app.py

import streamlit as st
from transformers import MarianMTModel, MarianTokenizer

# Load the pre-trained MarianMT model and tokenizer
model_name = "Helsinki-NLP/opus-mt-en-ROMANCE"
model = MarianMTModel.from_pretrained(model_name)
tokenizer = MarianTokenizer.from_pretrained(model_name)

def translate_text(text, target_lang):
    # Translate English to the target language
    inputs = tokenizer.encode(text, return_tensors="pt")
    translated = model.generate(inputs, decoder_start_token_id=tokenizer.lang_code_to_id[target_lang])
    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
    return translated_text
def main():
    st.title("English to Any Language Translator")

    # User input for English text
    text_to_translate = st.text_area("Enter text in English:")

    # Language options
    languages = {
        'French': 'fr',
        'German': 'de',
        'Italian': 'it',
        'Portuguese': 'pt',
        'Spanish': 'es',
        # Add more languages if needed
    }

    selected_language = st.selectbox("Select target language:", list(languages.keys()))

    if st.button("Translate"):
        if text_to_translate:
            target_lang = languages[selected_language]
            translated_text = translate_text(text_to_translate, target_lang)
            st.write(f"**Translation in {selected_language}:**")
            st.write(translated_text)
        else:
            st.warning("Please enter text to translate.")

if __name__ == "__main__":
    main()