app.py

import streamlit as st
from transformers import MarianMTModel, MarianTokenizer
import torch

@st.cache_resource
def load_model_and_tokenizer(src_lang, tgt_lang):
    model_name = f'Helsinki-NLP/opus-mt-{src_lang}-{tgt_lang}'
    model = MarianMTModel.from_pretrained(model_name)
    tokenizer = MarianTokenizer.from_pretrained(model_name)
    return model, tokenizer

def translate_text(text, model, tokenizer):
    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
    model = model.to(device)
    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True).to(device)
    translated = model.generate(**inputs)
    return tokenizer.decode(translated[0], skip_special_tokens=True)

st.set_page_config(page_title="Language Translator", layout="wide")
st.title("🌍 Language Translator")
st.markdown("Translate text quickly and easily between multiple languages using open-source models.")

language_codes = {
    "English": "en", "Spanish": "es", "French": "fr", "German": "de",
    "Chinese": "zh", "Japanese": "ja", "Hindi": "hi", "Arabic": "ar",
    "Russian": "ru", "Portuguese": "pt",
}

col1, col2 = st.columns(2)
with col1:
    source_language = st.selectbox("Select source language:", options=language_codes.keys(), index=0)
with col2:
    target_language = st.selectbox("Select target language:", options=language_codes.keys(), index=1)

st.subheader("Input Text")
input_text = st.text_area("Enter the text you want to translate:", height=150)

if st.button("Translate"):
    if not input_text.strip():
        st.error("Please enter text to translate.")
    elif source_language == target_language:
        st.warning("Source and target languages are the same. Please select different languages.")
    else:
        try:
            src_lang = language_codes[source_language]
            tgt_lang = language_codes[target_language]
            model, tokenizer = load_model_and_tokenizer(src_lang, tgt_lang)
            translation = translate_text(input_text, model, tokenizer)

            st.subheader("Translated Text")
            st.text_area("Translation:", value=translation, height=150, disabled=True)
        except Exception as e:
            st.error(f"An error occurred: {e}")

st.markdown("---")
st.markdown("Developed using [Helsinki-NLP](https://huggingface.co/Helsinki-NLP) open-source models and Streamlit.")