import gradio as gr
# Matplotlib
import matplotlib.pyplot as plt
# Tensorflow
import tensorflow as tf
# Numpy and Pandas
import numpy as np
import pandas as pd
# Ohter import
import sys
from numpy import zeros,array
StandardInstanceSize=50
import json

model = tf.keras.models.load_model('model.h5')
# Opening JSON file
with open('model_vocab_to_int') as json_file:
    vocab_to_int = json.load(json_file)
def greet(Word_pair):
    #item=w1+" "+w2
    item=Word_pair
    item=item.ljust(StandardInstanceSize)
    instances = zeros((1, StandardInstanceSize), float)
    instances[0]=([vocab_to_int[l] for l in item])  
    instances=instances.astype(float)
    return model.predict(instances)[0]

iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch()