app.py

import streamlit as st
from transformers import MarianMTModel, MarianTokenizer

# Load pre-trained model and tokenizer
model_name = 'Helsinki-NLP/opus-mt-ur-de'
model = MarianMTModel.from_pretrained(model_name)
tokenizer = MarianTokenizer.from_pretrained(model_name)

# Function to translate text
def translate_text(text, src_lang, tgt_lang):
    # Tokenize input text
    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)

    # Translate and decode
    translated = model.generate(**inputs)
    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
    return translated_text

# Streamlit app layout
st.title("Real-Time Urdu to German Translation")
st.write("Enter Urdu text below, and the app will translate it into German.")

# Input text area for Urdu text
input_text = st.text_area("Urdu Text", "", height=200)

# Translate when the button is pressed
if st.button("Translate"):
    if input_text:
        # Translate the text
        translated_text = translate_text(input_text, "ur", "de")
        st.subheader("Translated German Text:")
        st.write(translated_text)
    else:
        st.write("Please enter some Urdu text to translate.")