Update app.py

app.py

@@ -54,12 +54,12 @@ def analyze_personality_file(file) -> dict:
     # Get full list of scores for each label
     all_preds = personality_pipe(cv_text)[0]  # pipeline returns list per input
 
-    # Map to human-friendly trait names and percentages
+    # Map to human-friendly trait names (values between 0 and 1)
     trait_scores = {}
     for item in all_preds:
         trait = LABEL_TO_TRAIT.get(item['label'], item['label'])
-        # convert to percentage
-        trait_scores[trait] = round(item['score'] * 100, 1)
+        # keep probability in [0,1] for correct Gradio percentage display
+        trait_scores[trait] = round(item['score'], 3)
     return trait_scores
 
 with gr.Blocks() as demo:
@@ -74,6 +74,7 @@ if __name__ == "__main__":
     demo.launch()
 
 # requirements.txt
+
 gradio
 transformers
 torch