descriptions

app.py

@@ -33,6 +33,11 @@ This box presents a detailed breakdown of the evaluation for each model.
 (Esta caixa apresenta um detalhamento da avaliação para cada modelo.)
 """ }
 
+short_score_descriptions = {
+   0: "Unsuitable",
+   1: "Suitable"
+}
+
 score_descriptions = {
     0: "Negative: The answer is not suitable for the provided question.", 
     1: "Positive: The answer is suitable for the provided question.",
@@ -96,9 +101,10 @@ def predict(s1, s2, chosen_model):
       final_description = description + "\n \n" + description_pt
       return final_description
     
-    scores = { get_description(k):v for k,v in enumerate(logits) }
-
-    return scores
+    max_pos = logits.index(max(logits))
+    markdown_description = get_description(max_pos)
+    scores = { short_score_descriptions[k]:v for k,v in enumerate(logits) }
+    return scores, markdown_description
 
 
 inputs = [
@@ -108,7 +114,8 @@ inputs = [
 ]
 
 outputs = [
- gr.Label(label="Result")
+ gr.Label(label="Result"),
+ gr.Markdown()
 ]