app.py

# STEP 1: Install required libraries
!pip install transformers sentencepiece gradio -q

# STEP 2: Import libraries
from transformers import MarianMTModel, MarianTokenizer
import gradio as gr

# STEP 3: Load models and tokenizers for both directions
en_to_ur_model_name = "Helsinki-NLP/opus-mt-en-ur"
ur_to_en_model_name = "Helsinki-NLP/opus-mt-ur-en"

en_to_ur_tokenizer = MarianTokenizer.from_pretrained(en_to_ur_model_name)
en_to_ur_model = MarianMTModel.from_pretrained(en_to_ur_model_name)

ur_to_en_tokenizer = MarianTokenizer.from_pretrained(ur_to_en_model_name)
ur_to_en_model = MarianMTModel.from_pretrained(ur_to_en_model_name)

# STEP 4: Translation functions
def translate_en_to_ur(text):
    if not text.strip():
        return "Please enter some English text."
    inputs = en_to_ur_tokenizer(text, return_tensors="pt", padding=True)
    translated = en_to_ur_model.generate(**inputs)
    urdu_text = en_to_ur_tokenizer.decode(translated[0], skip_special_tokens=True)
    return urdu_text

def translate_ur_to_en(text):
    if not text.strip():
        return "براہ کرم کچھ اردو متن درج کریں۔"
    inputs = ur_to_en_tokenizer(text, return_tensors="pt", padding=True)
    translated = ur_to_en_model.generate(**inputs)
    english_text = ur_to_en_tokenizer.decode(translated[0], skip_special_tokens=True)
    return english_text

# STEP 5: Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("## English ↔ Urdu Translator")

    with gr.Tab("English to Urdu"):
        en_input = gr.Textbox(label="Enter English Text")
        en_output = gr.Textbox(label="Urdu Translation")
        en_button = gr.Button("Translate")
        en_button.click(fn=translate_en_to_ur, inputs=en_input, outputs=en_output)

    with gr.Tab("Urdu to English"):
        ur_input = gr.Textbox(label="اردو متن درج کریں")
        ur_output = gr.Textbox(label="English Translation")
        ur_button = gr.Button("Translate")
        ur_button.click(fn=translate_ur_to_en, inputs=ur_input, outputs=ur_output)

# STEP 6: Launch
demo.launch()