Update app.py

app.py

@@ -37,23 +37,16 @@ else:
 model = ORTModelForSequenceClassification.from_pretrained(model_id)
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 
-pipe = pipeline(task="text-classification", model=model, tokenizer=tokenizer)
+# Set top_k=3 to get the top 3 results
+pipe = pipeline(task="text-classification", model=model, tokenizer=tokenizer, top_k=3)
 
 def classify_text(text):
     results = pipe(text)
     output = ""
     
-    if len(results) > 0:
-        # Print the first result
-        output += f"Label 1: {results[0]['label']}, Score: {results[0]['score']:.4f}\n"
-        
-        # Print the second result if it exists
-        if len(results) > 1:
-            output += f"Label 2: {results[1]['label']}, Score: {results[1]['score']:.4f}\n"
-        
-        # Print the third result if it exists
-        if len(results) > 2:
-            output += f"Label 3: {results[2]['label']}, Score: {results[2]['score']:.4f}\n"
+    # Loop through up to 3 results
+    for i, result in enumerate(results[:3]):
+        output += f"Label {i+1}: {result['label']}, Score: {result['score']:.4f}\n"
 
     return output