Update app.py

app.py

@@ -28,10 +28,17 @@ def predict_sentiment(payload):
     #     sentiment_outputs = requests.post(API_URL, headers=headers, json=payload)
     #     sentiment_prediction = torch.nn.functional.softmax(sentiment_outputs.logits, dim=-1)
 
-    pos, neg, neutr = sentiment_prediction[:, 0].item(), sentiment_prediction[:, 1].item(), sentiment_prediction[:, 2].item()
+    for sentiment_prediction in response_json:
+        if sentiment_prediction['label'] == 'positive':
+            pos = sentiment_prediction['score']
+        elif sentiment_prediction['label'] == 'neutral':
+            neutr = sentiment_prediction.['score']
+        elif sentiment_prediction['label'] == 'negative':
+            neg = sentiment_prediction['score']
+
+    # pos, neg, neutr = sentiment_prediction[:, 0].item(), sentiment_prediction[:, 1].item(), sentiment_prediction[:, 2].item()
     sentiment_label = "Positive" if pos > neg and pos > neutr else "Negative" if neg > pos and neg > neutr else "Neutral"
 
-
     return sentiment_label