app.py

import streamlit as st
from transformers import pipeline

# Install sentencepiece (ensure it is installed)
# !pip install sentencepiece

@st.cache_resource
def load_translator(target_lang):
    model_name = f"Helsinki-NLP/opus-mt-en-{target_lang}"
    translator = pipeline("translation", model=model_name)
    return translator

def translate_text(translator, text):
    translation = translator(text)
    return translation[0]['translation_text']

def main():
    st.title("Language Translator")
    st.write("Translate text from English to your desired language.")

    # Input text
    input_text = st.text_area("Enter text in English:", "")

    # Select target language
    target_lang = st.selectbox("Select target language:", [
        "fr",  # French
        "es",  # Spanish
        "de",  # German
        "it",  # Italian
        "zh",  # Chinese
        "hi",  # Hindi
        "ja",  # Japanese
        "ru",  # Russian
        "ar"   # Arabic
        "ur"   # Urdu
    ])

    if st.button("Translate"):
        if input_text:
            translator = load_translator(target_lang)
            translated_text = translate_text(translator, input_text)
            st.write(f"**Translated text in {target_lang}:**")
            st.write(translated_text)
        else:
            st.write("Please enter text to translate.")

if __name__ == "__main__":
    main()