Update app.py

app.py

@@ -1,10 +1,14 @@
 import gradio as gr
+import nltk
+from nltk.sentiment import SentimentIntensityAnalyzer
+nltk.download('vader_lexicon')
 # from transformers import AutoTokenizer, AutoModelForSequenceClassification
 # import torch
 
 # pretrained = "rohanphadke/roberta-finetuned-triplebottomline"
 # tokenizer = AutoTokenizer.from_pretrained(pretrained)
 # model = AutoModelForSequenceClassification.from_pretrained(pretrained)
+sia = SentimentIntensityAnalyzer()
 # threshold = 0.5
 
 labels = {0: 'people', 1: 'planet', 2:'profit'}
@@ -15,7 +19,7 @@ def greet(name):
     return "Hello " + name + "!!"
 
 def predict_text(text):
-    return return_labels, return_sentiment
+    return return_labels, sia.polarity_scores(text)
 
 demo = gr.Interface(fn=predict_text, inputs="text", outputs=["label", "label"])
 demo.launch()