Update app.py

app.py

@@ -11,26 +11,20 @@ model.eval()
 labels = ["happy", "love", "angry", "sadness", "fear", "trust",
           "disgust", "surprise", "anticipation", "optimism", "pessimism"]
 
-def predict(text, threshold=0.5):
+def predict(text):
     inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True).to(model.device)
     with torch.no_grad():
         outputs = model(**inputs)
         probs = torch.sigmoid(outputs.logits)[0].cpu().numpy()
 
-    # เลือกเฉพาะอารมณ์ที่ prob > threshold
-    results = {
-        labels[i]: float(np.round(probs[i], 3))
-        for i in range(len(labels)) if probs[i] > threshold
-    }
+    max_idx = int(np.argmax(probs))
+    max_label = labels[max_idx]
+    max_score = round(probs[max_idx] * 100)
 
-    # ถ้าไม่มีอารมณ์ไหนผ่าน threshold
-    if not results:
-        return {"No dominant emotion": 1.0}
-
-    return results
+    return f"{max_label} ({max_score}%)"
 
 gr.Interface(
     fn=predict,
     inputs=gr.Textbox(label="Enter english comment"),
-    outputs=gr.Label(label="Detected Emotions")
+    outputs=gr.Text(label="Top Emotion")
 ).launch()