app.py

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

st.set_page_config(page_title="Francesco Daimon Fernicola", page_icon=":milky_way:", layout="wide")

with st.container():
    st.subheader("Hello, and welcome to my official webpage! I am Daimon :alien:")
    st.title("PhD Candidate in Machine Translation / Translator / Mountain enthusiast")
    st.write("I am passionate about finding new ways to effectively use and understand Machine Translation and effectively evaluating its quality.")
    st.write("""
    [Github](https://github.com/FrancescoFernicola)
    [Unibo](https://www.unibo.it/sitoweb/francesco.fernicola2)
    [LinkedIn](https://www.linkedin.com/in/francesco-fernicola-69a0771b7/?locale=en_US)
    [Twitter](https://twitter.com/FrancescoDaimon)
    """)

from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
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")



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

valid_languages = [
    'ar_AR', 'cs_CZ', 'de_DE', 'en_XX', 'es_XX', 'et_EE', 'fi_FI', 'fr_XX',
    'gu_IN', 'hi_IN', 'it_IT', 'ja_XX', 'kk_KZ', 'ko_KR', 'lt_LT', 'lv_LV', 'my_MM', 'ne_NP',
    'nl_XX', 'ro_RO', 'ru_RU', 'si_LK', 'tr_TR', 'vi_VN' 'zh_CN', 'af_ZA', 'az_AZ', 'bn_IN',
    'fa_IR', 'he_IL', 'hr_HR', 'id_ID', 'ka_GE', 'km_KH', 'mk_MK', 'ml_IN', 'mn_MN', 'mr_IN',
    'pl_PL', 'ps_AF', 'pt_XX', 'sv_SE', 'sw_KE', 'ta_IN', 'te_IN', 'th_TH', 'tl_XX', 'uk_UA',
    'ur_PK', 'xh_ZA', 'gl_ES', 'sl_SI'
    ]

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 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)
    if uploaded_file.name.endswith('.tsv'):
        data = pd.read_csv(uploaded_file, sep="\t")
        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
        
    else:
        data = pd.read_csv(uploaded_file)

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")