Update app.py

app.py

@@ -4,7 +4,7 @@ from transformers import AutoModelForSequenceClassification, AutoTokenizer, Auto
 from scipy.special import softmax
 
 # Load fine-tuned model and tokenizer
-MODEL_PATH = "ktr008/sentiment"  
+MODEL_PATH = "ktr008/sentiment"
 model = AutoModelForSequenceClassification.from_pretrained(MODEL_PATH)
 tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
 config = AutoConfig.from_pretrained(MODEL_PATH)
@@ -26,16 +26,17 @@ def predict_sentiment(text):
     scores = output[0][0].detach().numpy()
     scores = softmax(scores)
 
-    # Get sentiment labels and scores
+    # Get sentiment labels and scores (floating-point values)
     ranking = np.argsort(scores)[::-1]
-    result = {config.id2label[ranking[i]]: round(float(scores[ranking[i]]) * 100, 2) for i in range(scores.shape[0])}
+    result = {config.id2label[ranking[i]]: float(scores[ranking[i]]) for i in range(scores.shape[0])}
+    
     return result
 
 # Gradio Interface
 interface = gr.Interface(
     fn=predict_sentiment,
     inputs=gr.Textbox(lines=3, placeholder="Enter text..."),
-    outputs=gr.Label(),
+    outputs=gr.JSON(),
     title="Fine-Tuned Sentiment Analysis",
     description="Enter a sentence to analyze its sentiment (Positive, Neutral, Negative).",
 )