Update app.py

app.py

@@ -93,11 +93,26 @@ def process_final_text(text):
     
     # Transformer Interpret:
     word_attributions = cls_explainer(X_test)
-    intp = pd.DataFrame(word_attributions)
-    intp.columns = ["Token",'Score']
-    intp_dict = intp.set_index('Token').T.to_dict('list')
+    letter = []
+    score = []
+    for i in word_attributions:
+        if i[1]>0.5:
+            a = "++"
+        elif (i[1]<=0.5) and (i[1]>0.1):
+            a = "+"
+        elif (i[1]>=-0.5) and (i[1]<-0.1):
+            a = "-"
+        elif i[1]<-0.5:
+            a = "--"
+        else: 
+            a = "NA"
+    
+        letter.append(i[0])
+        score.append(a)
+    
+    word_attributions = [(letter[i], score[i]) for i in range(0, len(letter))]
     
-    return {"Resilience": float(scores.numpy()[1]), "Non-Resilience": float(scores.numpy()[0])},keywords,NER,intp_dict
+    return {"Resilience": float(scores.numpy()[1]), "Non-Resilience": float(scores.numpy()[0])},keywords,NER,word_attributions
     
 def main(prob1):
     text = str(prob1)
@@ -124,7 +139,10 @@ with gr.Blocks(title=title) as demo:
         color_map={"+++": "royalblue","++": "cornflowerblue",
          "+": "lightsteelblue", "NA":"white"})
         NER = gr.HTML(label = 'NER:')
-        intp = gr.Label(label = "Word Scores:")
+        intp =gr.HighlightedText(label="Word Scores",
+        combine_adjacent=False).style(color_map={"++": "darkgreen","+": "green", 
+                                                "--": "darkred",
+                                                "-": "red", "NA":"white"})
 
     submit_btn.click(
         main,