app.py

import streamlit as st
from transformers import MarianMTModel, MarianTokenizer

# Function to load the translation model
@st.cache_resource
def load_model():
    # Use a model for translating to English (Supports various languages)
    model_name = "Helsinki-NLP/opus-mt-en-ROMANCE"
    model = MarianMTModel.from_pretrained(model_name)
    tokenizer = MarianTokenizer.from_pretrained(model_name)
    return model, tokenizer

# Translate the text to English
def translate_to_english(text, model, tokenizer):
    inputs = tokenizer.encode(text, return_tensors="pt", padding=True)
    translated = model.generate(inputs, max_length=512)
    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
    return translated_text

# Streamlit UI setup
st.title("Language Translator to English")
st.write("Translate any language (Romanian, Spanish, French, etc.) to English using Hugging Face models!")

# Text input field
input_text = st.text_area("Enter text in any language", "")

if input_text:
    model, tokenizer = load_model()
    translated_text = translate_to_english(input_text, model, tokenizer)
    st.subheader("Translated Text:")
    st.write(translated_text)