import streamlit as st
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

# Function to load the translation model
@st.cache_resource
def load_model(model_name):
    tokenizer = AutoTokenizer.from_pretrained(model_name)
    model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
    return tokenizer, model

# Function to perform translation
def translate_text(tokenizer, model, input_text, src_lang, tgt_lang):
    # Format the input text for the model
    input_text = f">>{tgt_lang}<< {input_text}"  # Add language token
    inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True, max_length=512)
    outputs = model.generate(**inputs, max_length=512)
    translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return translated_text

# Streamlit app
def main():
    st.title("Language Translation App")
    st.markdown("Translate text between multiple languages using open-source models.")
    
    # Language options (expand as needed)
    languages = {
        "English": "en",
        "French": "fr",
        "German": "de",
        "Spanish": "es",
        "Chinese": "zh",
        "Arabic": "ar",
        "Hindi": "hi",
        "Urdu": "ur",
        "Russian": "ru",
        "Japanese": "ja",
    }
    
    # Sidebar for language selection
    st.sidebar.header("Settings")
    src_lang = st.sidebar.selectbox("Select Input Language", options=languages.keys())
    tgt_lang = st.sidebar.selectbox("Select Output Language", options=languages.keys())
    
    # Input text
    text_to_translate = st.text_area("Enter text to translate", height=150)
    
    # Load model and tokenizer
    model_name = "Helsinki-NLP/opus-mt-mul-en"  # Multi-lingual to English model
    tokenizer, model = load_model(model_name)
    
    # Translate button
    if st.button("Translate"):
        if text_to_translate.strip() == "":
            st.error("Please enter some text to translate.")
        elif src_lang == tgt_lang:
            st.warning("Input and output languages are the same. Please select different languages.")
        else:
            # Perform translation
            st.spinner("Translating...")
            translated_text = translate_text(tokenizer, model, text_to_translate, languages[src_lang], languages[tgt_lang])
            st.success("Translation Complete!")
            st.text_area("Translated Text", translated_text, height=150)

if __name__ == "__main__":
    main()