import streamlit as st
from transformers import MarianMTModel, MarianTokenizer

# Load pre-trained MarianMT model and tokenizer
model_name = "Helsinki-NLP/opus-mt-en-xx"  # Multilingual model supporting various languages
model = MarianMTModel.from_pretrained(model_name)
tokenizer = MarianTokenizer.from_pretrained(model_name)

# Supported languages and their target language codes
LANGUAGES = {
    'French': 'fr',
    'Spanish': 'es',
    'German': 'de',
    'Chinese': 'zh',
    'Russian': 'ru',
    'Japanese': 'ja',
    'Arabic': 'ar',
    'Urdu': 'ur',
    'Hindi': 'hi',
    'Bengali': 'bn',
}

def translate_text(text, target_lang):
    # Encode the text and prepare it for translation
    encoded_text = tokenizer(text, return_tensors="pt")
    # Translate text
    translated = model.generate(**encoded_text, forced_bos_token_id=tokenizer.get_lang_id(target_lang))
    # Decode the translated text
    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
    return translated_text

# Streamlit app
st.title('Language Translator')

# Input text and language selection
text_to_translate = st.text_area("Enter text to translate")
target_language = st.selectbox("Select target language", list(LANGUAGES.keys()))

# Translate button
if st.button('Translate'):
    if text_to_translate:
        if target_language in LANGUAGES:
            translated_text = translate_text(text_to_translate, LANGUAGES[target_language])
            st.write(f"Translated text ({target_language}): {translated_text}")
        else:
            st.error("Target language not supported.")
    else:
        st.error("Please enter text to translate.")