app.py

import os
os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "0"

from transformers import MBart50TokenizerFast, MBartForConditionalGeneration
import gradio as gr

# ---- Load model and tokenizer ----
model_name = "Mudasir692/mbart-eng-ur"

tokenizer = MBart50TokenizerFast.from_pretrained(model_name, src_lang="en_XX", tgt_lang="ur_PK")
model = MBartForConditionalGeneration.from_pretrained(model_name)

# ---- Translation function ----
def translate_to_urdu(text):
    if not text.strip():
        return "Please enter some English text."
    inputs = tokenizer(text, return_tensors="pt", padding=True)
    translated_tokens = model.generate(**inputs)
    urdu_output = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
    return urdu_output

# ---- Gradio Interface ----
examples = [
    ["How are you?"],
    ["Today is a beautiful day."],
    ["Where are you going?"],
    ["I am learning Artificial Intelligence."],
    ["Thank you very much!"]
]

app = gr.Interface(
    fn=translate_to_urdu,
    inputs=gr.Textbox(label="Enter English Text", placeholder="Type your English sentence here...", lines=2),
    outputs=gr.Textbox(label="Urdu Translation", lines=2),
    examples=examples,
    title="🕌 English → Urdu Translator",
    description="""
    <div style='text-align:center;'>
        <h3>Translate English sentences into Urdu using a fine-tuned mBART model.</h3>
        <p style='color:gray;'>Built by <b>Khurram Basharat</b> — powered by Transformers & Gradio.</p>
        <p><i>⏳ Please wait a few seconds for the model to load when you first open the app.</i></p>
    </div>
    """,
    theme="soft",
    css="""
        body {
            background: linear-gradient(to bottom right, #dff9fb, #c7ecee);
            font-family: 'Segoe UI', sans-serif;
        }
        .gr-button-primary {
            background-color: #1e3799 !important;
            color: white !important;
        }
    """,
)

app.launch()