import streamlit as st
from transformers import T5ForConditionalGeneration, T5TokenizerFast, T5Config

@st.cache(allow_output_mutation=True, suppress_st_warning=True)
def load_model():
    model_name = "north/demo-deuncaser-base"
    config = T5Config.from_pretrained(model_name)
    model = T5ForConditionalGeneration.from_pretrained(model_name,config=config)
    tokenizer = T5TokenizerFast.from_pretrained(model_name)
    return (model, tokenizer)

def deuncase(model, tokenizer, text):
        encoded_txt = tokenizer(text, return_tensors="pt")
        generated_tokens = model.generate(
            **encoded_txt
        )
        return tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)

def spaces():
    st.ta.value= "About"
    return None

st.title("DeUnCaser")

st.sidebar.write("This web app adds spaces, punctation and capitalisation back into the text.")
st.sidebar.write("You can use the examples below, but too really test the effect of the model: Write or copy text from the Internet, and then use the buttons to remove spaces, puctation, cases etc. Try to restore the text.")

option = st.sidebar.selectbox(
     "Examples:",
     ("tirsdag var travel for ukrainas president volodymyr zelenskyj på morgenen tok han imot polens statsminister mateusz morawiecki","tirsdagvartravelforukrainaspresidentvolodymyrzelenskyjpåkveldentokhanimotpolensstatsministermateuszmorawiecki","deterikkelettåholderedepåstoreogsmåbokstavermanmåforeksempelhuskestorforbokstavnårmanskriveromkrimhalvøyamenkunbrukelitenforbokstavnårmanhenvisertilenkrimroman","detteerenlitendemosomerlagetavperegilkummervoldhanerenforskersomtidligerejobbetvednasjonalbiblioteketimoirana", "sentpå60talletvardetfaktisknoensomkalteungensinperegilkummervoldidagerdetikkelengersåvanligåbrukedobbeltnavninorgehvasynesduomdet"))


col1, col2, col3 = st.columns([1,1,1])
with col1:
    uncase=st.button('Remove Casing')
with col2:
    unpunct=st.button('Remove Punctation')
with col3:
    unspace=st.button('Remove Spaces')

if uncase:
    mytext = mytext.lower()
elif unpunct:
    mytext = mytext.replace('.', ' ')


text = st.text_area(f"",max_chars=1000, value=mytext)

run = st.button('Run DeUnCaser')


#st.text("Fixed text: ")

#form = st.form(key='my_form')
#form.text_input(value="test",key="test",label='Enter some text')
#submit_button = form.form_submit_button(label='Submit')
#https://blog.streamlit.io/introducing-submit-button-and-forms/
    

#More stuff to try


if run:
    model, tokenizer = load_model()
    translated_text = deuncase(model, tokenizer, text)
    st.write(translated_text[0] if translated_text else "Unknown Error Translating Text")