Update app.py

app.py

@@ -1,20 +1,7 @@
+from transformers import pipeline
 import gradio as gr
-from nltk.sentiment.vader import SentimentIntensityAnalyzer
-import nltk
-nltk.download('vader_lexicon')
-def sentiment_analysis(sentiment_text):
-    score = SentimentIntensityAnalyzer().polarity_scores(sentiment_text)
-    print(score)
-    if score['neg']>=0.5:
-        return "Negative Feedback"
-    elif score['pos']>=0.5:
-        return "Positive Feedback"
-    elif score['compound']<(-0.3):
-        return "Negative Feedback"
-    elif score['compound']>0.3:
-        return "Positive Feedback"
-    else:
-        return "Neutral Feedback"
-
-iface = gr.Interface(fn = sentiment_analysis , inputs=['text'] , outputs=['text'])
+sentimentAnalyzer = pipeline("sentiment-analysis")
+def predict_sentiment(text):
+    return sentimentAnalyzer(text)[0]['label']
+iface = gr.Interface(fn=predict_sentiment,inputs=["text"],outputs=["text"])
 iface.launch(share=True)