Update main.py

main.py

@@ -135,18 +135,19 @@ async def test_classify_text(text: str = Form(...)):
         # Perform text classification using the updated model that returns positive, neutral, or negative
         result = nlp_classification_v2(text)
 
-        # Get the label (positive, neutral, negative) and format it as required
-        label = result[0]['label']
+        # Print the raw label for debugging purposes (can be removed later)
+        raw_label = result[0]['label']
+        print(f"Raw label from model: {raw_label}")
 
         # Map the model labels to human-readable format
         label_map = {
-            "LABEL_0": "Negative",  # Cardiff NLP's model may use these labels
-            "LABEL_1": "Neutral",   # Remap LABEL_1 to Neutral
-            "LABEL_2": "Positive"   # LABEL_2 corresponds to Positive
+            "negative": "Negative",  
+            "neutral": "Neutral",   
+            "positive": "Positive"   
         }
 
         # Get the readable label from the map
-        formatted_label = label_map.get(label, "Unknown")
+        formatted_label = label_map.get(raw_label, "Unknown")
 
         return {"label": formatted_label, "score": result[0]['score']}
     except Exception as e: