WATCHA-READIN / app.py
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Update app.py
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import gradio as gr
import tensorflow
from tensorflow.keras.models import load_model
import prepro
import numpy as np
import nltk
def classify(text):
nltk.download('stopwords')
model= load_model('nlp3.h5')
X= prepro.preprocess(text)
prediction = model.predict(np.array(X))
# return prediction
if(prediction<=0.4):
return "Looks like you are reading negative content. Some words sound negative in context."
elif(prediction>0.4 and prediction<=0.6):
return "Sounds Neutral. Speaks generally and not biased towards any value."
else :
return "Sounds Positive. Giving a good impression to start reading this stuff. "
iface= gr.Interface(
inputs=[gr.inputs.Textbox(lines=5, label="Context", placeholder="Type a sentence or paragraph here.")],
outputs=[gr.outputs.Textbox(label="Prediction")],
fn=classify,
title='WATCHA-READIN',
theme='dark-peach'
)
iface.launch()