-cased", "openai/clip-vit-base-patch32", "emilyalsentzer/Bio_ClinicalBERT",
               "sentence-transformers/all-mpnet-base-v2", "facebook/bart-large-cnn", "openai/clip-vit-base-patch16", "speechbrain/spkrec-ecapa-voxceleb", 
              "albert-base-v2"]