import gradio as gr
import string
from fastai.text.all import *

#loading the model from pretrained weights
model = load_learner('emot.pkl')

labels = ['sadnesss','joy','love','anger','fear','surprise']

def make_prediction(text):
    #text preprocessing
    tr = str.maketrans('','',string.punctuation)
    text=text.translate(tr).lower()
    
    #making prediction by passing to model 
    choice,pos,preds= model.predict(text)
    return {labels[i]:float(preds[i]) for i in range(len(labels))}

title = 'Emotional assist'
description = 'A haphazard tool for the critically inept, god forbid you actually need one of these in the future'
examples =['Hello Everyone!','How are you today','fine, thank you!','Oh my God!']
enable_queue=True

demo = gr.Interface(fn=make_prediction,inputs='text',outputs=gr.Label())

demo.launch()