RakshakRit / README.md
shubhamjaiswar's picture
Create README.md
56d146b
|
raw
history blame
476 Bytes
import gradio as gr
from nltk.sentiment.vader import SentimentIntensityAnalyzer
def sentiment_analysis(sentiment_text):
score = SentimentIntensityAnalyzer().polarity_scores(sentiment_text)
if score['neg']>score['pos']:
return "Negative Feedback"
elif score['neg']<score['pos']:
return "Positive Feedback"
else:
return "Neutral Feedback"
iface = gr.Interface(fn = sentiment_analysis , inputs=['text'] , outputs=['text'])
iface.launch()