# Install necessary libraries first:
# pip install streamlit transformers

import streamlit as st
from transformers import MarianMTModel, MarianTokenizer

# Function to load model and tokenizer
@st.cache_resource
def load_translation_model(src_lang, tgt_lang):
    model_name = f"Helsinki-NLP/opus-mt-{src_lang}-{tgt_lang}"
    tokenizer = MarianTokenizer.from_pretrained(model_name)
    model = MarianMTModel.from_pretrained(model_name)
    return tokenizer, model

# Function to translate text
def translate_text(text, tokenizer, model):
    tokens = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
    translated = model.generate(**tokens)
    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
    return translated_text

# List of supported language codes
languages = {
    "English": "en",
    "French": "fr",
    "Spanish": "es",
    "German": "de",
    "Italian": "it",
    "Dutch": "nl",
    "Chinese (Simplified)": "zh",
    "Russian": "ru",
    "Arabic": "ar",
    "Hindi": "hi",
}

# Streamlit UI
st.title("Language Translation App")
st.write("Translate text between multiple languages using an open-source translation model.")

# Language selection
source_language = st.selectbox("Select source language", list(languages.keys()), index=0)
target_language = st.selectbox("Select target language", list(languages.keys()), index=1)

# Input text
input_text = st.text_area("Enter text to translate", height=150)

# Load model and tokenizer
if source_language != target_language and input_text.strip():
    src_lang_code = languages[source_language]
    tgt_lang_code = languages[target_language]

    try:
        tokenizer, model = load_translation_model(src_lang_code, tgt_lang_code)
        translated_text = translate_text(input_text, tokenizer, model)
        st.subheader("Translated Text")
        st.success(translated_text)
    except Exception as e:
        st.error(f"Error: {e}")
else:
    st.info("Please select different source and target languages and enter text to translate.")