import os
os.system("pip install tensorflow")
import gradio as gra
import numpy as np
import keras
model = keras.models.load_model("text2seed-model")
max_sequence_length = 1000

def podgotovka(text_input):
  text_input_encoded = [ord(char) for char in text_input.lower()]
  padded_input = np.zeros((1, max_sequence_length), dtype=np.int)
  padded_input[0, :len(text_input_encoded)] = text_input_encoded
  return padded_input

def get_seed(text_input):
  padded_input = podgotovka(text_input)
  seed = model.predict(padded_input)
  seed = int(str(seed[0][0]).replace("0.", ""))
  print(seed)
  return seed

def text2seed(text_input):
    return str(get_seed(text_input))

def text2randint(text_input):
    np.random.seed(get_seed(text_input))
    number = np.random.randint(1, 10)
    return str(number)

def text2random(text_input):
    np.random.seed(get_seed(text_input))
    number = np.random.random()
    return str(number)

text2seed_interface = gra.Interface(fn = text2seed, inputs="text", outputs="text")
text2randint_interface = gra.Interface(fn = text2randint, inputs="text", outputs="text")
text2random_interface = gra.Interface(fn = text2random, inputs="text", outputs="text")
app = gra.Blocks()
with app:
    gra.Markdown("""
# Welcome to the text2seed!
Select the mode, enter text in text_input and enjoy the result!
    """)
    gra.TabbedInterface([text2seed_interface, text2randint_interface, text2random_interface], ["text2seed", "text2randint", "text2random"])
app.launch()