##Package
from transformers import pipeline
import gradio as gr

pipe_new  = pipeline(task="text-classification", 
                model="nlptown/bert-base-multilingual-uncased-sentiment")

def sentiment_score(text):
    return pipe_new(text)[0]['label']
# Create title, description and article strings
title = "Sentiment Abalysis"
description = "This model predicts the sentiment of the review as a number of stars (between 1 and 5) using  nlptown/bert-base-multilingual-uncased-sentiment model"
# article = "This model predicts the sentiment of the review as a number of stars (between 1 and 5) using  nlptown/bert-base-multilingual-uncased-sentiment model"


demo = gr.Interface(fn=sentiment_score, 
             inputs="text", 
             outputs="text",
             title=title, 
             description=description)

# Launch the app!
demo.launch()