import streamlit as st
# from transformers import (T5ForConditionalGeneration, AutoTokenizer, pipeline)
from transformers import pipeline

# import torch

st.set_page_config(layout="wide", page_title="تبدیل متون محاوره‌ای به فارسی")

model_path = 'erfan226/persian-t5-formality-transfer'
model = T5ForConditionalGeneration.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)
pipe = pipeline(task='text2text-generation', model=model, tokenizer=tokenizer)

def paraphrase(text):
  for j in range(3):
    out = pipe(text, encoder_no_repeat_ngram_size=4, do_sample=True, num_beams=5, max_length=128)[0]['generated_text']
    print("Paraphrase:", out)

link = st.text_area('Paste your link here...', "من با دوستام میرم بازی", height=50)
min_length = st.sidebar.slider('حداقل طول جمله', min_value=10, max_value=100, value=50, step=10)
max_length = st.sidebar.slider('حداکثر طول طول جمله', min_value=30, max_value=700, value=100, step=10)
num_beams = st.sidebar.slider('طول Beam', min_value=1, max_value=10, value=5, step=1)
out = paraphrase(link)
st.write(out)
# x = st.slider('Select a value')
# st.write(x, 'squared is', x * x)