import streamlit as st
import pandas as pd
from pathlib import Path
from transformers import MBartForConditionalGeneration, MBart50TokenizerFast

st.set_page_config(page_title="Translation Demo", page_icon=":milky_way:", layout="wide")


def get_translation(src_code, trg_code, src):

    tokenizer.src_lang = src_code
    encoded = tokenizer(src, return_tensors="pt")
    generated_tokens = model.generate(
        **encoded,
        forced_bos_token_id=tokenizer.lang_code_to_id[trg_code]
    )
    trg = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
    
    return trg


def open_input(the_file):
    
    if the_file.name.endswith('.tsv'):
        parsed = pd.read_csv(the_file, sep="\t")
    elif the_file.name.endswith('.xlsx'):
        parsed = pd.read_excel(the_file)

    return parsed


st.subheader("MBART-50 Translator")

source = "In the beginning the Universe was created. This has made a lot of people very angry and been widely regarded as a bad move."
target = ""
model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")


valid_languages = ['de_DE', 'en_XX', 'it_IT']



valid_languages_tuple = (lang for lang in valid_languages)
valid_languages_tuple_trg = (lang for lang in valid_languages)

with st.form("my_form"):
    left_c, right_c = st.columns(2)
    #with left_c:
    src_lang = st.selectbox(
        'Source language',
        valid_languages_tuple,
        )
    #with right_c:
    trg_lang = st.selectbox(
        'Target language',
        valid_languages_tuple_trg,
        )
    source = st.text_area("Source", value=source, height=130, placeholder="Enter the source text...")


    submitted = st.form_submit_button("Translate")
    if submitted:
        if len(source) > 0 and src_lang in valid_languages and trg_lang in valid_languages:
            with st.spinner("Translating..."):
                try:
                    target = get_translation(src_lang, trg_lang, source)[0]
                    st.subheader("Translation done!")
                    target = st.text_area("Target", value=target, height=130)
                except:
                    st.subheader("Translation failed :sad:")
                    
        else:
            st.write("Please enter the source text, source language and target language.")


st.subheader('Input Excel/TSV')
uploaded_file = st.file_uploader("Choose a file")
done = False


if uploaded_file is not None:
    valid_languages_col = (lang for lang in valid_languages)
    valid_languages_col_trg = (lang for lang in valid_languages)
    data = open_input(uploaded_file)
    st.subheader("DataFrame")
    st.write(data)
    st.write(data.describe())
    
    columns = (col for col in data.columns)
    src_col = st.selectbox(
    'Select the column to translate:',
    columns,
    )
    
    if src_col:
        col_src_lang = st.selectbox(
            'Source language:',
            valid_languages_col,
        )
        col_trg_lang = st.selectbox(
            'Target language:',
            valid_languages_col_trg,
        )
        submitted_cols = st.button("Translate column")
        
        if submitted_cols:
            translated_data = []
            new_df = data
            for text in data[src_col]:
                if len(text) > 0 and col_src_lang in valid_languages and col_trg_lang in valid_languages:
                    with st.spinner("Translating..."):
                        try:
                            target_text = get_translation(col_src_lang, col_trg_lang, text)[0]
                            translated_data.append(target_text)
                        except:
                            st.subheader("Translation failed :sad:")
                            break
                else:
                    st.write("Please enter the source text, source language and target language.")
                    
            new_df[src_col] = translated_data
            done = True

if done:
    st.subheader("Translated DataFrame")
    st.write(new_df)
    st.write(new_df.describe())
    to_dl = new_df.to_csv(index=False, sep='\t').encode('utf-8')
    st.download_button('Download TSV', to_dl, 'translated_file.tsv', 'text/tsv', key='download-tsv')

    
else:
    st.info("☝️ Upload a TSV file")