Update app.py

app.py

@@ -1,6 +1,25 @@
 import streamlit as st
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, Trainer, TextClassificationPipeline
+import operator
 
+def get_sentiment(out):
+  d = dict()
+  for k in out.keys():
+    label = out[k]['label']
+    score = out[k]['score']
+    d[label] = score
+    
+  winning_lab = max(d.iteritems(), key=operator.itemgetter(1))[0]
+  winning_score = d[winning_lab]
+  return winning_lab, winning_score
+      
+
+
+        neg = out[0]
+    neu = out[1]
+    pos = out[2]
+    
+  
 model_name =  "mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis"
 model = AutoModelForSequenceClassification.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -8,7 +27,8 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True)
 text = st.text_area(f'Ciao! This app uses {model_name}.\nEnter your text  to test it ❤️')
 
+
 if text:
   out = pipe(text)
   
-  st.json(out[0][0])
+  st.json(get_sentiment(out[0])